Convection ‐permitting modeling with regional climate models: Latest developments and next steps - Lucas‐Picher, Philippe; Argüeso, Daniel; Brisson, Erwan; Tramblay, Yves; Berg, Peter; Lemonsu, Aude; Kotlarski, Sven; Caillaud, Cécile (WIREs Climate Change, 2021)
Abstract Approximately 10 years ago, convection‐permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1–4 km) decadal‐long climate simulations with explicitly resolved deep convection. This explicit representation is expected to reduce climate projection uncertainty related to deep convection parameterizations found in most climate models. A recent surge in CPRCM decadal simulations over larger domains, sometimes covering continents, has led to important insights into CPRCM advantages and limitations. Furthermore, new observational gridded datasets with fine spatial and temporal (~1 km; ~1 h) resolutions have leveraged additional knowledge through evaluations of the added value of CPRCMs. With an improved coordination in the frame of ongoing international initiatives, the production of ensembles of CPRCM simulations is expected to provide more robust climate projections and a better identification of their associated uncertainties. This review paper presents an overview of the methodology to produce CPRCM simulations and the latest research on the related added value in current and future climates. Impact studies that are already taking advantage of these new CPRCM simulations are highlighted. This review paper ends by proposing next steps that could be accomplished to continue exploiting the full potential of CPRCMs. This article is categorized under: Climate Models and Modeling > Earth System Models

Contrasting lightning projection using the lightning potential index adapted in a convection-permitting regional climate model - Brisson, Erwan; Blahak, Ulrich; Lucas-Picher, Philippe; Purr, Christopher; Ahrens, Bodo (Climate Dynamics, 2021)
Abstract Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE $$×$$ × PREC parameterization, applied in a non-CPM on a coarser grid. The LPI’s implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE $$×$$ × PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of $$4.8%$$ 4.8 % in flash rate by the end of the century, in opposition to a projected increase of $$17.4%$$ 17.4 % as projected using the CAPE $$×$$ × PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.

Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012 - Li, Hanwei; Ding, Juhua; Zhang, Jiang; Yang, Zhenan; Yang, Bin; Zhu, Qiuan; Peng, Changhui (Land, 2020)
The 2001–2012 MODIS MCD12Q1 land cover data and MOD17A3 NPP data were used to calculate changes in land cover in China and annual changes in net primary productivity (NPP) during a 12-year period and to quantitatively analyze the effects of land cover change on the NPP of China’s terrestrial ecosystems. The results revealed that during the study period, no changes in land cover type occurred in 7447.31 thousand km2 of China, while the area of vegetation cover increased by 160.97 thousand km2 in the rest of the country. Forest cover increased to 20.91%, which was mainly due to the conversion of large areas of savanna (345.19 thousand km2) and cropland (178.96 thousand km2) to forest. During the 12-year study period, the annual mean NPP of China was 2.70 PgC and increased by 0.25 PgC, from 2.50 to 2.75 PgC. Of this change, 0.21 PgC occurred in areas where there was no land cover change, while 0.04 PgC occurred in areas where there was land cover change. The contributions of forest and cropland to NPP exhibited increasing trends, while the contributions of shrubland and grassland to NPP decreased. Among these land cover types, the contributions of forest and cropland to the national NPP were the greatest, accounting for 40.97% and 27.95%, respectively, of the annual total NPP. There was no significant correlation between changes in forest area and changes in total annual NPP (R2 < 0.1), while the correlation coefficient for changes in cropland area and total annual NPP was 0.48. Additionally, the area of cropland converted to other land cover types was negatively correlated with the changes in NPP, and the loss of cropland caused a reduction in the national NPP.

Estimating soil organic carbon redistribution in three major river basins of China based on erosion processes - Yang, Yan; Zhu, Qiuan; Liu, Jinxun; Li, Mingxu; Yuan, Minshu; Chen, Huai; Peng, Changhui; Yang, Zhenan (Soil Research, 2020)
Soil erosion by water affects soil organic carbon (SOC) migration and distribution, which are important processes for defining ecosystem carbon sources and sinks. Little has been done to quantify soil carbon erosion in the three major basins in China, the Yangtze River, Yellow River and Pearl River Basins, which contain the most eroded areas. This research attempts to quantify the lateral movement of SOC based on spatial and temporal patterns of water erosion rates derived from an empirical Unit Stream Power Erosion Deposition Model (USPED) model. The water erosion rates simulated by the USPED model agreed reasonably with observations (R2 = 0.43, P < 0.01). We showed that regional water erosion ranged within 23.3–50 Mg ha–1 year–1 during 1992–2013, inducing the lateral redistribution of SOC caused by erosion in the range of 0.027–0.049 Mg C ha–1 year–1, and that caused by deposition of 0.0079–0.015 Mg C ha–1 year–1, in the three basins. The total eroded SOC was 0.006, 0.002 and 0.001 Pg year–1 in the Yangtze River, Yellow River and Pearl River Basins respectively. The net eroded SOC in the three basins was ~0.0075 Pg C year–1. Overall, the annual average redistributed SOC rate caused by erosion was greater than that caused by deposition, and the SOC loss in the Yangtze River Basin was greatest among the three basins. Our study suggests that considering both processes of erosion and deposition – as well as effects of topography, rainfall, land use types and their interactions – on these processes are important to understand SOC redistribution caused by water erosion.

A review of the mechanisms and controlling factors of methane dynamics in forest ecosystems - Feng, Huili; Guo, Jiahuan; Han, Menghua; Wang, Weifeng; Peng, Changhui; Jin, Jiaxin; Song, Xinzhang; Yu, Shuiqiang (Forest Ecology and Management, 2020)

The effects of the soil environment on soil organic carbon in tea plantations in Xishuangbanna, southwestern China - Di, Sun; Zong, Mingming; Li, Shiyu; Li, Haixia; Duan, Changqun; Peng, Changhui; Zhao, Yonggui; Bai, Jinyue; Lin, Chen; Feng, Yuan; Huang, Wuping; Wang, Di (Agriculture, Ecosystems & Environment, 2020)

Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests - Chen, Jiaxin; Yang, Hongqiang; Man, Rongzhou; Wang, Weifeng; Sharma, Mahadev; Peng, Changhui; Parton, John; Zhu, Huaiping; Deng, Ziwang (Forest Ecology and Management, 2020)

Warming‐induced global soil carbon loss attenuated by downward carbon movement - Luo, Zhongkui; Luo, Yiqi; Wang, Guocheng; Xia, Jianyang; Peng, Changhui (Global Change Biology, 2020)
Abstract The fate of soil organic carbon (SOC) under warming is poorly understood, particularly across large extents and in the whole‐soil profile. Using a data‐model integration approach applied across the globe, we find that downward movement of SOC along the soil profile reduces SOC loss under warming. We predict that global SOC stocks (down to 2 m) will decline by 4% (~80 Pg) on average when SOC reaches the steady state under 2°C warming, assuming no changes in net primary productivity (NPP). To compensate such decline (i.e. maintain current SOC stocks), a 3% increase of NPP is required. Without the downward SOC movement, global SOC declines by 15%, while a 20% increase in NPP is needed to compensate that loss. This vital role of downward SOC movement in controlling whole‐soil profile SOC dynamics in response to warming is due to the protection afforded to downward‐moving SOC by depth, indicated by much longer residence times of SOC in deeper layers. Additionally, we find that this protection could not be counteracted by promoted decomposition due to the priming of downward‐moving new SOC from upper layers on native old SOC in deeper layers. This study provides the first estimation of whole‐soil SOC changes under warming and additional NPP required to compensate such changes across the globe, and reveals the vital role of downward movement of SOC in reducing SOC loss under global warming.

The significant contribution of lake depth in regulating global lake diffusive methane emissions - Li, Mingxu; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Yang, Gang; Song, Xinzhang; Zhang, Kerou (Water Research, 2020)

Effect of Urbanization on Ecosystem Service Values in the Beijing-Tianjin-Hebei Urban Agglomeration of China from 2000 to 2014 - Liu, Shan; Yang, Mingxia; Mou, Yuling; Meng, Yanrong; Zhou, Xiaolu; Peng, Changhui (Sustainability, 2020)
Rapid urbanization has led to the continuous deterioration of the surrounding natural ecosystem. It is important to identify the key urbanization factors that affect ecosystem services and analyze the potential effects of these factors on the ecosystem. We selected the Beijing, Tianjin, and Hebei (BTH) urban agglomeration to investigate these effects, and designed three indicators to map the urbanization level: Population density, gross domestic product (GDP) density, and the construction land proportion. Four indicators were chosen to quantify ecosystem services: Food production, carbon sequestration and oxygen production, water conservation, and soil conservation. To handle the nonlinear interactions, we used a random forest (RF) method to assess the effect of urbanization on ecosystem services in the BTH area from 2000 to 2014. Our study demonstrated that population density and economic growth were the internal driving forces affecting ecosystem services. We observed changing trends in the effect of urbanization: The effect of population density on ecosystem services increased, the effect of the proportion of construction land was consistent with population density, and the effect of GDP density on ecosystem services decreased. Our results suggest that controlling the population and GDP would significantly influence the sustainable development in large urban areas.

A new integrated framework to estimate the climate change impacts of biomass utilization for biofuel in life cycle assessment - Liu, Weiguo; Xu, Junming; Xie, Xinfeng; Yan, Yan; Zhou, Xiaolu; Peng, Changhui (Journal of Cleaner Production, 2020)

The Vertical Differences in the Change Rates and Controlling Factors of Soil Organic Carbon and Total Nitrogen along Vegetation Restoration in a Subtropical Area of China - Cao, Zhiwei; Fang, Xi; Xiang, Wenhua; Lei, Pifeng; Peng, Changhui (Sustainability, 2020)
The study was to investigate the change patterns of soil organic carbon (SOC), total nitrogen (TN), and soil C/N (C/N) in each soil sublayer along vegetation restoration in subtropical China. We collected soil samples in four typical plant communities along a restoration chronosequence. The soil physicochemical properties, fine root, and litter biomass were measured. Our results showed the proportion of SOC stocks (Cs) and TN stocks (Ns) in 20–30 and 30–40 cm soil layers increased, whereas that in 0–10 and 10–20 cm soil layers decreased. Different but well-constrained C/N was found among four restoration stages in each soil sublayer. The effect of soil factors was greater on the deep soil than the surface soil, while the effect of vegetation factors was just the opposite. Our study indicated that vegetation restoration promoted the uniform distribution of SOC and TN on the soil profile. The C/N was relatively stable along vegetation restoration in each soil layer. The accumulation of SOC and TN in the surface soil layer was controlled more by vegetation factors, while that in the lower layer was controlled by both vegetation factors and soil factors.

Global estimation of the climate change impact of logging residue utilization for biofuels - Liu, Weiguo; Hou, Yue; Liu, Wenyan; Yang, Mingxia; Yan, Yan; Peng, Changhui; Yu, Zhen (Forest Ecology and Management, 2020)

Effects of increasing aerosol optical depth on the gross primary productivity in China during 2000–2014 - Zhang, Jing; Ding, Juhua; Zhang, Jiang; Yuan, Minshu; Li, Peng; Xiao, Zhongyong; Peng, Changhui; Chen, Huai; Wang, Meng; Zhu, Qiuan (Ecological Indicators, 2020)

High uncertainties detected in the wetlands distribution of the Qinghai–Tibet Plateau based on multisource data - Wang, Jieyi; Zhu, Qiuan; Yang, Yan; Zhang, Xian; Zhang, Jiang; Yuan, Minshu; Chen, Huai; Peng, Changhui (Landscape and Ecological Engineering, 2020)

Assessment of biomass utilization potential of Caragana korshinskii and its effect on carbon sequestration on the Northern Shaanxi Loess Plateau, China - Liu, Weiguo; Yu, Zhen; Zhu, Qiuan; Zhou, Xiaolu; Peng, Changhui (Land Degradation & Development, 2020)
Abstract Biomass has been promoted as a promising energy resource to mitigate global climate change. To evaluate the contribution of biomass utilization to climate change mitigation under the “Grain for Green” program in Northern Shaanxi, China, a soil carbon dynamic model and a life cycle assessment model were integrated to examine the benefits of using Caragana korshinskii Kom. as an energy crop. We found that the annual dry biomass output is maintained at 0.7 Tg during the simulation period (2020–2097). Due to the compensatory effect of biomass regrowth, the global warming potential of biomass‐derived CO 2 emissions is approximately 0.045; therefore, the total annual biogenic CO 2 emission is 57,211 ± 6,168 Mg CO 2 eq. The total annual life cycle CO 2 emissions approach 867,072 Mg CO 2 eq yr −1 . Under the scenario of no biomass removal, final carbon storage ranges from 15.7 to 19.3 TgC, and the highest carbon sequestration rate is 0.47 TgC yr −1 . In comparison with the no biomass removal scenario, the carbon sequestration rate (close to 0 MgC yr −1 ) in the biomass utilization scenario indicates a carbon loss; however, a portion of the carbon loss (31.39–62.09%) can be offset by carbon emission reductions from the substitution of fossil fuels.

Dynamics of soil water extractable organic carbon and inorganic nitrogen and their environmental controls in mountain forest and meadow ecosystems in China - Zhang, Junjun; Peng, Changhui; Xue, Wei; Yang, Bin; Yang, Zhenan; Niu, Shuli; Zhu, Qiuan; Wang, Meng (CATENA, 2020)

Modeling the effects of precipitation and temperature patterns on agricultural drought in China from 1949 to 2015 - Yang, Mingxia; Mou, Yuling; Meng, Yanrong; Liu, Shan; Peng, Changhui; Zhou, Xiaolu (Science of The Total Environment, 2020)

Tree growth rate and soil nutrient status determine the shift in nutrient-use strategy of Chinese fir plantations along a chronosequence - Wu, Huili; Xiang, Wenhua; Ouyang, Shuai; Xiao, Wenfa; Li, Shenggong; Chen, Liang; Lei, Pifeng; Deng, Xiangwen; Zeng, Yelin; Zeng, Lixiong; Peng, Changhui (Forest Ecology and Management, 2020)

Aerial spraying of bacterial insecticides to control spruce budworm defoliation leads to reduced carbon losses - Liu, Zelin; Peng, Changhui; De Grandpré, Louis; Candau, Jean‐Noël; Work, Timothy; Zhou, Xiaolu; Kneeshaw, Daniel (Ecosphere, 2020)
Abstract Spruce budworm (SBW) outbreaks are a major natural disturbance in boreal forests of eastern North America. During large‐scale infestations, aerial spraying of bacterial insecticides is used to suppress local high‐density SBW populations. While the primary goal of spraying is the protection of wood volume for later harvest, it should also maintain carbon stored in trees. This study provides the first quantitative analysis of the efficacy of aerial spraying against SBW on carbon dynamics in balsam fir, spruce, and mixed fir–spruce forests. In this study, we used the TRIPLEX‐Insect model to simulate carbon dynamics with and without spray applications in 14 sites of the boreal forest located in various regions of Québec. We found that the efficacy of aerial spraying on reducing annual defoliation was greater in the early stage (<5 yr since the outbreak began) of the outbreak than in later (5–10 yr since the outbreak began) stage. Our results showed that more net ecosystem productivity is maintained in balsam fir (the most vulnerable species) than in either spruce or mixed fir–spruce forests following spraying. Also, average losses in aboveground biomass due to the SBW following spraying occurred more slowly than without spraying in balsam fir forests. Our findings suggest that aerial spraying could be used to maintain carbon in conifer forests during SBW disturbances, but that the efficacy of spray programs is affected by host species and stage of the SBW outbreak.

Soil GHG fluxes are altered by N deposition: New data indicate lower N stimulation of the N2 O flux and greater stimulation of the calculated C pools - Deng, Lei; Huang, Chunbo; Kim, Dong‐Gill; Shangguan, Zhouping; Wang, Kaibo; Song, Xinzhang; Peng, Changhui (Global Change Biology, 2020)
Abstract The effects of nitrogen (N) deposition on soil organic carbon (C) and greenhouse gas (GHG) emissions in terrestrial ecosystems are the main drivers affecting GHG budgets under global climate change. Although many studies have been conducted on this topic, we still have little understanding of how N deposition affects soil C pools and GHG budgets at the global scale. We synthesized a comprehensive dataset of 275 sites from multiple terrestrial ecosystems around the world and quantified the responses of the global soil C pool and GHG fluxes induced by N enrichment. The results showed that the soil organic C concentration and the soil CO 2 , CH 4 and N 2 O emissions increased by an average of 3.7%, 0.3%, 24.3% and 91.3% under N enrichment, respectively, and that the soil CH 4 uptake decreased by 6.0%. Furthermore, the percentage increase in N 2 O emissions (91.3%) was two times lower than that (215%) reported by Liu and Greaver ( Ecology Letters , 2009, 12:1103–1117). There was also greater stimulation of soil C pools (15.70 kg C ha −1 year −1 per kg N ha −1 year −1 ) than previously reported under N deposition globally. The global N deposition results showed that croplands were the largest GHG sources (calculated as CO 2 equivalents), followed by wetlands. However, forests and grasslands were two important GHG sinks. Globally, N deposition increased the terrestrial soil C sink by 6.34 Pg CO 2 /year. It also increased net soil GHG emissions by 10.20 Pg CO 2 ‐Geq (CO 2 equivalents)/year. Therefore, N deposition not only increased the size of the soil C pool but also increased global GHG emissions, as calculated by the global warming potential approach.

Global vegetation biomass production efficiency constrained by models and observations - He, Yue; Peng, Shushi; Liu, Yongwen; Li, Xiangyi; Wang, Kai; Ciais, Philippe; Arain, M. Altaf; Fang, Yuanyuan; Fisher, Joshua B.; Goll, Daniel; Hayes, Daniel; Huntzinger, Deborah N.; et al. (Global Change Biology, 2020)
Abstract Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon–nitrogen interactions tend to be more realistic. Using observation‐based estimates of global photosynthesis, we quantify the global BP of non‐cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model‐estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Nitrogen addition increased CO2 uptake more than non-CO2 greenhouse gases emissions in a Moso bamboo forest - Song, Xinzhang; Peng, Changhui; Ciais, Philippe; Li, Quan; Xiang, Wenhua; Xiao, Wenfa; Zhou, Guomo; Deng, Lei (Science Advances, 2020)
Moso bamboo forests have greater net carbon uptake benefits with increasing nitrogen deposition in the coming decades. , Atmospheric nitrogen (N) deposition affects the greenhouse gas (GHG) balance of ecosystems through the net atmospheric CO 2 exchange and the emission of non-CO 2 GHGs (CH 4 and N 2 O). We quantified the effects of N deposition on biomass increment, soil organic carbon (SOC), and N 2 O and CH 4 fluxes and, ultimately, the net GHG budget at ecosystem level of a Moso bamboo forest in China. Nitrogen addition significantly increased woody biomass increment and SOC decomposition, increased N 2 O emission, and reduced soil CH 4 uptake. Despite higher N 2 O and CH 4 fluxes, the ecosystem remained a net GHG sink of 26.8 to 29.4 megagrams of CO 2 equivalent hectare −1 year −1 after 4 years of N addition against 22.7 hectare −1 year −1 without N addition. The total net carbon benefits induced by atmospheric N deposition at current rates of 30 kilograms of N hectare −1 year −1 over Moso bamboo forests across China were estimated to be of 23.8 teragrams of CO 2 equivalent year −1 .

Evaluating soil nutrients of Dacrydium pectinatum in China using machine learning techniques - Wu, Chunyan; Chen, Yongfu; Hong, Xiaojiang; Liu, Zelin; Peng, Changhui (Forest Ecosystems, 2020)
Abstract Background The accurate estimation of soil nutrient content is particularly important in view of its impact on plant growth and forest regeneration. In order to investigate soil nutrient content and quality for the natural regeneration of Dacrydium pectinatum communities in China, designing advanced and accurate estimation methods is necessary. Methods This study uses machine learning techniques created a series of comprehensive and novel models from which to evaluate soil nutrient content. Soil nutrient evaluation methods were built by using six support vector machines and four artificial neural networks. Results The generalized regression neural network model was the best artificial neural network evaluation model with the smallest root mean square error (5.1), mean error (− 0.85), and mean square prediction error (29). The accuracy rate of the combined k -nearest neighbors ( k -NN) local support vector machines model (i.e. k -nearest neighbors -support vector machine (KNNSVM)) for soil nutrient evaluation was high, comparing to the other five partial support vector machines models investigated. The area under curve value of generalized regression neural network (0.6572) was the highest, and the cross-validation result showed that the generalized regression neural network reached 92.5%. Conclusions Both the KNNSVM and generalized regression neural network models can be effectively used to evaluate soil nutrient content and quality grades in conjunction with appropriate model variables. Developing a new feasible evaluation method to assess soil nutrient quality for Dacrydium pectinatum , results from this study can be used as a reference for the adaptive management of rare and endangered tree species. This study, however, found some uncertainties in data acquisition and model simulations, which will be investigated in upcoming studies.

Contrasting responses of soil exoenzymatic interactions and the dissociated carbon transformation to short- and long-term drainage in a minerotrophic peatland - Li, Tong; Ge, Leming; Huang, Jingjing; Yuan, Xin; Peng, Changhui; Wang, Shengzhong; Bu, Zhaojun; Zhu, Qiuan; Wang, Zucheng; Liu, Weiguo; Wang, Meng (Geoderma, 2020)

Interspecific difference in N:P stoichiometric homeostasis drives nutrient release and soil microbial community composition during decomposition - Song, Hanxiong; Huang, Jingjing; Ge, Leming; Peng, Changhui; Zhao, Pengxiang; Guo, Xinyi; Li, Tong; Shen, Xiaojuan; Zhu, Qiuan; Liu, Weiguo; Wei, Hua; Wang, Meng (Plant and Soil, 2020)

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand? - Paschalis, Athanasios; Fatichi, Simone; Zscheischler, Jakob; Ciais, Philippe; Bahn, Michael; Boysen, Lena; Chang, Jinfeng; De Kauwe, Martin; Estiarte, Marc; Goll, Daniel; Hanson, Paul J.; Harper, Anna B.; et al. (Global Change Biology, 2020)
Abstract Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

The impact of intensive management on net ecosystem productivity and net primary productivity of a Lei bamboo forest - Zhang, Minxia; Chen, Shulin; Jiang, Hong; Peng, Changhui; Zhang, Jinmeng; Zhou, Guomo (Ecological Modelling, 2020)

Long-term forest succession improves plant diversity and soil quality but not significantly increase soil microbial diversity: Evidence from the Loess Plateau - Liu, Yulin; Zhu, Guangyu; Hai, Xuying; Li, Jiwei; Shangguan, Zhouping; Peng, Changhui; Deng, Lei (Ecological Engineering, 2020)

No evidence for carryover effect in tree rings based on a pulse-labelling experiment on Juniperus communis in South Germany - He, Minhui; Bräuning, Achim; Rossi, Sergio; Gebrekirstos, Aster; Grießinger, Jussi; Mayr, Christoph; Peng, Changhui; Yang, Bao (Trees, 2021)

Effects of Nitrogen Additions on Soil Respiration in an Asian Tropical Montane Rainforest - Wu, Fangtao; Peng, Changhui; Liu, Weiguo; Liu, Zhihao; Wang, Hui; Chen, Dexiang; Li, Yide (Forests, 2021)
Understanding the impacts of nitrogen (N) addition on soil respiration (RS) and its temperature sensitivity (Q10) in tropical forests is very important for the global carbon cycle in a changing environment. Here, we investigated how RS respond to N addition in a tropical montane rainforest in Southern China. Four levels of N treatments (0, 25, 50, and 100 kg N ha−1 a−1 as control (CK), low N (N25), moderate N (N50), and high N (N100), respectively) were established in September 2010. Based on a static chamber-gas chromatography method, RS was measured from January 2015 to December 2018. RS exhibited significant seasonal variability, with low RS rates appeared in the dry season and high rates appeared in the wet season regardless of treatment. RS was significantly related to the measured soil temperature and moisture. Our results showed that soil RS increased after N additions, the mean annual RS was 7% higher in N25 plots, 8% higher in N50 plots, and 11% higher in N100 plots than that in the CK plots. However, the overall impacts of N additions on RS were statistically insignificant. For the entire study period, the CK, N25, N50, and N100 treatments yielded Q10 values of 2.27, 3.45, 4.11, and 2.94, respectively. N addition increased the temperature sensitivity (Q10) of RS. Our results suggest that increasing atmospheric N deposition may have a large impact on the stimulation of soil CO2 emissions from tropical rainforests in China.

Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China - Ren, Peixin; Liu, Zelin; Zhou, Xiaolu; Peng, Changhui; Xiao, Jingfeng; Wang, Songhan; Li, Xing; Li, Peng (Forest Ecosystems, 2021)
Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGS sif and EGS evi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient - Yang, Yanzheng; Gou, Ruikun; Li, Wei; Kassout, Jalal; Wu, Jun; Wang, Liming; Peng, Changhui; Lin, Guanghui (Journal of Geophysical Research: Biogeosciences, 2021)
Abstract Elevation gradients are frequently treated as useful space‐for‐time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass ( N mass ), leaf nitrogen per unit area ( N area ), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal‐to‐ambient CO 2 ratio ( C i : C a , termed χ ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analyzed using multivariate analysis and variance partitioning procedures. We found that (a) The first three principal components captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (b) N mass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapor pressure deficit (VPD), while χ showed negative relationships with elevation; and (c) 78% of the variation in the studied plant functional traits could be explained by climate, soil, and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning. , Plain Language Summary Changes of plant functional traits along elevation gradient are important indicators which reflect the behaviors and adaptations of plants. In this study we first analyzed the dominant signals of seven leaf functional traits and then we depicted the response of seven traits to changing elevation environments, and finally we quantified the contributions of climate, soil, and vegetation distribution. Our findings validate the hypothesis that trait covariation, and thus adaptation, occurs in response to the elevation gradients that most plant species experience. , Key Points The first three principal components captured 79% of the total leaf trait covariation Leaf nitrogen content ( N mass ) and leaf dry mass content (LDMC) were positively correlated with soil water content and negatively correlated with vapor pressure deficit Vegetation (family) distribution was the most important determining factor for trait covariation along the elevation gradient

A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services - Niu, Zhongen; He, Honglin; Peng, Shushi; Ren, Xiaoli; Zhang, Li; Gu, Fengxue; Zhu, Gaofeng; Peng, Changhui; Li, Pan; Wang, Junbang; Ge, Rong; Zeng, Na; et al. (Journal of Advances in Modeling Earth Systems, 2021)
Abstract Terrestrial ecosystems provide multiple services interacting in complex ways. However, most ecosystem services (ESs) models (e.g., InVEST and ARIES) ignored the relationships among ESs. Process‐based models can overcome this limitation, and the integration of ecological models with remote sensing data could greatly facilitate the investigation of the complex ecological processes. Therefore, based on the Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA) models, we developed a process‐based ES model (CEVSA‐ES) integrating remotely sensed leaf area index to evaluate four important ESs (i.e., productivity provision, carbon sequestration, water retention, and soil retention) at annual timescale in China. Compared to the traditional terrestrial biosphere models, the main innovation of CEVSA‐ES model was the consideration of soil erosion processes and its impact on carbon cycling. The new version also improved the carbon‐water cycle algorithms. Then, the Sobol and DEMC methods that integrated the CEVSA‐ES model with nine flux sites comprising 39 site‐years were used to identify and optimize parameters. Finally, the model using the optimized parameters was validated at 26 field sites comprising 135 site‐years. Simulation results showed good fits with ecosystem processes, explaining 95%, 92%, 76%, and 65% interannual variabilities of gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration, respectively. The CEVSA‐ES model performed well for productivity provision and carbon sequestration, which explained 96% and 81% of the spatial‐temporal variations of the observed annual productivity provision and carbon sequestration, respectively. The model also captured the interannual trends of water retention and soil erosion for most sites or basins. , Plain Language Summary Terrestrial ecosystems simultaneously provide multiple ecosystem services (ESs). The common environmental drivers and internal mechanisms lead to nonlinear and dynamic relationships among ESs. Assessing the spatiotemporal changes of ESs have recently emerged as an element of ecosystem management and environmental policies. However, appropriate methods linking ESs to biogeochemical and biophysical processes are still lacking. In this study, we developed a process‐based model Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA‐ES) that integrates remote sensing data for evaluating ESs. We first described the model framework and detailed algorithms of the processes related to ESs. Then a model‐fusion method was applied to optimize parameters to which the model was sensitive and to improve model performance based on multi‐source observational data. The calibrated CEVSA‐ES model showed good performance for carbon and water fluxes (i.e., gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration). The CEVSA‐ES model performed well for productivity provision, and carbon sequestration. It also captured the interannual trends of water retention and soil erosion for most sites or basins in Chinese terrestrial ecosystems. The CEVSA‐ES model not only has the potential to improve the accuracy of simulated ESs, but also can capture the relationships among ESs, which could support the trade‐offs and synergies among ESs. , Key Points We developed an ecosystem service model Carbon and Exchange between Vegetation, Soil, and Atmosphere‐ecosystem services (CEVSA‐ES) that integrates ecosystem processes with satellite‐based data Accounting for soil retention/erosion and its impact on carbon cycling was the main difference from other process‐based models The CEVSA‐ES model with optimized parameters explained 47%–96% of the spatial and temporal variations of four ecosystem services in China

Vulnerability of maize, millet, and rice yields to growing season precipitation and socio-economic proxies in Cameroon - Epule, Terence Epule; Chehbouni, Abdelghani; Dhiba, Driss; Etongo, Daniel; Driouech, Fatima; Brouziyne, Youssef; Peng, Changhui (PLOS ONE, 2021)
In sub-Saharan Africa growing season precipitation is affected by climate change. Due to this, in Cameroon, it is uncertain how some crops are vulnerable to growing season precipitation. Here, an assessment of the vulnerability of maize, millet, and rice to growing season precipitation is carried out at a national scale and validated at four sub-national scales/sites. The data collected were historical yield, precipitation, and adaptive capacity data for the period 1961–2019 for the national scale analysis and 1991–2016 for the sub-national scale analysis. The crop yield data were collected for maize, millet, and rice from FAOSTAT and the global yield gap atlas to assess the sensitivity both nationally and sub-nationally. Historical data on mean crop growing season and mean annul precipitation were collected from a collaborative database of UNDP/Oxford University and the climate portal of the World Bank to assess the exposure both nationally and sub-nationally. To assess adaptive capacity, literacy, and poverty rate proxies for both the national and regional scales were collected from KNOEMA and the African Development Bank. These data were analyzed using a vulnerability index that is based on sensitivity, exposure, and adaptive capacity. The national scale results show that millet has the lowest vulnerability index while rice has the highest. An inverse relationship between vulnerability and adaptive capacity is observed. Rice has the lowest adaptive capacity and the highest vulnerability index. Sub-nationally, this work has shown that northern maize is the most vulnerable crop followed by western highland rice. This work underscores the fact that at different scales, crops are differentially vulnerable due to variations in precipitation, temperature, soils, access to farm inputs, exposure to crop pest and variations in literacy and poverty rates. Therefore, caution should be taken when transitioning from one scale to another to avoid generalization. Despite these differences, in the sub-national scale, western highland rice is observed as the second most vulnerable crop, an observation similar to the national scale observation.

The Characteristics and Seasonal Variation of Methane Fluxes From an Alpine Wetland in the Qinghai Lake watershed, China - Wu, Fangtao; Cao, Shengkui; Cao, Guangchao; Chen, Kelong; Peng, Changhui (Wetlands, 2021)

Effect of Grazing Intensities on Soil N2O Emissions from an Alpine Meadow of Zoige Plateau in China - Zhan, Wei; Yang, Zhenan; Liu, Jianliang; Chen, Huai; Yang, Gang; Zhu, Erxiong; Hu, Ji; Jiang, Lin; Liu, Liangfeng; Zhu, Dan; He, Yixin; Zhao, Chuan; et al. (Atmosphere, 2021)
The alpine meadow of Zoige Plateau plays a key role in local livestock production of cattle and sheep. However, it remains unclear how animal grazing or its intensity affect nitrous oxide (N2O) emissions, and the main driving factors. A grazing experiment including four grazing intensities (G0, G0.7, G1.2, G1.6 yak ha−1) was conducted between January 2013 and December 2014 to evaluate the soil nitrous oxide (N2O) fluxes under different grazing intensities in an alpine meadow on the eastern Qinghai–Tibet Plateau of China. The N2O fluxes were examined with gas collected by the static chamber method and by chromatographic concentration analysis. N2O emissions in the growing seasons (from May to September) were lower than that in non-growing seasons (from October to April) in 2013, 1.94 ± 0.30 to 3.37 ± 0.56 kg N2O ha−1 yr−1. Annual mean N2O emission rates were calculated as 1.17 ± 0.50 kg N2O ha−1 yr−1 in non-grazing land (G0) and 1.94 ± 0.23 kg N2O ha−1 yr−1 in the grazing land (G0.7, G1.2, and G1.6). The annual mean N2O flux showed no significant differences between grazing treatments in 2013. However, there were significantly greater fluxes from the G0.7 treatment than from the G1.6 treatment in 2014, especially in the growing season. Over the two years, the soil N2O emission rate was significantly negatively correlated with soil water-filled pore space (WFPS) and dissolved organic carbon (DOC) content as well as positively correlated with soil available phosphorus (P). No relationship was observed between soil N2O emission rate and temperature or rainfall. Our results showed that the meadow soils acted as a source of N2O for most periods and turned into a weak sink of N2O later during the sampling period. Our results highlight the importance of proper grazing intensity in reducing N2O emissions from alpine meadow. The interaction between grazing intensity and N2O emissions should be of more concern during future management of pastures in Zoige Plateau.

Identifying maize yield and precipitation gaps in Uganda - Epule, Terence Epule; Dhiba, Driss; Etongo, Daniel; Peng, Changhui; Lepage, Laurent (SN Applied Sciences, 2021)
Abstract In sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.

Decoupling the Complementarity Effect and the Selection Effect on the Overyielding of Fine Root Production Along a Tree Species Richness Gradient in Subtropical Forests - Liu, Cong; Xiang, Wenhua; Xie, Binggeng; Ouyang, Shuai; Zeng, Yelin; Lei, Pifeng; Peng, Changhui (Ecosystems, 2021)

Nitrogen addition mediates the response of foliar stoichiometry to phosphorus addition: a meta-analysis - You, Chengming; Peng, Changhui; Xu, Zhenfeng; Liu, Yang; Zhang, Li; Yin, Rui; Liu, Lin; Li, Han; Wang, Lixia; Liu, Sining; Tan, Bo; Kardol, Paul (Ecological Processes, 2021)
Abstract Background Changes in foliar nitrogen (N) and phosphorus (P) stoichiometry play important roles in predicting the effects of global change on ecosystem structure and function. However, there is substantial debate on the effects of P addition on foliar N and P stoichiometry, particularly under different levels of N addition. Thus, we conducted a global meta-analysis to investigate how N addition alters the effects of P addition on foliar N and P stoichiometry across different rates and durations of P addition and plant growth types based on more than 1150 observations. Results We found that P addition without N addition increased foliar N concentrations, whereas P addition with N addition had no effect. The positive effects of P addition on foliar P concentrations were greater without N addition than with N addition. Additionally, the effects of P addition on foliar N, P and N:P ratios varied with the rate and duration of P addition. In particular, short-term or low-dose P addition with and without N addition increased foliar N concentration, and the positive effects of short-term or low-dose P addition on foliar P concentrations were greater without N addition than with N addition. The responses of foliar N and P stoichiometry of evergreen plants to P addition were greater without N addition than with N addition. Moreover, regardless of N addition, soil P availability was more effective than P resorption efficiency in predicting the changes in foliar N and P stoichiometry in response to P addition. Conclusions Our results highlight that increasing N deposition might alter the response of foliar N and P stoichiometry to P addition and demonstrate the important effect of the experimental environment on the results. These results advance our understanding of the response of plant nutrient use efficiency to P addition with increasing N deposition.

Gross Ecosystem Productivity Dominates the Control of Ecosystem Methane Flux in Rice Paddies - Li, Hong; Zhao, Min; Peng, Changhui; Guo, Haiqiang; Wang, Qing; Zhao, Bin (Land, 2021)
Although rice paddy fields are one of the world’s largest anthropogenic sources of methane CH4, the budget of ecosystem CH4 and its’ controls in rice paddies remain unclear. Here, we analyze seasonal dynamics of direct ecosystem-scale measurements of CH4 flux in a rice-wheat rotation agroecosystem over 3 consecutive years. Results showed that the averaged CO2 uptakes and CH4 emissions in rice seasons were 2.2 and 20.9 folds of the wheat seasons, respectively. In sum, the wheat-rice rotation agroecosystem acted as a large net C sink (averaged 460.79 g C m−2) and a GHG (averaged 174.38 g CO2eq m−2) source except for a GHG sink in one year (2016) with a very high rice seeding density. While the linear correlation between daily CH4 fluxes and gross ecosystem productivity (GEP) was not significant for the whole rice season, daily CH4 fluxes were significantly correlated to daily GEP both before (R2: 0.52–0.83) and after the mid-season drainage (R2: 0.71–0.79). Furthermore, the F partial test showed that GEP was much greater than that of any other variable including soil temperature for the rice season in each year. Meanwhile, the parameters of the best-fit functions between daily CH4 fluxes and GEP shifted between rice growth stages. This study highlights that GEP is a good predictor of daily CH4 fluxes in rice paddies.

Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change - Li, Peng; Liu, Zelin; Zhou, Xiaolu; Xie, Binggeng; Li, Zhongwu; Luo, Yunpeng; Zhu, Qiuan; Peng, Changhui (Agricultural and Forest Meteorology, 2021)

Analysis and Prediction of Expansion of Central Cities Based on Nighttime Light Data in Hunan Province, China - Liu, Yuxin; He, Tian; Wang, Yi; Peng, Changhui; Du, Hui; Yuan, Shuai; Li, Peng (Sustainability, 2021)
Quantifying the characteristics of urban expansion as well as influencing factors is essential for the simulation and prediction of urban expansion. In this study, we extracted the built-up regions of 14 central cities in the Hunan province using the DMSP-OLS night light remote sensing datasets from 1992 to 2018, and evaluated the spatial and temporal characteristics of the built-up regions in terms of the area, expansion speed, and main expansion direction. The backpropagation (BP) neural network and autoregressive integrated moving average (ARIMA) model were used to predict the area of the built-up regions from 2019 to 2026. The model predictions were based on the GDP, ratio of the secondary industry output to the GDP, ratio of the tertiary industry output to the GDP, year-end urban population, and urban road area. The results demonstrated that the built-up area and expansion speed of the central cities in the eastern part of the Hunan province were significantly higher than those in the western part. The main expansion directions of the 14 central cities were east and south. The urban road area, year-end urban population, and GDP were the main driving factors of the expansion. The urban expansion model based on the BP neural network provided a high prediction accuracy (R = 0.966). It was estimated that the total area of urban built-up regions in the Hunan province will reach 2463.80 km2 by 2026. These findings provide a new perspective for predicting urban areas rapidly and simply, and it also provides a useful reference for studying the spatial expansion characteristics of central cities and formulating a sustainable urban development strategy during the 14th Five-Year Plan of China.

Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient - Yang, Yanzheng; Kang, Le; Zhao, Jun; Qi, Ning; Li, Ruonan; Wen, Zhongming; Kassout, Jalal; Peng, Changhui; Lin, Guanghui; Zheng, Hua (Biology, 2021)
A trait-based approach is an effective way to quantify plant adaptation strategies in response to changing environments. Single trait variations have been well depicted before; however, multi-trait covariations and their roles in shaping plant adaptation strategies along aridity gradients remain unclear. The purpose of this study was to reveal multi-trait covariation characteristics, their controls and their relevance to plant adaptation strategies. Using eight relevant plant functional traits and multivariate statistical approaches, we found the following: (1) the eight studied traits show evident covariation characteristics and could be grouped into four functional dimensions linked to plant strategies, namely energy balance, resource acquisition, resource investment and water use efficiency; (2) leaf area (LA) together with traits related to the leaf economic spectrum, including leaf nitrogen content per area (Narea), leaf nitrogen per mass (Nmass) and leaf dry mass per area (LMA), covaried along the aridity gradient (represented by the moisture index, MI) and dominated the trait–environmental change axis; (3) together, climate, soil and family can explain 50.4% of trait covariations; thus, vegetation succession along the aridity gradient cannot be neglected in trait covariations. Our findings provide novel perspectives toward a better understanding of plant adaptations to arid conditions and serve as a reference for vegetation restoration and management programs in arid regions.

Observed Methane Uptake and Emissions at the Ecosystem Scale and Environmental Controls in a Subtropical Forest - Wang, Hui; Li, Hong; Liu, Zhihao; Lv, Jianhua; Song, Xinzhang; Li, Quan; Jiang, Hong; Peng, Changhui (Land, 2021)
Methane (CH4) is one of the three most important greenhouse gases. To date, observations of ecosystem-scale methane (CH4) fluxes in forests are currently lacking in the global CH4 budget. The environmental factors controlling CH4 flux dynamics remain poorly understood at the ecosystem scale. In this study, we used a state-of-the-art eddy covariance technique to continuously measure the CH4 flux from 2016 to 2018 in a subtropical forest of Zhejiang Province in China, quantify the annual CH4 budget and investigate its control factors. We found that the total annual CH4 budget was 1.15 ± 0.28~4.79 ± 0.49 g CH4 m−2 year−1 for 2017–2018. The daily CH4 flux reached an emission peak of 0.145 g m−2 d−1 during winter and an uptake peak of −0.142 g m−2 d−1 in summer. During the whole study period, the studied forest region acted as a CH4 source (78.65%) during winter and a sink (21.35%) in summer. Soil temperature had a negative relationship (p < 0.01; R2 = 0.344) with CH4 flux but had a positive relationship with soil moisture (p < 0.01; R2 = 0.348). Our results showed that soil temperature and moisture were the most important factors controlling the ecosystem-scale CH4 flux dynamics of subtropical forests in the Tianmu Mountain Nature Reserve in Zhejiang Province, China. Subtropical forest ecosystems in China acted as a net source of methane emissions from 2016 to 2018, providing positive feedback to global climate warming.

Response of Vegetation Photosynthetic Phenology to Urbanization in Dongting Lake Basin, China - Li, Peng; Sun, Mai; Liu, Yuxin; Ren, Peixin; Peng, Changhui; Zhou, Xiaolu; Tang, Jiayi (Remote Sensing, 2021)
Urbanization can induce environmental changes such as the urban heat island effect, which in turn influence the terrestrial ecosystem. However, the effect of urbanization on the phenology of subtropical vegetation remains relatively unexplored. This study analyzed the changing trend of vegetation photosynthetic phenology in Dongting Lake basin, China, and its response to urbanization using nighttime light and chlorophyll fluorescence datasets. Our results indicated the start of the growing season (SOS) of vegetation in the study area was significantly advanced by 0.70 days per year, whereas the end of the growing season (EOS) was delayed by 0.24 days per year during 2000–2017. We found that urbanization promoted the SOS advance and EOS delay. With increasing urbanization intensity, the sensitivity of SOS to urbanization firstly increased then decreased, while the sensitivity of EOS to urbanization decreased with urbanization intensity. The climate sensitivity of vegetation phenology varied with urbanization intensity; urbanization induced an earlier SOS by increasing preseason minimum temperatures and a later EOS by increasing preseason precipitation. These findings improve our understanding of the vegetation phenology response to urbanization in subtropical regions and highlight the need to integrate human activities into future vegetation phenology models.

Temperature and Moisture Modulate the Contribution of Soil Fauna to Litter Decomposition via Different Pathways - Tan, Bo; Yin, Rui; Zhang, Jian; Xu, Zhenfeng; Liu, Yang; He, Shuqin; Zhang, Li; Li, Han; Wang, Lixia; Liu, Sining; You, Chengming; Peng, Changhui (Ecosystems, 2021)

Modern cities modelled as “super‐cells” rather than multicellular organisms: Implications for industry, goods and services - Chang, Jie; Ge, Ying; Wu, Zhaoping; Du, Yuanyuan; Pan, Kaixuan; Yang, Guofu; Ren, Yuan; Heino, Mikko P.; Mao, Feng; Cheong, Kang Hao; Qu, Zelong; Fan, Xing; et al. (BioEssays, 2021)
Abstract The structure and “metabolism” (movement and conversion of goods and energy) of urban areas has caused cities to be identified as “super‐organisms”, placed between ecosystems and the biosphere, in the hierarchy of living systems. Yet most such analogies are weak, and render the super‐organism model ineffective for sustainable development of cities. Via a cluster analysis of 15 shared traits of the hierarchical living system, we found that industrialized cities are more similar to eukaryotic cells than to multicellular organisms; enclosed systems, such as factories and greenhouses, paralleling organelles in eukaryotic cells. We further developed a “super‐cell” industrialized city model: a “eukarcity” with citynucleus (urban area) as a regulating centre, and organaras (enclosed systems, which provide the majority of goods and services) as the functional components, and cityplasm (natural ecosystems and farmlands) as the matrix. This model may improve the vitality and sustainability of cities through planning and management.

Water table drawdown increases plant biodiversity and soil polyphenol in the Zoige Plateau - Zeng, Jia; Chen, Huai; Bai, Yinping; Dong, Faqin; Peng, Changhui; Yan, Fei; Cao, Qin; Yang, Zhenan; Yang, Suizhuang; Yang, Gang (Ecological Indicators, 2021)

African climate change policy performance index - Epule, Terence Epule; Chehbouni, Abdelghani; Dhiba, Driss; Moto, Mirielle Wase; Peng, Changhui (Environmental and Sustainability Indicators, 2021)

Woody plants reduce the sensitivity of soil extracellular enzyme activity to nutrient enrichment in wetlands: A meta-analysis - Li, Tong; Peng, Changhui; Bu, Zhaojun; Zhu, Qiuan; Song, Hanxiong; Guo, Xinyi; Wang, Meng (Soil Biology and Biochemistry, 2021)

Ecosystem service multifunctionality of Chinese fir plantations differing in stand age and implications for sustainable management - Zeng, Yelin; Wu, Huili; Ouyang, Shuai; Chen, Liang; Fang, Xi; Peng, Changhui; Liu, Shirong; Xiao, Wenfa; Xiang, Wenhua (Science of The Total Environment, 2021)

TRIPLEX-Mortality model for simulating drought-induced tree mortality in boreal forests: Model development and evaluation - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; Liu, Zelin; Zhou, Xiaolu; Kneeshaw, Daniel (Ecological Modelling, 2021)

Evaluation of Future Impacts of Climate Change, CO2, and Land Use Cover Change on Global Net Primary Productivity Using a Processed Model - Hu, Xiao; He, Yujie; Kong, Ze; Zhang, Jiang; Yuan, Minshu; Yu, Le; Peng, Changhui; Zhu, Qiuan (Land, 2021)
Few studies have focused on the combined impact of climate change, CO2, and land-use cover change (LUCC), especially the evaluation of the impact of LUCC on net primary productivity (NPP) in the future. In this study, we simulated the overall NPP change trend from 2010 to 2100 and its response to climatic factors, CO2 concentration, and LUCC conditions under three typical emission scenarios (Representative Concentration Pathway RCP2.6, RCP4.5, and RCP8.5). (1) Under the predicted global pattern, NPP showed an increasing trend, with the most prominent variation at the end of the century. The increasing trend is mainly caused by the positive effect of CO2 on NPP. However, the increasing trend of LUCC has only a small positive effect. (2) Under the RCP 8.5 scenario, from 2090 to 2100, CO2 has the most significant positive impact on tropical areas, reaching 8.328 Pg C Yr−1. Under the same conditions, climate change has the greatest positive impact on the northern high latitudes (1.175 Pg C Yr−1), but it has the greatest negative impact on tropical areas, reaching −4.842 Pg C Yr−1. (3) The average contribution rate of LUCC to NPP was 6.14%. Under the RCP8.5 scenario, LUCC made the largest positive contribution on NPP (0.542 Pg C Yr−1) globally from 2010 to 2020.

Headwater stream ecosystem: an important source of greenhouse gases to the atmosphere - Li, Mingxu; Peng, Changhui; Zhang, Kerou; Xu, Li; Wang, Jianming; Yang, Yan; Li, Peng; Liu, Zelin; He, Nianpeng (Water Research, 2021)

Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method - Meng, Yanrong; Yang, Mingxia; Liu, Shan; Mou, Yuling; Peng, Changhui; Zhou, Xiaolu (Ecological Informatics, 2021)

Drought effects on soil carbon and nitrogen dynamics in global natural ecosystems - Deng, Lei; Peng, Changhui; Kim, Dong-Gill; Li, Jiwei; Liu, Yulin; Hai, Xuying; Liu, Qiuyu; Huang, Chunbo; Shangguan, Zhouping; Kuzyakov, Yakov (Earth-Science Reviews, 2021)

Global response of terrestrial gross primary productivity to climate extremes - Yuan, Minshu; Zhu, Qiuan; Zhang, Jiang; Liu, Jinxun; Chen, Huai; Peng, Changhui; Li, Peng; Li, Mingxu; Wang, Meng; Zhao, Pengxiang (Science of The Total Environment, 2021)

Nitrogen, water content, phosphorus and active iron jointly regulate soil organic carbon in tropical acid red soil forest - Bai, Jinyue; Zong, Mingming; Li, Shiyu; Li, Haixia; Duan, Changqun; Feng, Yuan; Peng, Changhui; Zhang, Xiaoling; Sun, Di; Lin, Chen; Shi, Yucheng; Zheng, Guangyu; et al. (European Journal of Soil Science, 2021)
Abstract Increasing forest soil organic carbon (SOC) storage is important for reducing carbon dioxide (CO 2 ) emissions from terrestrial ecosystems and mitigating global climate change. Although the effects of altitude, temperature and rainfall on organic carbon have been studied extensively, it is difficult to increase SOC storage by changing these factors in actual forest management. This study determined the SOC, soil physical and chemical properties, nutrient elements, heavy metal elements, soil minerals and microbial biomass in the 0–140‐cm soil layer of the monsoon broad‐leaved forest in the acid red soil region of southwestern China by stratification. We tried to identify the soil factors affecting the SOC storage of the forest in the acid red soil region and determine the weights of the factors affecting the SOC, with the aim of improving the SOC retention capacity in forest management by changing the main soil factors affecting SOC storage. The results showed that the soil factors affecting the forest SOC storage in this area are total nitrogen (N, 22.7%) > soil water content (19.9%) > active iron (including poorly crystalline iron, Fe o , 15.5%) > pH (9.5%) > phosphorus (P, 9.4%) > aluminium (Al, 8.9%) > silicon (Si, 7.1%) > sulphur (S, 6.8%). Of these factors, N, the water content, Fe o , and P are practical factors for forest management, whereas the pH, Al, Si and S are not. SOC was significantly positively correlated with the soil N concentration, water content, active iron content and P concentration ( p < .05). In acidic red soil areas, with active iron as the highlight, N, soil water content, phosphorus and active iron jointly regulate the forest SOC storage capacity. Consequently, in actual forest management, any measures to promote soil N and water content and to activate inactive iron can enhance the storage of SOC, as appropriate input of N and P fertiliser and irrigation in dry years and the dry season. Highlights The soil environmental factors affecting SOC storage in forest soil are quantified Activation of inactive iron helps SOC storage in forest soil Irrigation and N and P input are effective for helping SOC storage in forest soil N, WC, P and Fe o jointly regulate SOC in tropical acid red soil forest

Management scheme influence and nitrogen addition effects on soil CO2, CH4, and N2O fluxes in a Moso bamboo plantation - Zhang, Junbo; Li, Quan; Lv, Jianhua; Peng, Changhui; Gu, Zhikang; Qi, Lianghua; Song, Xuzhong; Song, Xinzhang (Forest Ecosystems, 2021)
Abstract Background It is still not clear whether the effects of N deposition on soil greenhouse gas (GHG) emissions are influenced by plantation management schemes. A field experiment was conducted to investigate the effects of conventional management (CM) versus intensive management (IM), in combination with simulated N deposition levels of control (ambient N deposition), 30 kg N·ha − 1 ·year − 1 (N30, ambient + 30 kg N·ha − 1 ·year − 1 ), 60 kg N·ha − 1 ·year − 1 (N60, ambient + 60 kg N·ha − 1 ·year − 1 ), or 90 kg N·ha − 1 ·year − 1 (N90, ambient + 90 kg N·ha − 1 ·year − 1 ) on soil CO 2 , CH 4 , and N 2 O fluxes. For this, 24 plots were set up in a Moso bamboo ( Phyllostachys edulis ) plantation from January 2013 to December 2015. Gas samples were collected monthly from January 2015 to December 2015. Results Compared with CM, IM significantly increased soil CO 2 emissions and their temperature sensitivity ( Q 10 ) but had no significant effects on soil CH 4 uptake or N 2 O emissions. In the CM plots, N30 and N60 significantly increased soil CO 2 emissions, while N60 and N90 significantly increased soil N 2 O emissions. In the IM plots, N30 and N60 significantly increased soil CO 2 and N 2 O emissions, while N60 and N90 significantly decreased soil CH 4 uptake. Overall, in both CM and IM plots, N30 and N60 significantly increased global warming potentials, whereas N90 did not significantly affect global warming potential. However, N addition significantly decreased the Q 10 value of soil CO 2 emissions under IM but not under CM. Soil microbial biomass carbon was significantly and positively correlated with soil CO 2 and N 2 O emissions but significantly and negatively correlated with soil CH 4 uptake. Conclusion Our results indicate that management scheme effects should be considered when assessing the effect of atmospheric N deposition on GHG emissions in bamboo plantations.

The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings - Guo, Xinyi; Peng, Changhui; Li, Tong; Huang, Jingjing; Song, Hanxiong; Zhu, Qiuan; Wang, Meng (Biology, 2021)
Intense and frequent drought events strongly affect plant survival. Non-structural carbohydrates (NSCs) are important “buffers” to maintain plant functions under drought conditions. We conducted a drought manipulation experiment using three-year-old Pinus tabulaeformis Carr. seedlings. The seedlings were first treated under different drought intensities (i.e., no irrigation, severe, and moderate) for 50 days, and then they were re-watered for 25 days to explore the dynamics of NSCs in the leaves, twigs, stems, and roots. The results showed that the no irrigation and severe drought treatments significantly reduced photosynthetic rate by 93.9% and 32.6% for 30 days, respectively, leading to the depletion of the starch storage for hydraulic repair, osmotic adjustment, and plant metabolism. The seedlings under moderate drought condition also exhibited starch storage consumption in leaves and twigs. After re-watering, the reduced photosynthetic rate recovered to the control level within five days in the severe drought group but showed no sign of recovery in the no irrigation group. The seedlings under the severe and moderate drought conditions tended to invest newly fixed C to starch storage and hydraulic repair instead of growth due to the “drought legacy effect”. Our findings suggest the depletion and recovery of starch storage are important strategies for P. tabulaeformis seedlings, and they may play key roles in plant resistance and resilience under environmental stress.

Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest - Li, Quan; Peng, Changhui; Zhang, Junbo; Li, Yongfu; Song, Xinzhang (Scientific Reports, 2021)
Abstract Forest soils play an important role in controlling global warming by reducing atmospheric methane (CH 4 ) concentrations. However, little attention has been paid to how nitrogen (N) deposition may alter microorganism communities that are related to the CH 4 cycle or CH 4 oxidation in subtropical forest soils. We investigated the effects of N addition (0, 30, 60, or 90 kg N ha −1 yr −1 ) on soil CH 4 flux and methanotroph and methanogen abundance, diversity, and community structure in a Moso bamboo ( Phyllostachys edulis ) forest in subtropical China. N addition significantly increased methanogen abundance but reduced both methanotroph and methanogen diversity. Methanotroph and methanogen community structures under the N deposition treatments were significantly different from those of the control. In N deposition treatments, the relative abundance of Methanoculleus was significantly lower than that in the control. Soil pH was the key factor regulating the changes in methanotroph and methanogen diversity and community structure. The CH 4 emission rate increased with N addition and was negatively correlated with both methanotroph and methanogen diversity but positively correlated with methanogen abundance. Overall, our results suggested that N deposition can suppress CH 4 uptake by altering methanotroph and methanogen abundance, diversity, and community structure in subtropical Moso bamboo forest soils.

Identifying the greenhouses by Google Earth Engine to promote the reuse of fragmented land in urban fringe - Yang, Guofu; Xu, Ronghua; Chen, Yi; Wu, Zhaoping; Du, Yuanyuan; Liu, Shun; Qu, Zelong; Guo, Kejian; Peng, Changhui; Chang, Jie; Ge, Ying (Sustainable Cities and Society, 2021)

Tillage activates iron to prevent soil organic carbon loss following forest conversion to cornfields in tropical acidic red soils - Zong, Mingming; Lin, Chen; Li, Shiyu; Li, Haixia; Duan, Changqun; Peng, Changhui; Guo, Yongxing; An, Ruiqi (Science of The Total Environment, 2021)

The effects of elevated CO2, elevated O3, elevated temperature, and drought on plant leaf gas exchanges: a global meta-analysis of experimental studies - Zhang, Jinmeng; Deng, Lei; Jiang, Hong; Peng, Changhui; Huang, Chunbo; Zhang, Minxia; Zhang, Xiuying (Environmental Science and Pollution Research, 2021)

Effects of plant functional group removal on community structure, diversity and production in Alpine meadow - Jiang Lin, 姜林，胡骥，杨振安，詹伟，赵川，朱单，何奕忻，陈槐，彭长辉 (Acta Ecologica Sinica, 2021)

Stability in subtropical forests: The role of tree species diversity, stand structure, environmental and socio‐economic conditions - Ouyang, Shuai; Xiang, Wenhua; Gou, Mengmeng; Chen, Liang; Lei, Pifeng; Xiao, Wenfa; Deng, Xiangwen; Zeng, Lixiong; Li, Jiangrong; Zhang, Tao; Peng, Changhui; Forrester, David I. (Global Ecology and Biogeography, 2021)
Abstract Aim Tree species diversity can increase the stability of ecosystem productivity by increasing mean productivity and/or reducing the standard deviation in productivity. However, stand structure, environmental and socio‐economic conditions influence plant diversity and might strongly influence the relationships between diversity and stability in natural forest communities. The relative importance of these factors for community stability remains poorly understood in complex (species‐rich) subtropical forests. Location Subtropical area of southern China. Time period 1999–2014. Major taxa studied Forest trees. Methods We conducted bivariate analyses to examine the mechanisms (overyielding and species asynchrony) underlying the effects of diversity on stability. Multiple regression models were then used to determine the relative importance of tree species diversity, stand structure, socio‐economic factors and environmental conditions on stability. Structural equation modelling was used to disentangle how these variables directly and/or indirectly affect forest stability. Results Tree species richness exerted a positive effect on stability through overyielding and species asynchrony, and this effect was stronger in mountainous forests than in hilly forests. Species richness positively affected the mean productivity, whereas species asynchrony negatively affected the variability in productivity, hence increasing forest stability. Structural diversity also had a positive effect, whereas population density had a negative effect on stability. Precipitation variability and slope mainly had indirect influences on stability through their effects on tree species richness. Main conclusions Overall, tree species diversity governed stability; however, stand structure, socio‐economic conditions and environmental conditions also played an important role in shaping stability in these forests. Our work highlights the importance of regulating stand structure and socio‐economic factors in forest management and biodiversity conservation, to maintain and enhance their stability to provide ecosystem services in the face of unprecedented anthropogenic activities and global climate change.

Effects of vegetation restoration on soil nutrients, plant diversity, and its spatiotemporal heterogeneity in a desert–oasis ecotone - Wu, Chunyan; Deng, Lei; Huang, Chunbo; Chen, Yongfu; Peng, Changhui (Land Degradation & Development, 2021)
Abstract Vegetation restoration has been proposed as an effective measure for rehabilitating degraded land and slowing desertification in arid regions. However, the spatial variation in soil quality and plant diversity following vegetation restoration remains unclear. This study was designed to explore soil nutrient dynamics and how soil nutrients affect plant diversity and spatial heterogeneity after shrub restoration. We assessed the effect of Haloxylon ammodendron (C.A.Mey.) Bunge (which has been planted over 30 years) on the soil nutrients and plant diversity in a desert–oasis ecotone in Minqin County, Gansu, China, using geostatistics, beta diversity and rarefaction analyses, and Hill number extrapolation. Soil nutrients, including soil organic matter, total nitrogen, and alkali nitrogen, increased significantly after H. ammodendron planting. Species richness gradually increased from 1–5 years to 10–20 years after H. ammodendron was planted but then decreased at 20–30 years. The largest differences in plant composition were observed at 15 and 20 years. Plant diversity increased in the whole 30 years after shrub planting, increasing in the first 25 years and then decreasing at 26–30 year stage. The maximum coefficient of determination for the spatial heterogeneity model fit was 0.84 (25 years). The spatial heterogeneity in vegetation decreased with increasing soil available K content at 1–10 years. Our results suggest that planting shrubs can improve soil conditions and plant species diversity in desert–oasis ecotones and soil nutrients have a strong influence on plant diversity patterns and spatial heterogeneity following vegetation restoration.

Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models - Wang, Yue; Hu, Jinming; Yang, Yanzheng; Li, Ruonan; Peng, Changhui; Zheng, Hua (Forests, 2020)
The carbon use efficiency (CUE) of ecosystems, expressed as the ratio of net primary production (NPP) and gross primary production (GPP), is extremely sensitive to climate change and has a great effect on the carbon cycles of terrestrial ecosystems. Climate change leads to changes in vegetation, resulting in different CUE values, especially on the Qinghai-Tibet Plateau, one of the most climate-sensitive regions in the world. However, the change trend and the intrinsic mechanism of climate effects on CUE in the future climate change scenario are not clear in this region. Based on the scheme of the coupled model intercomparison project (CMIP6), we analyze the simulation results of the five models of the scenario model intercomparison project (ScenarioMIP) under three different typical future climate scenarios, including SSP1-2.6, SSP3-7.0 and SSP5-8.5, on the Qinghai-Tibet Plateau in 2015–2100 with methods of model-averaging to average the long-term forecast of the five several well-known forecast models for three alternative climate scenarios with three radiative forcing levels to discuss the CUE changes and a structural equations modeling (SEM) approach to examine how the trends in GPP, NPP, and CUE related to different climate factors. The results show that (1) GPP and NPP demonstrated an upward trend in a long time series of 86 years, and the upward trend became increasingly substantial with the increase in radiation forcing; (2) the ecosystem CUE of the Qinghai-Tibet Plateau will decrease in the long time series in the future, and it shows a substantial decreasing trend with the increase in radiation forcing; and (3) the dominant climate factor affecting CUE is temperature of the factors included in these models, which affects CUE mainly through GPP and NPP to produce indirect effects. Temperature has a higher comprehensive effect on CUE than precipitation and CO2, which are negative effects on CUE on an annual scale. Our finding that the CUE decreases in the future suggests that we must pay more attention to the vegetation and CUE changes, which will produce great effects on the regional carbon dynamics and balance.

Detecting and mapping tree crowns based on convolutional neural network and Google Earth images - Yang, Mingxia; Mou, Yuling; Liu, Shan; Meng, Yanrong; Liu, Zelin; Li, Peng; Xiang, Wenhua; Zhou, Xiaolu; Peng, Changhui (International Journal of Applied Earth Observation and Geoinformation, 2022)

Estimating natural nitrous oxide emissions from the Qinghai–Tibetan Plateau using a process-based model: Historical spatiotemporal patterns and future trends - Zhang, Kerou; Peng, Changhui; Zhu, Qiuan; Li, Mingxu; Yan, Zhongqing; Li, Meng; Yan, Liang; Zhang, Xiaodong; Wang, Jinzhi; Li, Yong; Kang, Enze; Song, Hanxiong; et al. (Ecological Modelling, 2022)

Evaluating and quantifying the effect of various spruce budworm intervention strategies on forest carbon dynamics in Atlantic Canada - Liu, Zelin; Peng, Changhui; MacLean, David A.; De Grandpré, Louis; Candau, Jean-Noël; Kneeshaw, Daniel (Forest Ecosystems, 2022)

Globally limited individual and combined effects of multiple global change factors on allometric biomass partitioning - Peng, Yan; Fornara, Dario A.; Yue, Kai; Peng, Xin; Peng, Changhui; Wu, Qiqian; Ni, Xiangyin; Liao, Shu; Yang, Yusheng; Wu, Fuzhong; Peñuelas, Josep (Global Ecology and Biogeography, 2022)
Abstract Aim Plant biomass allocation reflects the distribution of photosynthates among different organs in response to changing environmental conditions. Global change influences plant growth across terrestrial ecosystems, but impacts of individual and combined multiple global change factors (GCFs) on plant biomass allocation at the global scale are unclear. Location Global. Time period Contemporary. Major taxa studied Plants in terrestrial ecosystems. Methods We conducted a meta‐analysis of data comprising 4,180 pairwise observations to assess individual and combined effects of nitrogen addition (N), warming (W), elevated CO 2 (C), irrigation (I), and drought (D) on plant biomass allocation based on the ‘ratio‐based optimal partitioning’ and ‘isometric allocation’ hypotheses. Results We found that (a) ratio‐based plant biomass fractions of different organs were only minimally affected by individual and combined effects of the studied GCFs; (b) combined effects of two‐factor pairs of GCFs on plant biomass allocation were commonly additive, rather than synergistic or antagonistic; (c) moderator variables influenced, but seldom changed the direction of individual and combined effects of GCFs on plant biomass allocation; and (d) neither individual nor combined effects of the studied GCFs altered allometric relationships among different organs, indicating that patterns of plant biomass allocation under the environmental stress conditions exerted by the multiple GCFs were better explained by the isometric allocation rather than the ratio‐based optimal partitioning hypothesis. Main conclusions Our results show consistent patterns of allometric plant biomass partitioning under effects of multiple GCFs and provide evidence of an isometric plant biomass allocation trajectory in response to global change perturbations. These findings improve our understanding and prediction of terrestrial vegetation responses to future global change scenarios.

Global patterns of particulate organic carbon export from land to the ocean - Li, Mingxu; Peng, Changhui; He, Nianpeng (Ecohydrology, 2022)
Abstract Global rivers and streams are important carbon transport pathways from land to the ocean. However, few studies have quantified terrigenous carbon dynamics in river ecosystems and its variations due to climate change and anthropogenic perturbations. Therefore, our study analysed fluvial particulate organic carbon (POC) and developed a processed‐based model (TRIPLEX‐HYDRA) to simulate the production, transport and removal (i.e., deposition, degradation and dam retention) processes of fluvial POC along the land–ocean aquatic continuum (LOAC). Based on our results, approximately 0.29 Pg of POC is exported from land to the ocean through rivers each year. More specifically, we found that rivers at low latitudes (30°S–30°N, 0.18 Pg yr −1 ) and high northern latitudes (60°N–90°N, 0.05 Pg yr −1 ) had higher POC fluxes compared to rivers in other regions. This high POC flux is related to strong erosion rates and high soil organic carbon storage. Additionally, our model simulation revealed that total POC flux from global river has not significantly changed from 1983 to 2015 but displays markedly decreased or increased trend at regional scale. These regional variations in POC export are affected by climate warming and dam construction. Moreover, approximately 0.46 Pg of POC is deposited or trapped by dams along the LOAC system, which plays a vital role in the global river carbon budget. Although some limitations and uncertainties remain, this study establishes a theoretical and methodological basis for quantifying riverine POC dynamics in the LOAC system.

Quantification of Ecosystem-Scale Methane Sinks Observed in a Tropical Rainforest in Hainan, China - Liu, Zhihao; Li, Hong; Wu, Fangtao; Wang, Hui; Chen, Huai; Zhu, Qiuan; Yang, Gang; Liu, Weiguo; Chen, Dexiang; Li, Yide; Peng, Changhui (Land, 2022)
Tropical rainforest ecosystems are important when considering the global methane (CH4) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH4 fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH4 flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH4 uptake generally occurred in this tropical rainforest, where strong CH4 uptake occurred in the daytime, and a weak CH4 uptake occurred at night with a mean daily CH4 flux of −4.5 nmol m−2 s−1. In this rainforest, the mean annual budget of CH4 for the 3 years was −1260 mg CH4 m−2 year−1. Furthermore, the daily averaged CH4 flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH4 flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (Tair), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (Tsoil), although the linear correlation between the daily CH4 flux and any of these individual variables was relatively low. This indicates that CH4 uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH4 sink during 2016–2018, helping to counteract global warming.

Biochar amendments increase soil organic carbon storage and decrease global warming potentials of soil CH4 and N2O under N addition in a subtropical Moso bamboo plantation - Li, Quan; Cui, Kunkai; Lv, Jianhua; Zhang, Junbo; Peng, Changhui; Li, Yongfu; Gu, Zhikang; Song, Xinzhang (Forest Ecosystems, 2022)

Recent advances in carbon footprint studies of urban ecosystems: overview, application, and future challenges - Chen, Kexin; Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Tang, Jiayi; Peng, Changhui (Environmental Reviews, 2022)
Urban ecosystems are complex systems with anthropogenic features that generate considerable CO 2 emissions, which contributes to global climate change. Quantitative estimates of the carbon footprint of urban ecosystems are crucial for developing low-carbon development policies to mitigate climate change. Herein, we reviewed more than 195 urban carbon footprint and carbon footprint related studies, collated the recent progress in carbon footprint calculation methods and research applications of the urban ecosystem carbon footprint, analyzed the research applications of the carbon footprint of different cities, and focused on the need to study the urban ecosystem carbon footprint from a holistic perspective. Specifically, we aimed to: (i) compare the strengths and weaknesses of five existing carbon footprint calculation methods [life cycle assessment, input–output analysis, hybrid life cycle assessment, carbon footprint calculator, and Intergovernmental Panel on Climate Change (IPCC)]; (ii) analyze the status of current research on the carbon footprint of different urban subregions based on different features; and (iii) highlight new methods and areas of research on the carbon footprint of future urban ecosystems. Not all carbon footprint accounting methods are applicable to the carbon footprint determination of urban ecosystems; although the IPCC method is more widely used than the others, the hybrid life cycle assessment method is more accurate. With the emergence of new science and technology, quantitative methods to calculate the carbon footprint of urban ecosystems have evolved, becoming more accurate. Further development of new technologies, such as big data and artificial intelligence, to assess the carbon footprint of urban ecosystems is anticipated to help address the emerging challenges in urban ecosystem research effectively to achieve carbon neutrality and urban sustainability under global change.

Responses of soil CH4 fluxes to nitrogen addition in two tropical montane rainforests in southern China - Wu, Fangtao; Peng, Changhui; Wang, Chuanyao; Chen, Huai; Liu, Weiguo; Liu, Zhihao; Wang, Hui; Li, Hong; Chen, Dexiang; Li, Yide; Liu, Shirong (Forest Ecosystems, 2022)

Spatiotemporal patterns and drivers of stem methane flux from two poplar forests with different soil textures - Han, Menghua; Feng, Huili; Peng, Changhui; Lei, Xiangdong; Xue, Jianhui; Malghani, Saadatullah; Ma, Xuehong; Song, Xinzhang; Wang, Weifeng (Tree Physiology, 2022)
Abstract In forest ecosystems, the majority of methane (CH4) research focuses on soils, whereas tree stem CH4 flux and driving factors remain poorly understood. We measured the in situ stem CH4 flux using the static chamber–gas chromatography method at different heights in two poplar (Populus spp.) forests with separate soil textures. We evaluated the relationship between stem CH4 fluxes and environmental factors with linear mixed models and estimated the tree CH4 emission rate at the stand level. Our results showed that poplar stems were a net source of atmospheric CH4. The mean stem CH4 emission rates were 97.51 ± 6.21 μg·m−2·h−1 in Sihong and 67.04 ± 5.64 μg·m−2·h−1 in Dongtai. The stem CH4 emission rate in Sihong with clay loam soils was significantly higher (P < 0.001) than that in Dongtai with sandy loam soils. The stem CH4 emission rate also showed a seasonal variation, minimum in winter and maximum in summer. The stem CH4 emission rate generally decreased with increasing sampling height. Although the differences in CH4 emission rates between stem heights were significant in the annual averages, these differences were driven by differences observed in the summer. Stem CH4 emission rates were significantly and positively correlated with air temperature (P < 0.001), relative humidity (P < 0.001), soil water content (P < 0.001) and soil CH4 flux (P < 0.001). At these sites, the soil emitted CH4 to the atmosphere in summer (mainly from June to September) but absorbed CH4 from the atmosphere during the other season. At the stand level, tree CH4 emissions accounted for 2–35.4% of soil CH4 uptake. Overall, tree stem CH4 efflux could be an important component of the forest CH4 budget. Therefore, it is necessary to conduct more in situ monitoring of stem CH4 flux to accurately estimate the CH4 budget in the future.

A Review of General Methods for Quantifying and Estimating Urban Trees and Biomass - Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Tang, Jiayi; Xie, Binggeng; Peng, Changhui (Forests, 2022)
Understanding the biomass, characteristics, and carbon sequestration of urban forests is crucial for maintaining and improving the quality of life and ensuring sustainable urban planning. Approaches to urban forest management have been incorporated into interdisciplinary, multifunctional, and technical efforts. In this review, we evaluate recent developments in urban forest research methods, compare the accuracy and efficiency of different methods, and identify emerging themes in urban forest assessment. This review focuses on urban forest biomass estimation and individual tree feature detection, showing that the rapid development of remote sensing technology and applications in recent years has greatly benefited the study of forest dynamics. Included in the review are light detection and ranging-based techniques for estimating urban forest biomass, deep learning algorithms that can extract tree crowns and identify tree species, methods for measuring large canopies using unmanned aerial vehicles to estimate forest structure, and approaches for capturing street tree information using street view images. Conventional methods based on field measurements are highly beneficial for accurately recording species-specific characteristics. There is an urgent need to combine multi-scale and spatiotemporal methods to improve urban forest detection at different scales.

Nitrogen addition increases CO2, CH4, and N2O concentrations of topsoils and subsoils in a subtropical Moso bamboo forest - Lv, Jianhua; Li, Quan; Zhang, Junbo; Li, Yongfu; Peng, Changhui; Song, Xinzhang (CATENA, 2022)

Responses of autumn vegetation phenology to climate change and urbanization at northern middle and high latitudes - Du, Hui; Wang, Mei; Liu, Yuxin; Guo, Mengjiao; Peng, Changhui; Li, Peng (International Journal of Applied Earth Observation and Geoinformation, 2022)

Divergent responses of autumn vegetation phenology to climate extremes over northern middle and high latitudes - Wang, Mei; Li, Peng; Peng, Changhui; Xiao, Jingfeng; Zhou, Xiaolu; Luo, Yunpeng; Zhang, Cicheng (Global Ecology and Biogeography, 2022)
Abstract Aim Compared with gradual climate change, extreme climatic events have more direct and dramatic impacts on vegetation growth. However, the influence of climate extremes on important phenological periods, such as the end of the growing season (EOS), remains unclear. Here, we investigate the temporal trends of EOS across different biomes and quantify the response of EOS to multiple climate extreme indices (CEIs). Location Northern middle and high latitudes. Time period 2000–2020. Major taxa studied Plants. Methods Three phenology extraction methods were used to compute EOS from satellite, FLUXNET and Pan European Phenology Project PEP725 phenological datasets. Different stress states of cold, hot, dry and wet extremes were represented by 12 CEIs. Partial correlation and ridge regression analysis were used to quantify the response of EOS to climate extremes across latitudinal and biome scales. Results Our study showed a delayed EOS in boreal biomes, but a significantly advanced EOS in temperate biomes. The advanced EOS induced by cold stress was observed for c . 80% of the vegetated pixels. The warm‐related CEIs delayed the EOS in high latitudes, and the delayed effect weakened or even reversed with decreasing latitude. In contrast, EOS exhibited opposite response patterns to dry days and wet‐related CEIs. Overall, EOS exhibited higher sensitivity to extreme temperature in boreal biomes than in temperate biomes. Specifically, continuous drought and high heat stress induced an earlier EOS in some temperate forest biomes, whereas moderate heat stress delayed the EOS in most study biomes. In contrast, EOS was not sensitive to extreme drought in water‐restricted biomes. Main conclusions EOS exhibited divergent responses to various climate extremes with different intensities and frequencies. Moreover, the response of EOS to extreme climate stress was dependent on the biome and latitude. These findings emphasize the importance of incorporating the divergent extreme climate effects into vegetation phenological models and Earth system models.

Integrating major agricultural practices into the TRIPLEX-GHG model v2.0 for simulating global cropland nitrous oxide emissions: Development, sensitivity analysis and site evaluation - Song, Hanxiong; Peng, Changhui; Zhang, Kerou; Zhu, Qiuan (Science of The Total Environment, 2022)

Carbon and nitrogen cycling on the Qinghai–Tibetan Plateau - Chen, Huai; Ju, Peijun; Zhu, Qiuan; Xu, Xingliang; Wu, Ning; Gao, Yongheng; Feng, Xiaojuan; Tian, Jianqing; Niu, Shuli; Zhang, Yangjian; Peng, Changhui; Wang, Yanfen (Nature Reviews Earth & Environment, 2022)

Stand carbon storage and net primary production in China’s subtropical secondary forests are predicted to increase by 2060 - Jin, Jia; Xiang, Wenhua; Zeng, Yelin; Ouyang, Shuai; Zhou, Xiaolu; Hu, Yanting; Zhao, Zhonghui; Chen, Liang; Lei, Pifeng; Deng, Xiangwen; Wang, Hui; Liu, Shirong; et al. (Carbon Balance and Management, 2022)
Abstract Background Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5). Results The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060. Conclusions The obtained results lead to conclusion that proper management of China’s subtropical secondary forests could be considered as one of the steps towards achieving China’s target to become carbon neutral by 2060.

Photosynthetic and hydraulic traits influence forest resistance and resilience to drought stress across different biomes - Hu, Yanting; Xiang, Wenhua; Schäfer, Karina V.R.; Lei, Pifeng; Deng, Xiangwen; Forrester, David I.; Fang, Xi; Zeng, Yelin; Ouyang, Shuai; Chen, Liang; Peng, Changhui (Science of The Total Environment, 2022)

Stumps increased soil respiration in a subtropical Moso bamboo (Phyllostachys edulis) plantation under nitrogen addition - Li, Quan; Ma, Qiuhui; Gao, Jinpei; Zhang, Junbo; Li, Yongfu; Shi, Man; Peng, Changhui; Song, Xinzhang (Agricultural and Forest Meteorology, 2022)

Cold‐Season Methane Fluxes Simulated by GCP‐CH4 Models - Ito, A.; Li, T.; Qin, Z.; Melton, J. R.; Tian, H.; Kleinen, T.; Zhang, W.; Zhang, Z.; Joos, F.; Ciais, P.; Hopcroft, P. O.; Beerling, D. J.; et al. (Geophysical Research Letters, 2023)
Abstract Cold‐season methane (CH 4 ) emissions may be poorly constrained in wetland models. We examined cold‐season CH 4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH 4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH 4 yr −1 . While summer CH 4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH 4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade −1 . Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. , Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH 4 ) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH 4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH 4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH 4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH 4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH 4 emissions from wetlands need to be improved. , Key Points Cold‐season methane (CH 4 ) emissions simulated by 16 Global Carbon Project‐CH 4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau - Zhu, Qiuan; Chen, Huai; Peng, Changhui; Liu, Jinxun; Piao, Shilong; He, Jin-Sheng; Wang, Shiping; Zhao, Xinquan; Zhang, Jiang; Fang, Xiuqin; Jin, Jiaxin; Yang, Qi-En; et al. (Nature Communications, 2023)
Abstract Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO 2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships - Yang, Mingxia; Zhou, Xiaolu; Peng, Changhui; Li, Tong; Chen, Kexin; Liu, Zelin; Li, Peng; Zhang, Cicheng; Tang, Jiayi; Zou, Ziying (Forest Ecosystems, 2023)

Effects of daily variation of hydro-thermal factors on alpine grassland productivity on the Qinghai-Tibet Plateau - Ma Fulin, 马扶林，刘小伟，朵莹 (Acta Ecologica Sinica, 2023)

Plant functional trait diversity and structural diversity co-underpin ecosystem multifunctionality in subtropical forests - Ouyang, Shuai; Gou, Mengmeng; Lei, Pifeng; Liu, Yue; Chen, Liang; Deng, Xiangwen; Zhao, Zhonghui; Zeng, Yelin; Hu, Yanting; Peng, Changhui; Xiang, Wenhua (Forest Ecosystems, 2023)

Satellite monitoring reveals short-term cumulative and time-lag effect of drought and heat on autumn photosynthetic phenology in subtropical vegetation - Ren, Peixin; Li, Peng; Tang, Jiayi; Li, Tong; Liu, Zelin; Zhou, Xiaolu; Peng, Changhui (Environmental Research, 2023)

Growing season temperature and precipitation affect nutrient resorption in herbaceous species through a foliar stoichiometric control strategy - Liu, Xiaowei; Wang, Youqi; Fu, Wenhui; Yuan, Zhiyou; Yu, Qiang; Peng, Changhui; Koerner, Sally E.; Guo, Liang (Plant and Soil, 2023)

Divergent response of leaf unfolding to climate warming in subtropical and temperate zones - Yu, Haiying; Yang, Lilin; Wang, Zuhua; Guo, Liang; Peng, Changhui; Yao, Qifu; Mo, Zhongmei; Tan, Tinghong (Agricultural and Forest Meteorology, 2023)

C:N:P stoichiometry of plants, soils, and microorganisms: Response to altered precipitation - Li, Jiwei; Deng, Lei; Peñuelas, Josep; Wu, Jianzhao; Shangguan, Zhouping; Sardans, Jordi; Peng, Changhui; Kuzyakov, Yakov (Global Change Biology, 2023)
Abstract Precipitation changes modify C, N, and P cycles, which regulate the functions and structure of terrestrial ecosystems. Although altered precipitation affects above‐ and belowground C:N:P stoichiometry, considerable uncertainties remain regarding plant–microbial nutrient allocation strategies under increased (IPPT) and decreased (DPPT) precipitation. We meta‐analyzed 827 observations from 235 field studies to investigate the effects of IPPT and DPPT on the C:N:P stoichiometry of plants, soils, and microorganisms. DPPT reduced leaf C:N ratio, but increased the leaf and root N:P ratios reflecting stronger decrease of P compared with N mobility in soil under drought. IPPT increased microbial biomass C (+13%), N (+15%), P (26%), and the C:N ratio, whereas DPPT decreased microbial biomass N (−12%) and the N:P ratio. The C:N and N:P ratios of plant leaves were more sensitive to medium DPPT than to IPPT because drought increased plant N content, particularly in humid areas. The responses of plant and soil C:N:P stoichiometry to altered precipitation did not fit the double asymmetry model with a positive asymmetry under IPPT and a negative asymmetry under extreme DPPT. Soil microorganisms were more sensitive to IPPT than to DPPT, but they were more sensitive to extreme DPPT than extreme IPPT, consistent with the double asymmetry model. Soil microorganisms maintained stoichiometric homeostasis, whereas N:P ratios of plants follow that of the soils under altered precipitation. In conclusion, specific N allocation strategies of plants and microbial communities as well as N and P availability in soil critically mediate C:N:P stoichiometry by altered precipitation that need to be considered by prediction of ecosystem functions and C cycling under future climate change scenarios.

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET‐CH4 Sites Using Wavelet Analyses - Zhang, Zhen; Bansal, Sheel; Chang, Kuang‐Yu; Fluet‐Chouinard, Etienne; Delwiche, Kyle; Goeckede, Mathias; Gustafson, Adrian; Knox, Sara; Leppänen, Antti; Liu, Licheng; Liu, Jinxun; Malhotra, Avni; et al. (Journal of Geophysical Research: Biogeosciences, 2023)
Abstract Process‐based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site‐level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model‐observation disagreements are mainly at multi‐day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments. , Plain Language Summary Land surface models are useful tools to estimate and predict wetland methane (CH 4 ) flux but there is no evaluation of modeled CH 4 flux error at different time scales. Here we use a statistical approach and observations from eddy covariance sites to evaluate the performance of seven wetland models for different wetland types. The results suggest models have captured CH 4 flux variability at monthly or seasonal time scales for boreal and Arctic tundra wetlands but failed to capture the observed seasonal variability for temperate and tropical/subtropical wetlands. The analysis suggests that improving modeled flux at short time scale is important for future model development. , Key Points Significant model‐observation disagreements were found at multi‐day and weekly time scales (<15 days) Models captured variability at monthly and seasonal time (42–142 days) scales for boreal and Arctic tundra sites but not for temperate and tropical sites The model errors show that biases at multi‐day time scales may contribute to persistent systematic biases on longer time scales

Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data - Zhu, Shoutao; Tang, Jiayi; Zhou, Xiaolu; Li, Peng; Liu, Zelin; Zhang, Cicheng; Zou, Ziying; Li, Tong; Peng, Changhui (Environmental Reviews, 2023)
Satellite data are vital for understanding the large-scale spatial distribution of particulate matter (PM 2.5 ) due to their low cost, wide coverage, and all-weather capability. Estimation of PM 2.5 using satellite aerosol optical depth (AOD) products is a popular method. In this paper, we review the PM 2.5 estimation process based on satellite AOD data in terms of data sources (i.e., inversion algorithms, data sets, and interpolation methods), estimation models (i.e., statistical regression, chemical transport models, machine learning, and combinatorial analysis), and modeling validation (i.e., four types of cross-validation (CV) methods). We found that the accuracy of time-based CV is lower than others. We found significant differences in modeling accuracy between different seasons ( p < 0.01) and different spatial resolutions ( p < 0.01). We explain these phenomena in this article. Finally, we summarize the research process, present challenges, and future directions in this field. We opine that low-cost mobile devices combined with transfer learning or hybrid modeling offer research opportunities in areas with limited PM 2.5 monitoring stations and historical PM 2.5 estimation. These methods can be a good choice for air pollution estimation in developing countries. The purpose of this study is to provide a basic framework for future researchers to conduct relevant research, enabling them to understand current research progress and future research directions.

Can forest carbon sequestration offset industrial CO2 emissions? A case study of Hubei Province, China - Cheng, Jing; Huang, Chunbo; Gan, Xintao; Peng, Changhui; Deng, Lei (Journal of Cleaner Production, 2023)

Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change - Ren, Pei-Xin; Li, Peng; Peng, Chang-Hui; Zhou, Xiao-Lu; Yang, Ming-Xia; 1College of Geographic Sciences, Hunan Normal University, Changsha 410081, China; 2Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, Montreal H3C 3P8, Canada (Chinese Journal of Plant Ecology, 2023)

Divergent response of vegetation phenology to extreme temperatures and precipitation of different intensities on the Tibetan Plateau - Sun, Mai; Li, Peng; Ren, Peixin; Tang, Jiayi; Zhang, Cicheng; Zhou, Xiaolu; Peng, Changhui (Science China Earth Sciences, 2023)

Application of climate change scenarios in the simulation of forest ecosystems: an overview - Liu, Haoyun; Li, Peng; Peng, Changhui; Liu, Cong; Zhou, Xiaolu; Deng, Zhengmiao; Zhang, Cicheng; Liu, Zelin (Environmental Reviews, 2023)
Climate change scenarios established by the Intergovernmental Panel on Climate Change have developed a significant tool for analyzing, modeling, and predicting future climate change impacts in different research fields after more than 30 years of development and refinement. In the wake of future climate change, the changes in forest structure and functions have become a frontier and focal area of global change research. This study mainly reviews and synthesizes climate change scenarios and their applications in forest ecosystem research over the past decade. These applications include changes in (1) forest structure and spatial vegetation distribution, (2) ecosystem structure, (3) ecosystem services, and (4) ecosystem stability. Although climate change scenarios are useful for predicting future climate change impacts on forest ecosystems, the accuracy of model simulations needs to be further improved. Based on existing studies, climate change scenarios are used in future simulation applications to construct a biomonitoring network platform integrating observations and predictions for better conservation of species diversity.

Carbon fluxes and soil carbon dynamics along a gradient of biogeomorphic succession in alpine wetlands of Tibetan Plateau - Wang, Hao; Yu, Lingfei; Chen, Litong; Zhang, Zhenhua; Li, Xuefei; Liang, Naishen; Peng, Changhui; He, Jin-Sheng (Fundamental Research, 2023)

Soil-atmosphere exchange of carbon dioxide, methane and nitrous oxide in temperate forests along an elevation gradient in the Qinling Mountains, China - Pang, Junzhu; Peng, Changhui; Wang, Xiaoke; Zhang, Hongxing; Zhang, Shuoxin (Plant and Soil, 2023)

rTRIPLEXCWFlux: An R package for carbon–water coupling model to simulate net ecosystem productivity and evapotranspiration in forests - Sun, Shulan; Ouyang, Shuai; Hu, Yanting; Zhao, Zhonghui; Liu, Meixian; Chen, Liang; Zeng, Yelin; Peng, Changhui; Zhou, Xiaolu; Xiang, Wenhua (Environmental Modelling & Software, 2023)

Carbon in Chinese grasslands: meta-analysis and theory of grazing effects - Deng, Lei; Shangguan, Zhouping; Bell, Stephen Mackenzie; Soromotin, Andrey V.; Peng, Changhui; An, Shaoshan; Wu, Xing; Xu, Xingliang; Wang, Kaibo; Li, Jianping; Tang, Zhuangsheng; Yan, Weiming; et al. (Carbon Research, 2023)
Abstract Globally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha −1 ) and typical steppes (3 to 4 sheep ha −1 ), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha −1 ) and alpine steppes (7 to 8 sheep ha −1 ) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the ‘ intermediate disturbance hypothesis ’. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha −1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization ) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks. Graphical Abstract

Global estimates of forest soil methane flux identify a temperate and tropical forest methane sink - Feng, Huili; Guo, Jiahuan; Peng, Changhui; Ma, Xuehong; Kneeshaw, Daniel; Chen, Huai; Liu, Qiuyu; Liu, Mengyao; Hu, Cheng; Wang, Weifeng (Geoderma, 2023)

Global Climate Change Increases Terrestrial Soil CH4 Emissions - Guo, Jiahuan; Feng, Huili; Peng, Changhui; Chen, Huai; Xu, Xuan; Ma, Xuehong; Li, Li; Kneeshaw, Daniel; Ruan, Honghua; Yang, Hongqiang; Wang, Weifeng (Global Biogeochemical Cycles, 2023)
Abstract Increased greenhouse gas emissions are causing unprecedented climate change, which is, in turn, altering emissions and removals (referring to the oxidation of atmospheric CH 4 by methanotrophs within the soil) of the atmospheric CH 4 in terrestrial ecosystems. In the global CH 4 budget, wetlands are the dominant natural source and upland soils are the primary biological sink. However, it is unclear whether and how the soil CH 4 exchanges across terrestrial ecosystems and the atmosphere will be affected by warming and changes in precipitation patterns. Here, we synthesize 762 observations of in situ soil CH 4 flux data based on the chamber method from the past three decades related to temperature and precipitation changes across major terrestrial ecosystems worldwide. Our meta‐analysis reveals that warming (average warming of +2°C) promotes upland soil CH 4 uptake and wetland soil CH 4 emission. Decreased precipitation (ranging from −100% to −7% of local mean annual precipitation) stimulates upland soil CH 4 uptake. Increased precipitation (ranging from +4% to +94% of local mean annual precipitation) accelerates the upland soil CH 4 emission. By 2100, under the shared socioeconomic pathway with a high radiative forcing level (SSP585), CH 4 emissions from global terrestrial ecosystems will increase by 22.8 ± 3.6 Tg CH 4 yr −1 as an additional CH 4 source, which may be mainly attributed to the increase in precipitation over 30°N latitudes. Our meta‐analysis strongly suggests that future climate change would weaken the natural buffering ability of terrestrial ecosystems on CH 4 fluxes and thus contributes to a positive feedback spiral. , Plain Language Summary This study is the first investigation to include scenarios of CH 4 sink–source transition due to climate change and provides the global estimate of soil CH 4 budgets in natural terrestrial ecosystems in the context of climate change. The enhanced effect of climate change on CH 4 emissions was mainly attributed to increased CH 4 emissions from natural upland ecosystems. Although an increased CH 4 uptake by forest and grassland soils caused by increased temperature and decreased precipitation can offset some part of additional CH 4 sources, the substantial increase of increased precipitation on CH 4 emissions makes these sinks insignificant. These findings highlight that future climate change would weaken the natural buffering ability of terrestrial ecosystems on CH 4 emissions and thus form a positive feedback spiral between methane emissions and climate change. , Key Points This study is the first CH 4 budget investigation to include CH 4 sink‐source transition due to climate change Climate change is estimated to add 22.8 ± 3.6 Tg CH 4 yr −1 emission by 2100 under the high socioeconomic pathway Climate change weakens the buffering capacity of upland soils to CH 4 emissions

Predicting potential climate change impacts of bioenergy from perennial grasses in 2050 - Liu, Weiguo; Wang, Kui; Hao, Hongke; Yan, Yan; Zhang, Han; Zhang, Huanling; Peng, Changhui (Resources, Conservation and Recycling, 2023)

Drought‐induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada's boreal forests from 1970 to 2020 - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; McDowell, Nate G.; Kneeshaw, Daniel (Global Change Biology, 2023)
Abstract Canada's boreal forests, which occupy approximately 30% of boreal forests worldwide, play an important role in the global carbon budget. However, there is little quantitative information available regarding the spatiotemporal changes in the drought‐induced tree mortality of Canada's boreal forests overall and their associated impacts on biomass carbon dynamics. Here, we develop spatiotemporally explicit estimates of drought‐induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in significant biomass carbon losses at an approximate rate of 1.51 ± 0.29 MgC ha −1 year −1 (95% confidence interval) with an approximate total loss of 0.46 ± 0.09 PgC year −1 (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect.

Quantifying patterns, sources and uncertainty of nitrous oxide emissions from global grazing lands: Nitrogen forms are the determinant factors for estimation and mitigation - Song, Hanxiong; Peng, Changhui; Zhang, Kerou; Li, Tong; Yang, Mingxia; Liu, Qiuyu; Zhu, Qiuan (Global and Planetary Change, 2023)

Vegetation browning: global drivers, impacts, and feedbacks - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; Liu, Zelin; Zhou, Xiaolu; Du, Mingxi; Li, Peng; Jiang, Zihan; McDowell, Nate G.; Kneeshaw, Daniel (Trends in Plant Science, 2023)

Nitrogen addition promotes terrestrial plants to allocate more biomass to aboveground organs: A global meta‐analysis - Feng, Huili; Guo, Jiahuan; Peng, Changhui; Kneeshaw, Daniel; Roberge, Gabrielle; Pan, Chang; Ma, Xuehong; Zhou, Dan; Wang, Weifeng (Global Change Biology, 2023)
Abstract A significant increase in reactive nitrogen (N) added to terrestrial ecosystems through agricultural fertilization or atmospheric deposition is considered to be one of the most widespread drivers of global change. Modifying biomass allocation is one primary strategy for maximizing plant growth rate, survival, and adaptability to various biotic and abiotic stresses. However, there is much uncertainty as to whether and how plant biomass allocation strategies change in response to increased N inputs in terrestrial ecosystems. Here, we synthesized 3516 paired observations of plant biomass and their components related to N additions across terrestrial ecosystems worldwide. Our meta‐analysis reveals that N addition (ranging from 1.08 to 113.81 g m −2 year −1 ) increased terrestrial plant biomass by 55.6% on average. N addition has increased plant stem mass fraction, shoot mass fraction, and leaf mass fraction by 13.8%, 12.9%, and 13.4%, respectively, but with an associated decrease in plant reproductive mass (including flower and fruit biomass) fraction by 3.4%. We further documented a reduction in plant root‐shoot ratio and root mass fraction by 27% (21.8%–32.1%) and 14.7% (11.6%–17.8%), respectively, in response to N addition. Meta‐regression results showed that N addition effects on plant biomass were positively correlated with mean annual temperature, soil available phosphorus, soil total potassium, specific leaf area, and leaf area per plant. Nevertheless, they were negatively correlated with soil total N, leaf carbon/N ratio, leaf carbon and N content per leaf area, as well as the amount and duration of N addition. In summary, our meta‐analysis suggests that N addition may alter terrestrial plant biomass allocation strategies, leading to more biomass being allocated to aboveground organs than belowground organs and growth versus reproductive trade‐offs. At the global scale, leaf functional traits may dictate how plant species change their biomass allocation pattern in response to N addition.

Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange - Casas-Ruiz, Joan P.; Bodmer, Pascal; Bona, Kelly Ann; Butman, David; Couturier, Mathilde; Emilson, Erik J. S.; Finlay, Kerri; Genet, Hélène; Hayes, Daniel; Karlsson, Jan; Paré, David; Peng, Changhui; et al. (Nature Communications, 2023)
Abstract In this Perspective, we put forward an integrative framework to improve estimates of land-atmosphere carbon exchange based on the accumulation of carbon in the landscape as constrained by its lateral export through rivers. The framework uses the watershed as the fundamental spatial unit and integrates all terrestrial and aquatic ecosystems as well as their hydrologic carbon exchanges. Application of the framework should help bridge the existing gap between land and atmosphere-based approaches and offers a platform to increase communication and synergy among the terrestrial, aquatic, and atmospheric research communities that is paramount to advance landscape carbon budget assessments.

Time-lag effects of flood stimulation on methane emissions in the Dongting Lake floodplain, China - Wang, Tao; Deng, Zhengmiao; Xie, Yonghong; Wang, Buqing; Wu, Shaoan; Li, Feng; Wang, Wei; Zou, Yeai; Li, Xu; Hou, Zhiyong; Zeng, Jing; Wang, Mei; et al. (Agricultural and Forest Meteorology, 2023)

Eco-CCUS: A cost-effective pathway towards carbon neutrality in China - Li, Mingxu; He, Nianpeng; Xu, Li; Peng, Changhui; Chen, Huai; Yu, Guirui (Renewable and Sustainable Energy Reviews, 2023)

Climate change mitigation potential of kitchen waste utilization in China for combined heat and power production - Liu, Weiguo; Zhang, Dan; Tian, Jiajing; Yu, Feiyan; Xie, Yuanming; Cheng, Shengkui; Li, Qiang; Li, Weizhong; Peng, Changhui; Yan, Yan (Science of The Total Environment, 2023)

Climatic drivers and ecological implications of variation in the time interval between leaf-out and flowering - Guo, Liang; Liu, Xiaowei; Alatalo, Juha M.; Wang, Chuanyao; Xu, Jianchu; Yu, Haiying; Chen, Ji; Yu, Qiang; Peng, Changhui; Dai, Junhu; Luedeling, Eike (Current Biology, 2023)

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates - Chang, Kuang‐Yu; Riley, William J.; Collier, Nathan; McNicol, Gavin; Fluet‐Chouinard, Etienne; Knox, Sara H.; Delwiche, Kyle B.; Jackson, Robert B.; Poulter, Benjamin; Saunois, Marielle; Chandra, Naveen; Gedney, Nicola; et al. (Global Change Biology, 2023)
Abstract The recent rise in atmospheric methane (CH 4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH 4 source, estimates of global wetland CH 4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH 4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH 4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH 4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH 4 year −1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH 4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

Grazing alters vegetation phenology by regulating regional environmental factors on the Tibetan Plateau - Wang, Longjun; Li, Peng; Li, Tong; Zhou, Xiaolu; Liu, Zelin; Zou, Ziying; Zhu, Qiuan; Peng, Changhui (Agriculture, Ecosystems & Environment, 2023)

Stable oxic-anoxic transitional interface is beneficial to retard soil carbon loss in drained peatland - Liu, Liangfeng; Tian, Jianqing; Wang, Hongjun; Xue, Dan; Huang, Xinya; Wu, Ning; Wang, Meng; Xu, Xingliang; Peng, Changhui; Wang, Yanfen; Chen, Huai (Soil Biology and Biochemistry, 2023)

The microbial mechanisms by which long-term heavy metal contamination affects soil organic carbon levels - Xiao, Zhineng; Duan, Changqun; Li, Shiyu; Chen, Ji; Peng, Changhui; Che, Rongxiao; Liu, Chang'e; Huang, Yin; Mei, Runran; Xu, Liangliang; Luo, Pengfei; Yu, Yadong (Chemosphere, 2023)

Global net climate effects of anthropogenic reactive nitrogen - Gong, Cheng; Tian, Hanqin; Liao, Hong; Pan, Naiqing; Pan, Shufen; Ito, Akihiko; Jain, Atul K.; Kou-Giesbrecht, Sian; Joos, Fortunat; Sun, Qing; Shi, Hao; Vuichard, Nicolas; et al. (Nature, 2024)
Abstract Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times 1,2 , contributing to widespread eutrophication and air pollution 3–6 . Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of −0.34 [−0.20, −0.50] W m −2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N 2 O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

The effects of environmental factors and plant diversity on forest carbon sequestration vary between eastern and western regions of China - Chen, Kexin; Li, Tong; Yang, Mingxia; Zhou, Xiaolu; Peng, Changhui (Journal of Cleaner Production, 2024)

Fire effects on soil CH4 and N2O fluxes across terrestrial ecosystems - Guo, Jiahuan; Feng, Huili; Peng, Changhui; Du, Juan; Wang, Weifeng; Kneeshaw, Daniel; Pan, Chang; Roberge, Gabrielle; Feng, Lei; Chen, Anping (Science of The Total Environment, 2024)

Differential Responses of Soil Microbial and Carbon‐Nitrogen Processes to Future Environmental Changes Across Soil Depths and Environmental Factors - Wang, Kefeng; Wang, Gangsheng; Qu, Ruosong; Huang, Wenjuan; Zhou, Guoyi; Yue, Ming; Peng, Changhui (Earth's Future, 2024)
Abstract Accurately predicting carbon‐climate feedbacks relies on understanding the environmental factors regulating soil organic carbon (SOC) storage and dynamics. Here, we employed a microbial ecological model (MEND), driven by downscaled output data from six Earth system models under two Shared Socio‐economic Pathways (SSP1‐2.6 and SSP5‐8.5) scenarios, to simulate long‐term soil biogeochemical processes. We aim to analyze the responses of soil microbial and carbon‐nitrogen (C‐N) processes to changes in environmental factors, including litter input (L), soil moisture (W) and temperature (T), and soil pH, in a broadleaf forest (BF) and a pine forest (PF). For the entire soil layer in both forests, we found that, compared to the baseline period of 2009–2020, the mean SOC during 2081–2100 increased by 40.9%–90.6% under the L or T change scenarios, versus 5.2%–31.0% under the W change scenario. However, soil moisture emerged as a key regulator of SOC, MBC and inorganic N dynamics in the topsoil of BF and PF. For example, W change led to SOC gain of 5.5%–37.2%, compared to the SOC loss of 15.5%–18.0% under L or T scenario. Additionally, a further reduction in soil pH by 0.2 units in the BF, representing the acid rain effect, significantly resulted in an additional SOC gain by 14.2%–21.3%, compared to the LTW (simultaneous changes in the three factors) scenario. These results indicate that the results derived solely from topsoil may not be extrapolated to the entire soil profile. Overall, this study significantly advances our comprehension of how different environmental factors impact the dynamics of SOC and the implications they have for climate change. , Plain Language Summary Accurately predicting carbon‐climate feedbacks relies on understanding the environmental factors regulating soil organic carbon (SOC) storage and dynamics. We aim to analyze the responses of soil microbial and carbon‐nitrogen (C‐N) processes to changes in environmental factors, including litter input (L), soil moisture (W) and temperature (T), and soil pH, in a broadleaf forest (BF) and a pine forest (PF). We found that soil moisture change would be beneficial for SOC accumulation and serves as a key regulator of MBC and inorganic N in topsoil, whereas the change in litterfall or soil temperature are favorable for SOC accumulation in the entire soil profile. Additionally, a further reduction in soil pH by 0.2 units, representing the acid rain effect, significantly resulted in an additional SOC gain by 14.2%–21.3%, compared to the scenario with simultaneous changes in L, W, and T. These results indicate that findings solely from topsoil may not be extrapolated to the entire soil profile. Overall, this study significantly advances our comprehension of how different environmental factors impact the dynamics of SOC and the implications they have for climate change. , Key Points Soil C responses to climate change are depth dependent, therefore, results from just the topsoil may not apply to the entire soil profile Soil moisture change benefits topsoil SOC accumulation, whereas litterfall and soil temperature changes favor SOC accumulation in the entire soil profile We need to pay more attention to the effects of soil moisture and pH rather than temperature and litter‐input on soil biogeochemical processes

Impacts of landscape dynamics on terrestrial ecosystem health in the Three Gorges Reservoir Area, China - Huang, Chunbo; Cheng, Jing; Liu, Shuangshuang; Wan, Yunshan; Zhou, Jie; Liu, Zelin; Peng, Changhui (Journal of Cleaner Production, 2024)

Comparing standardised precipitation and barley yield across Quebec - Epule, Terence Epule; Poirier, Vincent; Lafontaine, Simon; Peng, Changhui (Environmental Science and Pollution Research, 2024)

Divergent contributions of spring and autumn photosynthetic phenology to seasonal carbon uptake of subtropical vegetation in China - Peng, Ying; Li, Peng; Zhou, Xiaolu; Luo, Yunpeng; Zhang, Cicheng; Wang, Longjun; Li, Tong; Peng, Changhui (Journal of Geographical Sciences, 2024)

Impacts of environmental and socioeconomic factors on gross ecosystem product of the Three Gorges reservoir area, China - Cheng, Jing; Liu, Shuangshuang; Huang, Chunbo; Wang, Lunche; Liu, Zelin; Peng, Changhui (Land Degradation & Development, 2024)
Abstract Environmental and socioeconomic drivers would alter landscapes, bringing various effects with different directions and magnitudes. Demonstrating these driving effects is key to relieving the conflicts between territorial vegetation restoration and regional economic growth. However, the relationship between ecological protection and economic development due to landscape dynamics has not been systematically demonstrated as environment is difficult to quantify by the monetary value. In this article, we explored the changes in gross ecosystem product (GEP) in the Three Gorges (TG) reservoir area and constructed a conceptual framework to explicate its driving mechanism. Our results suggested that topographic, soil, and climatic factors positively impact on GEP through their important effects on vegetation structure, distribution, and succession. Additionally, reforestation policies promote the conversion of farmland and grassland to forestland in the TG reservoir region, which was the main contributor to enhancing GEP. Conversely, socioeconomic factors negatively impact GEP, of which effects were mainly manifested by changes in the proportion of ecological land. Therefore, it is essential to maintain a suitable land use proportion in this region to optimize GEP, and we proposed a landscape restoration program to enhance four ecosystem productions. This article provides a reference for land resource allocation for environmental protection and sustainable development in ecologically fragile areas.

Climate warming accelerates carbon release from foliar litter—A global synthesis - Chen, Zihao; Ni, Xiangyin; Patoine, Guillaume; Peng, Changhui; Yue, Kai; Yuan, Ji; Wu, Qiuxia; Eisenhauer, Nico; Guerra, Carlos A.; Bol, Roland; Wu, Fuzhong; Wang, G. Geoff (Global Change Biology, 2024)
Abstract With over one‐third of terrestrial net primary productivity transferring to the litter layer annually, the carbon release from litter serves as a crucial valve in atmospheric carbon dioxide concentrations. However, few quantitative global projections of litter carbon release rate in response to climate change exist. Here, we combined a global foliar litter carbon release dataset (8973 samples) to generate spatially explicitly estimates of the response of their residence time ( τ ) to climate change. Results show a global mean litter carbon release rate () of 0.69 year −1 (ranging from 0.09–5.6 year −1 ). Under future climate scenarios, global mean τ is projected to decrease by a mean of 2.7% (SSP 1–2.6) and 5.9% (SSP 5–8.5) during 2071–2100 period. Locally, the alleviation of temperature and moisture restrictions corresponded to obvious decreases in τ in cold and arid regions, respectively. In contract, τ in tropical humid broadleaf forests increased by 4.6% under SSP 5–8.5. Our findings highlight the vegetation type as a powerful proxy for explaining global patterns in foliar litter carbon release rates and the role of climate conditions in predicting responses of carbon release to climate change. Our observation‐based estimates could refine carbon cycle parameterization, improving projections of carbon cycle–climate feedbacks.

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau - Zhang, Jiang; Chen, Huai; Wang, Meng; Liu, Xinwei; Peng, Changhui; Wang, Le; Yu, Dongxue; Zhu, Qiuan (iScience, 2024)

Responses of C:N:P stoichiometric correlations among plants, soils and microorganisms to warming: A meta-analysis - Yu, Zongkai; Zhang, Chao; Liu, Xiaowei; Lei, Jichu; Zhang, Qiang; Yuan, Zhiyou; Peng, Changhui; Koerner, Sally E.; Xu, Jianchu; Guo, Liang (Science of The Total Environment, 2024)

Potential future changes in soil carbon dynamics in the Ziwuling Forest, China under different climate change scenarios - Qu, Ruosong; Chen, Shiyi; Wang, Kefeng; Liu, Qiuyu; Yang, Bin; Yue, Ming; Peng, Changhui (Science of The Total Environment, 2024)

Effects of street plants on atmospheric particulate dispersion in urban streets: A review - Wang, Xiaoshuang; Zhou, Zhixiang; Xiang, Yang; Peng, Chucai; Peng, Changhui (Environmental Reviews, 2024)
Numerous empirical studies have demonstrated that street trees not only reduce dust pollution and absorb particulate matter (PM) but also improve microclimates, providing both ecological functions and aesthetic value. However, recent research has revealed that street tree canopy cover can impede the dispersion of atmospheric PM within street canyons, leading to the accumulation of street pollutants. Although many studies have investigated the impact of street trees on air pollutant dispersion within street canyons, the extent of their influence remains unclear and uncertain. Pollutant accumulation corresponds to the specific characteristics of individual street canyons, coupled with meteorological factors and pollution source strength. Notably, the characteristics of street tree canopy cover also exert a significant influence. There is still a quantitative research gap on street tree cover impacts with respect to pollution and dust reduction control measures within street spaces. To improve urban traffic environments, policymakers have mainly focused on scientifically based street vegetation deployment initiatives in building ecological garden cities and improving the living environment. To address uncertainties regarding the influence of street trees on the dispersion of atmospheric PM in urban streets, this study reviews dispersion mechanisms and key atmospheric PM factors in urban streets, summarizes the research approaches used to conceptualize atmospheric PM dispersion in urban street canyons, and examines urban plant efficiency in reducing atmospheric PM. Furthermore, we also address current challenges and future directions in this field to provide a more comprehensive understanding of atmospheric PM dispersion in urban streets and the role that street trees play in mitigating air pollution.

Global spectra of plant litter carbon, nitrogen and phosphorus concentrations and returning amounts - Yuan, Ji; Wu, Fuzhong; Peng, Changhui; Peñuelas, Josep; Vallicrosa, Helena; Sardans, Jordi; Peng, Yan; Wu, Qiqian; Li, Zimin; Heděnec, Petr; Li, Zhijie; Tan, Siyi; et al. (Journal of Ecology, 2024)
Abstract Litter decomposition is a key ecological process that determines carbon (C) and nutrient cycling in terrestrial ecosystems. The initial concentrations of C and nutrients in litter play a critical role in this process, yet the global patterns of litter initial concentrations of C, nitrogen (N) and phosphorus (P) are poorly understood. We employed machine learning with a global database to quantitatively assess the global patterns and drivers of leaf litter initial C, N and P concentrations, as well as their returning amounts (i.e. amounts returned to soils). The medians of litter C, N and P concentrations were 46.7, 1.1, and 0.1%, respectively, and the medians of litter C, N and P returning amounts were 1.436, 0.038 and 0.004 Mg ha −1 year −1 , respectively. Soil and climate emerged as the key predictors of leaf litter C, N and P concentrations. Predicted global maps showed that leaf litter N and P concentrations decreased with latitude, while C concentration exhibited an opposite pattern. Additionally, the returning amounts of leaf litter C, N and P all declined from the equator to the poles in both hemispheres. Synthesis : Our results provide a quantitative assessment of the global concentrations and returning amounts of leaf litter C, N and P, which showed new light on the role of leaf litter in global C and nutrients cycling.

Vegetation types and flood water level are dominant factors controlling the carbon sequestration potential in Dongting Lake floodplain, China - Wang, Tao; Deng, Zhengmiao; Zhang, Chengyi; Zou, Yeai; Xie, Yonghong; Li, Feng; Xiao, Fengjin; Peng, Changhui (Science of The Total Environment, 2024)

Dynamic carbon allocation trade‐off: A robust approach to model tree biomass allometry - Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Liu, Caixia; Huang, Huabing; Tang, Jiayi; Zhang, Cicheng; Zou, Ziying; Xie, Binggeng; Peng, Changhui (Methods in Ecology and Evolution, 2024)
Abstract Forest above‐ground biomass (AGB) is often estimated by converting the observed tree size using allometric scaling between the dry weight and size of an organism. However, the variations in biomass allocation and scaling between tree crowns and stems due to survival competition during a tree's lifecycle remain unclear. This knowledge gap can improve the understanding of modelling tree biomass allometry because traditional allometries ignore the dynamics of allocation. Herein, we characterised allometric scaling using the dynamic ratio ( r ) of the stem biomass (SB) to AGB and a dynamic exponent. The allometric models were biologically parameterised by the r values for initial, intermediate and final ages rather than only a regression result. The scaling was tested using field measurements of 421 species and 2213 different‐sized trees in pantropical regions worldwide. We found that the scaling fluctuated with tree size, and this fluctuation was driven by the trade‐off relationship of biomass allocation between the tree crown and stem depending on the dynamic crown trait. The allometric scaling between SB and AGB varied from 0.8 to 1.0 for a tree during its entire lifecycle. The fluctuations presented a general law for the allometric scaling of the pantropical tree biomass and size. Our model quantified the trade‐off and explained 94.1% of the allometric relationship between the SB and AGB (93.8% of which between D 2 H and AGB) for pantropical forests, which resulted in a better fit than that of the traditional model. Considering the effects of the trade‐off on modelling, the actual biomass of large trees could be substantially greater than conventional estimates. These results highlight the importance of coupling growth mechanisms in modelling allometry and provide a theoretical foundation for better describing and predicting forest carbon accumulation.

Quantification and uncertainty of global upland soil methane sinks: Processes, controls, model limitations, and improvements - Song, Hanxiong; Peng, Changhui; Zhu, Qiuan; Chen, Zhi; Blanchet, Jean-Pierre; Liu, Qiuyu; Li, Tong; Li, Peng; Liu, Zelin (Earth-Science Reviews, 2024)

Global responses of wetland methane emissions to extreme temperature and precipitation - Xu, Min; Zhang, Jiang; Zhang, Zhen; Wang, Meng; Chen, Huai; Peng, Changhui; Yu, Dongxue; Zhan, Hao; Zhu, Qiuan (Environmental Research, 2024)

Soil methane emissions from plain poplar (Populus spp.) plantations with contrasting soil textures - Ma, Xuehong; Feng, Huili; Guo, Jiahuan; Peng, Changhui; Kneeshaw, Daniel; Wang, Weifeng (Scientific Reports, 2024)
Abstract The forest soil methane (CH 4 ) flux exhibits high spatiotemporal variability. Understanding these variations and their driving factors is crucial for accurately assessing the forest CH 4 budget. In this study, we monitored the diurnal and seasonal variations in soil CH 4 fluxes in two poplar ( Populus spp.) plantations (Sihong and Dongtai) with different soil textures using the static chamber-based method. The results showed that the annual average soil CH 4 flux in the Sihong and Dongtai poplar plantations was 4.27 ± 1.37 kg CH 4 -C ha –1 yr –1 and 1.92 ± 1.07 kg CH 4 -C ha –1 yr –1 , respectively. Both plantations exhibited net CH 4 emissions during the growing season, with only weak CH 4 absorption (–0.01 to –0.007 mg m –2 h –1 ) during the non-growing season. Notably, there was a significant difference in soil CH 4 flux between the clay loam of the Sihong poplar plantation and the sandy loam of the Dongtai poplar plantation. From August to December 2019 and from July to August and November 2020, the soil CH 4 flux in the Sihong poplar plantation was significantly higher than in the Dongtai poplar plantation. Moreover, the soil CH 4 flux significantly increased with rising soil temperature and soil water content. Diurnally, the soil CH 4 flux followed a unimodal variation pattern at different growing stages of poplars, with peaks occurring at noon and in the afternoon. However, the soil CH 4 flux did not exhibit a consistent seasonal pattern across different years, likely due to substantial variations in precipitation and soil water content. Overall, our study emphasizes the need for a comprehensive understanding of the spatiotemporal variations in forest soil CH 4 flux with different soil textures. This understanding is vital for developing reasonable forest management strategies and reducing uncertainties in the global CH 4 budget.

Natural variability of the Arctic Ocean sea ice during the present interglacial - De Vernal, Anne; Hillaire-Marcel, Claude; Le Duc, Cynthia; Roberge, Philippe; Brice, Camille; Matthiessen, Jens; Spielhagen, Robert F.; Stein, Ruediger (Proceedings of the National Academy of Sciences, 2020)
Significance Arctic sea ice is an important component of the Earth’s climate system, but prior to its recent reduction, its long-term natural instabilities need to be better documented. In this study, information on past sea-ice conditions across the Arctic Ocean demonstrates that whereas its western and central parts remained occupied by perennial sea ice throughout the present interglacial, its southeastern sector close to the Russian margin experienced, at least, sporadic seasonal sea-ice-free conditions during the warmer part of the present interglacial until ∼4,000 y ago. Sea-ice-free conditions during summer in the southeastern Arctic Ocean seem, therefore, to be a recurrent feature linked to its natural variability during warm episodes of the past. , The impact of the ongoing anthropogenic warming on the Arctic Ocean sea ice is ascertained and closely monitored. However, its long-term fate remains an open question as its natural variability on centennial to millennial timescales is not well documented. Here, we use marine sedimentary records to reconstruct Arctic sea-ice fluctuations. Cores collected along the Lomonosov Ridge that extends across the Arctic Ocean from northern Greenland to the Laptev Sea were radiocarbon dated and analyzed for their micropaleontological and palynological contents, both bearing information on the past sea-ice cover. Results demonstrate that multiyear pack ice remained a robust feature of the western and central Lomonosov Ridge and that perennial sea ice remained present throughout the present interglacial, even during the climate optimum of the middle Holocene that globally peaked ∼6,500 y ago. In contradistinction, the southeastern Lomonosov Ridge area experienced seasonally sea-ice-free conditions, at least, sporadically, until about 4,000 y ago. They were marked by relatively high phytoplanktonic productivity and organic carbon fluxes at the seafloor resulting in low biogenic carbonate preservation. These results point to contrasted west–east surface ocean conditions in the Arctic Ocean, not unlike those of the Arctic dipole linked to the recent loss of Arctic sea ice. Hence, our data suggest that seasonally ice-free conditions in the southeastern Arctic Ocean with a dominant Arctic dipolar pattern, may be a recurrent feature under “warm world” climate.

Palynology, biostratigraphy, and paleoceanography of the Plio-Pleistocene at Ocean Drilling Program Site 887, Gulf of Alaska - Zorzi, Coralie; Matthiessen, Jens; De Vernal, Anne (Palaeogeography, Palaeoclimatology, Palaeoecology, 2020)

From bi-polar to regional distribution of modern dinoflagellate cysts, an overview of their biogeography - Marret, Fabienne; Bradley, Lee; De Vernal, Anne; Hardy, William; Kim, So-Young; Mudie, Peta; Penaud, Aurélie; Pospelova, Vera; Price, Andrea M.; Radi, Taoufik; Rochon, André (Marine Micropaleontology, 2020)

Dinocyst and acritarch biostratigraphy of the Late Pliocene to Early Pleistocene at Integrated Ocean Drilling Program Site U1307 in the Labrador Sea - Aubry, Aurélie Marcelle Renée; De Schepper, Stijn; De Vernal, Anne (Journal of Micropalaeontology, 2020)
Abstract. We have analyzed marine palynomorphs (mainly dinocysts and acritarchs) from the Integrated Ocean Drilling Program Site U1307 in the Labrador Sea in order to establish a detailed biostratigraphy for the Late Pliocene to Early Pleistocene. We have defined three magnetostratigraphically calibrated dinocyst and acritarch biozones in the Late Pliocene to Early Pleistocene. Zone LS1 is defined based on the highest occurrence of Barssidinium graminosum and covers the later Pliocene from 3.21 to 2.75 Ma. Zone LS2 is marked by the acme of Pyxidinopsis braboi which occurs between 2.75 and 2.57 Ma, thus encompassing the Plio–Pleistocene transition. Finally, zone LS3 extends from 2.57 to 2.23 Ma in the Early Pleistocene. The palynostratigraphic record of IODP Site U1307 is difficult to correlate to other North Atlantic and Nordic Seas sites mainly because of a different temporal resolution and a lack of well-defined biostratigraphic marker species at the basin scale. The low abundance, discontinuous occurrence and asynchronous events of warm-water Pliocene taxa such as Invertocysta lacrymosa, Impagidinium solidum, Ataxiodinium confusum, Melitasphaeridium choanophorum and Operculodinium? eirikianum suggest cooler conditions in the Labrador Sea than elsewhere in the North Atlantic, reflecting a strong regionalism. Nevertheless, as recorded at other locations in the North Atlantic, the disappearance of many dinocyst and acritarch taxa around 2.75 Ma at Site U1307 reflects a strong ecological response accompanying the intensification of the Northern Hemisphere glaciation.

Biomarker Distributions in (Sub)‐Arctic Surface Sediments and Their Potential for Sea Ice Reconstructions - Kolling, Henriette M.; Stein, Ruediger; Fahl, Kirsten; Sadatzki, Henrik; De Vernal, Anne; Xiao, Xiaotong (Geochemistry, Geophysics, Geosystems, 2020)
Abstract To evaluate the present sea ice changes in a longer‐term perspective, the knowledge of sea ice variability on preindustrial and geological time scales is essential. For the interpretation of proxy reconstructions it is necessary to understand the recent signals of different sea ice proxies from various regions. We present 260 new sediment surface samples collected in the (sub‐)Arctic Oceans that were analyzed for specific sea ice (IP 25 ) and open‐water phytoplankton biomarkers (brassicasterol, dinosterol, and highly branched isoprenoid [HBI] III). This new biomarker data set was combined with 615 previously published biomarker surface samples into a pan‐Arctic database. The resulting pan‐Arctic biomarker and sea ice index (PIP 25 ) database shows a spatial distribution correlating well with the diverse modern sea ice concentrations. We find correlations of P B IP 25 , P D IP 25 , and P III IP 25 with spring and autumn sea ice concentrations. Similar correlations with modern sea ice concentrations are observed in Baffin Bay. However, the correlations of the PIP 25 indices with modern sea ice concentrations differ in Fram Strait from those of the (sub‐)Arctic data set, which is likely caused by region‐specific differences in sea ice variability, nutrient availability, and other environmental conditions. The extended (sea ice) biomarker database strengthens the validity of biomarker sea ice reconstructions in different Arctic regions and shows how different sea ice proxies combined may resolve specific seasonal sea ice conditions. , Key Points IP 25 provides information about modern sea ice cover on a (sub‐)Arctic‐wide scale All PIP 25 indices correlate well with spring and autumn sea ice concentrations on a (sub‐)Arctic‐wide scale The combination of biomarker data and dinoflagellate cysts may yield an approach to reconstruct sea ice conditions during different seasons

A global database of Holocene paleotemperature records - Kaufman, Darrell; McKay, Nicholas; Routson, Cody; Erb, Michael; Davis, Basil; Heiri, Oliver; Jaccard, Samuel; Tierney, Jessica; Dätwyler, Christoph; Axford, Yarrow; Brussel, Thomas; Cartapanis, Olivier; et al. (Scientific Data, 2020)
Abstract A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

Distribution of dinocyst assemblages in surface sediment samples from the West Greenland margin - Allan, Estelle; De Vernal, Anne; Krawczyk, Diana; Moros, Matthias; Radi, Taoufik; Rochon, André; Seidenkrantz, Marit-Solveig; Zaragosi, Sébastien (Marine Micropaleontology, 2020)

Pollen-based climate reconstruction techniques for late Quaternary studies - Chevalier, Manuel; Davis, Basil A.S.; Heiri, Oliver; Seppä, Heikki; Chase, Brian M.; Gajewski, Konrad; Lacourse, Terri; Telford, Richard J.; Finsinger, Walter; Guiot, Joël; Kühl, Norbert; Maezumi, S. Yoshi; et al. (Earth-Science Reviews, 2020)

A database of Holocene temperature records for north‐eastern North America and the north‐western Atlantic - Van Bellen, Simon; De Vernal, Anne; To, Anna; Ouellet‐Bernier, Marie‐Michèle; Roy, Natasha; ClimHuNor Members (Geoscience Data Journal, 2020)
Abstract Centennial‐to‐millennial temperature records of the past provide a context for the interpretation of current and future changes in climate. Quaternary climates have been relatively well studied in north‐east North America and the adjacent Atlantic Ocean over the last decades, and new research methods have been developed to improve reconstructions. We present newly inferred reconstructions of sea surface temperature for the north‐western Atlantic region, together with a compilation of published temperature records. The database thus comprises a total of 86 records from both marine and terrestrial sites, including lakes, peatlands, ice and tree rings, each covering at least part of the Holocene. For each record, we present details on seasons covered, chronologies and information on radiocarbon dates and analytical time steps. The 86 records contain a total of 154 reconstructions of temperature and temperature‐related variables. Main proxies include pollen and dinocysts, while summer was the season for which the highest number of reconstructions were available. Many records covered most of the Holocene, but many dinocyst records did not extend to the surface, due to sediment mixing, and dendroclimate records were limited to the last millennium. The database allows for the exploration of linkages between sea ice and climate and may be used in conjunction with other palaeoclimate and palaeoenvironmental records, such as wildfire records and peatland dynamics. This inventory may also aid the identification of gaps in the geographic distribution of past temperature records thus guiding future research efforts.

An overview and brief description of common marine organic-walled dinoflagellate cyst taxa occurring in surface sediments of the Northern Hemisphere - Van Nieuwenhove, Nicolas; Head, Martin J.; Limoges, Audrey; Pospelova, Vera; Mertens, Kenneth N.; Matthiessen, Jens; De Schepper, Stijn; De Vernal, Anne; Eynaud, Frédérique; Londeix, Laurent; Marret, Fabienne; Penaud, Aurélie; et al. (Marine Micropaleontology, 2020)

Historical Perspectives on Exceptional Climatic Years at the Labrador/Nunatsiavut Coast 1780 to 1950 - Ouellet-Bernier, Marie-Michèle; De Vernal, Anne; Chartier, Daniel; Boucher, Étienne (Quaternary Research, 2021)
Abstract This interdisciplinary study presents a human perspective on climatic variations by combining documentary, discursive, instrumental, and proxy data. Historical sources were used to characterize climate variations along the coast of Labrador/Nunatsiavut during the 19 th century and the first half of the 20 th century. Written and early instrumental archives provided original information on the state and perception of climate before the establishment of meteorological stations, which permitted an intra-annual perspective on climatic variations. Written sources depicted the sensitivity of humans to climatic variations. Exceptional seasonal climatic events were extracted from documentary and discursive sources, which were complemented by tree-ring and early instrumental data. From 1780 to 1900, data indicated a succession of relatively warm and cold episodes. Most warm periods were described as stormy and variable. The final part of the studied records showed cold conditions from 1900 to 1925 and warm conditions from 1925 to 1950. Historical sources helped to discriminate a seasonal signal. Mild autumn-winter conditions were recorded since 1910 in relation with positive anomalies of the North Atlantic Oscillation in winter. Relatively warm spring-summer conditions were recorded after 1920, which corresponds to a phase of positive anomaly of the Atlantic Multidecadal Oscillation.

Holocene variability in sea ice and primary productivity in the northeastern Baffin Bay - Saini, Jeetendra; Stein, Ruediger; Fahl, Kirsten; Weiser, Jens; Hebbeln, Dierk; Hillaire-Marcel, Claude; De Vernal, Anne (arktos, 2020)
Abstract Arctic sea ice is a critical component of the climate system, known to influence ocean circulation, earth’s albedo, and ocean–atmosphere heat and gas exchange. Current developments in the use of IP 25 (a sea ice proxy with 25 carbon atoms only synthesized by Arctic sea ice diatoms) have proven it to be a suitable proxy for paleo-sea ice reconstructions over hundreds of thousands to even millions of years. In the NE Baffin Bay, off NW Greenland, Melville Bugt is a climate-sensitive region characterized by strong seasonal sea ice variability and strong melt-water discharge from the Greenland Ice Sheet (GIS). Here, we present a centennial-scale resolution Holocene sea ice record, based on IP 25 and open-water phytoplankton biomarkers (brassicasterol, dinosterol and HBI III) using core GeoB19927-3 (73° 35.26′ N, 58° 05.66′ W). Seasonal to ice-edge conditions near the core site are documented for most of the Holocene period with some significant variability. In the lower-most part, a cold interval characterized by extensive sea ice cover and very low local productivity is succeeded by an interval (~ 9.4–8.5 ka BP) with reduced sea ice cover, enhanced GIS spring melting, and strong influence of the West Greenland Current (WGC). From ~ 8.5 until ~ 7.8 ka BP, a cooling event is recorded by ice algae and phytoplankton biomarkers. They indicate an extended sea ice cover, possibly related to the opening of Nares Strait, which may have led to an increased influx of Polar Water into NE-Baffin Bay. The interval between ~ 7.8 and ~ 3.0 ka BP is characterized by generally reduced sea ice cover with millennial-scale variability of the (late winter/early spring) ice-edge limit, increased open-water conditions (polynya type), and a dominant WGC carrying warm waters at least as far as the Melville Bugt area. During the last ~ 3.0 ka BP, our biomarker records do not reflect the late Holocene ‘Neoglacial cooling’ observed elsewhere in the Northern Hemisphere, possibly due to the persistent influence of the WGC and interactions with the adjacent fjords. Peaks in HBI III at about ~ 2.1 and ~ 1.3 ka BP, interpreted as persistent ice-edge situations, might correlate with the Roman Warm Period (RWP) and Medieval Climate Anomaly (MCA), respectively, in-phase with the North Atlantic Oscillation (NAO) mode. When integrated with marine and terrestrial records from other circum-Baffin Bay areas (Disko Bay, the Canadian Arctic, the Labrador Sea), the Melville Bugt biomarker records point to close ties with high Arctic and Northern Hemispheric climate conditions, driven by solar and oceanic circulation forcings.

Distribution of common modern dinoflagellate cyst taxa in surface sediments of the Northern Hemisphere in relation to environmental parameters: The new n=1968 database - De Vernal, Anne; Radi, Taoufik; Zaragosi, Sebastien; Van Nieuwenhove, Nicolas; Rochon, André; Allan, Estelle; De Schepper, Stijn; Eynaud, Frédérique; Head, Martin J.; Limoges, Audrey; Londeix, Laurent; Marret, Fabienne; et al. (Marine Micropaleontology, 2020)

Identifying the signature of sea-surface properties in dinocyst assemblages: Implications for quantitative palaeoceanographical reconstructions by transfer functions and analogue techniques - Hohmann, Sabrina; Kucera, Michal; De Vernal, Anne (Marine Micropaleontology, 2020)

Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4) - Otto-Bliesner, Bette L.; Brady, Esther C.; Zhao, Anni; Brierley, Chris M.; Axford, Yarrow; Capron, Emilie; Govin, Aline; Hoffman, Jeremy S.; Isaacs, Elizabeth; Kageyama, Masa; Scussolini, Paolo; Tzedakis, Polychronis C.; et al. (Climate of the Past, 2021)
Abstract. The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to the Coupled Model Intercomparison Project (CMIP6) is the Tier 1 Last Interglacial experiment for 127 000 years ago (lig127k), designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models as for the future and following a common experimental protocol. Here we present a first analysis of a multi-model ensemble of 17 climate models, all of which have completed the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. The equilibrium climate sensitivity (ECS) of these models varies from 1.8 to 5.6 ∘C. The seasonal character of the insolation anomalies results in strong summer warming over the Northern Hemisphere continents in the lig127k ensemble as compared to the CMIP6 piControl and much-reduced minimum sea ice in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than the CMIP6 midHolocene simulations as expected from the larger insolation anomalies at 127 than 6 ka. New synthesis for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and for precipitation over the Northern Hemisphere continents. The model–data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6–Paleoclimate Modeling Intercomparison Project (PMIP4) lig127k simulations, in combination with the proxy record, improve our confidence in future projections of monsoons, surface temperature, and Arctic sea ice, thus providing a key target for model evaluation and optimization.

Baffin Bay late Neogene palynostratigraphy at Ocean Drilling Program Site 645 - Aubry, Aurélie M.R.; De Vernal, Anne; Knutz, Paul C. (Canadian Journal of Earth Sciences, 2021)
Analyses of marine and terrestrial palynomorphs of Ocean Drilling Program (ODP) Site 645 in Baffin Bay led us to define a new biostratigraphical scheme covering the late Miocene to Pleistocene based on dinocyst and acritarch assemblages. Four biozones were defined. The first one, from 438.6 m below sea floor (mbsf) to 388 mbsf, can be assigned a late Miocene to early Pliocene age (>4.5 Ma), based on the common occurrence of Cristadinium diminutivum and Selenopemphix brevispinosa. Biozone 2, spanning from an erosional unconformity to a recovery hiatus, is marked by the highest occurrences (HOs) of Veriplicidium franklinii and Cristadinium diminutivum, which suggest an early Pliocene age >3.6 Ma (∼4.5 to ∼3.6 Ma). Biozone 3, above the recovery hiatus and up to 220.94 mbsf, corresponds to a late Pliocene or early Pleistocene age based on occurrences of Bitectatodinium readwaldii, Cymatiosphaera? icenorum, and Lavradosphaera canalis. Finally, between 266.4 and 120.56 mbsf, Biozone 4, marked by the HO of Filisphaera filifera, Filisphaera microornata, and Habibacysta tectata, has an early Pleistocene age (>1.4 Ma). Our biostratigraphy implies that horizon b1 of the Baffin Bay seismic stratigraphy corresponds to the recovery hiatus at ODP Site 645, which suggests a very thick Pliocene sequence along the Baffin Island slope. Dinocyst assemblages and terrestrial palynomorphs in our records indicate that the late Miocene and (or) early Pliocene were characterized by relatively warm coastal surface waters and boreal forest or forested tundra vegetation over adjacent lands. In contrast, the early Pleistocene dinocyst assemblages above the recovery hiatus indicate cold surface waters, while pollen data suggest reduced vegetation cover on adjacent lands.

The role of Arctic gateways on sea ice and circulation in the Arctic and North Atlantic Oceans: a sensitivity study with an ocean-sea-ice model - Karami, Mehdi Pasha; Myers, Paul G.; De Vernal, Anne; Tremblay, L. Bruno; Hu, Xianmin (Climate Dynamics, 2021)

Past abrupt changes, tipping points and cascading impacts in the Earth system - Brovkin, Victor; Brook, Edward; Williams, John W.; Bathiany, Sebastian; Lenton, Timothy M.; Barton, Michael; DeConto, Robert M.; Donges, Jonathan F.; Ganopolski, Andrey; McManus, Jerry; Praetorius, Summer; De Vernal, Anne; et al. (Nature Geoscience, 2021)

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences - Kageyama, Masa; Sime, Louise C.; Sicard, Marie; Guarino, Maria-Vittoria; De Vernal, Anne; Stein, Ruediger; Schroeder, David; Malmierca-Vallet, Irene; Abe-Ouchi, Ayako; Bitz, Cecilia; Braconnot, Pascale; Brady, Esther C.; et al. (Climate of the Past, 2021)
Abstract. The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×106 km2, compared to 6.46×106 km2 for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×106 km2 for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 % yr−1) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Biogenic carbonate fluxes and preservation in the northwestern Labrador Sea since the Last Glacial Maximum - Marshall, Nicole R.; De Vernal, Anne; Mucci, Alfonso; Filippova, Alexandra; Kienast, Markus; Gibb, Olivia; Hillaire-Marcel, Claude (Palaeogeography, Palaeoclimatology, Palaeoecology, 2021)

Insolation vs. meltwater control of productivity and sea surface conditions off SW Greenland during the Holocene - Allan, Estelle; De Vernal, Anne; Seidenkrantz, Marit‐Solveig; Briner, Jason P.; Hillaire‐Marcel, Claude; Pearce, Christof; Meire, Lorenz; Røy, Hans; Mathiasen, Anders Møller; Nielsen, Mikkel Thy; Plesner, Jane Lund; Perner, Kerstin (Boreas, 2021)
We address here the specific timing and amplitude of sea‐surface conditions and productivity changes off SW Greenland, northern Labrador Sea, in response to the high deglacial meltwater rates, the Early Holocene maximum insolation and Neoglacial cooling. Dinocyst assemblages from sediment cores collected off Nuuk were used to set up quantitative records of sea ice cover, seasonal sea‐surface temperature (SST), salinity (SSS), and primary productivity, with a centennial to millennial scale resolution. Until ~10 ka BP, ice‐proximal conditions are suggested by the quasi‐exclusive dominance of heterotrophic taxa and low dinocyst concentrations. At about 10 ka BP, an increase in species diversity and abundance of phototrophic taxa marks the onset of interglacial conditions at a regional scale, with summer SST reaching up to 10 °C between 8 and 5 ka BP, thus in phase with the Holocene Thermal Maximum as recorded in the southern Greenlandic areas/northern Labrador Sea. During this interval, low SSS but high productivity prevailed in response to high meltwater discharge and nutrient inputs from the Greenland Ice Sheet. After ~5 ka BP, a decrease in phototrophic taxa marks a two‐step cooling of surface waters. The first started at ~5 ka BP, and the second at ~3 ka BP, with a shift toward colder conditions and higher SSS suggesting reduced meltwater discharge during the Neoglacial. This second step coincides with the disappearance of the Saqqaq culture. The gap in human occupation in west Greenland, between the Dorset and the Norse settlements from 2000 to 1000 years BP, might be linked to high amplitude and high frequency variability of ocean and climate conditions.

Past Warmth and Its Impacts During the Holocene Thermal Maximum in Greenland - Axford, Yarrow; De Vernal, Anne; Osterberg, Erich C. (Annual Review of Earth and Planetary Sciences, 2021)
Higher boreal summer insolation in the early to middle Holocene drove thousands of years of summer warming across the Arctic. Modern-day warming has distinctly different causes, but geologic data from this past warm period hold lessons for the future. We compile Holocene temperature reconstructions from ice, lake, and marine cores around Greenland, where summer temperatures are globally important due to their influence on ice sheet mass balance, ocean circulation, and sea ice. Highlighting and accounting for some key issues with proxy interpretation, we find that much of Greenland experienced summers 3 to 5°C warmer than the mid-twentieth century in the early Holocene—earlier and stronger warming than often presumed. Warmth had dramatic consequences: Many glaciers disappeared, perennial sea ice retreated, plants and animals migrated northward, the Greenland Ice Sheet shrank rapidly, and increased meltwater discharge led to strong marine water stratification and enhanced winter sea ice in some areas. ▪  Summer air temperatures and open ocean temperatures around much of Greenland peaked in the early Holocene in response to elevated summer insolation. ▪  Peak summer air temperatures ranged from 3 to 5°C warmer than the mid-twentieth century in northwest and central Greenland to perhaps 1 to 2°C warmer in south Greenland. ▪  Many differences between records can be explained by proxy seasonality, ice sheet elevation changes, vegetation analogs and lags, and the nearshore effects of ice sheet meltwater. ▪  Early Holocene warmth dramatically affected glaciers and the Greenland Ice Sheet; meltwater discharge, nearshore ocean salinity, and sea ice; and diverse flora and fauna.

Challenging the hypothesis of an Arctic Ocean lake during recent glacial episodes - Hillaire‐Marcel, Claude; Myers, Paul G.; Marshall, Shawn; Tarasov, Lev; Purcell, Karl; Not, Christelle; De Vernal, Anne (Journal of Quaternary Science, 2022)
ABSTRACT The Arctic Ocean is one of the last frontiers on Earth with many unknowns about its geological and climate history and considerable speculation on its role in the Earth's climate and ocean system. It has been proposed recently that it was occupied by a freshwater body of more than 9.5 × 10 6 km 3 underneath a thick ice mass during part of glacial isotopic stages 6 and 4. We argue that such a dramatic scenario, implying replacement of marine waters by freshwater throughout the entire Arctic Ocean and Nordic Seas, is physically implausible. The very low 230 Th excesses ( 230 Th xs ) observed in sediments from these intervals were used as evidence for the presence of a U‐depleted overlying freshwater column. We show here that they may simply result from short, sporadic sedimentary pulses, below multiyear sea ice or ice shelves, linked to deglacial ice streaming and surging events interrupting long‐duration sedimentary gaps. Due to this sporadic sedimentation regime, interpolating time from 230 Th xs data or between benchmark ages in sedimentary sequences would simply be erroneous.

Complex spatio-temporal structure of the Holocene Thermal Maximum - Cartapanis, Olivier; Jonkers, Lukas; Moffa-Sanchez, Paola; Jaccard, Samuel L.; De Vernal, Anne (Nature Communications, 2022)
Abstract Inconsistencies between Holocene climate reconstructions and numerical model simulations question the robustness of climate models and proxy temperature records. Climate reconstructions suggest an early-middle Holocene Thermal Maximum (HTM) followed by gradual cooling, whereas climate models indicate continuous warming. This discrepancy either implies seasonal biases in proxy-based climate reconstructions, or that the climate model sensitivity to forcings and feedbacks needs to be reevaluated. Here, we analyze a global database of Holocene paleotemperature records to investigate the spatiotemporal structure of the HTM. Continental proxy records at mid and high latitudes of the Northern Hemisphere portray a “classic” HTM (8–4 ka). In contrast, marine proxy records from the same latitudes reveal an earlier HTM (11–7ka), while a clear temperature anomaly is missing in the tropics. The results indicate a heterogeneous response to climate forcing and highlight the lack of globally synchronous HTM.

A reassessment of Nd-isotopes and clay minerals as tracers of the Holocene Pacific water flux through Bering Strait - Song, Tengfei; Hillaire-Marcel, Claude; De Vernal, Anne; Liu, Yanguang; Wang, Weiguo; Huang, Yuanhui (Marine Geology, 2022)

Potential and limitation of 230Th-excess as a chronostratigraphic tool for late Quaternary Arctic Ocean sediment studies: An example from the Southern Lomonosov Ridge - Purcell, Karl; Hillaire-Marcel, Claude; De Vernal, Anne; Ghaleb, Bassam; Stein, Ruediger (Marine Geology, 2022)

Challenging Radiocarbon Chronostratigraphies in Central Arctic Ocean Sediment - Hillaire‐Marcel, C.; De Vernal, A.; Rong, Y.; Roberge, P.; Song, T. (Geophysical Research Letters, 2022)
Abstract Based on the analysis of fish otolith assemblages from surface sediments of the Lomonosov Ridge (Arctic Ocean), we demonstrate that the very low Holocene sedimentation rates and winnowing of fine sediments result in the mixing of the whole Holocene populations at the sediment surface. Specimens from the Marine Isotope Stage (MIS) 3 or older could even be recovered in the surface due to a sedimentary hiatus at some locations in the central Arctic during the last glacial maximum. Two examples illustrate that 14 C‐stratigraphies from planktic foraminifers in underlying cored sediments reflect the mixing between Holocene and MIS 3 or older populations, thus invalidating continuous age‐depth inferences based on 14 C ages. Hence, much caution is required when attempting to set paleoceanographic reconstructions based on 14 C chronologies in a low sediment accumulation rate environment such as the central Arctic Ocean. Already published paleoceanographic reconstructions from this area might thus require some revisions. , Plain Language Summary Radiocarbon ages of microfossils (fish otoliths) collected at the surface sediments of the Lomonosov Ridge, in the central Arctic Ocean, indicate that all populations that developed during the present interglacial are mixed within the approximately 1 cm‐thick surface layer. Fossil assemblages occasionally include specimens from older warm intervals. The stacking of fossil spanning thousands of years is due to the very low sediment accumulation rate of the area, the post‐depositional winnowing of fine sediments and mixing by benthic organisms. These process result in the impossibility to document the faunal evolution in the central Arctic Ocean during the last few tens of thousands of years using such fossils. , Key Points Fish otolith radiocarbon age distributions in surface sediments illustrate the mixing of Holocene and pre‐Last Glacial Maximum populations Low sedimentation rates, particle winnowing and sedimentary gaps may impact microfossil mixing and 14 C chronologies Published paleoclimate/paleoceanographic records from similar sites might thus require some reinterpretation

A comment about "A sedimentary record from the Makarov Basin, Arctic Ocean, reveals changing middle to Late Pleistocene glaciation patterns" (Quat. Sci. Rev., 270 (2021), p. 107176) from W. Xiao, L. Polyak, R. Wang, C. Not, L. Dong, Y. Liu, T. Ma, T. Zhang - Hillaire-Marcel, Claude; De Vernal, Anne (Quaternary Science Reviews, 2022)

Millennial‐scale oscillations and an environmental regime shift around the Middle to Late Holocene transition in the North Atlantic region based on a multiproxy record from Isfjorden, West Spitsbergen - Brice, Camille; De Vernal, Anne; Francus, Pierre; Forwick, Matthias; Nam, Seung‐Il (Boreas, 2023)
Palynological and sedimentological analyses were performed on the sediment core HH16‐1205‐GC retrieved from the central Isfjorden, West Spitsbergen. The sequence, which spans the last 7000 years, revealed an overall cooling trend with an important climate shift between 4.4 and 3.8 cal. ka BP, in addition to millennial‐scale oscillations. Sea‐surface reconstruction from dinocyst assemblages indicates a decrease in summer sea‐surface temperature, from 2.5 to 1.5 °C, and primary productivity, from 750 to 650 gC m −2 a −1 over the last 7000 years. From around 6.8 to 5.8 cal. ka BP, the sedimentological and palynological data suggest a predominant sediment supply from the inner part of the fjord, ice rafting, dense sea ice cover, strongly stratified water masses and high primary productivity. The interval from 4.4 to 3.8 cal. ka BP is marked by a layer of coarser material and a significant decrease in the grain‐size mode. Our geochemical data show large‐amplitude fluctuations after 2.0 cal. ka BP, while an increase in the dinocysts Impagidinium pallidum and Spiniferites elongatus from 2.0 to 1.2 cal. ka BP suggests enhanced Atlantic Water inflow. The dinocyst‐based reconstructions also reveal large‐amplitude millennial fluctuations in sea ice cover, summer sea‐surface temperature and salinity. Wavelet analysis and cross‐wavelet analysis on K/Ti ratio coupled with sea‐ice estimates confirm a strong signal with a periodicity of 1200–1500 years.

Distribution of modern dinocysts and pollen in the western Mediterranean Sea (Algerian margin and Gulf of Lion) - Coussin, V.; Penaud, A.; Combourieu-Nebout, N.; Peyron, O.; Schmidt, S.; Zaragosi, S.; De Vernal, A.; Babonneau, N. (Marine Micropaleontology, 2022)

Benthic Foraminiferal Assemblages from the Laurentian Channel in the Lower Estuary and Gulf of ST. Lawrence, Eastern Canada: Tracers of Bottom-Water Hypoxia - Audet, Tiffany; De Vernal, Anne; Mucci, Alfonso; Seidenkrantz, Marit-Solveig; Hillaire-Marcel, Claude; Carnero-Bravo, Vladislav; Gélinas, Yves (Journal of Foraminiferal Research, 2023)
ABSTRACT Over the past century, an increase in temperatures and a decrease in dissolved oxygen concentrations have been observed in the bottom waters of the Laurentian Channel (LC), throughout the Lower St. Lawrence Estuary (LSLE) and the Gulf of St. Lawrence (GSL), eastern Canada. To document the impact of these changes, we analyzed the benthic foraminiferal assemblages and geochemical signatures of four sediment cores taken in the LC. Radiometric measurements (210Pb, 226Ra, 137Cs) indicate that the studied cores encompass the last 50 years of sedimentation in the LSLE and the last ∼160 years in the GSL. The sedimentary record shows a 60 to 65% decrease in benthic foraminiferal taxonomic diversity in the LC since the 1960s. An accelerated change in the foraminiferal assemblages is observed at approximately the same time at all studied sites, around the late 1990s and the early 2000s, towards populations dominated by the hypoxia-tolerant indicator taxa Brizalina subaenariensis, Eubuliminella exilis, and Globobulimina auriculata. This evolution of assemblages reflects incursions of the hypoxic zone into the western GSL over the last decades. The results of our multivariate analyses highlight the potential of benthic foraminiferal assemblages as a proxy of bottom-water hypoxia.

Holocene Paleoenvironmental Implications of Diatom, Non-Pollen Palynomorph, and Organic Carbon Records from the Kandalaksha Bay of the White Sea (European Arctic) - Polyakova, Yelena; Agafonova, Elizaveta; Novichkova, Ekaterina; De Vernal, Anne (Geosciences, 2023)
Variations in sea surface conditions and sea level through the Holocene in the Kandalaksha Bay, the White Sea, were reconstructed based on the study of core sediments from the outer Kandalaksha Bay, using the modern analog technique applied to dinocysts in addition to diatoms, TOC, δ13Corg, CaCO3, and grain size data. The chronostratigraphy of the core sediments was defined from accelerator mass spectrometry 14C dates on mollusk shells. The results indicated an increase in water depth in the outer Kandalaksha Bay and in the central Dvina Bay until the late Holocene. From about 9.5 to 7.5 cal kyr BP, the data suggested a general trend of increasing sea surface temperatures (up to 14 °C), at least in areas with inflow of Atlantic waters. The last 2.5 kyr were characterized by increased freshwater runoff to the White Sea.

Microfaunal Recording of Recent Environmental Changes in the Herschel Basin, Western Arctic Ocean - Falardeau, Jade; De Vernal, Anne; Seidenkrantz, Marit-Solveig; Cronin, Thomas M.; Gemery, Laura; Chassiot, Léo; Fritz, Michael; Carnero-Bravo, Vladislav; Hillaire-Marcel, Claude; Archambault, Philippe (Journal of Foraminiferal Research, 2023)
ABSTRACT Microfaunal assemblages of benthic foraminifera, ostracods, and tintinnids from two marine sediment cores retrieved from the Herschel Basin of the Canadian Beaufort Sea shelf document relationships with environmental parameters such as salinity, sea-ice cover, and turbulence. Cores YC18-HB-GC01 and PG2303-1 were collected at 18 and 32 m water depth, respectively. At these sites, sediment accumulation rates range between 0.6 and 1.7 cm yr–1 allowing a near-annual temporal resolution over the last 50 years. Multivariate analyses indicate that benthic foraminiferal assemblages respond primarily to food supply. Dissimilarities between the microfaunal assemblages of the two cores are mainly the result of bottom water salinity levels linked to water depth. High abundance of the benthic foraminiferal species Elphidium clavatum and occurrences of Elphidium bartletti point to varying, but relatively low, salinities at the shallow core site YC18-HB-GC01, which may be affected by variations in the summer halocline depth. Higher species diversity and more abundant Cassidulina reniforme and Stainforthia feylingi characterize the deeper core PG2303-1, which might reflect more stable conditions and higher bottom-water salinities throughout the studied time interval. The most important microfaunal shift of the last 50 years, observed in the shallower longer core YC18-HB-GC01, occurred at the turn of the 21st century. Prior to ∼2000 CE, the presence of Islandiella norcrossi indicates more stable and saline conditions. Since ∼2000 CE, increased abundances of Haynesina nivea and of the ciliate Tintinnopsis fimbriata suggest decreased salinity and increased turbidity. An increased abundance of Eoeponidella pulchella after ∼2000 CE suggests a concurrent increase in productivity in the last two decades. This shift is nearly synchronous with a decrease in mean summer sea-ice concentration, which can play an important role in bottom water stability on the shelf. Easterly winds can induce a reduction in the sea-ice cover, but also foster a westward spreading of the Mackenzie River plume and the upwelling of nutrient-rich Pacific waters onto the shelf. Both factors would explain the increased freshening and productivity of the Herschel Basin. The last two decades were also marked by a decrease in ostracod abundance that may relate to higher water turbidity. This study shows that combining information from benthic foraminifera, ostracods, and tintinnids provides a comprehensive insight into recent hydrographic/climatic changes in nearshore Arctic habitats, where productivity is critical for the food security of local communities.

Southern westerly winds and paleoceanography of the San Jorge Gulf (SW-Atlantic ocean, Argentina) during the last 14,000 years - Faye, Simon; Rochon, André; St-Onge, Guillaume; Vilanova, Isabel; De Vernal, Anne; Desiage, Pierre-Arnaud (Quaternary Science Reviews, 2023)

Northward extension of the East Asian summer monsoon during the mid-Holocene - Piao, Jinling; Chen, Wen; Wang, Lin; Pausata, Francesco S.R.; Zhang, Qiong (Global and Planetary Change, 2020)

Development and testing scenarios for implementing land use and land cover changes during the Holocene in Earth system model experiments - Harrison, Sandy P.; Gaillard, Marie-José; Stocker, Benjamin D.; Vander Linden, Marc; Klein Goldewijk, Kees; Boles, Oliver; Braconnot, Pascale; Dawson, Andria; Fluet-Chouinard, Etienne; Kaplan, Jed O.; Kastner, Thomas; Pausata, Francesco S. R.; et al. (Geoscientific Model Development, 2020)
Abstract. Anthropogenic changes in land use and land cover (LULC) during the pre-industrial Holocene could have affected regional and global climate. Existing scenarios of LULC changes during the Holocene are based on relatively simple assumptions and highly uncertain estimates of population changes through time. Archaeological and palaeoenvironmental reconstructions have the potential to refine these assumptions and estimates. The Past Global Changes (PAGES) LandCover6k initiative is working towards improved reconstructions of LULC globally. In this paper, we document the types of archaeological data that are being collated and how they will be used to improve LULC reconstructions. Given the large methodological uncertainties involved, both in reconstructing LULC from the archaeological data and in implementing these reconstructions into global scenarios of LULC, we propose a protocol to evaluate the revised scenarios using independent pollen-based reconstructions of land cover and climate. Further evaluation of the revised scenarios involves carbon cycle model simulations to determine whether the LULC reconstructions are consistent with constraints provided by ice core records of CO2 evolution and modern-day LULC. Finally, the protocol outlines how the improved LULC reconstructions will be used in palaeoclimate simulations in the Palaeoclimate Modelling Intercomparison Project to quantify the magnitude of anthropogenic impacts on climate through time and ultimately to improve the realism of Holocene climate simulations.

Initiation of a stable convective hydroclimatic regime in Central America circa 9000 years BP - Winter, Amos; Zanchettin, Davide; Lachniet, Matthew; Vieten, Rolf; Pausata, Francesco S. R.; Ljungqvist, Fredrik Charpentier; Cheng, Hai; Edwards, R. Lawrence; Miller, Thomas; Rubinetti, Sara; Rubino, Angelo; Taricco, Carla (Nature Communications, 2020)
Abstract Many Holocene hydroclimate records show rainfall changes that vary with local orbital insolation. However, some tropical regions display rainfall evolution that differs from gradual precessional pacing, suggesting that direct rainfall forcing effects were predominantly driven by sea-surface temperature thresholds or inter-ocean temperature gradients. Here we present a 12,000 yr continuous U/Th-dated precipitation record from a Guatemalan speleothem showing that Central American rainfall increased within a 2000 yr period from a persistently dry state to an active convective regime at 9000 yr BP and has remained strong thereafter. Our data suggest that the Holocene evolution of Central American rainfall was driven by exceeding a temperature threshold in the nearby tropical oceans. The sensitivity of this region to slow changes in radiative forcing is thus strongly mediated by internal dynamics acting on much faster time scales.

The Greening of the Sahara: Past Changes and Future Implications - Pausata, Francesco S.R.; Gaetani, Marco; Messori, Gabriele; Berg, Alexis; Maia De Souza, Danielle; Sage, Rowan F.; deMenocal, Peter B. (One Earth, 2020)

The Effect of Strong Volcanic Eruptions on ENSO - McGregor, Shayne; Khodri, Myriam; Maher, Nicola; Ohba, Masamichi; Pausata, Francesco S. R.; Stevenson, Samantha (Geophysical Monograph Series, 2020)

ITCZ shift and extratropical teleconnections drive ENSO response to volcanic eruptions - Pausata, Francesco S. R.; Zanchettin, Davide; Karamperidou, Christina; Caballero, Rodrigo; Battisti, David S. (Science Advances, 2020)
Volcanic eruptions trigger ENSO response through shifts in the ITCZ and extratropical-to-tropical teleconnections. , The mechanisms through which volcanic eruptions affect the El Niño–Southern Oscillation (ENSO) state are still controversial. Previous studies have invoked direct radiative forcing, an ocean dynamical thermostat (ODT) mechanism, and shifts of the Intertropical Convergence Zone (ITCZ), among others, to explain the ENSO response to tropical eruptions. Here, these mechanisms are tested using ensemble simulations with an Earth system model in which volcanic aerosols from a Tambora-like eruption are confined either in the Northern or the Southern Hemisphere. We show that the primary drivers of the ENSO response are the shifts of the ITCZ together with extratropical circulation changes, which affect the tropics; the ODT mechanism does not operate in our simulations. Our study highlights the importance of initial conditions in the ENSO response to tropical volcanic eruptions and provides explanations for the predominance of posteruption El Niño events and for the occasional posteruption La Niña in observations and reconstructions.

End of Green Sahara amplified mid- to late Holocene megadroughts in mainland Southeast Asia - Griffiths, Michael L.; Johnson, Kathleen R.; Pausata, Francesco S. R.; White, Joyce C.; Henderson, Gideon M.; Wood, Christopher T.; Yang, Hongying; Ersek, Vasile; Conrad, Cyler; Sekhon, Natasha (Nature Communications, 2020)
Abstract Between 5 and 4 thousand years ago, crippling megadroughts led to the disruption of ancient civilizations across parts of Africa and Asia, yet the extent of these climate extremes in mainland Southeast Asia (MSEA) has never been defined. This is despite archeological evidence showing a shift in human settlement patterns across the region during this period. We report evidence from stalagmite climate records indicating a major decrease of monsoon rainfall in MSEA during the mid- to late Holocene, coincident with African monsoon failure during the end of the Green Sahara. Through a set of modeling experiments, we show that reduced vegetation and increased dust loads during the Green Sahara termination shifted the Walker circulation eastward and cooled the Indian Ocean, causing a reduction in monsoon rainfall in MSEA. Our results indicate that vegetation-dust climate feedbacks from Sahara drying may have been the catalyst for societal shifts in MSEA via ocean-atmospheric teleconnections.

Robust Longitudinally Variable Responses of the ITCZ to a Myriad of Climate Forcings - Atwood, Alyssa R.; Donohoe, Aaron; Battisti, David S.; Liu, Xiaojuan; Pausata, Francesco S. R. (Geophysical Research Letters, 2020)
Abstract We evaluate the longitudinal variation in meridional shifts of the tropical rainbelt in response to natural and anthropogenic forcings using a large suite of coupled climate model simulations. We find that the energetic framework of the zonal mean Hadley cell is generally not useful for characterizing shifts of the rainbelt at regional scales, regardless of the characteristics of the forcing. Forcings with large hemispheric asymmetry such as extratropical volcanic forcing, meltwater forcing, and the Last Glacial Maximum give rise to robust zonal mean shifts of the rainbelt; however, the direction and magnitude of the shift vary strongly as a function of longitude. Even the Pacific rainband does not shift uniformly under any forcing considered. Forcings with weak hemispheric asymmetry such as CO 2 and mid‐Holocene forcing give rise to zonal mean shifts that are small or absent, but the rainbelt does shift regionally in coherent ways across models that may have important dynamical consequences. , Plain Language Summary A band of heavy precipitation spanning the deep tropics is an essential feature of the climate system that diverse ecosystems and billions of people depend on. It is well known that this rainbelt, when averaged across all longitudes, shifts north and south in response to heating or cooling the atmosphere in one hemisphere more than the other; this framework has been widely applied to study past tropical rainfall changes under differing climate states. However, we show using many different climate model experiments that this framework does not apply to regional shifts in the rainbelt. Changes in the rainbelt vary from place to place, and thus, data documenting north or south shifts in one location cannot be used to infer similar shifts at other longitudes. , Key Points The zonal mean ITCZ framework is generally not useful for characterizing regional shifts of the tropical rainbelt, regardless of the forcing Meridional shifts of the tropical rainbelt vary strongly with longitude under all forcings considered All forcings produce robust regional shifts in the rainbelt that are larger than (and sometime oppose the direction of) the zonal mean shift

Atlantic hurricane response to Saharan greening and reduced dust emissions during the mid-Holocene - Dandoy, Samuel; Pausata, Francesco S. R.; Camargo, Suzana J.; Laprise, René; Winger, Katja; Emanuel, Kerry (Climate of the Past, 2021)
Abstract. We use a high-resolution regional climate model to investigate the changes in Atlantic tropical cyclone (TC) activity during the period of the mid-Holocene (MH: 6000 years BP) with a larger amplitude of the seasonal cycle relative to today. This period was characterized by increased boreal summer insolation over the Northern Hemisphere, a vegetated Sahara and reduced airborne dust concentrations. A set of sensitivity experiments was conducted in which solar insolation, vegetation and dust concentrations were changed in turn to disentangle their impacts on TC activity in the Atlantic Ocean. Results show that the greening of the Sahara and reduced dust loadings (MHGS+RD) lead to a larger increase in the number of Atlantic TCs (27 %) relative to the pre-industrial (PI) climate than the orbital forcing alone (MHPMIP; 9 %). The TC seasonality is also highly modified in the MH climate, showing a decrease in TC activity during the beginning of the hurricane season (June to August), with a shift of its maximum towards October and November in the MHGS+RD experiment relative to PI. MH experiments simulate stronger hurricanes compared to PI, similar to future projections. Moreover, they suggest longer-lasting cyclones relative to PI. Our results also show that changes in the African easterly waves are not relevant in altering the frequency and intensity of TCs, but they may shift the location of their genesis. This work highlights the importance of considering vegetation and dust changes over the Sahara region when investigating TC activity under a different climate state.

The remote response of the South Asian Monsoon to reduced dust emissions and Sahara greening during the middle Holocene - Pausata, Francesco S. R.; Messori, Gabriele; Yun, Jayoung; Jalihal, Chetankumar A.; Bollasina, Massimo A.; Marchitto, Thomas M. (Climate of the Past, 2021)
Abstract. Previous studies based on multiple paleoclimate archives suggested a prominent intensification of the South Asian Monsoon (SAM) during the mid-Holocene (MH, ∼6000 years before present). The main forcing that contributed to this intensification is related to changes in the Earth's orbital parameters. Nonetheless, other key factors likely played important roles, including remote changes in vegetation cover and airborne dust emission. In particular, northern Africa also experienced much wetter conditions and a more mesic landscape than today during the MH (the so-called African Humid Period), leading to a large decrease in airborne dust globally. However, most modeling studies investigating the SAM changes during the Holocene overlooked the potential impacts of the vegetation and dust emission changes that took place over northern Africa. Here, we use a set of simulations for the MH climate, in which vegetation over the Sahara and reduced dust concentrations are considered. Our results show that SAM rainfall is strongly affected by Saharan vegetation and dust concentrations, with a large increase in particular over northwestern India and a lengthening of the monsoon season. We propose that this remote influence is mediated by anomalies in Indian Ocean sea surface temperatures and may have shaped the evolution of the SAM during the termination of the African Humid Period.

The archaeology of climate change: The case for cultural diversity - Burke, Ariane; Peros, Matthew C.; Wren, Colin D.; Pausata, Francesco S. R.; Riel-Salvatore, Julien; Moine, Olivier; De Vernal, Anne; Kageyama, Masa; Boisard, Solène (Proceedings of the National Academy of Sciences, 2021)
Anthropogenic climate change is currently driving environmental transformation on a scale and at a pace that exceeds historical records. This represents an undeniably serious challenge to existing social, political, and economic systems. Humans have successfully faced similar challenges in the past, however. The archaeological record and Earth archives offer rare opportunities to observe the complex interaction between environmental and human systems under different climate regimes and at different spatial and temporal scales. The archaeology of climate change offers opportunities to identify the factors that promoted human resilience in the past and apply the knowledge gained to the present, contributing a much-needed, long-term perspective to climate research. One of the strengths of the archaeological record is the cultural diversity it encompasses, which offers alternatives to the solutions proposed from within the Western agro-industrial complex, which might not be viable cross-culturally. While contemporary climate discourse focuses on the importance of biodiversity, we highlight the importance of cultural diversity as a source of resilience.

The sensitivity of the El Niño–Southern Oscillation to volcanic aerosol spatial distribution in the MPI Grand Ensemble - Ward, Benjamin; Pausata, Francesco S. R.; Maher, Nicola (Earth System Dynamics, 2021)
Abstract. Using the Max Planck Institute Grand Ensemble (MPI-GE) with 200 members for the historical simulation (1850–2005), we investigate the impact of the spatial distribution of volcanic aerosols on the El Niño–Southern Oscillation (ENSO) response. In particular, we select three eruptions (El Chichón, Agung and Pinatubo) in which the aerosol is respectively confined to the Northern Hemisphere, the Southern Hemisphere or equally distributed across the Equator. Our results show that relative ENSO anomalies start at the end of the year of the eruption and peak in the following one. We especially found that when the aerosol is located in the Northern Hemisphere or is symmetrically distributed, relative El Niño-like anomalies develop, while aerosol distribution confined to the Southern Hemisphere leads to a relative La Niña-like anomaly. Our results point to the volcanically induced displacement of the Intertropical Convergence Zone (ITCZ) as a key mechanism that drives the ENSO response, while suggesting that the other mechanisms (the ocean dynamical thermostat and the cooling of tropical northern Africa or the Maritime Continent) commonly invoked to explain the post-eruption ENSO response may be less important in our model.

Holocene forcing of East Asian hydroclimate recorded in a subtropical peatland from southeastern China - Huang, Xianyu; Zhang, Hongbin; Griffiths, Michael L.; Zhao, Bingyan; Pausata, Francesco S. R.; Tabor, Clay; Shu, Junwu; Xie, Shucheng (Climate Dynamics, 2023)

A fully calibrated and updated mid-Holocene climate reconstruction for Eastern South America - Gorenstein, Iuri; Prado, Luciana F.; Bianchini, Paula R.; Wainer, Ilana; Griffiths, Michael L.; Pausata, Francesco S.R.; Yokoyama, Elder (Quaternary Science Reviews, 2022)

Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data - Ramos, R. D.; LeGrande, A. N.; Griffiths, M. L.; Elsaesser, G. S.; Litchmore, D. T.; Tierney, J. E.; Pausata, F. S. R.; Nusbaumer, J. (Journal of Advances in Modeling Earth Systems, 2022)
Abstract Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof‐of‐concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere‐only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present‐day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid‐Holocene (MH) and pre‐industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non‐stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations. , Plain Language Summary Equilibrium climate sensitivity (ECS) is a key climate metric that quantifies the rise in global mean surface temperature in response to doubling of atmospheric CO 2 . Changes in hydroclimate, temperature extremes, and other aspects of future climate projections are closely tied to a model's ECS. For decades, ECS range has remained wide despite improvements from using multiple lines of evidence. One persistent source of this spread is related to cloud and convective processes, which occur at scales too small to be explicitly resolved, and thus require parameterizations to be represented in climate models. These parameterizations directly influence water isotopes by modulating simulated clouds and atmospheric circulation, and thus can be used to constrain model processes and identify model biases. In this work, we demonstrated that paleoclimate simulations are more parameter sensitive than the modern, highlighting the potential of past climates in discriminating cloud and convective parameterizations. Using satellite‐ and proxy‐model comparisons, we identified the top performing parameterizations which differ for each time period likely due to varying cloud feedbacks under diverse climatic forcing. Overall, our results provide a framework for fine‐tuning model representations using combined paleoclimate and satellite data, offering a unique opportunity to assess model uncertainties over a broader range of climate variability. , Key Points Paleoclimate relative to modern are more parameter sensitive, allowing for an assessment of uncertainties over a variety of climate forcing Certain simulations reproduced the δ 18 O of precipitation from paleoclimate proxies better than the default parameterization No single set of parameters works well in all climate states likely due to varying boundary conditions influencing cloud feedbacks

Unravelling the roles of orbital forcing and oceanic conditions on the mid-Holocene boreal summer monsoons - Mudra, Lekshmi; Sabin, T. P.; Krishnan, R.; Pausata, Francesco S. R.; Marti, Olivier; Braconnot, Pascale (Climate Dynamics, 2023)

Sensitivity of northwest Australian tropical cyclone activity to ITCZ migration since 500 CE - Denniston, Rhawn F.; Ummenhofer, Caroline C.; Emanuel, Kerry; Ingrosso, Roberto; Pausata, Francesco S. R.; Wanamaker, Alan D.; Lachniet, Matthew S.; Carr, Kenneth T.; Asmerom, Yemane; Polyak, Victor J.; Nott, Jonathan; Zhang, Wei; et al. (Science Advances, 2023)
Tropical cyclones (TCs) regularly form in association with the intertropical convergence zone (ITCZ), and thus, its positioning has implications for global TC activity. While the poleward extent of the ITCZ has varied markedly over past centuries, the sensitivity with which TCs responded remains poorly understood from the proxy record, particularly in the Southern Hemisphere. Here, we present a high-resolution, composite stalagmite record of ITCZ migrations over tropical Australia for the past 1500 years. When integrated with a TC reconstruction from the Australian subtropics, this time series, along with downscaled climate model simulations, provides an unprecedented examination of the dependence of subtropical TC activity on meridional shifts in the ITCZ. TCs tracked the ITCZ at multidecadal to centennial scales, with a more southward position enhancing TC-derived rainfall in the subtropics. TCs may play an increasingly important role in Western Australia’s moisture budgets as subtropical aridity increases due to anthropogenic warming. , Stalagmites and climate models reveal ITCZ shifts drove concurrent changes in Australian tropical cyclone and monsoon rainfall.

Revisiting the Mechanisms of ENSO Response to Tropical Volcanic Eruptions - Pausata, Francesco S. R.; Zhao, Yang; Zanchettin, Davide; Caballero, Rodrigo; Battisti, David S. (Geophysical Research Letters, 2023)
Abstract Stratospheric volcanic aerosol can have major impacts on global climate. Despite a consensus among studies on an El Niño‐like response in the first or second post‐eruption year, the mechanisms that trigger a change in the state of El Niño‐Southern Oscillation (ENSO) following volcanic eruptions are still debated. Here, we shed light on the processes that govern the ENSO response to tropical volcanic eruptions through a series of sensitivity experiments with an Earth System Model where a uniform stratospheric volcanic aerosol loading is imposed over different parts of the tropics. Three tropical mechanisms are tested: the “ocean dynamical thermostat” (ODT); the cooling of the Maritime Continent; and the cooling of tropical northern Africa (NAFR). We find that the NAFR mechanism plays the largest role, while the ODT mechanism is absent in our simulations as La Niña‐like rather than El‐Niño‐like conditions develop following a uniform radiative forcing over the equatorial Pacific. , Plain Language Summary Volcanic eruptions emit large quantity of sulfate aerosol up to the stratosphere. Such aerosol can alter global climate by interacting with solar radiation and in turn modifying atmospheric and ocean circulation. In particular, volcanic aerosol can alter the state of the El Niño‐Southern Oscillation (ENSO), the major mode of tropical climate variability. However, the mechanisms that trigger a change in the ENSO state following volcanic eruptions are still debated. In this study, we use an Earth System Model to revisit the main mechanisms that have been proposed to alter ENSO, causing positive temperature anomalies over the equatorial Pacific (EqPAC) Ocean. We tested three mechanisms: the “ocean dynamical thermostat” (ODT); the cooling of the Maritime Continent; and the cooling of tropical northern Africa (NAFR). Our experiments show that the NAFR mechanism plays the largest role, while the ODT mechanism is absent in our simulations as cold rather than warm develop over the EqPAC Ocean following the applied volcanic forcing. , Key Points Radiative cooling by volcanic aerosol over the tropical northern Africa triggers El Niño‐like conditions via atmospheric circulation changes The “ocean thermostat mechanism” is absent in our simulations when a uniform aerosol forcing is applied over the equatorial Pacific (EqPAC) The Maritime Continent cooling mechanism is not at play when the aerosol forcing extends over the entire EqPAC

Elevation-dependent intensification of fire danger in the western United States - Alizadeh, Mohammad Reza; Abatzoglou, John T.; Adamowski, Jan; Modaresi Rad, Arash; AghaKouchak, Amir; Pausata, Francesco S. R.; Sadegh, Mojtaba (Nature Communications, 2023)
Abstract Studies have identified elevation-dependent warming trends, but investigations of such trends in fire danger are absent in the literature. Here, we demonstrate that while there have been widespread increases in fire danger across the mountainous western US from 1979 to 2020, trends were most acute at high-elevation regions above 3000 m. The greatest increase in the number of days conducive to large fires occurred at 2500–3000 m, adding 63 critical fire danger days between 1979 and 2020. This includes 22 critical fire danger days occurring outside the warm season (May–September). Furthermore, our findings indicate increased elevational synchronization of fire danger in western US mountains, which can facilitate increased geographic opportunities for ignitions and fire spread that further complicate fire management operations. We hypothesize that several physical mechanisms underpinned the observed trends, including elevationally disparate impacts of earlier snowmelt, intensified land-atmosphere feedbacks, irrigation, and aerosols, in addition to widespread warming/drying.

On the Remote Impacts of Mid‐Holocene Saharan Vegetation on South American Hydroclimate: A Modeling Intercomparison - Tiwari, S.; Ramos, R. D.; Pausata, F. S. R.; LeGrande, A. N.; Griffiths, M. L.; Beltrami, H.; Wainer, I.; De Vernal, A.; Litchmore, D. T.; Chandan, D.; Peltier, W. R.; Tabor, C. R. (Geophysical Research Letters, 2023)
Abstract Proxy reconstructions from the mid‐Holocene (MH: 6,000 years ago) indicate an intensification of the West African Monsoon and a weakening of the South American Monsoon, primarily resulting from orbitally‐driven insolation changes. However, model studies that account for MH orbital configurations and greenhouse gas concentrations can only partially reproduce these changes. Most model studies do not account for the remarkable vegetation changes that occurred during the MH, in particular over the Sahara, precluding realistic simulations of the period. Here, we study precipitation changes over northern Africa and South America using four fully coupled global climate models by accounting for the Saharan greening. Incorporating the Green Sahara amplifies orbitally‐driven changes over both regions, and leads to an improvement in proxy‐model agreement. Our work highlights the local and remote impacts of vegetation and the importance of considering vegetation changes in the Sahara when studying and modeling global climate. , Plain Language Summary Paleoclimate modeling offers a way to test the ability of climate models to detect climate change outside the envelope of historical climatic variability. The mid‐Holocene (MH: 6,000 years ago) is a key interval for paleoclimate studies, as the Northern Hemisphere received greater summer‐time insolation and experienced stronger monsoons than today. Due to a stronger MH West African Monsoon, the Saharan region received enough rainfall to be able to host vegetation. The vegetation changes in the Sahara affected not only the local climate but also far‐afield locations through teleconnections in the global climate system. In this study, we simulate the MH climate using four climate models, each with two types of simulations—with and without the Green Sahara. We show that simulations with the Green Sahara capture greater drying over the South American continent than the simulations which only account for changes in orbital forcing and greenhouse gas concentrations. The simulations with the Green Sahara are more in line with proxy reconstructions, lending further support to incorporating vegetation changes as a necessary boundary condition to simulate the MH climate realistically. , Key Points We simulate the mid‐Holocene with and without the Green Sahara using four fully coupled global climate models The mid‐Holocene simulation with the Green Sahara shows intensification of orbitally‐driven changes in precipitation over northern Africa and South America Incorporation of the Green Sahara leads to greater proxy‐model agreement over both northern Africa and South America

Effect of urban heat island mitigation strategies on precipitation and temperature in Montreal, Canada: Case studies - Lauer, Audrey; Pausata, Francesco S. R.; Leroyer, Sylvie; Argueso, Daniel (PLOS Climate, 2023)
High-resolution numerical weather prediction experiments using the Global Environmental Multiscale (GEM) model at a 250-m horizontal resolution are used to investigate the effect of the urban land-use on 2-m surface air temperature, thermal comfort, and rainfall over the Montreal (Canada) area. We focus on two different events of high temperatures lasting 2–3 days followed by intense rainfall: one is a large-scale synoptic system that crosses Montreal at night and the other is an afternoon squall line. Our model shows an overall good performance in adequately capturing the surface air temperature, dew-point temperature and rainfall during the events, although the precipitation pattern seems to be slightly blocked upwind of the city. Sensitivity experiments with different land use scenarios were conducted. Replacing all urban surfaces by low vegetation showed an increase of human comfort, lowering the heat index during the night between 2° and 6°C. Increasing the albedo of urban surfaces led to an improvement of comfort of up to 1°C during daytime, whereas adding street-level low vegetation had an improvement of comfort throughout the day of up to 0.5°C in the downtown area. With respect to precipitation, significant differences are only seen for the squall line event, for which removing the city modifies the precipitation pattern. For the large-scale synoptic system, the presence of the city does not seem to impact precipitation. These findings offer insight on the effects of urban morphology on the near-surface atmospheric conditions.

Deciphering local and regional hydroclimate resolves contradicting evidence on the Asian monsoon evolution - Wolf, Annabel; Ersek, Vasile; Braun, Tobias; French, Amanda D.; McGee, David; Bernasconi, Stefano M.; Skiba, Vanessa; Griffiths, Michael L.; Johnson, Kathleen R.; Fohlmeister, Jens; Breitenbach, Sebastian F. M.; Pausata, Francesco S. R.; et al. (Nature Communications, 2023)
Abstract The winter and summer monsoons in Southeast Asia are important but highly variable sources of rainfall. Current understanding of the winter monsoon is limited by conflicting proxy observations, resulting from the decoupling of regional atmospheric circulation patterns and local rainfall dynamics. These signals are difficult to decipher in paleoclimate reconstructions. Here, we present a winter monsoon speleothem record from Southeast Asia covering the Holocene and find that winter and summer rainfall changed synchronously, forced by changes in the Pacific and Indian Oceans. In contrast, regional atmospheric circulation shows an inverse relation between winter and summer controlled by seasonal insolation over the Northern Hemisphere. We show that disentangling the local and regional signal in paleoclimate reconstructions is crucial in understanding and projecting winter and summer monsoon variability in Southeast Asia.

Changes in climate extremes in Zambia during green and dry Sahara periods and their potential impacts on hominid dispersal - Pausata, Francesco S.R.; Alain, Dominic; Ingrosso, Roberto; Winger, Katja; Drapeau, Michelle S.M.; Burke, Ariane (Quaternary Science Reviews, 2023)

A 50-year cycle of sea surface temperature regulates decadal precipitation in the tropical and South Atlantic region - Gorenstein, Iuri; Wainer, Ilana; Pausata, Francesco S. R.; Prado, Luciana F.; Khodri, Myriam; Dias, Pedro L. Silva (Communications Earth & Environment, 2023)
Abstract Northeast Brazil and Western Africa are two regions geographically separated by the Atlantic Ocean, both home to vulnerable populations living in semi-arid areas. Atlantic Ocean modes of variability and their interactions with the atmosphere are the main drivers of decadal precipitation in these Atlantic Ocean coastal areas. How these low-frequency modes of variability evolve and interact with each other is key to understanding and predicting decadal precipitation. Here we use the Self-Organizing Maps neural network with different variables to unravel causality between the Atlantic modes of variability and their interactions with the atmosphere. Our study finds an 82% (p<0.05) anti-correlation between decadal rainfall in Northeast Brazil and Western Africa from 1979 to 2005. We also find three multi-decadal cycles: 1870-1920, 1920-1970, and 1970-2019 (satellite era), pointing to a 50-year periodicity governing the sea surface temperature anomalies of Tropical and South Atlantic. Our results demonstrate how Northeast Brazil and Western Africa rainfall anti-correlation was formed in the satellite era and how it might be part of a 50-year cycle from the Tropical and South Atlantic decadal variability.

Contrasting consequences of the Great Green Wall: Easing aridity while increasing heat extremes - Ingrosso, Roberto; Pausata, Francesco S.R. (One Earth, 2024)

On the length and intensity of the West African summer monsoon during the last interglacial African humid period - Shi, Xiaoxu; Werner, Martin; Pausata, Francesco S.R.; Yang, Hu; Liu, Jiping; D'Agostino, Roberta; Ingrosso, Roberto; Yang, Chaoyuan; Gao, Qinggang; Lohmann, Gerrit (Quaternary Science Reviews, 2024)

Evaluating the role of city representation in modelling the urban precipitation effect of Kuala Lumpur - Ghielmini, Chiara; Pausata, Francesco S.R.; Argüeso, Daniel; Demuzere, Matthias; Vhuiyan, Razib (Urban Climate, 2024)

Causes of Past African Temperature Change in PMIP Simulations of the Mid‐Holocene - Marshall, Charlie; Morrill, Carrie; Dee, Sylvia; Pausata, Francesco S. R.; Russell, James (Paleoceanography and Paleoclimatology, 2024)
Abstract Current‐generation climate models project that Africa will warm by up to 5°C in the coming century, severely stressing African populations. Past and ongoing work indicates, however, that the models used to create these projections do not match proxy records of past temperature in Africa during the mid‐Holocene (MH), raising concerns that their future projections may house large uncertainties. Rather than reproducing proxy‐based reconstructions of MH warming relative to the Pre‐Industrial (PI), models instead simulate MH temperatures very similar to or slightly colder than the PI. This data‐model mismatch could be due to a variety of factors, including biases in model surface energy budgets or inaccurate representation of the feedbacks between temperature and hydrologic change during the “Green Sahara.” We focus on the differences among model simulations in the Paleoclimate Modeling Intercomparison Project Phases 3 and 4 (PMIP3 and PMIP4), examining surface temperature and energy budgets to investigate controls on temperature and the potential model sources of this paleoclimate data‐model mismatch. Our results suggest that colder conditions simulated by PMIP3 and PMIP4 models during the MH are in large part due to the joint impacts of feedback uncertainties in response to increased precipitation, a strengthened West African Monsoon (WAM) in the Sahel, and the Green Sahara. We extend these insights into suggestions for model physics and boundary condition changes, and discuss implications for the accuracy of future climate model projections over Africa. , Key Points We evaluate the simulation of African air temperatures in Paleoclimate Modeling Intercomparison Project Phases 3 and 4 simulations of the mid‐Holocene Energy balance decomposition analyses indicate the hydrologic cycle plays a key role in causing mid‐Holocene cooling in model simulations “Green Sahara” experiments show that dust and vegetation affect simulated temperatures, revealing pathways for refining model simulations

An assessment of climate change impacts on oases in northern Africa - Leal Filho, Walter; Stojanov, Robert; Matsoukas, Christos; Ingrosso, Roberto; Franke, James A.; Pausata, Francesco S.R.; Grassi, Tommaso; Landa, Jaromír; Harrouni, Cherif (Ecological Indicators, 2024)

Mid-Holocene climate at mid-latitudes: assessing the impact of Saharan greening - Gaetani, Marco; Messori, Gabriele; Pausata, Francesco S. R.; Tiwari, Shivangi; Alvarez Castro, M. Carmen; Zhang, Qiong (Climate of the Past, 2024)
Abstract. During the first half of the Holocene (11 000 to 5000 years ago), the Northern Hemisphere experienced a strengthening of the monsoonal regime, with climate reconstructions robustly suggesting a greening of the Sahara region. Palaeoclimate archives also show that this so-called African humid period (AHP) was accompanied by changes in climate conditions at middle to high latitudes. However, inconsistencies still exist in reconstructions of the mid-Holocene (MH) climate at mid-latitudes, and model simulations provide limited support in reducing these discrepancies. In this paper, a set of simulations performed using a climate model are used to investigate the hitherto unexplored impact of Saharan greening on mid-latitude atmospheric circulation during the MH. Numerical simulations show Saharan greening has a year-round impact on the main circulation features in the Northern Hemisphere, especially during boreal summer (when the African monsoon develops). Key findings include a westward shift in the global Walker Circulation, leading to modifications in the North Atlantic jet stream in summer and the North Pacific jet stream in winter. Furthermore, Saharan greening modifies atmospheric synoptic circulation over the North Atlantic, enhancing the effect of orbital forcing on the transition of the North Atlantic Oscillation phase from predominantly positive to negative in winter and summer. Although the prescription of vegetation in the Sahara does not improve the proxy–model agreement, this study provides the first constraint on the influence of Saharan greening on northern mid-latitudes, opening new opportunities for understanding MH climate anomalies in regions such as North America and Eurasia.

WINTRE-MIX Field Collected Sounding Data. Version 4.0 - Winters, A.; Minder, J. R.; Han, B.; Thériault, J.; Lachapelle, M.; Gyakum, J.; Wray, J.; Baiman, R. (UCAR/NCAR - Earth Observing Laboratory, 2022)
Sounding data collected during the WINTRE-MIX project field phase are included in this dataset. This dataset has soundings from the University of Colorado (CU) DOWs, McGill University at Gault, St Jean sur Richelieu, University at Albany (UA) DOWs, Université du Québec à Montréal (UQAM), and UA Essex sites. data file names are of the form "upperair.sounding.YYYYMMDDHHMM.siteName.[txt or csv]" where the YYYMMDDHHMM indicates the date and time of the sounding and the siteName indicates the site source and location. See the documentation for more information on this dataset.

WINTRE-MIX: CFI Climate Sentinels Pyranometer and Radiation Data. Version 1.0 - Low, Y.; Lachapelle, M.; Gyakum, J.; Bigras, È.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Fraser, D.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
The Sentinel Radiation MetData provided in situ measurements of radiation fluxes for the Winter Precip Type Research Multi-scale Experiment (WINTRE-MIX) are included in this dataset. Pyranometer and radiation data are provided in netCDF format. Data were collected from the following 4 sites: Gault, Arboretum, UQAM-PK and Trois-Rivières.

WINTRE-MIX: CFI Climate Sentinels Pressure, Wind, Temperature, Relative Humidity, and Precipitation Data. Version 1.0 - Low, Y.; Lachapelle, M.; Kinnard, C.; Gyakum, J.; Bigras, È.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Fraser, D.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
The Sentinel Non-Radiation MetData provided in situ measurements of meteorological variables (such as 2-meter temperature, relative humidity, wind speed and direction, and precipitation) collected for the the Winter Precip Type Research Multi-scale Experiment (WINTRE-MIX) are included in this dataset. Data are provided in netCDF format. Data were collected from the following 4 sites: Gault, Arboretum, UQAM-PK and Trois-Rivières.

WINTRE-MIX: CFI Climate Sentinels Hotplate Precipitation Gauge data. Version 1.0 - Girouard, M.; Lachapelle, M.; Thériault, J.; Gyakum, J.; Bigras, È.; Meunier, V.; Thompson, H.; Fraser, D.; Wray, J.; Low, Y. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset includes hotplate precipitation gauge data from 4 different sites sitting in the St. Lawrence River Valley. The hotplate data were obtained by the K63 Hotplate Total Precipitation Gauge. The instruments belonged to Université du Québec à Montréal (UQAM) and McGill University. UQAM has one hotplate permanently installed on the rooftop of the President-Kennedy building, in downtown Montreal. Another hotplate was temporarily deployed by the UQAM team in the instrument yard of UQTR as part of the WINTRE-MIX field campaign. McGill’s instruments are permanently installed in the instrument yards of Gault and Arboretum.

WINTRE-MIX: CFI Climate Sentinels Snow Depth Data. Version 1.0 - Girouard, M.; Lachapelle, M.; Thompson, H.; Bigras, È.; Meunier, V.; Fraser, D.; Low, Y.; Wray, J.; Thériault, J.; Gyakum, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset includes snow depth and snow water equivalent data from 4 sites in the St. Lawrence River Valley collected for the WINTRE-MIX field project. The snow depth data were obtained by the SDMS40: Multipoint Scanning Snowfall Sensor and the SR50A Snow-Depth Sensor. The CS725 Snow-Water Equivalent Sensor measured the snow water equivalent data. This dataset includes measurements done at 4 different sites: UQAM-PK (UQAM), Trois-Rivières, Gault and Arboretum.

WINTRE-MIX: CFI Climate Sentinels Icing Detector Data. Version 1.0 - Fraser, D.; Bigras, È.; Gyakum, J.; Lachapelle, M.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains ice thickness data collected by ice detectors installed at various climate sentinels within the Saint Lawrence River Valley for the WINTRE-MIX field project. The names of four stations for which ice accretion data are available in ‘CFI_Climate_Sentinels_Icing_Detector_Data.nc’ are given in Table 1 of the readme documentation, along with their corresponding four-letter identifiers.

WINTRE-MIX: CFI Climate Sentinels Gault Parsivel Disdrometer Data. Version 1.0 - Fraser, D.; Bigras, È.; Gyakum, J.; Lachapelle, M.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data collected from an OTT Parsivel laser disdrometer installed at a climate sentinel (Gault) in the Saint Lawrence River Valley The data is available from 1 Nov 2021 to 31 March 2022 (inclusive) to support the Winter Precipitation Type Research Multi-Scale Experiment (WINTRE-MIX). The instrument provides histograms of hydrometeor size and fallspeed. The Gault site is located behind Mont-Saint-Hilaire, about an hour’s drive east of Montreal. Other sites also collected Parsivel data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels Arboretum Parsivel Disdrometer Data. Version 1.0 - Fraser, D.; Bigras, È.; Gyakum, J.; Lachapelle, M.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data collected from an OTT Parsivel laser disdrometer installed at a climate sentinel (Arboretum) in the Saint Lawrence River Valley. The data is available from 1 Nov 2021 to 31 March 2022 (inclusive) to support the Winter Precipitation Type Research Multi-Scale Experiment (WINTRE-MIX). The instrument provides histograms of hydrometeor size and fallspeed. The Arboretum site is located on the southwestern tip of Montreal Island near the confluence of the Ottawa River and the St. Lawrence River. Several other sites also collected Parsivel data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels Trois-Rivières MRR-Pro data. Version 1.0 - Lachapelle, M.; Girouard, M.; Thompson, H.; Thériault, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains data from a METEK vertically profiling K-band Micro Rain Radar Pro (MRR-Pro) that was temporarily installed at the Université du Québec à Trois-Rivières (UQTR) campus during February and March 2022 to support the Winter Precipitation Type Research Multi-Scale Experiment (WINTRE-MIX). The instrument provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site sits in the St. Lawrence River Valley. Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels UQAM-PK MRR-2 Processed Data. Version 1.0 - Lachapelle, M.; Girouard, M.; Thompson, H.; Thériault, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains processed data from a METEK vertically profiling K-band Micro Rain Radar (MRR-2) permanently installed on the rooftop of UQAM President-Kennedy building in Montréal downtown, Québec. The instrument provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site sits in the St. Lawrence River Valley. Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels UQAM-PK MRR-2 Raw Data. Version 1.0 - Lachapelle, M.; Girouard, M.; Thompson, H.; Thériault, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data from a METEK vertically profiling K-band Micro Rain Radar (MRR-2) permanently installed on the rooftop of UQAM President-Kennedy building in Montréal downtown, Québec. The instrument provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site sits in the St. Lawrence River Valley. Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels UQAM-PK Parsivel Disdrometer Data. Version 1.0 - Lachapelle, M.; Girouard, M.; Thompson, H.; Thériault, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data from an OTT Parsivel laser disdrometer permanently installed on the rooftop of UQAM President-Kennedy building in Montréal downtown, Québec. The instrument provides histograms of hydrometeor size and fallspeed. The site sits in the St. Lawrence River Valley. Several other sites also collected Parsivel data during WINTRE-MIX 2022.

WINTRE-MIX: Trois-Rivieres Parsivel Disdrometer Data. Version 1.0 - Lachapelle, M.; Girouard, M.; Thompson, H.; Thériault, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data from an OTT Parsivel laser disdrometer that was temporarily installed at the Université du Québec à Trois-Rivières (UQTR) campus from December 2021 to April 2022 to support the Winter Precipitation Type Research Multi-Scale Experiment (WINTRE-MIX). The instrument provides histograms of hydrometeor size and fallspeed. The site sits in the St. Lawrence River Valley. Several other sites also collected Parsivel data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels Gault MRR-2 Raw Data. Version 1.0 - Lachapelle, M.; Fraser, D.; Bigras, È.; Gyakum, J.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data from a METEK vertically profiling K-band Micro Rain Radar (MRR-2) installed at the climate sentinel in the Gault Nature Reserve (GAUL), about 30 km east of Montréal, Québec.The data were collected as part of the Winter Precipitation Type Research Multi-scale Experiment (WINTRE-MIX) field project held in February and March of 2022. The instrument provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site is located at the southern flank of Mont-Saint-Hilaire, a mountain with an elevation of about 400 m (above mean sea-level). Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels Gault MRR-2 Processed Data. Version 1.0 - Lachapelle, M.; Fraser, D.; Bigras, È.; Gyakum, J.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains post-processed data from a METEK vertically profiling K-band Micro Rain Radar (MRR-2) installed at the climate sentinel in the Gault Nature Reserve (GAUL), about 30 km east of Montréal, Québec. The data were collected as part of the Winter Precipitation Type Research Multi-scale Experiment (WINTRE-MIX) field project held in February and March of 2022. The instrument provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site is located at the southern flank of Mont-Saint-Hilaire, a mountain with an elevation of about 400 m (above mean sea-level). Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: CFI Climate Sentinels Arboretum MRR-2 raw data. Version 1.0 - Lachapelle, M.; Fraser, D.; Bigras, È.; Gyakum, J.; Meunier, V.; Thériault, J.; Thompson, H.; Girouard, M.; Low, Y.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
This dataset contains raw data from a METEK vertically profiling K-band Micro Rain Radar (MRR-2) installed at the climate sentinel in the Arboretum forest reserve (ARBO), about 30 km west of Montréal downtown, Québec, Canada. The data were collected as part of the Winter Precipitation Type Research Multi-scale Experiment (WINTRE-MIX) field project held in February and March of 2022. The instrument used to collect the data in this dataset provides vertical profiles of reflectivity, Doppler velocity, and spectrum width. The site is located near the confluence of the Ottawa River and the St. Lawrence River. Several other sites also collected MRR data during WINTRE-MIX.

WINTRE-MIX: Manual Hydrometeor Photographs Dataset. Version 1.0 - Lachapelle, M.; Han, B.; Minder, J. R.; Winters, A.; Baiman, R.; Thériault, J.; Gyakum, J.; Wray, J. (UCAR/NCAR - Earth Observing Laboratory, 2022)
Manual hydrometeor macro photographs were collected during the Winter Precipitation Type Research Multi-Scale Experiment (WINTRE-MIX) between 01 Feb – 15 March 2022. The macro photographs were collected by manual ground observation teams from the University at Albany (UAlbany), University of Colorado Boulder (CU), Université du Québec à Montréal (UQAM), and McGill University (McGill). Sections in the readme provide information on the camera setup, protocol, and dataset file formats, as well as limitations associated with the data.

Near-0 °C surface temperature and precipitation type patterns across Canada - Mekis, Eva; Stewart, Ronald E.; Theriault, Julie M.; Kochtubajda, Bohdan; Bonsal, Barrie R.; Liu, Zhuo (Hydrology and Earth System Sciences, 2020)
Abstract. The 0 ∘C temperature threshold is critical for many meteorological and hydrological processes driven by melting and freezing in the atmosphere, surface, and sub-surface and by the associated precipitation varying between rain, freezing rain, wet snow, and snow. This threshold is especially important in cold regions such as Canada, because it is linked with freeze–thaw, snowmelt, and permafrost. This study develops a Canada-wide perspective on near-0 ∘C conditions using hourly surface temperature and precipitation type observations from 92 climate stations for the period from 1981 to 2011. In addition, nine stations from various climatic regions are selected for further analysis. Near-0 ∘C conditions are defined as periods when the surface temperature is between −2 and 2 ∘C. Near-0 ∘C conditions occur often across all regions of the country, although the annual number of days and hours and the duration of these events varies dramatically. Various types of precipitation (e.g., rain, freezing rain, wet snow, and ice pellets) sometimes occur with these temperatures. Near-0 ∘C conditions and the reported precipitation type occurrences tend to be higher in Atlantic Canada, although high values also occur in other regions. Trends of most temperature-based and precipitation-based indicators show little or no change despite a systematic warming in annual surface temperatures over Canada. Over the annual cycle, near-0 ∘C temperatures and precipitation often exhibit a pattern: short durations occur around summer, driven by the diurnal cycle, and a tendency toward longer durations around winter, associated with storms. There is also a tendency for near-0 ∘C surface temperatures to occur more often than expected relative to other temperature windows at some stations due, at least in part, to diabatic cooling and heating that take place with melting and freezing, respectively, in the atmosphere and at the surface.

Impacts of Predicting the Liquid Fraction of Mixed-Phase Particles on the Simulation of an Extreme Freezing Rain Event: The 1998 North American Ice Storm - Cholette, Mélissa; Thériault, Julie M.; Milbrandt, Jason A.; Morrison, Hugh (Monthly Weather Review, 2020)
Abstract A prognostic equation for the liquid fraction of mixed-phase particles has been recently added to the Predicted Particle Properties (P3) bulk microphysics scheme. Mixed-phase particles are necessary to simulate key microphysical processes leading to various winter precipitation types, such as ice pellets and freezing rain. To illustrate the impacts of predicting the bulk liquid fraction, the 1998 North American Ice Storm is simulated using the Weather Research and Forecasting (WRF) Model with the modified P3 scheme. It is found that simulating partial melting by predicting the bulk liquid fraction produces higher mass and number mixing ratios of rain. This leads to smaller rain sizes reaching the refreezing layer as well as a decrease in the freezing rain accumulation at the surface by up to 30% in some locations compared to when no liquid fraction is predicted. The increase in fall speed and density and decrease of particle diameter during partial melting combined with an improved representation of the refreezing process in the modified P3 leads to generally higher total solid surface precipitation rates than using the original P3 scheme. There is also an increase of solid precipitation in regions of ice pellet accumulation. Overall, the simulation of mixed-phase particles notably impacts the vertical and spatial distributions of precipitation properties.

Summary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 2: Future change in cryosphere, vegetation, and hydrology - DeBeer, Chris M.; Wheater, Howard S.; Pomeroy, John W.; Barr, Alan G.; Baltzer, Jennifer L.; Johnstone, Jill F.; Turetsky, Merritt R.; Stewart, Ronald E.; Hayashi, Masaki; Van Der Kamp, Garth; Marshall, Shawn; Campbell, Elizabeth; et al. (Hydrology and Earth System Sciences, 2021)
Abstract. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

Precipitation Type Distribution and Microphysical Processes During the 1998 Ice Storm Simulated Under Pseudo‐Warmer Conditions - Cholette, Mélissa; Thériault, Julie Mireille (Journal of Geophysical Research: Atmospheres, 2021)
Abstract In the future, the intensity, phases, and frequency of precipitation are expected to change due to global warming, in particular during colder seasons when temperatures are near 0°C. To investigate the impacts of warmer atmospheric conditions on the microphysical processes that lead to several precipitation types, the extreme 1998 Ice Storm was simulated using the Weather Research and Forecasting (WRF) model, with and without a pseudo‐global warming. The pseudo‐global warming approach simulates similar large‐scale conditions but in warmer conditions, which allows for the assessment of thermodynamic feedback from cloud and precipitation microphysics. For both simulations, WRF was coupled with the Predicted Particle Properties (P3) bulk microphysics scheme that predicts the liquid fraction of mixed‐phase particles. Results of the pseudo‐global warming simulation show an increase of ∼828 m in the upper 0°C level and a northeastward migration (∼60 km) of the rain‐snow transition region. The results also show a 20% decrease in domain‐averaged freezing rain amounts, but with an increased maximum amount of 50%. The horizontal distance associated with a melting aloft and a refreezing layer near the surface is 105 km longer in southern Quebec due to the combined effects of the pseudo‐warming and the presence of the Appalachian Mountains. The microphysical processes that lead to precipitation are impacted as well; the increased ice mass and riming conditions aloft in warmer temperatures result in higher liquid precipitation rates. This study contributes to our understanding of the changes in the fine‐scale processes of an extreme storm, simulated with pseudo‐global warming conditions. , Key Points The major 1998 Ice Storm was simulated with the Weather Research and Forecasting model, with and without a pseudo‐global warming A higher melting layer in warmer conditions led to more riming aloft, larger drops, and higher maximum amounts of rain and freezing rain The precipitation type transition region is wider in the warmer conditions over the geographical areas of both southern Quebec and Maine

Meteorological observations collected during the Storms and Precipitation Across the continental Divide Experiment (SPADE), April–June 2019 - Thériault, Julie M.; Déry, Stephen J.; Pomeroy, John W.; Smith, Hilary M.; Almonte, Juris; Bertoncini, André; Crawford, Robert W.; Desroches-Lapointe, Aurélie; Lachapelle, Mathieu; Mariani, Zen; Mitchell, Selina; Morris, Jeremy E.; et al. (Earth System Science Data, 2021)
Abstract. The continental divide along the spine of the Canadian Rockies in southwestern Canada is a critical headwater region for hydrological drainages to the Pacific, Arctic, and Atlantic oceans. Major flooding events are typically attributed to heavy precipitation on its eastern side due to upslope (easterly) flows. Precipitation can also occur on the western side of the divide when moisture originating from the Pacific Ocean encounters the west-facing slopes of the Canadian Rockies. Often, storms propagating across the divide result in significant precipitation on both sides. Meteorological data over this critical region are sparse, with few stations located at high elevations. Given the importance of all these types of events, the Storms and Precipitation Across the continental Divide Experiment (SPADE) was initiated to enhance our knowledge of the atmospheric processes leading to storms and precipitation on either side of the continental divide. This was accomplished by installing specialized meteorological instrumentation on both sides of the continental divide and carrying out manual observations during an intensive field campaign from 24 April–26 June 2019. On the eastern side, there were two field sites: (i) at Fortress Mountain Powerline (2076 m a.s.l.) and (ii) at Fortress Junction Service, located in a high-elevation valley (1580 m a.s.l.). On the western side, Nipika Mountain Resort, also located in a valley (1087 m a.s.l.), was chosen as a field site. Various meteorological instruments were deployed including two Doppler light detection and ranging instruments (lidars), three vertically pointing micro rain radars, and three optical disdrometers. The three main sites were nearly identically instrumented, and observers were on site at Fortress Mountain Powerline and Nipika Mountain Resort during precipitation events to take manual observations of precipitation type and microphotographs of solid particles. The objective of the field campaign was to gather high-temporal-frequency meteorological data and to compare the different conditions on either side of the divide to study the precipitation processes that can lead to catastrophic flooding in the region. Details on field sites, instrumentation used, and collection methods are discussed. Data from the study are publicly accessible from the Federated Research Data Repository at https://doi.org/10.20383/101.0221 (Thériault et al., 2020). This dataset will be used to study atmospheric conditions associated with precipitation events documented simultaneously on either side of a continental divide. This paper also provides a sample of the data gathered during a precipitation event.

Freezing Rain Events that Impacted the Province of New Brunswick, Canada, and Their Evolution in a Warmer Climate - Chartrand, Julien; Thériault, Julie M.; Marinier, Sébastien (Atmosphere-Ocean, 2023)

A Multi‐Algorithm Analysis of Projected Changes to Freezing Rain Over North America in an Ensemble of Regional Climate Model Simulations - McCray, Christopher D.; Paquin, Dominique; Thériault, Julie M.; Bresson, Émilie (Journal of Geophysical Research: Atmospheres, 2022)
Abstract Freezing rain events have caused severe socioeconomic and ecosystem impacts. An understanding of how these events may evolve as the Earth warms is necessary to adequately adapt infrastructure to these changes. We present an analysis of projected changes to freezing rain events over North America relative to the 1980–2009 recent past climate for the periods during which +2, +3, and +4°C of global warming is attained. We diagnose freezing rain using four precipitation‐type algorithms (Cantin and Bachand, Bourgouin, Ramer, and Baldwin) applied to four simulations of the fifth‐generation Canadian Regional Climate Model (CRCM5) driven by four global climate models (GCMs). We find that the choice of driving GCM strongly influences the spatial pattern of projected change. The choice of algorithm has a comparatively smaller impact, and primarily affects the magnitude but not the sign of projected change. We identify several regions where all simulations and algorithms agree on the sign of change, with increases projected over portions of western Canada and decreases over the central, eastern, and southern United States. However, we also find large regions of disagreement on the sign of change depending on driving GCM and even ensemble member of the same GCM, highlighting the importance of examining freezing rain events in a multi‐member ensemble of simulations driven by multiple GCMs to sufficiently account for uncertainty in projections of these hazardous events. , Plain Language Summary Freezing rain events, or ice storms, can have major impacts on electrical infrastructure, agriculture, and road and air travel. Despite these impacts, relatively little research has been done on how these events may change as the Earth warms. We therefore examine several climate model simulations to determine how the frequency of freezing rain may change at different levels of future global warming. We focus in particular on how sensitive the projected changes are to the method used to identify freezing rain in the model output, as well as to the choice of climate model used to produce the projections. We find strong agreement among methods and models on a decrease in freezing rain frequency over much of the United States (from Texas northeastward to Maine) and an increase in freezing rain frequency over portions of western Canada (Alberta, Saskatchewan, Manitoba). In many other areas, however, the different methods and simulations disagree on the direction of projected change. Our findings highlight the importance of using many different climate models, rather than single simulations, to paint a clearer picture of the level of certainty in projections of freezing rain in the context of global warming. , Key Points Freezing rain is projected to increase in frequency over portions of western and central Canada and decrease over most of the United States The sign of projected changes is not highly sensitive to the precipitation‐type algorithm used to diagnose freezing rain The choice of driving global climate model is a key source of uncertainty in both the sign and magnitude of projected changes

Snow Level From Post‐Processing of Atmospheric Model Improves Snowfall Estimate and Snowpack Prediction in Mountains - Vionnet, V.; Verville, M.; Fortin, V.; Brugman, M.; Abrahamowicz, M.; Lemay, F.; Thériault, J. M.; Lafaysse, M.; Milbrandt, J. A. (Water Resources Research, 2022)
Abstract In mountains, the precipitation phase greatly varies in space and time and affects the evolution of the snow cover. Snowpack models usually rely on precipitation‐phase partitioning methods (PPMs) that use near‐surface variables. These PPMs ignore conditions above the surface thus limiting their ability to predict the precipitation phase at the surface. In this study, the impact on snowpack simulations of atmospheric‐based PPMs, incorporating upper atmospheric information, is tested using the snowpack scheme Crocus. Crocus is run at 2.5‐km grid spacing over the mountains of southwestern Canada and northwestern United States and is driven by meteorological fields from an atmospheric model at the same resolution. Two atmospheric‐based PPMs were considered from the atmospheric model: the output from a detailed microphysics scheme and a post‐processing algorithm determining the snow level and the associated precipitation phase. Two ground‐based PPMs were also included as lower and upper benchmarks: a single air temperature threshold at 0°C and a PPM using wet‐bulb temperature. Compared to the upper benchmark, the snow‐level based PPM improved the estimation of snowfall occurrence by 5% and the simulation of snow water equivalent (SWE) by 9% during the snow melting season. In contrast, due to missing processes, the microphysics scheme decreased performances in phase estimate and SWE simulations compared to the upper benchmark. These results highlight the need for detailed evaluation of the precipitation phase from atmospheric models and the benefit for mountain snow hydrology of the post‐processed snow level. The limitations to drive snowpack models at slope scale are also discussed. , Plain Language Summary The partitioning of precipitation between rainfall and snowfall is a crucial component of the evolution of the snowpack in mountains. Most snowpack models use the air temperature and humidity near the surface to derive the precipitation phase. However, the phase at the surface is strongly influenced by processes such as melting and refreezing of falling hydrometeors that occur above the surface. Atmospheric models simulate these processes and the corresponding phase at the surface. However, snowpack models rarely use this information. In this study, we considered two estimates of precipitation phase from an atmospheric model and tested them with a physically‐based snow model over the mountains of southwestern Canada and northwestern United States. The results were compared with traditional approaches using the air temperature and humidity near the surface to derive the precipitation phase. Our results showed that the precipitation phase associated with the snow level obtained from the atmospheric model improved snowfall estimate and snowpack prediction compared to the traditional approaches. In contrast, the cloud/precipitation scheme of the atmospheric model decreased performance in phase estimate and snow simulations due to missing physical processes. Our study highlights that snowpack predictions in the mountains can be improved if valuable information is obtained from atmospheric models. , Key Points Estimates of precipitation phase from an atmospheric model were used to drive snow simulations with a detailed snowpack model Snowfall prediction and snowpack modeling are improved by using the snow level from post‐processing of the atmospheric model Direct precipitation phase from the microphysics scheme does not improve snow simulations compared to simpler rain‐snow partitioning schemes

Changes in freezing rain occurrence over eastern Canada using convection-permitting climate simulations - Marinier, Sébastien; Thériault, Julie M.; Ikeda, Kyoko (Climate Dynamics, 2023)
Abstract Freezing precipitation has major consequences for ground and air transportation, the health of citizens, and power networks. Previous studies using coarse resolution climate models have shown a northward migration of freezing rain in the future. Increased model resolution can better define local topography leading to improved representation of conditions that are favorable for freezing rain. The goal of this study is to examine the climatology and characteristics of future freezing rain events using very-high resolution climate simulations. Historical and pseudo-global warming simulations with a 4-km horizontal grid length were used and compared with available observations. Simulations revealed a northerly shift of freezing rain occurrence, and an increase in the winter. Freezing rain was still shown to occur in the Saint-Lawrence River Valley in a warmer climate, primarily due to stronger wind channeling. Up to 50% of the future freezing rain events also occurred in present day climate within 12 h of each other. In northern Maine, they are typically shorter than 6 h in current climate and longer than 6 h in warmer conditions due to the onset of precipitation during low-pressure systems occurrences. The occurrence of freezing rain also locally increases slightly north of Québec City in a warmer climate because of freezing rain that is produced by warm rain processes. Overall, the study shows that high-resolution regional climate simulations are needed to study freezing rain events in warmer climate conditions, because high horizontal resolutions better define small-scale topographic features and local physical mechanisms that have an influence on these events.

The Occurrence of Near‐0°C Surface Air Temperatures in the Current and Pseudo‐Global Warming Future Over Southern Canada - Stewart, R. E.; Liu, Z.; Thériault, J. M.; Ruman, C. J. (Journal of Geophysical Research: Atmospheres, 2023)
Abstract Temperatures near 0°C represent a critical threshold for many environmental processes and socio‐economic activities. This study examines surface air temperatures ( T ) near 0°C (−2°C ≤ T ≤ 2°C) across much of southern Canada over a 13 year period (October 2000–September 2013). It utilized hourly data from 39 weather stations and from 4‐km resolution Weather Research and Forecasting model simulations that were both a retrospective simulation as well as a pseudo‐global warming simulation applicable near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% from 985 hr in the current climate to 1,035 hr within the future one. Near‐0°C occurrences with precipitation vary from <5% to approximately 50% of these values. Near‐0°C occurrences are sometimes higher than values of neighboring temperatures. These near‐0°C peaks in temperature distributions can occur in both the current and future climate, in only one, or in neither. Only 4.3% of southern Canada is not associated with a near‐0°C peak and 65.8% is associated with a near‐0°C peak in both climates. It is inferred that latent heat exchanges from the melting and freezing of, for example, precipitation and the snowpack contribute significantly to some of these findings. , Plain Language Summary Our changing climate is spurring the development of huge efforts to improve resiliency. For many regions of the world, these efforts must account for potential changes in near‐0°C conditions within which both melting and freezing can occur and the accompanying latent heat exchanges can push air temperature toward 0°C. This article focuses on the occurrence of near‐0°C surface temperatures across southern Canada through an examination of observational and model information including projections in a future warmer (average 6.1°C increase) climate near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% in the future climate and highest values continue to be along the Pacific coast or within the Western Cordillera and lowest values continue to be within central and northern areas. Near‐0°C occurrences are often higher than those of neighboring temperatures in the present climate and some of these elevated occurrences persist into the future one despite dramatic warming. It is inferred that latent heat exchanges from the melting and freezing of precipitation and snowcover contribute to these findings. , Key Points Near‐0°C surface air temperatures were examined over southern Canada using retrospective and pseudo‐global warming simulations Overall average occurrences increase slightly and their spatial patterns are largely maintained in the warmer climate Near‐0°C occurrences sometimes exceed those of neighboring temperatures and this feature often persists despite dramatic warming

Adhering Solid Precipitation in the Current and Pseudo-Global Warming Future Climate over the Canadian Provinces of Manitoba and Saskatchewan - Stewart, Ronald; Liu, Zhuo; Painchaud-Niemi, Dylan; Hanesiak, John; Thériault, Julie M. (Atmosphere, 2023)
Solid precipitation falling near 0 °C, mainly snow, can adhere to surface features and produce major impacts. This study is concerned with characterizing this precipitation over the Canadian Prairie provinces of Manitoba and Saskatchewan in the current (2000–2013) and pseudo-global warming future climate, with an average 5.9 °C temperature increase, through the use of high resolution (4 km) model simulations. On average, simulations in the current climate suggest that this precipitation occurs within 11 events per year, lasting 33.6 h in total and producing 27.5 mm melted equivalent, but there are wide spatial variations that are partly due to enhancements arising from its relatively low terrain. Within the warmer climate, average values generally increase, and spatial patterns shift somewhat. This precipitation consists of four categories covering its occurrence just below and just above a wet-bulb temperature of 0 °C, and with or without liquid precipitation. It generally peaks in March or April, as well as in October, and these peaks move towards mid-winter by approximately one month within the warmer climate. Storms producing this precipitation generally produce winds with a northerly component during or shortly after the precipitation; these winds contribute to further damage. Overall, this study has determined the features of and expected changes to adhering precipitation across this region.

Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS) - Thompson, Hadleigh D.; Thériault, Julie M.; Déry, Stephen J.; Stewart, Ronald E.; Boisvert, Dominique; Rickard, Lisa; Leroux, Nicolas R.; Colli, Matteo; Vionnet, Vincent (Earth System Science Data, 2023)
Abstract. The amount and the phase of cold-season precipitation accumulating in the upper Saint John River (SJR) basin are critical factors in determining spring runoff, ice jams, and flooding. To study the impact of winter and spring storms on the snowpack in the upper SJR basin, the Saint John River Experiment on Cold Season Storms (SAJESS) was conducted during winter–spring 2020–2021. Here, we provide an overview of the SAJESS study area, field campaign, and data collected. The upper SJR basin represents 41 % of the entire SJR watershed and encompasses parts of the US state of Maine and the Canadian provinces of Quebec and New Brunswick. In early December 2020, meteorological instruments were co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick. This included a separate weather station for measuring standard meteorological variables, an optical disdrometer, and a micro rain radar. This instrumentation was augmented during an intensive observation period that also included upper-air soundings, surface weather observations, a multi-angle snowflake camera, and macrophotography of solid hydrometeors throughout March and April 2021. During the study, the region experienced a lower-than-average snowpack that peaked at ∼ 65 cm, with a total of 287 mm of precipitation (liquid-equivalent) falling between December 2020 and April 2021, a 21 % lower amount of precipitation than the climatological normal. Observers were present for 13 storms during which they conducted 183 h of precipitation observations and took more than 4000 images of hydrometeors. The inclusion of local volunteers and schools provided an additional 1700 measurements of precipitation amounts across the area. The resulting datasets are publicly available from the Federated Research Data Repository at https://doi.org/10.20383/103.0591 (Thompson et al., 2023). We also include a synopsis of the data management plan and a brief assessment of the rewards and challenges of conducting the field campaign and utilizing community volunteers for citizen science.

Characteristics of Rain-Snow Transitions Over the Canadian Rockies and their Changes in Warmer Climate Conditions - Thériault, Julie M.; Leroux, Nicolas R.; Tchuem Tchuente, Obert; Stewart, Ronald E. (Atmosphere-Ocean, 2023)

Climatology of and Factors Contributing to Occurrences of Near-0°C Temperatures and Associated Precipitation At and Near Terrace, British Columbia, Canada - Cardinal, Émile; Thériault, Julie M.; Stewart, Ronald E.; Thompson, Hadleigh D.; Déry, Stephen J. (Atmosphere-Ocean, 2024)

Performance of precipitation phase partitioning methods and their impact on snowpack evolution in a humid continental climate - Leroux, Nicolas R.; Vionnet, Vincent; Thériault, Julie M. (Hydrological Processes, 2023)
Abstract Accurate estimations of the precipitation phase at the surface are critical for hydrological and snowpack modelling in cold regions. Precipitation phase partitioning methods (PPMs) vary in their ability to estimate the precipitation phase at around 0°C and can significantly impact simulations of snowpack accumulation and melt. The goal of this study is to evaluate PPMs of varying complexity using high‐quality observations of precipitation phase and to assess the impact on snowpack simulations. We used meteorological data collected in Edmundston, New Brunswick, Canada, during the 2021 Saint John River Experiment on Cold Season Storms (SAJESS). These data were combined with manual observations of snow depth. Five PPMs commonly used in hydrological models were tested against observations from a laser‐optical disdrometer and a Micro Rain Radar. Most PPMs produced similar accuracy in estimating only rainfall and snowfall. Mixed precipitation was the most difficult phase to predict. The multi‐physics model Crocus was then used to simulate snowpack evolution and to diagnose model sensitivity to snowpack accumulation processes (PPM, snowfall density, and snowpack compaction). Sixteen snowpack accumulation periods, including nine warm accumulation events (average temperatures above −2°C) were observed during the study period. When considering all accumulation events, simulated changes in snow water equivalent ( SWE ) were more sensitive to the type of PPM used, whereas simulated changes in snow depth were more sensitive to uncertainties in snowfall density. Choice of PPM was the main source of model sensitivity for changes in SWE and snow depth when only considering warm events. Overall, this study highlights the impact of precipitation phase estimations on snowpack accumulation at the surface during near‐0°C conditions.

Climatological context of the mid-November 2021 floods in the province of British Columbia, Canada - Richards-Thomas, Tamar S.; Déry, Stephen J.; Stewart, Ronald E.; Thériault, Julie M. (Weather and Climate Extremes, 2024)

IMERG in the Canadian Precipitation Analysis (CaPA) System for Winter Applications - Bélair, Stéphane; Feng, Pei-Ning; Lespinas, Franck; Khedhaouiria, Dikra; Hudak, David; Michelson, Daniel; Aubry, Catherine; Beaudry, Florence; Carrera, Marco L.; Thériault, Julie M. (Atmosphere, 2024)
Several configurations of the Canadian Precipitation Analysis system (CaPA) currently produce precipitation analyses at Environment and Climate Change Canada (ECCC). To improve CaPA’s performance during the winter season, the impact of assimilating the IMERG V06 product (IMERG: Integrated Multi-satellitE Retrievals for GPM—Global Precipitation Measurement mission) into CaPA is examined in this study. Tests are conducted with CaPA’s 10 km deterministic version, evaluated over Canada and the northern part of the United States (USA). Maps from a case study show that IMERG plays a contradictory role in the production of CaPA’s precipitation analyses for a synoptic-scale winter storm over North America’s eastern coast. While its contribution appears to be physically correct over southern portions of the meteorological system, and early in its intensification phase, IMERG displays unrealistic spatial structures over land later in the system’s life cycle when it is located over northern (colder) areas. Objective evaluation of CaPA’s analyses when IMERG is assimilated without any restrictions shows an overall decrease in precipitation, which has a mixed effect (positive and negative) on the bias indicators. But IMERG’s influence on the Equitable Threat Score (ETS), a measure of CaPA’s analyses accuracy, is clearly negative. Using IMERG’s quality index (QI) to filter out areas where it is less accurate improves CaPA’s objective evaluation, leading to better ETS versus the control experiment in which no IMERG data are assimilated. Several diagnostics provide insight into the nature of IMERG’s contribution to CaPA. For the most successful configuration, with a QI threshold of 0.3, IMERG’s impact is mostly found in the warmer parts of the domain, i.e., in northern US states and in British Columbia. Spatial means of the temporal sums of absolute differences between CaPA’s analyses with and without IMERG indicate that this product also contributes meaningfully over land areas covered by snow, and areas where air temperature is below −2 °C (where precipitation is assumed to be in solid phase).

Application of a High‐Resolution Distributed Hydrological Model on a U.S.‐Canada Transboundary Basin: Simulation of the Multiyear Mean AnnualHydrograph and 2011 Flood of theRichelieu River Basin - Lucas‐Picher, Philippe; Arsenault, Richard; Poulin, Annie; Ricard, Simon; Lachance‐Cloutier, Simon; Turcotte, Richard (Journal of Advances in Modeling Earth Systems, 2020)
Abstract During spring 2011, an extreme flood occurred along the Richelieu River located in southern Quebec, Canada. The Richelieu River is the last section of the complex Richelieu basin, which is composed of the large Lake Champlain located in a valley between two large mountains. Previous attempts in reproducing the Richelieu River flow relied on the use of simplified lumped models and showed mixed results. In order to prepare a tool to assess accurately the change of flood recurrences in the future, a state‐of‐the‐art distributed hydrological model was applied over the Richelieu basin. The model setup comprises several novel methods and data sets such as a very high resolution river network, a modern calibration technique considering the net basin supply of Lake Champlain, a new optimization algorithm, and the use of an up‐to‐date meteorological data set to force the model. The results show that the hydrological model is able to satisfactorily reproduce the multiyear mean annual hydrograph and the 2011 flow time series when compared with the observed river flow and an estimation of the Lake Champlain net basin supply. Many factors, such as the quality of the meteorological forcing data, that are affected by the low density of the station network, the steep terrain, and the lake storage effect challenged the simulation of the river flow. Overall, the satisfactory validation of the hydrological model allows to move to the next step, which consists in assessing the impacts of climate change on the recurrence of Richelieu River floods. , Plain Language Summary In order to study the 2011 Richelieu flood and prepare a tool capable of estimating the effects of climate change on the recurrence of floods, a hydrological model is applied over the Richelieu basin. The application of a distributed hydrological model is useful to simulate the flow of all the tributaries of the Richelieu basin. This new model setup stands out from past models due to its distribution in several hydrological units, its high‐resolution river network, the calibration technique, and the high‐resolution weather forcing data set used to drive the model. The model successfully reproduced the 2011 Richelieu River flood and the annual hydrograph. The simulation of the Richelieu flow was challenging due to the contrasted elevation of the Richelieu basin and the presence of the large Lake Champlain that acts as a reservoir and attenuates short‐term fluctuations. Overall, the application was deemed satisfactory, and the tool is ready to assess the impacts of climate change on the recurrence of Richelieu River floods. , Key Points An advanced high‐resolution distributed hydrological model is applied over a U.S.‐Canada transboundary basin The simulated net basin supply of Lake Champlain and the Richelieu River discharge are in good agreement with observations of the 2011 flood The flow simulation is challenging due to the topographic and meteorological complexities of the basin and uncertainties in the observations

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation - Martel, Jean-Luc; Brissette, François P.; Lucas-Picher, Philippe; Troin, Magali; Arsenault, Richard (Journal of Hydrologic Engineering, 2021)

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin? - Lucas‐Picher, Philippe; Lachance‐Cloutier, Simon; Arsenault, Richard; Poulin, Annie; Ricard, Simon; Turcotte, Richard; Brissette, François (JAWRA Journal of the American Water Resources Association, 2021)
Abstract In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.

Impacts du changement climatique sur les pluies intenses et les crues en Méditerranée - Tramblay, Yves; Ribes, Aurélien; Somot, Samuel; Neppel, Luc; Lucas-Picher, Philippe; Vinet, Freddy; Sauquet, Eric (LHB, 2021)

Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies - Sebok, Eva; Henriksen, Hans Jørgen; Pastén-Zapata, Ernesto; Berg, Peter; Thirel, Guillaume; Lemoine, Anthony; Lira-Loarca, Andrea; Photiadou, Christiana; Pimentel, Rafael; Royer-Gaspard, Paul; Kjellström, Erik; Christensen, Jens Hesselbjerg; et al. (Hydrology and Earth System Sciences, 2022)
Abstract. Various methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. In this study both climate and hydrological models are analysed, and the result of a research experiment is presented using model weighting with the participation of six climate model experts and six hydrological model experts. For the experiment, seven climate models are a priori selected from a larger EURO-CORDEX (Coordinated Regional Downscaling Experiment – European Domain) ensemble of climate models, and three different hydrological models are chosen for each of the three European river basins. The model weighting is based on qualitative evaluation by the experts for each of the selected models based on a training material that describes the overall model structure and literature about climate models and the performance of hydrological models for the present period. The expert elicitation process follows a three-stage approach, with two individual rounds of elicitation of probabilities and a final group consensus, where the experts are separated into two different community groups: a climate and a hydrological modeller group. The dialogue reveals that under the conditions of the study, most climate modellers prefer the equal weighting of ensemble members, whereas hydrological-impact modellers in general are more open for assigning weights to different models in a multi-model ensemble, based on model performance and model structure. Climate experts are more open to exclude models, if obviously flawed, than to put weights on selected models in a relatively small ensemble. The study shows that expert elicitation can be an efficient way to assign weights to different hydrological models and thereby reduce the uncertainty in climate impact. However, for the climate model ensemble, comprising seven models, the elicitation in the format of this study could only re-establish a uniform weight between climate models.

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America - Martel, J.‐L.; Brissette, F.; Troin, M.; Arsenault, R.; Chen, J.; Su, T.; Lucas‐Picher, P. (Geophysical Research Letters, 2022)
Abstract A warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies. , Plain Language Summary Greenhouse gas emissions are causing the climate to warm significantly, which in turn impacts flows in rivers worldwide. To adapt to these changes, it is essential to quantify them and assess future risk and vulnerability. Climate models are the primary tools used to achieve this. The main data set that provides scientists with state‐of‐the‐art climate model simulations is known as the Coupled Model Intercomparison Project (CMIP). The fifth phase of that project (CMIP5) has been used over the past decade in multiple hydrological studies to assess the impacts of climate change on streamflow. The more recent sixth phase (CMIP6) has started to generate projections, which brings the following question: is it necessary to update the hydrological impact studies performed using CMIP5 with the new CMIP6 models? To answer this question, a comparison between CMIP5 and CMIP6 using 3,107 catchments over North America was conducted. Results show that there is less spread in temperature and precipitation projections for CMIP6. This translates into a smaller spread of future mean, high and low flow values, except for mountainous areas. Overall, we assess that using the CMIP6 data set would provide a more concerted range of future climate projections, leading to more confident hydrological impact studies. , Key Points A comparison of hydrological impacts using Coupled Model Intercomparison Project version 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles is performed over 3,107 catchments in North America The CMIP6 ensembles provide a narrower band of uncertainty for hydrological indicators in the future It is recommended to update hydrological impact studies performed using CMIP5 with the CMIP6 ensemble

Evaluation of the convection-permitting regional climate model CNRM-AROME41t1 over Northwestern Europe - Lucas-Picher, Philippe; Brisson, E.; Caillaud, C.; Alias, A.; Nabat, P.; Lemonsu, A.; Poncet, N.; Cortés Hernandez, V. E.; Michau, Y.; Doury, A.; Monteiro, D.; Somot, S. (Climate Dynamics, 2024)
Abstract Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation of precipitation extremes. In this article, the CPRCM CNRM-AROME developed at the Centre National de Recherches Météorologiques (CNRM) since a few years is described and evaluated using a 2.5-km 19-year long hindcast simulation over a large northwestern European domain using different observations through an added-value analysis in which a comparison with its driving 12-km RCM CNRM-ALADIN is performed. The evaluation is challenging due to the lack of high-quality observations at both high temporal and spatial resolutions. Thus, a high spatio-temporal observed gridded precipitation dataset was built from the collection of seven national datasets that helped the identification of added value in CNRM-AROME. The evaluation is based on a series of standard climatic features that include long-term means and mean annual cycles of precipitation and near-surface temperature where CNRM-AROME shows little improvements compared to CNRM-ALADIN. Additional indicators such as the summer diurnal cycle and indices of extreme precipitation show, on the contrary, a more realistic behaviour of the CNRM-AROME model. Moreover, the analysis of snow cover shows a clear added-value in the CNRM-AROME simulation, principally due to the improved description of the orography with the CPRCM high resolution. Additional analyses include the evaluation of incoming shortwave radiation, and cloud cover using satellite estimates. Overall, despite some systematic biases, the evaluation indicates that CNRM-AROME is a suitable CPRCM that is superior in many aspects to the RCM CNRM-ALADIN.

Evaluation of the Urban Heat Island of 12 cities of France in a high-resolution regional climate model simulation - Michau, Y.; Lemonsu, A.; Lucas-Picher, P.; Caillaud, C. (Urban Climate, 2023)

What added value of CNRM-AROME convection-permitting regional climate model compared to CNRM-ALADIN regional climate model for urban climate studies ? Evaluation over Paris area (France) - Lemonsu, A.; Caillaud, C.; Alias, A.; Riette, S.; Seity, Y.; Le Roy, B.; Michau, Y.; Lucas-Picher, P. (Climate Dynamics, 2023)

Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations - Ricard, Simon; Lucas-Picher, Philippe; Thiboult, Antoine; Anctil, François (Hydrology and Earth System Sciences, 2023)
Abstract. A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. This alternative approach is designed by combining asynchronous hydroclimatic modelling and quantile perturbation applied to streamflow observations. Calibration is run by forcing hydrologic models with raw climate model outputs using an objective function that excludes the day-to-day temporal correlation between simulated and observed hydrographs. The resulting hydrologic scenarios provide useful and reliable information considering that they (1) preserve trends and physical consistency between simulated climate variables, (2) are implemented from a modelling cascade despite observation scarcity, and (3) support the participation of end-users in producing and interpreting climate change impacts on water resources. The proposed modelling workflow is implemented over four sub-catchments of the Chaudière River, Canada, using nine North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) simulations and a pool of lumped conceptual hydrologic models. Results confirm that the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. They also highlight the sensibility of the proposed workflow to strong biases affecting raw climate model outputs, frequently causing outlying projections of the hydrologic regime. Inappropriate forcing climate simulations were however successfully identified (and excluded) using the performance of the simulated hydrologic response as a ranking criterion. Results finally suggest that further works should be conducted to confirm the reliability of the proposed workflow to assess the impact of climate change on high- and low-flow events.

On the future evolution of heatwaves in French cities and associated rural areas: Insights from a convection-permitting model - Michau, Y.; Lemonsu, A.; Lucas-Picher, P.; Schneider, M.; Caillaud, C. (Urban Climate, 2024)

Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods? - Poncet, Nils; Lucas-Picher, Philippe; Tramblay, Yves; Thirel, Guillaume; Vergara, Humberto; Gourley, Jonathan; Alias, Antoinette (Natural Hazards and Earth System Sciences, 2024)
Abstract. Floods are the primary natural hazard in the French Mediterranean area, causing damages and fatalities every year. These floods are triggered by heavy precipitation events (HPEs) characterized by limited temporal and spatial extents. A new generation of regional climate models at the kilometer scale have been developed, allowing an explicit representation of deep convection and improved simulations of local-scale phenomena such as HPEs. Convection-permitting regional climate models (CPMs) have been scarcely used in hydrological impact studies, and future projections of Mediterranean floods remain uncertain with regional climate models (RCMs). In this paper, we use the CNRM-AROME CPM (2.5 km) and its driving CNRM-ALADIN RCM (12 km) at the hourly timescale to simulate floods over the Gardon d'Anduze catchment located in the French Mediterranean region. Climate simulations are bias-corrected with the CDF-t method. Two hydrological models, a lumped and conceptual model (GR5H) and a process-based distributed model (CREST), forced with historical and future climate simulations from the CPM and from the RCM, have been used. The CPM model confirms its ability to better reproduce extreme hourly rainfall compared to the RCM. This added value is propagated on flood simulation with a better reproduction of flood peaks. Future projections are consistent between the hydrological models but differ between the two climate models. Using the CNRM-ALADIN RCM, the magnitude of all floods is projected to increase. With the CNRM-AROME CPM, a threshold effect is found: the magnitude of the largest floods is expected to intensify, while the magnitude of the less severe floods is expected to decrease. In addition, different flood event characteristics indicate that floods are expected to become flashier in a warmer climate, with shorter lag time between rainfall and runoff peak and a smaller contribution of base flow, regardless of the model. This study is a first step for impact studies driven by CPMs over the Mediterranean.

Evaluation of the convection permitting regional climate model CNRM-AROME on the orographically complex island of Corsica - Cortés-Hernández, Virginia Edith; Caillaud, Cécile; Bellon, Gilles; Brisson, Erwan; Alias, Antoinette; Lucas-Picher, Philippe (Climate Dynamics, 2024)
Abstract Meteorological processes over islands with complex orography could be better simulated by Convection Permitting Regional Climate Models (CP-RCMs) thanks to an improved representation of the orography, land–sea contrasts, the combination of coastal and orographic effects, and explicit deep convection. This paper evaluates the ability of the CP-RCM CNRM-AROME (2.5-km horizontal resolution) to simulate relevant meteorological characteristics of the Mediterranean island of Corsica for the 2000–2018 period. These hindcast simulations are compared to their driving Regional Climate Model (RCM) CNRM-ALADIN (12.5-km horizontal resolution and parameterised convection), weather stations for precipitation and wind and gridded precipitation datasets. The main benefits are found in the representation of (i) precipitation extremes resulting mainly from mesoscale convective systems affected by steep mountains during autumn and (ii) the formation of convection through thermally induced diurnal circulations and their interaction with the orography during summer. Simulations of hourly precipitation extremes, the diurnal cycle of precipitation, the distribution of precipitation intensities, the duration of precipitation events, and sea breezes are all improved in the 2.5-km simulations with respect to the RCM, confirming an added value. However, existing differences between model simulations and observations are difficult to explain as the main biases are related to the availability and quality of observations, particularly at high elevations. Overall, better results from the 2.5-km resolution, increase our confidence in CP-RCMs to investigate future climate projections for Corsica and islands with complex terrain.

Characterizing and avoiding physical inconsistency generated by the application of univariate quantile mapping on daily minimum and maximum temperatures over Hudson Bay - Agbazo, Médard Noukpo; Grenier, Patrick (International Journal of Climatology, 2020)
Abstract Quantile mapping (QM) is a technique often used for statistical post‐processing (SPP) of climate model simulations, in order to adjust their biases relative to a selected reference product and/or to downscale their resolution. However, when QM is applied in univariate mode, there is a risk of generating other problems, like intervariable physical inconsistency (PI). Here, such a risk is investigated with daily temperature minimum ( T min ) and maximum ( T max ), for which the relationship T min > T max would be inconsistent with the definition of the variables. QM is applied to an ensemble of 78 daily CMIP5 simulations over Hudson Bay for the application period 1979–2100, with Climate Forecast System Reanalysis (CFSR) selected as the reference product during the calibration period 1979–2010. This study's specific objectives are as follows: to investigate the conditions under which PI situations are generated; to test whether PI may be prevented simply by tuning some of the QM technique's numerical choices; and to compare the suitability of alternative approaches that hinder PI by design. Primary results suggest that PI situations appear preferentially for small values of the initial (simulated) diurnal temperature range (DTR), but the differential between the respective biases of T min and T max also plays an important role; one cannot completely prevent the generation of PI simply by adjusting QM parameters and options, but forcing preservation of the simulated long‐term trends generates fewer PI situations; for avoiding PI between T min and T max , the present study supports a previous recommendation to directly post‐process T max and DTR before deducing T min .

Projected economic losses from milk performance detriments under heat stress in Quebec dairy herds - Ouellet, V.; Grenier, P.; Santschi, D.E.; Cabrera, V.E.; Fadul-Pacheco, L.; Charbonneau, É. (Canadian Journal of Animal Science, 2021)
The objective of this study was to estimate economic losses associated with milk performance detriments under different climate scenarios. A dataset containing milk records of Holstein and daily temperature–humidity indexes compiled over 6 yr in two contrasting climatic dairy regions of Quebec [eastern (EQ) and southwestern Quebec (SWQ)] was used to develop equations for modeling milk performance. Milk performance, including milk, fat, protein, and lactose yields of dairy herds (kg·d −1 ), were then projected considering six plausible climate scenarios during a climatic reference period (REF: 1971–2000) and two future periods (FUT1: 2020–2049; FUT2: 2050–2079). Economic losses were assessed by comparing future to reference milk prices based on components. Results indicated that fat and protein yields could decline in the future, thus resulting in economic losses ranging from $5.34 to $7.07 CAD·hL −1 in EQ and from $5.03 to $6.99 CAD·hL −1 in SWQ, depending on the amplitude of future temperature and humidity changes and on whether it is milk quota or cow number which is adjusted to avoid under-quota production. The projected increase in occurrence and duration of heat stress episodes under climate change could result in substantial financial harm for producers, thereby reinforcing the necessity of implementing heat-abatement strategies on dairy farms.

Modeled performance of forage mixtures and annual crops grown in eastern Canada under climate change - Payant, Camille; Jégo, Guillaume; Ouellet, Véronique; Grenier, Patrick; Tremblay, Gaëtan F.; Bélanger, Gilles; Charbonneau, Édith (Agronomy Journal, 2021)
Abstract Timothy ( Phleum pratense L.) is expected to be more affected by climate change than other forage grasses. Therefore, alternatives to timothy, such as tall fescue [ Schedonorus arundinaceus (Shreb.) Dumort.], meadow fescue [ S. pratensis (Huds.) P. Beauv.], or meadow bromegrass ( Bromus biebersteinii Roem. & Schult.) should be explored. Our objective was to simulate and compare the yield and nutritive value of four alfalfa ( Medicago sativa L.)–grass mixtures and annual crops grown on two virtual dairy farms representative of eastern Canada under future climate conditions. The Integrated Farm System Model (IFSM) was used for these projections under the reference (1971–2000), near future (2020–2049), and distant future (2050–2079) climates for two climatically contrasting agricultural areas in eastern Canada (eastern Quebec; southwestern Quebec). In both future periods, annual forage dry matter (DM) yields of the four alfalfa–grass mixtures are projected to increase because of additional harvests, with greater DM yield increases projected in the colder area than in the warmer area. In both areas, the highest yield increase is projected for alfalfa–tall fescue mixture and the lowest for alfalfa–timothy mixture. The nutritive value of all mixtures should increase due to a greater proportion of alfalfa. In both areas, yields of silage and grain corn ( Zea mays L.), and soybean [ Glycine max (L.) Merr.] are projected to increase, but not those of wheat ( Triticum aestivum L.) and barley ( Hordeum vulgare L.). Tall fescue, meadow bromegrass, and meadow fescue are adequate alternatives to timothy grown in association with alfalfa under future climate conditions. , Core Ideas Forage yields of alfalfa–grass mixtures are projected to increase due to additional harvests. Mixture with tall fescue is projected to increase the most and timothy the least. Tall fescue, meadow fescue, and meadow bromegrass are valuable alternatives to timothy. Nutritive value is projected to increase due to more alfalfa in the mixture. Corn and soybean grain yields are projected to increase but not those of wheat and barley.

The distinct problems of physical inconsistency and of multivariate bias involved in the statistical adjustment of climate simulations - Alavoine, Mégane; Grenier, Patrick (International Journal of Climatology, 2023)
Abstract Bias adjustment of numerical climate model simulations involves several arguments wherein the notion of physical inconsistency is referred to, either for rejecting the legitimacy of bias adjustment in general or for justifying the necessity of sophisticated multivariate techniques. However, this notion is often mishandled, in part because the literature generally proceeds without defining it. In this context, the central objective of this study is to clarify and illustrate the distinction between physical inconsistency and multivariate bias, by investigating the effect of bias adjustment on two different kinds of intervariable relationships, namely a physical constraint expected to hold at every step of a time series and statistical properties that emerge with potential bias over a climatic timescale. To this end, 18 alternative bias adjustment techniques are applied on 10 climate simulations at 12 sites over North America. Adjusted variables are temperature, pressure, relative humidity and specific humidity, linked by a thermodynamic constraint. The analysis suggests on the one hand that a clear instance of potential physical inconsistency can be avoided with either a univariate or a multivariate technique, if and only if the bias adjustment strategy explicitly considers the physical constraint to be preserved. On the other hand, it also suggests that sophisticated multivariate techniques alone are not complete adjustment strategies in presence of a physical constraint, as they cannot replace its explicit consideration. By involving common bias adjustment procedures with likely effects on diverse basic statistical properties, this study may also help guide climate information users in the determination of adequate bias adjustment strategies for their research purposes.

Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S. - Khan, Salah Uddin; Ogden, Nicholas H.; Fazil, Aamir A.; Gachon, Philippe H.; Dueymes, Guillaume U.; Greer, Amy L.; Ng, Victoria (Environmental Health Perspectives, 2020)

Psychological impacts of the 2019 Quebec floods: findings from a large population-based study - Genereux, M; Maltais, D; Lansard, A L; Gachon, P (European Journal of Public Health, 2020)
Abstract Background During Spring 2019, many regions in Quebec (Canada) experienced severe floods. As much as 5,245 households were flooded and 7,452 persons were evacuated, causing extensive material and human damages. A large population-based study was therefore conducted to examine medium-term effects of this natural disaster on health and well-being. Methods Six to eight months post-floods, households located in the flooded zones (in one of the 6 Quebec regions the most severely affected) were randomly invited to participate to a telephone or a web-based survey (response rate=15.3%). Several psychological health outcomes were examined, including psychological distress (based on the 6-item Kessler Scale, score 0-24) and post-traumatic stress (based on the 15-item Impact of Event Scale, score 0-75). These outcomes were compared among 3 levels of exposure using Chi-square test: flooded (floodwater in ≥ 1 liveable room), disrupted (floodwater in non-liveable areas, loss of utilities, loss of access to services, or evacuation), and unaffected. Results Of the 3,437 participating households, 349 (10.2%) were flooded and 1230 (35.8%) were disrupted (but not flooded) during the 2019 floods. A steep gradient was observed for moderate/severe symptoms of post-traumatic stress (score ≥ 26) according to the level of exposure to flooding (unaffected: 3.0%; disrupted: 14.6%; flooded: 44.1%; p < 0.0005). For psychological distress (score ≥ 7), the baseline level (i.e. unaffected group) was 7.3% while it reached 15.0% and 38.4% in the disrupted and the flooded groups, respectively (p < 0.0005). Conclusions This study is among the largest to examine the psychological impacts of flooding. The magnitude of effects observed in flooded households is consistent with the literature and calls for stronger social and economic measures to support flood victims. Such support should help coping with initial stress, but also alleviating secondary stressors classically observed in post-flood settings. Key messages Psychological impacts of floods may persist for several months and may be observed in both flooded and disrupted people. Stronger social and economic measures are needed to better support flood victims, not only in the short but also in the longer term.

Evaluating the Dependence between Temperature and Precipitation to Better Estimate the Risks of Concurrent Extreme Weather Events - Wazneh, Hussein; Arain, M. Altaf; Coulibaly, Paulin; Gachon, Philippe (Advances in Meteorology, 2020)
Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.

Projected Wind Impact on Abies balsamea (Balsam fir)-Dominated Stands in New Brunswick (Canada) Based on Remote Sensing and Regional Modelling of Climate and Tree Species Distribution - Bourque, Charles P.-A.; Gachon, Philippe; MacLellan, Benjamin R.; MacLellan, James I. (Remote Sensing, 2020)
The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4–5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP’s 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006–2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.

Atmospheric blocking events in the North Atlantic: trends and links to climate anomalies and teleconnections - Wazneh, Hussein; Gachon, Philippe; Laprise, René; De Vernal, Anne; Tremblay, Bruno (Climate Dynamics, 2021)
Abstract Atmospheric blockings are generally associated with large-scale high-pressure systems that interrupt west-to-east atmospheric flow in mid and high latitudes. Blockings cause several days of quasi-stationary weather conditions, and therefore can result in monthly or seasonal climate anomalies and extreme weather events on the affected regions. In this paper, the long-term coupled CERA-20C reanalysis data from 1901 to 2010 are used to evaluate the links between blocking events over the North Atlantic north of 35° N, and atmospheric and oceanic modes of climate variability on decadal time scales. This study indicates more frequent and longer lasting blocking events than previous studies using other reanalyses products. A strong relationship was found between North Atlantic blocking events and North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO) and Baffin Island–West Atlantic (BWA) indices, in fall, winter and spring. More blocking events occur during the negative phases of the NAO index and positive phases of the BWA mode. In some situations, the BWA patterns provide clearer links with the North Atlantic blocking occurrence than with the NAO alone. The correlation between the synchronous occurrences of AMO and blocking is generally weak, although it does increase for a lag of about 6–10 years. Convergent cross mapping (CCM) furthermore demonstrates a significant two-way causal effect between blocking occurrences and the NAO and BWA indices. Finally, while we find no significant trends in blocking frequencies over the last 110 years in the Northern Hemisphere, these events become longer lasting in summer and fall, and more intense in spring in the North Atlantic.

Yellow fever virus outbreak in Brazil under current and future climate - Sadeghieh, Tara; Sargeant, Jan M.; Greer, Amy L.; Berke, Olaf; Dueymes, Guillaume; Gachon, Philippe; Ogden, Nicholas H.; Ng, Victoria (Infectious Disease Modelling, 2021)

Zika virus outbreak in Brazil under current and future climate - Sadeghieh, Tara; Sargeant, Jan M.; Greer, Amy L.; Berke, Olaf; Dueymes, Guillaume; Gachon, Philippe; Ogden, Nicholas H.; Ng, Victoria (Epidemics, 2021)

Respiratory and Otolaryngology Symptoms Following the 2019 Spring Floods in Quebec - Landaverde, Elsa; Généreux, Mélissa; Maltais, Danielle; Gachon, Philippe (International Journal of Environmental Research and Public Health, 2022)
Background: Although floods may have important respiratory health impacts, few studies have examined this issue. This study aims to document the long-term impacts of the spring floods of 2019 in Quebec by (1) describing the population affected by the floods; (2) assessing the impacts on the respiratory system according to levels of exposure; and (3) determining the association between stressors and respiratory health. Methods: A population health survey was carried out across the six most affected regions 8–10 months post-floods. Data were collected on self-reported otolaryngology (ENT) and respiratory symptoms, along with primary and secondary stressors. Three levels of exposure were examined: flooded, disrupted and unaffected. Results: One in ten respondents declared being flooded and 31.4% being disrupted by the floods. Flooded and disrupted participants reported significantly more ENT symptoms (adjusted odds ratio (aOR): 3.18; 95% CI: 2.45–4.14; aOR: 1.76; 95% CI: 1.45–2.14) and respiratory symptoms (aOR: 3.41; 95% CI: 2.45–4.75; aOR: 1.45; 95% CI: 1.10–1.91) than the unaffected participants. All primary stressors and certain secondary stressors assessed were significantly associated with both ENT and respiratory symptoms, but no “dose–response” gradient could be observed. Conclusion: This study highlights the long-term adverse effects of flood exposure on respiratory health.

The influence of the environment and indoor residual spraying on malaria risk in a cohort of children in Uganda - Sadoine, Margaux L.; Smargiassi, Audrey; Liu, Ying; Gachon, Philippe; Dueymes, Guillaume; Dorsey, Grant; Fournier, Michel; Nankabirwa, Joaniter I.; Rek, John; Zinszer, Kate (Scientific Reports, 2022)
Abstract Studies have estimated the impact of the environment on malaria incidence although few have explored the differential impact due to malaria control interventions. Therefore, the objective of the study was to evaluate the effect of indoor residual spraying (IRS) on the relationship between malaria and environment (i.e. rainfall, temperatures, humidity, and vegetation) using data from a dynamic cohort of children from three sub-counties in Uganda. Environmental variables were extracted from remote sensing sources and averaged over different time periods. General linear mixed models were constructed for each sub-counties based on a log-binomial distribution. The influence of IRS was analysed by comparing marginal effects of environment in models adjusted and unadjusted for IRS. Great regional variability in the shape (linear and non-linear), direction, and magnitude of environmental associations with malaria risk were observed between sub-counties. IRS was significantly associated with malaria risk reduction (risk ratios vary from RR = 0.03, CI 95% [0.03–0.08] to RR = 0.35, CI95% [0.28–0.42]). Model adjustment for this intervention changed the magnitude and/or direction of environment-malaria associations, suggesting an interaction effect. This study evaluated the potential influence of IRS in the malaria-environment association and highlighted the necessity to control for interventions when they are performed to properly estimate the environmental influence on malaria. Local models are more informative to guide intervention program compared to national models.

Climate change alone cannot explain boreal caribou range recession in Quebec since 1850 - Morineau, Chloé; Boulanger, Yan; Gachon, Philippe; Plante, Sabrina; St‐Laurent, Martin‐Hugues (Global Change Biology, 2023)
Abstract The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change should also be considered. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources to assess the potential effects of recent climate change on the observed northward contraction of the range of boreal populations of woodland caribou ( Rangifer tarandus caribou ) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved ~105 km north over time under all reanalysis datasets, a trend drastically different from the ~620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This relatively limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat‐mediated apparent competition and overharvesting. Our results also call for a reconsideration of past ranges in models aiming at projecting future distributions, especially for endangered species.

Analysis of the Development Mechanisms of a Polar Low over the Norwegian Sea Simulated with the Canadian Regional Climate Model - Moreno-Ibáñez, Marta; Laprise, René; Gachon, Philippe (Atmosphere, 2023)
Polar lows (PLs) are maritime mesoscale cyclones associated with severe weather. They develop during marine cold air outbreaks near coastlines and the sea ice edge. Unfortunately, our knowledge about the mechanisms leading to PL development is still incomplete. This study aims to provide a detailed analysis of the development mechanisms of a PL that formed over the Norwegian Sea on 25 March 2019 using the output of a simulation with the sixth version of the Canadian Regional Climate Model (CRCM6/GEM4), a convection-permitting model. First, the life cycle of the PL is described and the vertical wind shear environment is analysed. Then, the horizontal wind divergence and the baroclinic conversion term are computed, and a surface pressure tendency equation is developed. In addition, the roles of atmospheric static stability, latent heat release, and surface heat and moisture fluxes are explored. The results show that the PL developed in a forward-shear environment and that moist baroclinic instability played a major role in its genesis and intensification. Baroclinic instability was initially only present at low levels of the atmosphere, but later extended upward until it reached the mid-troposphere. Whereas the latent heat of condensation and the surface heat fluxes also contributed to the development of the PL, convective available potential energy and barotropic conversion do not seem to have played a major role in its intensification. In conclusion, this study shows that a convection-permitting model simulation is a powerful tool to study the details of the structure of PLs, as well as their development mechanisms.

Precipitation Extremes and Their Links with Regional and Local Temperatures: A Case Study over the Ottawa River Basin, Canada - Llerena, Ana; Gachon, Philippe; Laprise, René (Atmosphere, 2023)
In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of links between precipitation extremes and 2 m air temperature for the Ottawa River Basin (ORB, Canada) over the period 1981–2010, applying an exponential relationship between the 99th percentile of precipitation and temperature characteristics. Three simulations of the Canadian Regional Climate Model version 5 (CRCM5), at three different resolutions (0.44°, 0.22°, and 0.11°), one simulation using the recent CRCM version 6 (CRCM6) at “convection-permitting” resolution (2.5 km), and two reanalysis products (ERA5 and ERA5-Land) were used to investigate the CC scaling hypothesis that precipitation increases at the same rate as the atmospheric moisture-holding capacity (i.e., 6.8%/°C). In general, daily precipitation follows a lower rate of change than the CC scaling with median values between 2 and 4%/°C for the ORB and with a level of statistical significance of 5%, while hourly precipitation increases faster with temperature, between 4 and 7%/°C. In the latter case, rates of change greater than the CC scaling were even up to 10.2%/°C for the simulation at 0.11°. A hook shape is observed in summer for CRCM5 simulations, near the 20–25 °C temperature threshold, where the 99th percentile of precipitation decreases with temperature, especially at higher resolution with the CRCM6 data. Beyond the threshold of 20 °C, it appears that the atmospheric moisture-holding capacity is not the only determining factor for generating precipitation extremes. Other factors need to be considered, such as the moisture availability at the time of the precipitation event, and the presence of dynamical mechanisms that increase, for example, upward vertical motion. As mentioned in previous studies, the applicability of the CC scaling should not be generalised in the study of precipitation extremes. The time and spatial scales and season are also dependent factors that must be taken into account. In fact, the evolution of precipitation extremes and temperature relationships should be identified and evaluated with very high spatial resolution simulations, knowing that local temperature and regional physiographic features play a major role in the occurrence and intensity of precipitation extremes. As precipitation extremes have important effects on the occurrence of floods with potential deleterious damages, further research needs to explore the sensitivity of projections to resolution with various air temperature and humidity thresholds, especially at the sub-daily scale, as these precipitation types seem to increase faster with temperature than with daily-scale values. This will help to develop decision-making and adaptation strategies based on improved physical knowledge or approaches and not on a single assumption based on CC scaling.

Mixture Probability Models with Covariates: Applications in Estimating Risk of Hydroclimatic Extremes - Yousfi, Nawres; El Adlouni, Salaheddine; Papalexiou, Simon Michael; Gachon, Philippe (Journal of Hydrologic Engineering, 2023)

Differential Influence of Environmental Factors on Malaria Due to Vector Control Interventions in Uganda - Sadoine, Margaux L.; Smargiassi, Audrey; Liu, Ying; Gachon, Philippe; Fournier, Michel; Dueymes, Guillaume; Namuganga, Jane Frances; Dorsey, Grant; Nasri, Bouchra; Zinszer, Kate (International Journal of Environmental Research and Public Health, 2023)
Background: Few studies have explored how vector control interventions may modify associations between environmental factors and malaria. Methods: We used weekly malaria cases reported from six public health facilities in Uganda. Environmental variables (temperature, rainfall, humidity, and vegetation) were extracted from remote sensing sources. The non-linearity of environmental variables was investigated, and negative binomial regression models were used to explore the influence of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) on associations between environmental factors and malaria incident cases for each site as well as pooled across the facilities, with or without considering the interaction between environmental variables and vector control interventions. Results: An average of 73.3 weekly malaria cases per site (range: 0–597) occurred between 2010 and 2018. From the pooled model, malaria risk related to environmental variables was reduced by about 35% with LLINs and 63% with IRS. Significant interactions were observed between some environmental variables and vector control interventions. There was site-specific variability in the shape of the environment–malaria risk relationship and in the influence of interventions (6 to 72% reduction in cases with LLINs and 43 to 74% with IRS). Conclusion: The influence of vector control interventions on the malaria–environment relationship need to be considered at a local scale in order to efficiently guide control programs.

Intersectoral approaches: the key to mitigating psychosocial and health consequences of disasters and systemic risks - Gousse-Lessard, Anne-Sophie; Gachon, Philippe; Lessard, Lily; Vermeulen, Valérie; Boivin, Maxime; Maltais, Danielle; Landaverde, Elsa; Généreux, Mélissa; Motulsky, Bernard; Le Beller, Julien (Disaster Prevention and Management: An International Journal, 2023)
Purpose The current pandemic and ongoing climate risks highlight the limited capacity of various systems, including health and social ones, to respond to population-scale and long-term threats. Practices to reduce the impacts on the health and well-being of populations must evolve from a reactive mode to preventive, proactive and concerted actions beginning at individual and community levels. Experiences and lessons learned from the pandemic will help to better prevent and reduce the psychosocial impacts of floods, or other hydroclimatic risks, in a climate change context. Design/methodology/approach The present paper first describes the complexity and the challenges associated with climate change and systemic risks. It also presents some systemic frameworks of mental health determinants, and provides an overview of the different types of psychosocial impacts of disasters. Through various Quebec case studies and using lessons learned from past and recent flood-related events, recommendations are made on how to better integrate individual and community factors in disaster response. Findings Results highlight the fact that people who have been affected by the events are significantly more likely to have mental health problems than those not exposed to flooding. They further demonstrate the adverse and long-term effects of floods on psychological health, notably stemming from indirect stressors at the community and institutional levels. Different strategies are proposed from individual-centered to systemic approaches, in putting forward the advantages from intersectoral and multirisk researches and interventions. Originality/value The establishment of an intersectoral flood network, namely the InterSectoral Flood Network of Québec (RIISQ), is presented as an interesting avenue to foster interdisciplinary collaboration and a systemic view of flood risks. Intersectoral work is proving to be a major issue in the management of systemic risks, and should concern communities, health and mental health professionals, and the various levels of governance. As climate change is called upon to lead to more and more systemic risks, close collaboration between all the areas concerned with the management of the factors of vulnerability and exposure of populations will be necessary to respond effectively to damages and impacts (direct and indirect) linked to new meteorological and compound hazards. This means as well to better integrate the communication managers into the risk management team.

Assessment of simulations of a polar low with the Canadian Regional Climate Model - Moreno-Ibáñez, Marta; Laprise, René; Gachon, Philippe (PLOS ONE, 2023)
Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.

Estimating the Incidence and Economic Cost of Lyme Disease Cases in Canada in the 21st Century with Projected Climate Change - Ogden, Nicholas H.; Dumas, Ariane; Gachon, Philippe; Rafferty, Ellen (Environmental Health Perspectives, 2024)

The 2023 wildfire season in Québec: an overview of extreme conditions, impacts, lessons learned and considerations for the future - Boulanger, Yan; Arseneault, Dominique; Bélisle, Annie Claude; Bergeron, Yves; Boucher, Jonathan; Boucher, Yan; Danneyrolles, Victor; Erni, Sandy; Gachon, Philippe; Girardin, Martin P.; Grant, Eliane; Grondin, Pierre; et al. (Canadian Journal of Forest Research, 2024)
The 2023 wildfire season in Québec set records due to extreme warm and dry conditions, burning 4.5 million hectares and indicating persistent and escalating impacts associated with climate change. This study reviews the unusual weather conditions that led to the fires, discussing their extensive impacts on the forest sector, fire management, boreal caribou habitats, and particularly the profound effects on First Nation communities. The wildfires led to significant declines in forest productivity and timber supply, overwhelming fire management resources, and necessitating widespread evacuations. First Nation territories were dramatically altered, facing severe air quality issues and disruptions. While caribou impacts were modest across the province, the broader ecological, economical, and social repercussions were considerable. To mitigate future extreme wildfire seasons, the study suggests changes in forest management practices to increase forest resilience and resistance, adapting industrial structures to changes in wood type harvested, and enhancing fire suppression and risk management strategies. It calls for a comprehensive, unified approach to risk management that incorporates the lessons learned from the 2023 fire season and accounts for ongoing climate change. The studyunderscores the urgent need for detailed planning and proactive measures to reduce the growing risks and impacts of wildfires in a changing climate.

Predicting malaria risk considering vector control interventions under climate change scenarios - Sadoine, Margaux L.; Zinszer, Kate; Liu, Ying; Gachon, Philippe; Fournier, Michel; Dueymes, Guillaume; Dorsey, Grant; Llerena, Ana; Namuganga, Jane Frances; Nasri, Bouchra; Smargiassi, Audrey (Scientific Reports, 2024)
Abstract Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010–2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min–Max]: 16,785 [9,902–74,382] vs 21,289 [11,796–70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda.

Storms as Forming and Threatening Factors for Coasts - Von Storch, Hans; Feser, Frauke; Blender, Richard; Camargo, Suzana J.; Cavicchia, Leone; Di Luca, Alejandro; Fu, Gang; Gozzo, Luiz Felippe; Koks, Elco; Messmer, Martina; Mori, Nobuhito; Priestley, Matthew D.K.; et al. (Oxford Research Encyclopedia of Climate Science, 2024)
Storms are the most significant meteorological phenomena that affect the formation of coasts and human livelihood along them. Thus, risks related to coastal storms, such as flooding, loss of land, shipping, and other offshore activity, have had a significant influence on coastal societies and their economies. In the early 21st century, anthropogenic climate change will affect the locations and intensities of coastal storminess, impacting society. Storms are studied not only by natural scientists but also by social scientists. The former deal with the climatologies, dynamics, and mechanisms of storms but also with the identification of different types of storms, such as extratropical baroclinic storms, explosive cyclones, tropical storms, polar lows, medicanes, Vb-cyclones, and Australian east coast storms. Their significance is often through their physical impacts, in particular ocean waves and storm surges, which were and are associated with massive losses of lives, sometimes up to several hundred thousand people, and wealth. The perceptions of what storms constitute were different in different cultural contexts and times. In earlier days, higher forces were responsible for such storms, which they used to transfer messages to humans, physically based ideas have been forming since the 16th century. Another significant historical development was societies preparing to reduce their vulnerability to storms and to implement practices of insurance and risk management.

Projected changes in vertical temperature profiles for Australasia - Ji, Fei; Evans, Jason P.; Di Virgilio, Giovanni; Nishant, Nidhi; Di Luca, Alejandro; Herold, Nicholas; Downes, Stephanie M.; Tam, Eugene; Beyer, Kathleen (Climate Dynamics, 2020)

Regional Versus Remote Atmosphere‐Ocean Drivers of the Rapid Projected Intensification of the East Australian Current - Bull, Christopher Y. S.; Kiss, Andrew E.; Gupta, Alex Sen; Jourdain, Nicolas C.; Argüeso, Daniel; Di Luca, Alejandro; Sérazin, Guillaume (Journal of Geophysical Research: Oceans, 2020)
Abstract Like many western boundary currents, the East Australian Current (EAC) extension is projected to get stronger and warmer in the future. The CMIP5 multimodel mean (MMM) projection suggests up to 5°C of warming under an RCP85 scenario by 2100. Previous studies employed Sverdrup balance to associate a trend in basin wide zonally integrated wind stress curl (resulting from the multidecadal poleward intensification in the westerly winds over the Southern Ocean) with enhanced transport in the EAC extension. Possible regional drivers are yet to be considered. Here we introduce the NEMO‐OASIS‐WRF coupled regional climate model as a framework to improve our understanding of CMIP5 projections. We analyze a hierarchy of simulations in which the regional atmosphere and ocean circulations are allowed to freely evolve subject to boundary conditions that represent present‐day and CMIP5 RCP8.5 climate change anomalies. Evaluation of the historical simulation shows an EAC extension that is stronger than similar ocean‐only models and observations. This bias is not explained by a linear response to differences in wind stress. The climate change simulations show that regional atmospheric CMIP5 MMM anomalies drive 73% of the projected 12 Sv increase in EAC extension transport whereas the remote ocean boundary conditions and regional radiative forcing (greenhouse gases within the domain) play a smaller role. The importance of regional changes in wind stress curl in driving the enhanced EAC extension is consistent with linear theory where the NEMO‐OASIS‐WRF response is closer to linear transport estimates compared to the CMIP5 MMM. , Plain Language Summary In recent decades, enhanced warming, severe marine heatwaves, and increased transport by the East Australian Current have led to the invasion of nonnative species and the destruction of kelp forests east of Tasmania. The East Australian Current extension is projected to get stronger and warmer in the future. We seek to better understand coupled climate model projections for the Tasman Sea. This is difficult because there is large model diversity and considerable uncertainty as to how and where future changes will occur. In addition, little is known about the possible importance of regional versus large‐scale changes in surface time‐mean winds in driving future circulation changes. Here we use a single limited‐domain ocean‐atmosphere coupled model that takes the average model projections as its inputs and finds that changes in the regional wind stress are most important for the enhanced projected East Australian Current extension. We also find that these projected changes are consistent with simple linear theory and the simulated regional changes in wind stress. , Key Points NEMO‐OASIS‐WRF coupled regional climate model is evaluated and introduced as a new tool for analyzing Tasman Sea climate projections NEMO‐OASIS‐WRF projections suggest that local atmospheric changes drive 73% of the projected 12 Sv increase in EAC extension transport The importance of regional changes in wind stress curl driving the enhanced EAC extension is consistent with linear theory

Realised added value in dynamical downscaling of Australian climate change - Di Virgilio, Giovanni; Evans, Jason P.; Di Luca, Alejandro; Grose, Michael R.; Round, Vanessa; Thatcher, Marcus (Climate Dynamics, 2020)

Future Changes in the Occurrence of Hybrid Cyclones: The Added Value of Cyclone Classification for the East Australian Low‐Pressure Systems - Cavicchia, L.; Pepler, A.; Dowdy, A.; Evans, J.; Di Luca, A.; Walsh, K. (Geophysical Research Letters, 2020)
Abstract Several regions of the world, including the east coast of Australia, are characterized by the occurrence of low‐pressure systems with a range of different dynamical structures, including tropical, extratropical, and hybrid cyclones. Future changes in the occurrence of cyclones are better understood if storms are classified according to their dynamical structure. Therefore, we apply a classification of cyclones according to their cold‐core or warm‐core structure to an ensemble of regional climate model simulations. First, we show that historical simulations reproduce well the reanalysis results in terms of cyclone classification. We then show that once cyclone classification is applied, projections of future cyclone activity become more robust, including a decrease in the occurrence of both cold‐core and warm‐core cyclones. Finally, we show that in a warmer climate warm‐core hybrid cyclone activity could increase close to the coast, while the associated rainfall and wind are projected to increase. , Plain Language Summary Cyclones in the tropics derive their energy from the temperature difference between warm ocean waters and the atmosphere and their interior is warmer than the environment (warm core), while cyclones in the midlatitudes derive their energy from differences in the atmospheric temperature and density at different locations and their interior is colder than the environment (cold core). In subtropical regions both types of cyclone can form. Also in those regions cyclones known as hybrid cyclones form, with mixed tropical‐extratropical features, such as a partial lower tropospheric warm core and a partial upper tropospheric cold core. This study is focused on cyclones along the eastern coast of Australia. Here we show that dividing cyclones in different classes according to their thermal structure provides a better framework to interpret changes in cyclone activity at subtropical latitudes. This study has two main results. First, classifying cyclones adds value to climate projection robustness. A large number of models agree on the decrease in the occurrence of both cold‐core and warm‐core cyclones. The study also indicates increased occurrence of hybrid cyclones close to the Australian coast. Second, the study shows evidence of future changes in cyclone‐related impacts, such as an increase in the associated rainfall. , Key Points A physically based classification of hybrid cyclones is applied to an ensemble of regional climate model simulations The cyclone classification method adds value to the projections of future cyclone activity, making them more robust Results indicate future changes (2060–2079) toward more intense impacts associated with hybrid cyclones

An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets - Iturbide, Maialen; Gutiérrez, José M.; Alves, Lincoln M.; Bedia, Joaquín; Cerezo-Mota, Ruth; Cimadevilla, Ezequiel; Cofiño, Antonio S.; Di Luca, Alejandro; Faria, Sergio Henrique; Gorodetskaya, Irina V.; Hauser, Mathias; Herrera, Sixto; et al. (Earth System Science Data, 2020)
Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

Assessing the role of the ocean–atmosphere coupling frequency in the western Maritime Continent rainfall - Li, Yue; Gupta, Alex Sen; Taschetto, Andréa S.; Jourdain, Nicolas C.; Di Luca, Alejandro; Done, James M.; Luo, Jing-Jia (Climate Dynamics, 2020)

Global hotspots for the occurrence of compound events - Ridder, Nina N.; Pitman, Andy J.; Westra, Seth; Ukkola, Anna; Do, Hong X.; Bador, Margot; Hirsch, Annette L.; Evans, Jason P.; Di Luca, Alejandro; Zscheischler, Jakob (Nature Communications, 2020)
Abstract Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980–2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.

Decomposing Temperature Extremes Errors in CMIP5 and CMIP6 Models - Di Luca, Alejandro; Pitman, Andrew J.; de Elía, Ramón (Geophysical Research Letters, 2020)
Abstract We quantify the skill of Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 models to represent daily temperature extremes. We find CMIP models systematically exaggerate the magnitude of daily temperature anomalies for both cold and hot extremes. We assess the contribution to a daily temperature extreme from four terms: the long‐term mean annual cycle, the diurnal cycle, synoptic variability, and seasonal variability for both cold and hot extremes. These four terms are combined, and the overall performance of individual climate models assessed. This identifies those models that can simulate temperature extremes well and simulate them well for the right reasons. The new error metric shows that increases in horizontal resolution usually lead to a better performance particularly for the coarser resolution models. The CMIP6 improvements relative to CMIP5 are systematic across most land regions and are only partially explained by the increase in horizontal resolution, and other differences must therefore help explain the higher CMIP6 skill. , Key Points CMIP5 and CMIP6 models exaggerate the magnitude of daily temperature anomalies for hot days and cold nights extremes Higher‐resolution models improve the simulation of temperature extremes largely due to better simulation of synoptic scales CMIP6 outperforms the simulation of temperature extremes compared to CMIP5 beyond the benefits given by the higher resolution

Contribution of mean climate to hot temperature extremes for present and future climates - Di Luca, Alejandro; De Elía, Ramón; Bador, Margot; Argüeso, Daniel (Weather and Climate Extremes, 2020)

East Australian Cyclones and Air‐Sea Feedbacks - Sérazin, G.; Di Luca, A.; Sen Gupta, A.; Rogé, M.; Jourdain, N. C.; Argüeso, D.; Bull, C. Y. S. (Journal of Geophysical Research: Atmospheres, 2021)
Abstract The importance of resolving mesoscale air‐sea interactions to represent cyclones impacting the East Coast of Australia, the so‐called East Coast Lows (ECLs), is investigated using the Australian Regional Coupled Model based on NEMO‐OASIS‐WRF (NOW) at resolution. The fully coupled model is shown to be capable of reproducing correctly relevant features such as the seasonality, spatial distribution and intensity of ECLs while it partially resolves mesoscale processes, such as air‐sea feedbacks over ocean eddies and fronts. The mesoscale thermal feedback (TFB) and the current feedback (CFB) are shown to influence the intensity of northern ECLs (north of ), with the TFB modulating the pre‐storm sea surface temperature (SST) by shifting ECL locations eastwards and the CFB modulating the wind stress. By fully uncoupling the atmospheric model of NOW, the intensity of northern ECLs is increased due to the absence of the cold wake that provides a negative feedback to the cyclone. The number of ECLs might also be affected by the air‐sea feedbacks but large interannual variability hampers significant results with short‐term simulations. The TFB and CFB modify the climatology of SST (mean and variability) but no direct link is found between these changes and those noticed in ECL properties. These results show that the representation of ECLs, mainly north of , depend on how air‐sea feedbacks are simulated. This is particularly important for atmospheric downscaling of climate projections as small‐scale SST interactions and the effects of ocean currents are not accounted for. , Plain Language Summary Air‐sea interactions occur at a variety of spatial scales, including those of the size of ocean eddies. Such interactions are partially resolved in the Australian Regional Coupled Model used to simulate the cyclones impacting the East Coast of Australia, the so‐called East Coast Lows (ECLs). The effect of different feedbacks between the ocean and the atmosphere, including those due to mechanical and thermal exchanges over ocean eddies, are tested on the properties of ECLs. Significant effects are found on the intensity of ECLs north of , with also potential effects on the number of ECLs. The air‐sea feedbacks modify the climatology of sea surface temperature, with no direct link to ECL changes. Such experiments eventually demonstrate that small‐scale air‐sea feedbacks may matter for representing current Australian climate and its change in the future. , Key Points High‐resolution regional coupled modeling can simulate key features of East Australian cyclones Cyclone intensity is sensitive to mechanical and thermal air‐sea feedbacks at mesoscales Coupled and atmosphere‐only models mainly differ in simulating cyclone properties north of

Evaluating Precipitation Errors Using the Environmentally Conditioned Intensity‐Frequency Decomposition Method - Di Luca, A.; Argüeso, D.; Sherwood, S.; Evans, J. P. (Journal of Advances in Modeling Earth Systems, 2021)
Abstract A fundamental issue when evaluating the simulation of precipitation is the difficulty of quantifying specific sources of errors and recognizing compensation of errors. We assess how well a large ensemble of high‐resolution simulations represents the precipitation associated with strong cyclones. We propose a framework to breakdown precipitation errors according to different dynamical (vertical velocity) and thermodynamical (vertically integrated water vapor) regimes and the frequency and intensity of precipitation. This approach approximates the error in the total precipitation of each regime as the sum of three terms describing errors in the large‐scale environmental conditions, the frequency of precipitation and its intensity. We show that simulations produce precipitation too often, that its intensity is too weak, that errors are larger for weak than for strong dynamical forcing and that biases in the vertically integrated water vapor can be large. Using the error breakdown presented above, we define four new error metrics differing on the degree to which they include the compensation of errors. We show that convection‐permitting simulations consistently improve the simulation of precipitation compared to coarser‐resolution simulations using parameterized convection, and that these improvements are revealed by our new approach but not by traditional metrics which can be affected by compensating errors. These results suggest that convection‐permitting models are more likely to produce better results for the right reasons. We conclude that the novel decomposition and error metrics presented in this study give a useful framework that provides physical insights about the sources of errors and a reliable quantification of errors. , Plain Language Summary The simulations of complex physical processes always entail various sources of errors. These errors can be of different sign and can consequently cancel each other out when using traditional performance metrics such as the bias error metric. We present a formal framework that allows us to approximate precipitation according to three terms that describe different aspects of the rainfall field including large‐scale environmental conditions and the frequency and intensity of rainfall. We apply the methodology to a large ensemble of high‐resolution simulations representing the precipitation associated with strong cyclones in eastern Australia. We show that simulations produce precipitation too often, with an intensity that is too weak leading to strong compensation. We further define new error metrics that explicitly quantify the degree of error compensation when simulating precipitation. We show that convection‐permitting simulations consistently improve the performance compared to coarser resolution simulations using parameterized convection and that these improvements are only revealed when using the new error metrics but are not apparent in traditional metrics (e.g., bias). , Key Points Multiple high‐resolution simulations produce precipitation too often with underestimated intensity leading to strong error compensation Errors in precipitation are quantified using novel metrics that prevent error compensation showing value compared with traditional metrics Convection permitting simulations outperform the representation of precipitation compared to simulations using parameterized convection

Seasonality of Continental Extratropical‐Cyclone Wind Speeds Over Northeastern North America - Chen, Ting‐Chen; Di Luca, Alejandro; Winger, Katja; Laprise, René; Thériault, Julie M. (Geophysical Research Letters, 2022)
Abstract This study investigates the seasonality of near‐surface wind speeds associated with extratropical cyclones (ETCs) over northeastern North America using a global reanalysis data set during 1979–2020. As opposed to most studies that emphasize winter storms, ETCs during the fall exhibit significantly stronger 10‐m winds over this region due to the slightly stronger continental cyclones and significantly weaker low‐level stability during that time of the year. Also, ETCs favor inland lakes and Hudson Bay during the low‐ice‐content fall season, leading to lower surface roughness. Combining these results, we derive simple linear regressions to predict the 10‐m wind speed given three variables: 850‐hPa wind speed, low‐level Richardson number, and surface roughness length. This formula captures the observed seasonality and serves as a valuable tool for cyclone near‐surface wind risk assessment. , Plain Language Summary Extratropical cyclones can bring powerful winds that can cause severe damage to infrastructure. We find that cyclones with severe winds are the most frequent in the fall season over continental northeastern North America. Three reasons are found responsible: stronger continental cyclones, weaker low‐level atmospheric stability, and the lower surface roughness over lakes and Hudson Bay, where cyclones frequently occur in fall. A simple formula that can effectively assess the near‐surface wind speeds associated with cyclones is derived based on these results. , Key Points Extratropical‐cyclone‐associated 10‐m wind speeds are the strongest in the fall season over northeastern North America Besides stronger continental cyclones and 850‐hPa winds, weaker low‐level stability in fall favors stronger 10‐m wind speeds in this region Linear regression using 850‐hPa wind, Richardson number, and surface roughness well predicts cyclones' 10‐m wind speeds and seasonality

On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation - Asselin, Olivier; Leduc, Martin; Paquin, Dominique; Di Luca, Alejandro; Winger, Katja; Bukovsky, Melissa; Music, Biljana; Giguère, Michel (Climate, 2022)
The biogeophysical effects of severe forestation are quantified using a new ensemble of regional climate simulations over North America and Europe. Following the protocol outlined for the Land-Use and Climate Across Scales (LUCAS) intercomparison project, two sets of simulations are compared, FOREST and GRASS, which respectively represent worlds where all vegetation is replaced by trees and grasses. Three regional climate models were run over North America. One of them, the Canadian Regional Climate Model (CRCM5), was also run over Europe in an attempt to bridge results with the original LUCAS ensemble, which was confined to Europe. Overall, the CRCM5 response to forestation reveals strong inter-continental similarities, including a pronounced wintertime and springtime warming concentrated over snow-masking evergreen forests. Crucially, these northern evergreen needleleaf forests populate lower, hence sunnier, latitudes in North America than in Europe. Snow masking reduces albedo similarly over both continents, but stronger insolation amplifies the net shortwave radiation and hence warming simulated over North America. In the summertime, CRCM5 produces a mixed response to forestation, with warming over northern needleleaf forests and cooling over southern broadleaf forests. The partitioning of the turbulent heat fluxes plays a major role in determining this response, but it is not robust across models over North America. Implications for the inter-continental transferability of the original LUCAS results are discussed.

Rapid Warming in the Australian Alps from Observation and NARCliM Simulations - Ji, Fei; Nishant, Nidhi; Evans, Jason P.; Di Luca, Alejandro; Di Virgilio, Giovanni; Cheung, Kevin K. W.; Tam, Eugene; Beyer, Kathleen; Riley, Matthew L. (Atmosphere, 2022)
The Australian Alps are the highest mountain range in Australia, which are important for biodiversity, energy generation and winter tourism. Significant increases in temperature in the past decades has had a huge impact on biodiversity and ecosystem in this region. In this study, observed temperature is used to assess how temperature changed over the Australian Alps and surrounding areas. We also use outputs from two generations of NARCliM (NSW and Australian Regional Climate Modelling) to investigate spatial and temporal variation of future changes in temperature and its extremes. The results show temperature increases faster for the Australian Alps than the surrounding areas, with clear spatial and temporal variation. The changes in temperature and its extremes are found to be strongly correlated with changes in albedo, which suggests faster warming in cool season might be dominated by decrease in albedo resulting from future changes in natural snowfall and snowpack. The warming induced reduction in future snow cover in the Australian Alps will have a significant impact on this region.

Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America - Chen, Ting‐Chen; Collet, François; Di Luca, Alejandro (International Journal of Climatology, 2024)
Abstract While the ERA5 reanalysis is commonly utilized in climate studies on extratropical cyclones (ETCs), only a few studies have quantified its ability in the representation of ETCs over land. To address this gap, this study evaluates ERA5's skill in representing the ETC‐associated 10‐m wind speed and the precipitation in central and eastern North America during 2005–2019. Hourly data collected from ~3000 stations, amounting to around 420 million reports stored in the Integrated Surface Database, is used as reference. For the spatial‐averaged ETC properties, ERA5 shows a good skill for wind speed with normalized mean bias (NMB) of −0.7% and normalized root‐mean‐square error (NRMSE) of 14.3%, despite a tendency to overestimate low winds and underestimate high winds. The ERA5 skill is worse for precipitation than for wind speed with NMB of −10.4% and NRMSE of 56.5% and a strong tendency to underestimate high values. For both variables, the best and worst performance is found in DJF and JJA, respectively. Negative biases are often identified over regions with stronger precipitation/wind speeds, and a systematic underestimation of wind speed is found over the Rockies with complex topography. Compared to the averaged ETCs, ERA5's performance deteriorates for the top 5% extreme ETCs with a stronger tendency to underestimate both wind speed and precipitation (NMB of −10.2% and −22.6%, respectively). Furthermore, ERA5's skill is worse for local extreme values within ETCs than for spatial averages. Our results highlight some important limitations of the ERA5 reanalysis products for studies looking at the possible impacts of ETCs.

Uncertainty and outliers in high‐resolution gridded precipitation products over eastern North America - Picart, Tangui; Di Luca, Alejandro; Laprise, René (International Journal of Climatology, 2024)
Abstract Several observational precipitation products that provide high temporal (≤3 h) and spatial (≤0.25°) resolution gridded estimates are available, although no single product can be assumed worldwide to be closest to the (unknown) “reality.” Here, we propose and apply a methodology to quantify the uncertainty of a set of precipitation products and to identify, at individual grid points, the products that are likely wrong (i.e., outliers). The methodology is applied over eastern North America for the 2015–2019 period for eight high‐resolution gridded precipitation products: CMORPH, ERA5, GSMaP, IMERG, MSWEP, PERSIANN, STAGE IV and TMPA. Four difference metrics are used to quantify discrepancies in different aspects of the precipitation time series, such as the total accumulation, two characteristics of the intensity‐frequency distribution, and the timing of precipitating events. Large regional and seasonal variations in the observational uncertainty are found across the ensemble. The observational uncertainty is higher in Canada than in the United States, reflecting large differences in the density of precipitation gauge measurements. In northern midlatitudes, the uncertainty is highest in winter, demonstrating the difficulties of satellite retrieval algorithms in identifying precipitation in snow‐covered areas. In southern midlatitudes, the uncertainty is highest in summer, probably due to the more discontinuous nature of precipitation. While the best product cannot be identified due to the lack of an absolute reference, our study is able to identify products that are likely wrong and that should be excluded depending on the specific application.

Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model - Roberge, François; Di Luca, Alejandro; Laprise, René; Lucas-Picher, Philippe; Thériault, Julie (Geoscientific Model Development, 2024)
Abstract. A fundamental issue associated with the dynamical downscaling technique using limited-area models is related to the presence of a “spatial spin-up” belt close to the lateral boundaries where small-scale features are only partially developed. Here, we introduce a method to identify the distance from the border that is affected by the spatial spin-up (i.e., the spatial spin-up distance) of the precipitation field in convection-permitting model (CPM) simulations. Using a domain over eastern North America, this new method is applied to several simulations that differ on the nesting approach (single or double nesting) and the 3-D variables used to drive the CPM simulation. Our findings highlight three key points. Firstly, when using a single nesting approach, the spin-up distance from lateral boundaries can extend up to 300 km (around 120 CPM grid points), varying across seasons, boundaries and driving variables. Secondly, the greatest spin-up distances occur in winter at the western and southern boundaries, likely due to strong atmospheric inflow during these seasons. Thirdly, employing a double nesting approach with a comprehensive set of microphysical variables to drive CPM simulations offers clear advantages. The computational gains from reducing spatial spin-up outweigh the costs associated with the more demanding intermediate simulation of the double nesting. These results have practical implications for optimizing CPM simulation configurations, encompassing domain selection and driving strategies.

Extratropical storms induce carbon outgassing over the Southern Ocean - Carranza, Magdalena M.; Long, Matthew. C.; Di Luca, Alejandro; Fassbender, Andrea J.; Johnson, Kenneth S.; Takeshita, Yui; Mongwe, Precious; Turner, Katherine E. (npj Climate and Atmospheric Science, 2024)
Abstract The strength and variability of the Southern Ocean carbon sink is a significant source of uncertainty in the global carbon budget. One barrier to reconciling observations and models is understanding how synoptic weather patterns modulate air-sea carbon exchange. Here, we identify and track storms using atmospheric sea level pressure fields from reanalysis data to assess the role that storms play in driving air-sea CO 2 exchange. We examine the main drivers of CO 2 fluxes under storm forcing and quantify their contribution to Southern Ocean annual air-sea CO 2 fluxes. Our analysis relies on a forced ocean-ice simulation from the Community Earth System Model, as well as CO 2 fluxes estimated from Biogeochemical Argo floats. We find that extratropical storms in the Southern Hemisphere induce CO 2 outgassing, driven by CO 2 disequilibrium. However, this effect is an order of magnitude larger in observations compared to the model and caused by different reasons. Despite large uncertainties in CO 2 fluxes and storm statistics, observations suggest a pivotal role of storms in driving Southern Ocean air-sea CO 2 outgassing that remains to be well represented in climate models, and needs to be further investigated in observations.

How Can Municipalities in British Columbia and Quebec Contribute to Flood Risk Reduction? - Deschamps, Bernard; Bourdeau-Brien, Michael; Boudreault, Mathieu (Institute on Municipal Finance and Governance, 2023)
Flood-related losses are on the rise in Canada and private insurance remains costly or unavailable in high-risk areas. Despite the introduction of overland flood insurance in 2015, following the federal government’s invitation to the insurance industry to participate in flood risk-sharing, federal and provincial disaster financial assistance programs still cover a large portion of these costs. As the risks increase, governments are questioning the sustainability of using taxpayers’ money to finance such losses, leaving municipalities with significant residual risk. The growing number of people and assets occupying flood-prone areas, including public infrastructure, has contributed to the sharp increase in flood damage costs. Based on a literature review and discussions with experts, this paper describes the municipal role in flood-risk management, and shows how provincial and federal financial assistance to municipalities for flood damage in British Columbia and Québec may be counterproductive in fostering flood-risk management at the municipal level. We conclude that municipalities can play a more proactive role in incorporating risk reduction as the key objective of disaster financial assistance and propose three specific policy instruments to help reduce the growing number of people living in flood zones: flood mapping, land-use planning, and the relocation of high-risk properties.

Pricing Flood Insurance with a Hierarchical Physics-Based Model - Boudreault, Mathieu; Grenier, Patrick; Pigeon, Mathieu; Potvin, Jean-Mathieu; Turcotte, Richard (North American Actuarial Journal, 2020)

Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters - Bégin, Jean-François; Boudreault, Mathieu (Journal of Computational and Graphical Statistics, 2021)

A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning - Carozza, David A.; Boudreault, Mathieu (Journal of Advances in Modeling Earth Systems, 2021)
Abstract Large scale flood risk analyses are fundamental to many applications requiring national or international overviews of flood risk. While large‐scale climate patterns such as teleconnections and climate change become important at this scale, it remains a challenge to represent the local hydrological cycle over various watersheds in a manner that is physically consistent with climate. As a result, global models tend to suffer from a lack of available scenarios and flexibility that are key for planners, relief organizations, regulators, and the financial services industry to analyze the socioeconomic, demographic, and climatic factors affecting exposure. Here we introduce a data‐driven, global, fast, flexible, and climate‐consistent flood risk modeling framework for applications that do not necessarily require high‐resolution flood mapping. We use statistical and machine learning methods to examine the relationship between historical flood occurrence and impact from the Dartmouth Flood Observatory (1985–2017), and climatic, watershed, and socioeconomic factors for 4,734 HydroSHEDS watersheds globally. Using bias‐corrected output from the NCAR CESM Large Ensemble (1980–2020), and the fitted statistical relationships, we simulate 1 million years of events worldwide along with the population displaced in each event. We discuss potential applications of the model and present global flood hazard and risk maps. The main value of this global flood model lies in its ability to quickly simulate realistic flood events at a resolution that is useful for large‐scale socioeconomic and financial planning, yet we expect it to be useful to climate and natural hazard scientists who are interested in socioeconomic impacts of climate. , Plain Language Summary Flood is among the deadliest and most damaging natural disasters. To protect against large scale flood risk, stakeholders need to understand how floods can occur and their potential impacts. Stakeholders rely on global flood models to provide them with plausible flood scenarios around the world. For a flood model to operate at the global scale, climate effects must be represented in addition to hydrological ones to demonstrate how rivers can overflow throughout the world each year. Global flood models often lack the flexibility and variety of scenarios required by many stakeholders because they are computationally demanding. Designed for applications where detailed local flood impacts are not required, we introduce a rapid and flexible global flood model that can generate hundreds of thousands of scenarios everywhere in the world in a matter of minutes. The model is based on a historical flood database from 1985 to 2017 that is represented using an algorithm that learns from the data. With this model, the output from a global climate model is used to simulate a large sample of floods for risk analyses that are coherent with global climate. Maps of the annual average number of floods and number of displaced people illustrate the models results. , Key Points We present a global flood model built using machine learning methods fitted with historical flood occurrences and impacts Forced with a climate model, the global flood model is fast, flexible and consistent with global climate We provide global flood hazard (occurrence) and risk (population displaced) maps over 4,734 watersheds

Gridded flood depth estimates from satellite-derived inundations - Bryant, Seth; McGrath, Heather; Boudreault, Mathieu (Natural Hazards and Earth System Sciences, 2022)
Abstract. Canada's RADARSAT missions improve the potential to study past flood events; however, existing tools to derive flood depths from this remote-sensing data do not correct for errors, leading to poor estimates. To provide more accurate gridded depth estimates of historical flooding, a new tool is proposed that integrates Height Above Nearest Drainage and Cost Allocation algorithms. This tool is tested against two trusted, hydraulically derived, gridded depths of recent floods in Canada. This validation shows the proposed tool outperforms existing tools and can provide more accurate estimates from minimal data without the need for complex physics-based models or expert judgement. With improvements in remote-sensing data, the tool proposed here can provide flood researchers and emergency managers accurate depths in near-real time.

Ratemaking territories and adverse selection for flood insurance - Boudreault, Mathieu; Ojeda, Angelica (Insurance: Mathematics and Economics, 2022)

On the Measurement of Hedging Effectiveness for Long-Term Investment Guarantees - Augustyniak, Maciej; Badescu, Alexandru; Boudreault, Mathieu (Journal of Risk and Financial Management, 2023)
Although the finance literature has devoted a lot of research into the development of advanced models for improving the pricing and hedging performance, there has been much less emphasis on approaches to measure dynamic hedging effectiveness. This article discusses a statistical framework based on regression analysis to measure the effectiveness of dynamic hedges for long-term investment guarantees. The importance of taking model risk into account is emphasized. The difficulties in reducing hedging risk to an appropriately low level lead us to propose a new perspective on hedging, and recognize it as a tool to modify the risk–reward relationship of the unhedged position.

Global Asymmetries in the Influence of ENSO on Flood Risk Based on 1,600 Years of Hybrid Simulations - Del Rio Amador, L.; Boudreault, M.; Carozza, D. A. (Geophysical Research Letters, 2023)
Abstract El Niño‐Southern Oscillation (ENSO) is often considered as a source of long‐term predictability for extreme events via its teleconnection patterns. However, given that its characteristic cycle varies from two to 7 years, it is difficult to obtain statistically significant conclusions based on observational periods spanning only a few decades. To overcome this, we apply the global flood risk modeling framework developed by Carozza and Boudreault to an equivalent of 1,600 years of bias‐corrected General Circulation Model outputs. The results show substantial anomalies in flood occurrences and impacts for El Niño and La Niña when compared to the all‐year baseline. We were able to obtain a larger global coverage of statistically significant results than previous studies limited to observational data. Asymmetries in anomalies for both ENSO phases show a larger global influence of El Niño than La Niña on flood hazard and risk. , Plain Language Summary El Niño‐Southern Oscillation (ENSO) is one of the most important global climate phenomena. It is well‐known to affect precipitation and temperature in many areas of the world. It is therefore very important for researchers (environmental and climate sciences, economics, etc.), risk managers, decision‐ and policy‐makers to understand the influence of ENSO on flooding. Previous studies analyzed the link between ENSO and flooding but because they were based upon 40 years of data, a lot of uncertainties remained as to how ENSO has any significance on flooding. In this study, we use outputs from a climate model large ensemble that provides 1,600 years of simulated data to determine the impacts of ENSO on flooding. But because it is very difficult to run traditional flood models on 1,600 years of data, we rather leverage a machine learning approach to accelerate computations in a context where the focus is on socioeconomic impacts. We find that ENSO is a significant driver of flooding in more regions than what was previously found. Finally, there appears to be a greater global influence of El Niño than La Niña on flooding. , Key Points We simulated an equivalent of 1,600 years of realistic flood events globally using a statistical model forced with climate model outputs We found a statistically significant ( α = 0.05) influence of El Niño‐Southern Oscillation (ENSO) over 55% of land area for flood occurrence and over 69% for flood impact Asymmetries in anomalies for both ENSO phases show a larger global influence of El Niño than La Niña on flood hazard and risk

Comparison of three flood-related relocation programs with probabilistic cost-benefit analyses - Boudreault, Mathieu; Bourdeau-Brien, Michael; Milot, Nicolas (International Journal of Disaster Risk Reduction, 2023)

Leveraging prices from credit and equity option markets for portfolio risk management - Bégin, Jean‐François; Boudreault, Mathieu; Thériault, Mathieu (Journal of Futures Markets, 2024)
Abstract This study presents a firm‐specific methodology for extracting implied default intensities and recovery rates jointly from unit recovery claim prices—backed by out‐of‐the‐money put options—and credit default swap premiums, therefore providing time‐varying and market‐consistent views of credit risk at the individual level. We apply the procedure to about 400 firms spanning different sectors of the US economy between 2003 and 2019. The main determinants of default intensities and recovery rates are analyzed with statistical and machine learning methods linking default risk and credit losses to market, sector, and individual variables. Consistent with the literature, we find that individual volatility, leverage, and corporate bond market determinants are key factors explaining the implied default intensities and recovery rates. Then, we apply the framework in the context of credit risk management in applications, like, market‐consistent credit value‐at‐risk calculation and stress testing.

UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models - Carozza, David A.; Boudreault, Mathieu; Grenier, Manuel; Caron, Louis‐Philippe (Journal of Advances in Modeling Earth Systems, 2024)
Abstract Tropical cyclones (TCs) are among the most destructive natural hazards and yet, quantifying their financial impacts remains a significant methodological challenge. It is therefore of high societal value to synthetically simulate TC tracks and winds to assess potential impacts along with their probability distributions for example, land use planning and financial risk management. A common approach to generate TC tracks is to apply storm detection methodologies to climate model output, but such an approach is sensitive to the method and parameterization used and tends to underestimate intense TCs. We present a global TC model (the UQAM‐TCW model thereafter) that melds statistical modeling, to capture historical risk features, with a climate model large ensemble, to generate large samples of physically coherent TC seasons. Integrating statistical and physical methods, the model is probabilistic and consistent with the physics of how TCs develop. The model includes frequency and location of cyclogenesis, full trajectories with maximum sustained winds and the entire wind structure along each track for the six typical cyclogenesis basins from IBTrACS. Being an important driver of TCs globally, we also integrate ENSO effects in key components of the model. The global TC model thus belongs to a recent strand of literature that combines probabilistic and physical approaches to TC track generation. As an application of the model, we show global hazard maps for direct and indirect hits expressed in terms of return periods. The global TC model can be of interest to climate and environmental scientists, economists and financial risk managers. , Plain Language Summary Tropical cyclones (TCs) are among the most destructive natural hazards and yet, quantifying their financial impacts remains a difficult task. Being able to randomly simulate TCs and their features (such as wind speed) with mathematical models is therefore critical to build scenarios (and their corresponding probability) for land use planning and financial risk management. A common approach is to simulate TCs by tracking them directly in climate model outputs but this often underestimates the frequency of intense TCs while being computationally costly overall to generate a large number of events. For these reasons, many authors have looked into alternative approaches that replicate key physical features of TCs but rather using statistical models that are much less computationally demanding. This paper therefore presents a global TC model that leverages the strengths of both statistical and climate models to simulate a large number of TCs whose features are consistent with the physics and observations. As an important global phenomenon that affects TCs globally, we also integrate in our model the effects of El Niño. The paper focuses on the methodology and validation of each model component and concludes with global hazard maps for direct and indirect hits. , Key Points We present a global tropical cyclone (TC) wind model built upon a climate model large ensemble that can be used for risk analysis We integrate ENSO into our model since it is a strong driver of storm annual frequency, cyclogenesis, trajectories, and intensity We present global hazard maps consistent with statistical features of TC components and coherent with a global climate model

A Simulation and Empirical Study of the Maximum Likelihood Estimator for Stochastic Volatility Jump-Diffusion Models - Bégin, Jean-François; Boudreault, Mathieu (Studies in Nonlinear Dynamics & Econometrics, 2024)
Abstract We investigate the behaviour of the maximum likelihood estimator (MLE) for stochastic volatility jump-diffusion models commonly used in financial risk management. A simulation study shows the practical conditions under which the MLE behaves according to theory. In an extensive empirical study based on nine indices and more than 6000 individual stocks, we nonetheless find that the MLE is unable to replicate key higher moments. We then introduce a moment-targeted MLE – robust to model misspecification – and revisit both simulation and empirical studies. We find it performs better than the MLE, improving the management of financial risk.

Projected seasonal flooding in Canada under climate change with statistical and machine learning - Grenier, Manuel; Boudreault, Jérémie; Raymond, Sébastien; Boudreault, Mathieu (Journal of Hydrology: Regional Studies, 2024)

A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada - Bourget, Mathilde; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie; Raymond, Sébastien (ASTIN Bulletin, 2024)
Abstract There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.

Flood occurrence and impact models for socioeconomic applications over Canada and the United States - Grenier, Manuel; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie; Raymond, Sébastien (Natural Hazards and Earth System Sciences, 2024)
Abstract. Large-scale socioeconomic studies of the impacts of floods are difficult and costly for countries such as Canada and the United States due to the large number of rivers and size of watersheds. Such studies are however very important for analyzing spatial patterns and temporal trends to inform large-scale flood risk management decisions and policies. In this paper, we present different flood occurrence and impact models based upon statistical and machine learning methods of over 31 000 watersheds spread across Canada and the US. The models can be quickly calibrated and thereby easily run predictions over thousands of scenarios in a matter of minutes. As applications of the models, we present the geographical distribution of the modelled average annual number of people displaced due to flooding in Canada and the US, as well as various scenario analyses. We find for example that an increase of 10 % in average precipitation yields an increase in the displaced population of 18 % in Canada and 14 % in the US. The model can therefore be used by a broad range of end users ranging from climate scientists to economists who seek to translate climate and socioeconomic scenarios into flood probabilities and impacts measured in terms of the displaced population.

A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset - Morin, Gabriel; Boudreault, Mathieu; García-Franco, Jorge L. (Scientific Data, 2024)
Abstract A global tropical cyclone precipitation dataset covering the period from January 1979 to February 2023 is presented. Global precipitation estimates were taken from the newly developed high-resolution Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2) and TC tracks were obtained from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset. This Global Multi-Source Tropical Cyclone Precipitation (MSTCP) dataset is comprised of two main products and files in the format of tables: the main and profile datasets. The main file provides various TCP statistics per TC track, including mean and maximum precipitation rates over a fixed and symmetrical radius of 500 km. The profile dataset comprises the azimuthally averaged precipitation every 10-km away from the center of each storm (until 500 km). The case study of Hurricane Harvey is used to show that MSWEP estimates agree well with another commonly used satellite product. The main statistics of the dataset are analyzed as well, including the differences in the dataset metrics for each of the six TC basins and for each Saffir-Simpson category for storm intensity.

A new parameterization of ice heterogeneous nucleation coupled to aerosol chemistry in WRF-Chem model version 3.5.1: evaluation through ISDAC measurements - Keita, Setigui Aboubacar; Girard, Eric; Raut, Jean-Christophe; Leriche, Maud; Blanchet, Jean-Pierre; Pelon, Jacques; Onishi, Tatsuo; Cirisan, Ana (Geoscientific Model Development, 2020)
Abstract. In the Arctic, during polar night and early spring, ice clouds are separated into two leading types of ice clouds (TICs): (1) TIC1 clouds characterized by a large concentration of very small crystals and TIC2 clouds characterized by a low concentration of large ice crystals. Using a suitable parameterization of heterogeneous ice nucleation is essential for properly representing ice clouds in meteorological and climate models and subsequently understanding their interactions with aerosols and radiation. Here, we describe a new parameterization for ice crystal formation by heterogeneous nucleation in water-subsaturated conditions coupled to aerosol chemistry in the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The parameterization is implemented in the Milbrandt and Yau (2005a, b) two-moment cloud microphysics scheme, and we assess how the WRF-Chem model responds to the run-time interaction between chemistry and the new parameterization. Well-documented reference cases provided us with in situ data from the spring 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) over Alaska. Our analysis reveals that the new parameterization clearly improves the representation of the ice water content (IWC) in polluted or unpolluted air masses and shows the poor performance of the reference parameterization in representing ice clouds with low IWC. The new parameterization is able to represent TIC1 and TIC2 microphysical characteristics at the top of the clouds, where heterogenous ice nucleation is most likely occurring, even with the known bias of simulated aerosols by WRF-Chem over the Arctic.

Accuracy in starphotometry - Ivănescu, Liviu; Baibakov, Konstantin; O'Neill, Norman T.; Blanchet, Jean-Pierre; Schulz, Karl-Heinz (Atmospheric Measurement Techniques, 2021)
Abstract. Starphotometry, the night-time counterpart of sunphotometry, has not yet achieved the commonly sought observational error level of 1 %: a spectral optical depth (OD) error level of 0.01. In order to address this issue, we investigate a large variety of systematic (absolute) uncertainty sources. The bright-star catalogue of extraterrestrial references is noted as a major source of errors with an attendant recommendation that its accuracy, particularly its spectral photometric variability, be significantly improved. The small field of view (FOV) employed in starphotometry ensures that it, unlike sun- or moonphotometry, is only weakly dependent on the intrinsic and artificial OD reduction induced by scattering into the FOV by optically thin clouds. A FOV of 45 arcsec (arcseconds) was found to be the best trade-off for minimizing such forward-scattering errors concurrently with flux loss through vignetting. The importance of monitoring the sky background and using interpolation techniques to avoid spikes and to compensate for measurement delay was underscored. A set of 20 channels was identified to mitigate contamination errors associated with stellar and terrestrial atmospheric gas absorptions, as well as aurora and airglow emissions. We also note that observations made with starphotometers similar to our High Arctic instrument should be made at high angular elevations (i.e. at air masses less than 5). We noted the significant effects of snow crystal deposition on the starphotometer optics, how pseudo OD increases associated with this type of contamination could be detected, and how proactive techniques could be employed to avoid their occurrence in the first place. If all of these recommendations are followed, one may aspire to achieve component errors that are well below 0.01: in the process, one may attain a total 0.01 OD target error.

Central Role of Nitrogen Fertilizer Relative to Water Management in Determining Direct Nitrous Oxide Emissions From Global Rice‐Based Ecosystems - Song, Hanxiong; Zhu, Qiuan; Blanchet, Jean‐Pierre; Chen, Zhi; Zhang, Kerou; Li, Tong; Zhou, Feng; Peng, Changhui (Global Biogeochemical Cycles, 2023)
Abstract The increasing atmospheric nitrous oxide (N 2 O) concentration stems from the development of agriculture. However, N 2 O emissions from global rice‐based ecosystems have not been explicitly and systematically quantified. Therefore, this study aims to estimate the spatiotemporal magnitudes of the N 2 O emissions from global rice‐based ecosystems and determine different contribution factors by improving a process‐based biogeochemical model, TRIPLEX‐GHG v2.0. Model validation suggested that the modeled N 2 O agreed well with field observations under varying management practices at daily, seasonal, and annual steps. Simulated N 2 O emissions from global rice‐based ecosystems exhibited significant increasing trends from 0.026 ± 0.0013 to 0.18 ± 0.003 TgN yr −1 from 1910 to 2020, with ∼69.5% emissions attributed to the rice‐growing seasons. Irrigated rice ecosystems accounted for a majority of global rice N 2 O emissions (∼76.9%) because of their higher N 2 O emission rates than rainfed systems. Regarding spatial analysis, Southern China, Northeast India, and Southeast Asia are hotspots for rice‐based N 2 O emissions. Experimental scenarios revealed that N fertilizer is the largest global rice‐N 2 O source, especially since the 1960s (0.047 ± 0.010 TgN yr −1 , 35.24%), while the impact of expanded irrigation plays a minor role. Overall, this study provides a better understanding of the rice‐based ecosystem in the global agricultural N 2 O budget; further, it quantitively demonstrated the central role of N fertilizer in rice‐based N 2 O emissions by including rice crop calendars, covering non‐rice growing seasons, and differentiating the effects of various water regimes and input N forms. Our findings emphasize the significance of co‐management of N fertilizer and water regimes in reducing the net climate impact of global rice cultivation. , Plain Language Summary Nitrous oxide (N 2 O) is a greenhouse gas with ∼300 times greater effect on climate warming than carbon dioxide. Global croplands represent the largest source of anthropogenic N 2 O emissions. However, the contribution of global rice‐based cropping ecosystems to the N 2 O budget remains largely uncertain because of inconsistent observed results. Inspired by the increasing availability of reliable global data sets, we improved and applied a process‐based biogeochemical model by describing the dynamics of various microbial activities to simulate N 2 O emissions from rice‐based ecosystems on a global scale. Model simulations showed that 0.18 million tons of N 2 O‐N were emitted from global rice‐based N 2 O emissions in the 2010s, which was five times larger than that in the 1910s. In the context of regional contribution, southern China, northern India, and Southeast Asia are responsible for more than 80% of the total emissions during 1910–2020. Results suggest that N fertilizer is the most important rice‐N 2 O source quantitively and that increasing irrigation exerts a buffering effect. This study confirmed the potential mitigating effect of co‐managing N fertilizer and irrigation on mitigating rice‐based N 2 O emissions globally. , Key Points N 2 O emissions from global rice‐based ecosystem increased from 0.026 to 0.18 TgN yr −1 between 1910 and 2020 Irrigated rice‐based ecosystems showed larger N 2 O fluxes than rainfed rice globally due to higher N fertilizer use and frequent aerations N fertilizer represents the largest N 2 O source, and co‐management of N fertilizer and flooding regimes is important for mitigation

Contribution of the Order Ericales to Improving Paleoclimate Reconstructions - Wei, Gang; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Liu, Weiguo (Sustainability, 2022)
Paleobotanists have long built leaf climate models based on site mean of leaf physiognomic characteristics of woody dicotyledons species (WDS) for estimating past climate. To explore the potential of the order Ericales in estimating paleoclimate, we developed two linear models for each climatic factor. One is based on WDS, and the other is based on both WDS and leaf physiognomic characters of the order Ericales (WDS-E). We found that, compared with WDS models, WDS-E models improved greatly in mean annual precipitation (MAP), growing season precipitation (GSP) and mean annual range in temperature (MART). When the minimum species number of the order Ericales is three per site, the WDS-E models improved the r2 from 0.64 to 0.78 for MART, from 0.23 to 0.61 for ln(MAP), and from 0.37 to 0.64 for ln(GSP) compared with the WDS models. For mean annual temperature (MAT), the WDS-E model (r2 = 0.86) also exhibited a moderate improvement in precision over the WDS model (r2 = 0.82). This study demonstrates that other patterns, such as those of the order Ericales, can contribute additional information towards building more precise paleoclimate models.

Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle - Ding, Juhua; Zhu, Qiuan; Li, Hanwei; Zhou, Xiaolu; Liu, Weiguo; Peng, Changhui (Land, 2022)
Phosphorus (P) is a key and a limiting nutrient in ecosystems and plays an important role in many physiological and biochemical processes, affecting both terrestrial ecosystem productivity and soil carbon storage. However, only a few global land surface models have incorporated P cycle and used to investigate the interactions of C-N-P and its limitation on terrestrial ecosystems. The overall objective of this study was to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. In this study, key processes of the P cycle, including P pool sizes and fluxes in plant, litter, and soil were integrated into a new model framework, TRIPLEX-CNP. We also added dynamic P:C ratios for different ecosystems. Based on sensitivity analysis results, we identified the phosphorus resorption coefficient of leaf (rpleaf) as the most influential parameter to gross primary productivity (GPP) and biomass, and determined optimal coefficients for different plant functional types (PFTs). TRIPLEX-CNP was calibrated with 49 sites and validated against 116 sites across eight biomes globally. The results suggested that TRIPLEX-CNP performed well on simulating the global GPP and soil organic carbon (SOC) with respective R2 values of 0.85 and 0.78 (both p < 0.01) between simulated and observed values. The R2 of simulation and observation of total biomass are 0.67 (p < 0.01) by TRIPLEX-CNP. The overall model performance had been improved in global GPP, total biomass and SOC after adding the P cycle comparing with the earlier version. Our work represents the promising step toward new coupled ecosystem process models for improving the quantifications of land carbon cycle and reducing uncertainty.

Improving a Process-Based Model to Simulate Forest Carbon Allocation under Varied Stand Density - Jiao, Wenxing; Wang, Weifeng; Peng, Changhui; Lei, Xiangdong; Ruan, Honghua; Li, Haikui; Yang, Yanrong; Grabarnik, Pavel; Shanin, Vladimir (Forests, 2022)
Carbon allocation is an important mechanism through which plants respond to environmental changes. To enhance our understanding of maximizing carbon uptake by controlling planting densities, the carbon allocation module of a process-based model, TRIPLEX-Management, was modified and improved by introducing light, soil water, and soil nitrogen availability factors to quantify the allocation coefficients for different plant organs. The modified TRIPLEX-Management model simulation results were verified against observations from northern Jiangsu Province, China, and then the model was used to simulate dynamic changes in forest carbon under six density scenarios (200, 400, 600, 800, 1000, and 1200 stems ha−1). The mean absolute errors between the predicted and observed variables of the mean diameter at breast height, mean height, and estimated aboveground biomass ranged from 15.0% to 26.6%, and were lower compared with the original model simulated results, which ranged from 24.4% to 60.5%. The normalized root mean square errors ranged from 0.2 to 0.3, and were lower compared with the original model simulated results, which ranged from 0.3 to 0.6. The Willmott index between the predicted and observed variables also varied from 0.5 to 0.8, indicating that the modified TRIPLEX-Management model could accurately simulate the dynamic changes in poplar (Populus spp.) plantations with different densities in northern Jiangsu Province. The density scenario results showed that the leaf and fine root allocation coefficients decreased with the increase in stand density, while the stem allocation increased. Overall, our study showed that the optimum stand density (approximately 400 stems ha−1) could reach the highest aboveground biomass for poplar stands and soil organic carbon storage, leading to higher ecological functions related to carbon sequestration without sacrificing wood production in an economical way in northern Jiangsu Province. Therefore, reasonable density control with different soil and climate conditions should be recommended to maximize carbon sequestration.

The Importance of Energy Theory in Shaping Elevational Species Richness Patterns in Plants - Jiang, Zihan; Liu, Qiuyu; Xu, Wei; Peng, Changhui (Biology, 2022)
Many hypotheses have been proposed to explain elevational species richness patterns; however, evaluating their importance remains a challenge, as mountains that are nested within different biogeographic regions have different environmental attributes. Here, we conducted a comparative study for trees, shrubs, herbs, and ferns along the same elevational gradient for 22 mountains worldwide, examining the performance of hypotheses of energy, tolerance, climatic variability, and spatial area to explain the elevational species richness patterns for each plant group. Results show that for trees and shrubs, energy-related factors exhibit greater explanatory power than other factors, whereas the factors that are associated with climatic variability performed better in explaining the elevational species richness patterns of herbs and ferns. For colder mountains, energy-related factors emerged as the main drivers of woody species diversity, whereas in hotter and wetter ecosystems, temperature and precipitation were the most important predictors of species richness along elevational gradients. For herbs and ferns, the variation in species richness was less than that of woody species. These findings provide important evidence concerning the generality of the energy theory for explaining the elevational species richness pattern of plants, highlighting that the underlying mechanisms may change among different growth form groups and regions within which mountains are nested.

Temporal and Spatial Variation of Wetland CH4 Emissions from the Qinghai–Tibet Plateau under Future Climate Change Scenarios - Zhang, Xian; Wang, Jieyi; Zhang, Jiang; Chen, Huai; Peng, Changhui; Zhu, Qiuan (Atmosphere, 2022)
Wetlands are an important natural source of methane (CH4), so it is important to quantify how their emissions may vary under future climate change conditions. The Qinghai–Tibet Plateau contains more than a third of China’s wetlands. Here, we simulated temporal and spatial variation in CH4 emissions from natural wetlands on the Qinghai–Tibet Plateau from 2008 to 2100 under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Based on the simulation results of the TRIPLEX-GHG model forced with data from 24 CMIP5 models of global climate, we predict that, assuming no change in wetland distribution on the Plateau, CH4 emissions from natural wetlands will increase by 35%, 98% and 267%, respectively, under RCP 2.6, 4.5 and 8.5. The predicted increase in atmospheric CO2 concentration will contribute 10–28% to the increased CH4 emissions from wetlands on the Plateau by 2100. Emissions are predicted to be majorly in the range of 0 to 30.5 g C m−2·a−1 across the Plateau and higher from wetlands in the southern region of the Plateau than from wetlands in central or northern regions. Under RCP8.5, the methane emissions of natural wetlands on the Qinghai–Tibet Plateau increased much more significantly than that under RCP2.6 and RCP4.5.

The Severe Multi-Day October 2019 Snow Storm Over Southern Manitoba, Canada - Hanesiak, John; Stewart, Ronald; Painchaud-Niemi, Dylan; Milrad, Shawn; Liu, George; Vieira, Michael; Theriault, Julie; Cholette, Melissa; Ziolkowski, Kyle (Atmosphere-Ocean, 2022)

Ocean Productivity in the Gulf of Cadiz Over the Last 50 kyr - Penaud, A.; Eynaud, F.; Etourneau, J.; Bonnin, J.; De Vernal, A.; Zaragosi, S.; Kim, J.‐H.; Kang, S.; Gal, J.‐K.; Oliveira, D.; Waelbroeck, C. (Paleoceanography and Paleoclimatology, 2022)
Abstract Reconstructions of ocean primary productivity (PP) help to explain past and present biogeochemical cycles and climate changes in the oceans. We document PP variations over the last 50 kyr in a currently oligotrophic subtropical region, the Gulf of Cadiz. Data combine refined results from previous investigations on dinocyst assemblages, alkenones, and stable isotopes ( 18 O, 13 C) in planktonic ( Globigerina bulloides ) and endobenthic ( Uvigerina mediterranea ) foraminifera from cores MD04‐2805 CQ and MD99‐2339, with new isotopic measurements on epibenthic ( Cibicides pachyderma ‐ Cibicidoides wuellerstorfi ) foraminifera and dinocyst‐based estimates of PP using the new n = 1,968 modern database. We constrain PP variations and export production by integrating qualitative information from bioindicators with dinocyst‐based quantitative reconstructions such as PP and seasonal sea surface temperature and information about remineralization from the benthic Δδ 13 C (difference between epibenthic and endobenthic foraminiferal δ 13 C signatures). This study also includes new information on alkenone‐based SST and total organic carbon which provides insights into the relationship between past regional hydrological activity and PP regime change. We show that PP, carbon export, and remineralization were generally high in the NE subtropical Atlantic Ocean during the last glacial period and that the Last Glacial Maximum (LGM) had lower Δδ 13 C than the Heinrich Stadials with sustained high PP, likely allowing enhanced carbon sequestration. We link these PP periods to the dynamics of upwelling, active almost year‐round during sadials, but restricted to spring‐summer during interstadials and LGM, like today. During interstadials, nutrient advection through freshwater inputs during autumn‐winter needs also to be considered to fully understand PP regimes. , Key Points Productivity (PP) in the Gulf of Cadiz is dependent on the seasonality control for both upwelling and nutrient‐enriched freshwater inputs We show generally high PP, carbon export, and remineralization during the last glacial period at the study site The Last Glacial Maximum had lower Δδ 13 C than the Heinrich Stadials with sustained high PP likely allowing enhanced carbon sequestration

The signal of climate changes over the last two millennia in the Gulf of St. Lawrence, eastern Canada - Wu, Xiner; De Vernal, Anne; Fréchette, Bianca; Moros, Matthias; Perner, Kerstin (Quaternary Research, 2022)
Abstract Climate changes over the past two millennia in the central part of the Gulf of St. Lawrence are documented in this paper with the aim of determining and understanding the natural climate variability and the impact of anthropogenic forcing at a regional scale. The palynological content (dinocysts, pollen, and spores) of the composite marine sediment core MSM46-03 collected in the Laurentian Channel was used to reconstruct oceanographic and climatic changes with a multidecadal temporal resolution. Sea-surface conditions, including summer salinity and temperature, sea-ice cover, and primary productivity, were reconstructed from dinocyst assemblages. Results revealed a remarkable cooling trend of about 4°C after 1230 cal yr BP (720 CE) and a culmination with a cold pulse dated to 170–40 cal yr BP (1780–1910 CE), which likely corresponds to the regional signal of the Little Ice Age. This cold interval was followed by a rapid warming of about 3°C. In the pollen assemblages, the decrease of Pinus abundance over the past 1700 yr suggests changes in wind regimes, likely resulting from increased southerly incursions of cold and dry Arctic air masses into southeastern Canada.

Pacific walrus diet across 4000 years of changing sea ice conditions - Clark, Casey T.; Horstmann, Lara; De Vernal, Anne; Jensen, Anne M.; Misarti, Nicole (Quaternary Research, 2022)
Abstract Declining sea ice is expected to change the Arctic's physical and biological systems in ways that are difficult to predict. This study used stable isotope compositions (δ 13 C and δ 15 N) of archaeological, historic, and modern Pacific walrus ( Odobenus rosmarus divergens ) bone collagen to investigate the impacts of changing sea ice conditions on walrus diet during the last ~4000 yr. An index of past sea ice conditions was generated using dinocyst-based reconstructions from three locations in the northeastern Chukchi Sea. Archaeological walrus samples were assigned to intervals of high and low sea ice, and δ 13 C and δ 15 N were compared across ice states. Mean δ 13 C and δ 15 N values were similar for archaeological walruses from intervals of high and low sea ice; however, variability among walruses was greater during low-ice intervals, possibly indicating decreased availability of preferred prey. Overall, sea ice conditions were not a primary driver of changes in walrus diet. The diet of modern walruses was not consistent with archaeological low sea ice intervals. Rather, the low average trophic position of modern walruses (primarily driven by males), with little variability among individuals, suggests that trophic changes to this Arctic ecosystem are still underway or are unprecedented in the last ~4000 yr.

Relationship between environmental pollution and economic development in late-developing regions shows an inverted V - Yu, Yadong; Duan, Changqun; Li, Shiyu; Peng, Changhui; Yang, Jian; Yan, Kun; Bi, Xiaoyi; Zou, Ping (Science of The Total Environment, 2022)

Effects of diversity, climate and litter on soil organic carbon storage in subtropical forests - Li, Yin; Liu, Xiaojuan; Xu, Wubing; Bongers, Franca J.; Bao, Weikai; Chen, Bin; Chen, Guoke; Guo, Ke; Lai, Jiangshan; Lin, Dunmei; Mi, Xiangcheng; Tian, Xingjun; et al. (Forest Ecology and Management, 2020)

Palynological evidence of sea-surface conditions in the Barents Sea off northeast Svalbard during the postglacial period - Brice, Camille; De Vernal, Anne; Ivanova, Elena; Van Bellen, Simon; Van Nieuwenhove, Nicolas (Quaternary Research, 2022)
Abstract Postglacial changes in sea-surface conditions, including sea-ice cover, summer temperature, salinity, and productivity were reconstructed from the analyses of dinocyst assemblages in core S2528 collected in the northwestern Barents Sea. The results show glaciomarine-type conditions until about 11,300 ± 300 cal yr BP and limited influence of Atlantic water at the surface into the Barents Sea possibly due to the proximity of the Svalbard-Barents Sea ice sheet. This was followed by a transitional period generally characterized by cold conditions with dense sea-ice cover and low-salinity pulses likely related to episodic freshwater or meltwater discharge, which lasted until 8700 ± 700 cal yr BP. The onset of “interglacial” conditions in surface waters was marked by a major change in dinocyst assemblages, from dominant heterotrophic to dominant phototrophic taxa. Until 4100 ± 150 cal yr BP, however, sea-surface conditions remained cold, while sea-surface salinity and sea-ice cover recorded large amplitude variations. By ~4000 cal yr BP optimum sea-surface temperature of up to 4°C in summer and maximum salinity of ~34 psu suggest enhanced influence of Atlantic water, and productivity reached up to 150 gC/m 2 /yr. After 2200 ± 1300 cal yr BP, a distinct cooling trend accompanied by sea-ice spreading characterized surface waters. Hence, during the Holocene, with exception of an interval spanning about 4000 to 2000 cal yr BP, the northern Barents Sea experienced harsh environments, relatively low productivity, and unstable conditions probably unsuitable for human settlements.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review - Asif, Zunaira; Chen, Zhi; Stranges, Saverio; Zhao, Xin; Sadiq, Rehan; Olea-Popelka, Francisco; Peng, Changhui; Haghighat, Fariborz; Yu, Tong (Sustainable Cities and Society, 2022)

Do Jumps Matter in the Long Term? A Tale of Two Horizons - Bégin, Jean-François; Boudreault, Mathieu (North American Actuarial Journal, 2022)

Application of machine learning methods for paleoclimatic reconstructions from leaf traits - Wei, Gang; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Yang, Bin (International Journal of Climatology, 2021)
Abstract Digital leaf physiognomy (DLP) is considered as one of the most promising methods for estimating past climate. However, current models built using the DLP data set still lack precision, especially for mean annual precipitation (MAP). To improve predictive power, we developed five machine learning (ML) models for mean annual temperature (MAT) and MAP respectively, and then tested the precision of these models and some of their averaging compared with that obtained from other models. The precision of all models was assessed using a repeated stratified 10‐fold cross‐validation. For MAT, three combinations of models ( R 2 = .77) presented moderate improvements in precision over the multiple linear regression (MLR) model ( R 2 = .68). For log e (MAP), the averaging of the support vector machine (SVM) and boosting models improved the R 2 from .19 to .63 compared with that of the MLR model. For MAP, the R 2 of this model combination was 0.49, which was much better than that of the artificial neural network (ANN) model ( R 2 = .21). Even the bagging model, which had the lowest R 2 (.37) for log e (MAP), demonstrated better precision ( R 2 = .27) for MAP. Our palaeoclimate estimates for nine fossil floras were also more accurate, because they were in better agreement with independent paleoclimate evidence. Our study confirms that our ML models and their averaging can improve paleoclimatic reconstructions, providing a better understanding of the relationship between climate and leaf physiognomy.

Optimal Configuration of a Far‐Infrared Radiometer to Study the Arctic Winter Atmosphere - Coursol, Laurence; Libois, Quentin; Gauthier, Pierre; Blanchet, Jean‐Pierre (Journal of Geophysical Research: Atmospheres, 2020)
Abstract Several far‐infrared (FIR) satellite missions are planned for the next decade, with a special interest for the Arctic region. A theoretical study is performed to help with the design of an FIR radiometer, whose configuration in terms of channels number and frequencies is optimized based on information content analysis. The problem is cast in a context of vertical column experiments (1D) to determine the optimal configuration of a FIR radiometer to study the Arctic polar night. If only observations of the FIR radiometer were assimilated, the results show that for humidity, 90% of the total information content is obtained with four bands, whereas for temperature, 10 bands are needed. When the FIR measurements are assimilated on top of those from the advanced infrared sounder (AIRS), the former bring in additional information between the surface and 850 hPa and from 550 to 250 hPa for humidity. Moreover, between 400 and 200 hPa, the FIR radiometer is better than AIRS at reducing the analysis error variance for humidity. This indicates the potential of FIR observations for improving water vapor analysis in the Arctic. , Key Points FIR channels add information for UTLS water vapor compared to standard MIR channels IC is used to optimize the channels frequencies and widths of a FIR radiometer A high DFS is reached with only a few channels of an optimized FIR radiometer
Keywords: Arctique; Atmosphère; Radiométrie

Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites - Mariani, Zen; Huang, Laura; Crawford, Robert; Blanchet, Jean-Pierre; Hicks-Jalali, Shannon; Mekis, Eva; Pelletier, Ludovick; Rodriguez, Peter; Strawbridge, Kevin (Earth System Science Data, 2022)
Abstract. The changing Arctic climate is creating increased economic, transportation, and recreational activities requiring reliable and relevant weather information. However, the Canadian Arctic is sparsely observed, and processes governing weather systems in the Arctic are not well understood. There is a recognized lack of meteorological data to characterize the Arctic atmosphere for operational forecasting and to support process studies, satellite calibration/validation, search and rescue operations (which are increasing in the region), high-impact weather (HIW) detection and prediction, and numerical weather prediction (NWP) model verification and evaluation. To address this need, Environment and Climate Change Canada commissioned two supersites, one in Iqaluit (63.74∘ N, 68.51∘ W) in September 2015 and the other in Whitehorse (60.71∘ N, 135.07∘ W) in November 2017 as part of the Canadian Arctic Weather Science (CAWS) project. The primary goals of CAWS are to provide enhanced meteorological observations in the Canadian Arctic for HIW nowcasting (short-range forecast) and NWP model verification, evaluation, and process studies and to provide recommendations on the optimal cost-effective observing system for the Canadian Arctic. Both sites are in provincial/territorial capitals and are economic hubs for the region; they also act as transportation gateways to the north and are in the path of several common Arctic storm tracks. The supersites are located at or next to major airports and existing Meteorological Service of Canada ground-based weather stations that provide standard meteorological surface observations and upper-air radiosonde observations; they are also uniquely situated in close proximity to frequent overpasses by polar-orbiting satellites. The suite of in situ and remote sensing instruments at each site is completely automated (no on-site operator) and operates continuously in all weather conditions, providing near-real-time data to operational weather forecasters, the public, and researchers via obrs.ca. The two sites have similar instruments, including mobile Doppler weather radars, multiple vertically profiling and/or scanning lidars (Doppler, ceilometer, water vapour), optical disdrometers, precipitation gauges in different shielded configurations, present weather sensors, fog monitoring devices, radiation flux sensors, and other meteorological instruments. Details on the two supersites, the suites of instruments deployed, the data collection methods, and example case studies of HIW events are discussed. CAWS data are publicly accessible via the Canadian Government Open Data Portal (https://doi.org/10.18164/ff771396-b22c-4bc3-844d-38fc697049e9, Mariani et al., 2022a, and https://doi.org/10.18164/d92ed3cf-4ba0-4473-beec-357ec45b0e78, Mariani et al., 2022b); this dataset is being used to improve our understanding of synoptic and fine-scale meteorological processes in the Arctic and sub-Arctic, including HIW detection and prediction and NWP verification, assimilation, and processes.
Keywords: Arctique

Simulation of Arctic Thin Ice Clouds with Canadian Regional Climate Model Version 6: Verification against CloudSat-CALIPSO - Sankaré, Housseyni; Blanchet, Jean-Pierre; Laprise, René; O’Neill, Norman T. (Atmosphere, 2022)
Polar clouds are, as a consequence of the paucity of in situ observations, poorly understood compared to their lower latitude analogs, yet highly climate-sensitive through thermal radiation emission. The prevalence of Thin Ice Clouds (TIC) dominates in cold Polar Regions and the Upper Troposphere Lower Stratosphere (UTLS) altitudes. They can be grouped into 2 broad categories. The first thin ice cloud type (TIC1) is made up of high concentrations of small, non-precipitating ice crystals. The second type (TIC2) is composed of relatively small concentrations of larger, precipitating ice crystals. In this study, we investigate the ability of a developmental version of the Canadian Regional Climate Model (CRCM6) in simulating cold polar-night clouds over the Arctic Ocean, a remote region that is critical to atmospheric circulation reaching out to the mid-latitudes. The results show that, relative to CloudSat-CALIPSO vertical profile products, CRCM6 simulates high-latitude and low spatial frequency variations of Ice Water Content (IWC), effective radius (re) and cooling rates reasonably well with only small to moderate wet and dry biases. The model can also simulate cloud type, location, and temporal occurrence effectively. As well, it successfully simulated higher altitude TIC1 clouds whose small size evaded CloudSat detection while being visible to CALIPSO.
Keywords: Arctique; Atmosphère

CNT Parameterization Based on the Observed INP Concentration during Arctic Summer Campaigns in a Marine Environment - Cirisan, Ana; Girard, Eric; Blanchet, Jean-Pierre; Keita, Setigui Aboubacar; Gong, Wanmin; Irish, Vickie; Bertram, Allan K. (Atmosphere, 2020)
Aerosol–cloud interactions present a large source of uncertainties in atmospheric and climate models. One of the main challenges to simulate ice clouds is to reproduce the right ice nucleating particle concentration. In this study, we derive a parameterization for immersion freezing according to the classical nucleation theory. Our objective was to constrain this parameterization with observations taken over the Canadian Arctic during the Amundsen summer 2014 and 2016 campaigns. We found a linear dependence of contact angle and temperature. Using this approach, we were able to reproduce the scatter in ice nucleated particle concentrations within a factor 5 of observed values with a small negative bias. This parameterization would be easy to implement in climate and atmospheric models, but its representativeness has to first be validated against other datasets.
Keywords: Arctique