Reconstruction of the Spring 2011 Richelieu River Flood by Two Regional Climate Models and a Hydrological Model - Lucas-Picher, Philippe; Riboust, Philippe; Somot, Samuel; Laprise, René (Journal of Hydrometeorology, 2015)
Abstract Climate simulations made with two regional climate models (RCMs), the French Aire Limitée Adaptation Dynamique Développement International (ALADIN) and the Canadian Regional Climate Model, version 5 (CRCM5), operating on 10-km meshes for the period 1989–2011, and the Hydro-Québec hydrological model (HSAMI), are used to reconstruct the spring 2011 Richelieu River flood in the southern region of the province of Québec, Canada. The analysis shows that the simulated fields of 2-m air temperature, precipitation, and snow water equivalent by the RCMs closely match the observations with similar multiyear means and a high correlation of the monthly anomalies. The climatic conditions responsible for the 2011 flood are generally well simulated by the RCMs. The use of multidecadal RCM simulations facilitates the identification of anomalies that contributed to the flood. The flood was linked to a combination of factors: the 2010/11 winter was cold and snowy, the snowmelt in spring was fast, and there was a record amount of precipitation in April and May. Driven by outputs from the RCMs, HSAMI was able to reproduce the mean hydrograph of the Richelieu River, but it underestimated the peak of the 2011 flood. HSAMI adequately computes the water transport from the mountains to the river mouth and the storage effect of Lake Champlain, which dampens the flood over a long period. Overall, the results suggest that RCM simulations can be useful for reconstructing high-resolution climate information and providing new variables that can help better understand the causes of extreme climatic events.

Evidence of added value in North American regional climate model hindcast simulations using ever-increasing horizontal resolutions - Lucas-Picher, Philippe; Laprise, René; Winger, Katja (Climate Dynamics, 2017)

Impacts of combining reanalyses and weather station data on the accuracy of discharge modelling - Essou, Gilles R.C.; Brissette, François; Lucas-Picher, Philippe (Journal of Hydrology, 2017)

Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology - Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe (Climate Dynamics, 2016)

Assessing the limits of bias‐correcting climate model outputs for climate change impact studies - Chen, Jie; Brissette, François P.; Lucas‐Picher, Philippe (Journal of Geophysical Research: Atmospheres, 2015)
Abstract Bias correction of climate model outputs has emerged as a standard procedure in most recent climate change impact studies. A crucial assumption of all bias correction approaches is that climate model biases are constant over time. The validity of this assumption has important implications for impact studies and needs to be verified to properly address uncertainty in future climate projections. Using 10 climate model simulations, this study specifically tests the bias stationarity of climate model outputs over Canada and the contiguous United States (U.S.) by comparing model outputs with corresponding observations over two 20 year historical periods (1961–1980 and 1981–2000). The results show that precipitation biases are clearly nonstationary over much of Canada and the contiguous U.S. and where they vary over much shorter time scales than those normally considered in climate change impact studies. In particular, the difference in biases over two very close periods of the recent past are, in fact, comparable to the climate change signal between future (2061–2080) and historical (1961–1980) periods for precipitation over large parts of Canada and the contiguous U.S., indicating that the uncertainty of future impacts may have been underestimated in most impact studies. In comparison, temperature bias can be considered to be approximately stationary for most of Canada and the contiguous U.S. when compared with the magnitude of the climate change signal. Given the reality that precipitation is usually considered to be more important than temperature for many impact studies, it is advisable that natural climate variability and climate model sensitivity be better emphasized in future impact studies. , Key Points Climate model biases are nonstationary over much of North America The difference in biases is comparable to the climate change signal The uncertainty of impacts may have been underestimated in most impact studies

The Use of Reanalyses and Gridded Observations as Weather Input Data for a Hydrological Model: Comparison of Performances of Simulated River Flows Based on the Density of Weather Stations - Essou, Gilles R. C.; Brissette, François; Lucas-Picher, Philippe (Journal of Hydrometeorology, 2017)
Abstract Precipitation forcing is critical for hydrological modeling as it has a strong impact on the accuracy of simulated river flows. In general, precipitation data used in hydrological modeling are provided by weather stations. However, in regions with sparse weather station coverage, the spatial interpolation of the individual weather stations provides a rough approximation of the real precipitation fields. In such regions, precipitation from interpolated weather stations is generally considered unreliable for hydrological modeling. Precipitation estimates from reanalyses could represent an interesting alternative in regions where the weather station density is low. This article compares the performances of river flows simulated by a watershed model using precipitation and temperature estimates from reanalyses and gridded observations. The comparison was carried out based on the density of surface weather stations for 316 Canadian watersheds located in three climatic regions. Three state-of-the-art atmospheric reanalyses—ERA-Interim, CFSR, and MERRA—and one gridded observations database over Canada—Natural Resources Canada (NRCan)—were used. Results showed that the Nash–Sutcliffe values of simulated river flows using precipitation and temperature data from CFSR and NRCan were generally equivalent regardless of the weather station density. ERA-Interim and MERRA performed significantly better than NRCan for watersheds with weather station densities of less than 1 station per 1000 km2 in the mountainous region. Overall, these results indicate that for hydrological modeling in regions with high spatial variability of precipitation such as mountainous regions, reanalyses perform better than gridded observations when the weather station density is low.

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.

How does large-scale nudging in a regional climate model contribute to improving the simulation of weather regimes and seasonal extremes over North America? - Lucas-Picher, Philippe; Cattiaux, Julien; Bougie, Alexandre; Laprise, René (Climate Dynamics, 2016)

Quantification of the Lateral Boundary Forcing of a Regional Climate Model Using an Aging Tracer - Lucas-Picher, Philippe; Caya, Daniel; Biner, Sébastien; Laprise, René (Monthly Weather Review, 2008)
Abstract The present work introduces a new and useful tool to quantify the lateral boundary forcing of a regional climate model (RCM). This tool, an aging tracer, computes the time the air parcels spend inside the limited-area domain of an RCM. The aging tracers are initialized to zero when the air parcels enter the domain and grow older during their migrations through the domain with each time step in the integration of the model. This technique was employed in a 10-member ensemble of 10-yr (1980–89) simulations with the Canadian RCM on a large domain covering North America. The residency time is treated and archived as the other simulated meteorological variables, therefore allowing computation of its climate diagnostics. These diagnostics show that the domain-averaged residency time is shorter in winter than in summer as a result of the faster winter atmospheric circulation. The residency time decreases with increasing height above the surface because of the faster atmospheric circulation at high levels dominated by the jet stream. Within the domain, the residency time increases from west to east according to the transportation of the aging tracer with the westerly general atmospheric circulation. A linear relation is found between the spatial distribution of the internal variability—computed with the variance between the ensemble members—and residency time. This relation indicates that the residency time can be used as a quantitative indicator to estimate the level of control exerted by the lateral boundary conditions on the RCM simulations.

Impacts of weighting climate models for hydro-meteorological climate change studies - Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel (Journal of Hydrology, 2017)

Dynamical Downscaling with Reinitializations: A Method to Generate Finescale Climate Datasets Suitable for Impact Studies - Lucas-Picher, Philippe; Boberg, Fredrik; Christensen, Jens H.; Berg, Peter (Journal of Hydrometeorology, 2013)
Abstract To retain the sequence of events of a regional climate model (RCM) simulation driven by a reanalysis, a method that has not been widely adopted uses an RCM with frequent reinitializations toward its driving field. In this regard, this study highlights the benefits of an RCM simulation with frequent (daily) reinitializations compared to a standard continuous RCM simulation. Both simulations are carried out with the RCM HIRHAM5, driven with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data, over the 12-km-resolution European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain covering the period 1989–2009. The analysis of daily precipitation shows improvements in the sequence of events and the maintenance of the added value from the standard continuous RCM simulation. The validation of the two RCM simulations with observations reveals that the simulation with reinitializations indeed improves the temporal correlation. Furthermore, the RCM simulation with reinitializations has lower systematic errors compared to the continuous simulation, which has a tendency to be too wet. A comparison of the distribution of wet day precipitation intensities shows similar added value in the continuous and reinitialized simulations with higher variability and extremes compared to the driving field ERA-Interim. Overall, the results suggest that the finescale climate dataset of the RCM simulation with reinitializations better suits the needs of impact studies by providing a sequence of events matching closely the observations, while limiting systematic errors and generating reliable added value. Downsides of the method with reinitializations are increased computational costs and the introduction of temporal discontinuities that are similar to those of a reanalysis.

Investigation of regional climate models’ internal variability with a ten-member ensemble of 10-year simulations over a large domain - Lucas-Picher, Philippe; Caya, Daniel; De Elía, Ramón; Laprise, René (Climate Dynamics, 2008)

Implementation of a large‐scale variable velocity river flow routing algorithm in the Canadian Regional Climate Model (CRCM) - Lucas‐Picher, Philippe; Arora, Vivek K.; Caya, Daniel; Laprise, René (Atmosphere-Ocean, 2003)

On the need for bias correction of regional climate change projections of temperature and precipitation - Christensen, Jens H.; Boberg, Fredrik; Christensen, Ole B.; Lucas‐Picher, Philippe (Geophysical Research Letters, 2008)
Within the framework of the European project ENSEMBLES (ensembles‐based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty‐five percent warmest and wettest months, respectively, we find that a derived second‐order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4–6 °C above present day conditions.

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.

Use of Four Reanalysis Datasets to Assess the Terrestrial Branch of the Water Cycle over Quebec, Canada - Sabarly, Florent; Essou, Gilles; Lucas-Picher, Philippe; Poulin, Annie; Brissette, François (Journal of Hydrometeorology, 2016)
Abstract Reanalyses have the potential to provide meteorological information in areas where few or no traditional observation records are available. The terrestrial branch of the water cycle of CFSR, MERRA, ERA-Interim, and NARR is examined over Quebec, Canada, for the 1979–2008 time period. Precipitation, evaporation, runoff, and water balance are studied using observed precipitation and streamflows, according to three spatial scales: 1) the entire province of Quebec, 2) five regions derived from a climate classification, and 3) 11 river basins. The results reveal that MERRA provides a relatively closed water balance, while a significant residual was found for the other three reanalyses. MERRA and ERA-Interim seem to provide the most reliable precipitation over the province. On the other hand, precipitation from CFSR and NARR do not appear to be particularly reliable, especially over southern Quebec, as they almost systematically showed the highest and the lowest values, respectively. Moreover, the partitioning of precipitation into evaporation and runoff from MERRA and NARR does not agree with what was expected, particularly over southern, central, and eastern Quebec. Despite the weaknesses identified, the ability of reanalyses to reproduce the terrestrial water cycle of the recent past (i.e., 1979–2008) remains globally satisfactory. Nonetheless, their potential to provide reliable information must be validated by comparing reanalyses directly with weather stations, especially in remote areas.

Using Natural Variability as a Baseline to Evaluate the Performance of Bias Correction Methods in Hydrological Climate Change Impact Studies - Chen, Jie; St-Denis, Blaise Gauvin; Brissette, François P.; Lucas-Picher, Philippe (Journal of Hydrometeorology, 2016)
Abstract Postprocessing of climate model outputs is usually performed to remove biases prior to performing climate change impact studies. The evaluation of the performance of bias correction methods is routinely done by comparing postprocessed outputs to observed data. However, such an approach does not take into account the inherent uncertainty linked to natural climate variability and may end up recommending unnecessary complex postprocessing methods. This study evaluates the performance of bias correction methods using natural variability as a baseline. This baseline implies that any bias between model simulations and observations is only significant if it is larger than the natural climate variability. Four bias correction methods are evaluated with respect to reproducing a set of climatic and hydrological statistics. When using natural variability as a baseline, complex bias correction methods still outperform the simplest ones for precipitation and temperature time series, although the differences are much smaller than in all previous studies. However, after driving a hydrological model using the bias-corrected precipitation and temperature, all bias correction methods perform similarly with respect to reproducing 46 hydrological metrics over two watersheds in different climatic zones. The sophisticated distribution mapping correction methods show little advantage over the simplest scaling method. The main conclusion is that simple bias correction methods appear to be just as good as other more complex methods for hydrological climate change impact studies. While sophisticated methods may appear more theoretically sound, this additional complexity appears to be unjustified in hydrological impact studies when taking into account the uncertainty linked to natural climate variability.

Evaluation of the regional climate model ALADIN to simulate the climate over North America in the CORDEX framework - Lucas-Picher, Philippe; Somot, Samuel; Déqué, Michel; Decharme, Bertrand; Alias, Antoinette (Climate Dynamics, 2013)

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.

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)

Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological Modeling? - Essou, Gilles R. C.; Sabarly, Florent; Lucas-Picher, Philippe; Brissette, François; Poulin, Annie (Journal of Hydrometeorology, 2016)
Abstract This paper investigates the potential of reanalyses as proxies of observed surface precipitation and temperature to force hydrological models. Three global atmospheric reanalyses (ERA-Interim, CFSR, and MERRA), one regional reanalysis (NARR), and one global meteorological forcing dataset obtained by bias-correcting ERA-Interim [Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] were compared to one gridded observation database over the contiguous United States. Results showed that all temperature datasets were similar to the gridded observation over most of the United States. On the other hand, precipitation from all three global reanalyses was biased, especially in summer and winter in the southeastern United States. The regional reanalysis precipitation was closer to observations since it indirectly assimilates surface precipitation. The WFDEI dataset was generally less biased than the reanalysis datasets. All datasets were then used to force a global conceptual hydrological model on 370 watersheds of the Model Parameter Estimation Experiment (MOPEX) database. River flows were computed for each watershed, and results showed that the flows simulated using NARR and gridded observations forcings were very similar to the observed flows. The simulated flows forced by the global reanalysis datasets were also similar to the observations, except in the humid continental and subtropical climatic regions, where precipitation seasonality biases degraded river flow simulations. The WFDEI dataset led to better river flows than reanalysis in the humid continental and subtropical climatic regions but was no better than reanalysis—and sometimes worse—in other climatic zones. Overall, the results indicate that global reanalyses have good potential to be used as proxies to observations to force hydrological models, especially in regions with few weather stations.

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

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature - Takhsha, Maryam; Nikiéma, Oumarou; Lucas-Picher, Philippe; Laprise, René; Hernández-Díaz, Leticia; Winger, Katja (Climate Dynamics, 2018)

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.

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)

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.

Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements - Simonsen, Sebastian B.; Stenseng, Lars; Ađalgeirsdóttir, Guðfinna; Fausto, Robert S.; Hvidberg, Christine S.; Lucas-Picher, Philippe (Journal of Glaciology, 2013)
Abstract A method to assess firn compaction using data collected with the Airborne SAR (Synthetic Aperture Radar)/Interferometric Radar Altimeter System (ASIRAS) is developed. For this, we develop a dynamical firn-compaction model that includes meltwater retention. Based on the ASIRAS data, which show internal layers as annual horizons in the uppermost firn, the method relies on inferring the age/ depth (internal layers) information from the radar data using a Monte Carlo inversion technique to tune in parallel both the firn model and the atmospheric forcing parameters (temperature and accumulation). The model is validated against two firn cores, and it is shown that applying both firn densities and age/ depth information for the inversion gives the most accurate understanding of model biases. The method is then applied to a 67 km section of the EGIG line forced by atmospheric output from a regional climate model using only age/depth information in the inversion step. The layers traced by the ASIRAS data are modeled with a root-mean-square error of 9 cm, which is within the estimated error of the layer tracing. This gives us confidence in applying observed annual layering from firn radar data to assess firn compaction; however, the study also indicates that our firn-model-tuning parameters are site-dependent and cannot be parameterized by temperature and accumulation alone.

Very high resolution regional climate model simulations over Greenland: Identifying added value - Lucas‐Picher, Philippe; Wulff‐Nielsen, Maria; Christensen, Jens H.; Aðalgeirsdóttir, Guðfinna; Mottram, Ruth; Simonsen, Sebastian B. (Journal of Geophysical Research: Atmospheres, 2012)
This study presents two simulations of the climate over Greenland with the regional climate model (RCM) HIRHAM5 at 0.05° and 0.25° resolution driven at the lateral boundaries by the ERA‐Interim reanalysis for the period 1989–2009. These simulations are validated against observations from meteorological stations (Danish Meteorological Institute) at the coast and automatic weather stations on the ice sheet (Greenland Climate Network). Generally, the temperature and precipitation biases are small, indicating a realistic simulation of the climate over Greenland that is suitable to drive ice sheet models. However, the bias between the simulations and the few available observations does not reduce with higher resolution. This is partly explained by the lack of observations in regions where the higher resolution is expected to improve the simulated climate. The RCM simulations show that the temperature has increased the most in the northern part of Greenland and at lower elevations over the period 1989–2009. Higher resolution increases the relief variability in the model topography and causes the simulated precipitation to be larger on the coast and smaller over the main ice sheet compared to the lower‐resolution simulation. The higher‐resolution simulation likely represents the Greenlandic climate better, but the lack of observations makes it difficult to validate fully. The detailed temperature and precipitation fields that are generated with the higher resolution are recommended for producing adequate forcing fields for ice sheet models, particularly for their improved simulation of the processes occurring at the steep margins of the ice sheet. , Key Points Validation of regional climate model simulations over Greenland Description of the climate over Greenland Assessment of added value

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.

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

A metrics‐based analysis of seasonal daily precipitation and near‐surface temperature within seven Coordinated Regional Climate Downscaling Experiment domains - Glisan, Justin M.; Jones, Richard; Lennard, Chris; Castillo Pérez, Nadia I.; Lucas‐Picher, Philippe; Rinke, Annette; Solman, Silvina; Gutowski, William J. (Atmospheric Science Letters, 2019)
We compare ensemble mean daily precipitation and near‐surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain‐wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA‐Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root‐mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA‐Interim precipitation is closer to observations than raw ERA‐Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation.

Can Regional Climate Models Represent the Indian Monsoon? - Lucas-Picher, Philippe; Christensen, Jens H.; Saeed, Fahad; Kumar, Pankaj; Asharaf, Shakeel; Ahrens, Bodo; Wiltshire, Andrew J.; Jacob, Daniela; Hagemann, Stefan (Journal of Hydrometeorology, 2011)
Abstract The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach - Kumar, Pankaj; Wiltshire, Andrew; Mathison, Camilla; Asharaf, Shakeel; Ahrens, Bodo; Lucas-Picher, Philippe; Christensen, Jens H.; Gobiet, Andreas; Saeed, Fahad; Hagemann, Stefan; Jacob, Daniela (Science of The Total Environment, 2013)

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.

Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details - Laprise, René; Kornic, Dragana; Rapaić, Maja; Šeparović, Leo; Leduc, Martin; Nikiema, Oumarou; Di Luca, Alejandro; Diaconescu, Emilia; Alexandru, Adelina; Lucas-Picher, Philippe; De Elía, Ramón; Caya, Daniel; et al. (Climate Change, 2012)

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.