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This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. These results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

Abstract River ice breakup has extensive implications on cold-region hydrological, ecological and river morphological systems. However, spatial and temporal breakup patterns under the changing climate are not well explored on large scale. This study discusses the spatial-temporal variations of breakup timing over terrestrial ecozones and five selected river basins of Canada based on long-term (1950–2016) data record. The link between the discovered patterns and climatic drivers (including air temperature, snowfall and rainfall), as well as elevation and anthropogenic activities are analyzed. An overall earlier breakup trend is observed across Canada and the spring air temperature is found to be the main driver behind it. However, the most pronounced warming trends across Canada is observed in winter. Spring warming trend is not as strong as winter warming and even becomes weak as period changes from 1950–2016 to 1970–2016, resulting in more stations showing later and significant later breakup during 1970–2016. Breakup pattern also displays evident spatial differences. Significant earlier breakup trends are mainly seen in western Canada (e.g. the Nelson River basin) and Arctic where spring warming trends are evident. Later and mixed breakup trends are generally identified in regions with weak warming or even cooling trends, such as Atlantic Canada and the St. Lawrence River basin. Spring snowfall generally delays breakup. Spring rainfall usually advances breakup dates while winter-rainfall can also delay breakup through refreezing. The increased snowfall in the north and increased rainfall in the south may be the reason why breakup timing is more sensitive to climatic warming in lower latitude regions than in higher latitude regions. Additionally, breakup timing in main streams and large rivers appears to be less sensitive to the warming trend than the headwaters and small tributaries. Elevation and flow regulation are also found to be contributing factors to the changes in breakup timing.

En marge de la Cinquième Plateforme régionale pour la Réduction des risques de catastrophes des Amériques (PRA), le gouvernement du Canada a approché l’Institut des sciences de l’environnement(ISE) de l’Université du Québec à Montréal(UQAM) afin d’organiser un forum public. Les échanges de ce dernier devaient servir à alimenter les discussions de la PRA. Au total, 21 experts ont discuté avec une centaine de participants lors de panels organisés à l’UQAM sous les thèmes de la santé, de la sécurité civile et de l’aménagement du territoire. Plusieurs thèmes transversaux ont aussi émergé tout au long du forum. Il importe de pérenniser le rôle de la recherche et d’améliorer les capacités de formation technique et universitaire afin de former des spécialistes en mesure d’appréhender la complexité de la gestion du risque dans un contexte de changements environnementaux et climatiques. Ceci est également essentiel pour l’identification des facteurs de risque (multisources ou multidimensionnels), pour tirer des leçons apprises des événements majeurs passés et récents, et pour développer ou mettre à jour la connaissance sur les tendances en cours et à venir des aléas météorologiques, ainsi que des facteurs de vulnérabilité et d’exposition. Tous les panels ont discuté de l’importance de favoriser le décloisonnement intra/interorganisationnel pour promouvoir la transsectorialité et les retours d’expériences systématiques. Pour ce faire, il faut s’inspirer des modèles internationaux, notamment du système d’alertes hydrométéorologiques présenté par Météo-France. Celui-ci inclut une vigilance météorologique qui cible des populations et des autorités publiques, et les informe des comportements et des règles à suivre lors d’alertes plus problématiques (vigilance aux stades orange et rouge). Finalement, l’amélioration de la communication et le libre accès à l’information sont des éléments essentiels pour protéger les individus et développer une société plus résiliente.

Semantic Scholar extracted view of "CLIMATE VARIABILITY AND CHANGE IN CANADA" by E. Barrow et al.

Snowmelt dominated regions are receiving increasing attention due to their noticeably rapid response to ongoing climate change, which raises concerns about the altered hydrological risks under climate change scenarios. This study aims to assess the climate change impacts on hydrology over two contrasted catchments in southern Québec: Acadie River and Montmorency River catchments. These river catchments represent two predominant landscapes of the St. Lawrence River watershed; an intensive farming landscape in the south shore lowlands and the forested landscape on the Canadian Shield on the north shore, respectively. In this study, a physically based hydrological model has been developed using the Cold Regions Hydrological Model (CRHM) for both of the catchments. The hydrological model outputs showed that we were able to simulate snow surveys and discharge measurements with a reasonable accuracy for both catchments. The acceptable performance of the model along with the strong physical basis of structure suggested that this model could be used for climate change sensitivity simulations. Based on the climate scenarios reviewed, a temperature increase up to 8°C and an increase in total precipitation up to 20% were analysed for both of the catchments. Both catchments were found to be sensitive to climate change, however the degree of sensitivity was found to be catchment specific. Snow processes in the Acadie River catchment were simulated to be more sensitive to warming than in the Montmorency River catchment. In case of 2°C warming, reduction in peak SWE was not be able to be compensated even by increased precipitation scenario. Given that, the Acadie River has already a mixed flow regime, even if 2°C warming is combined with an increase in precipitation, pluvial regime kept becoming more dominant, resulting in higher peaks of rain events. On the other hand, even 3°C of warming did not modify the flow regime of the Montmorency River. While there is shift towards earlier peak spring flows in both catchments, the shift was found to be more pronounced in the Acadie River. An earlier occurrence of snowmelt floods and an overall increase in winter streamflow during winter have been simulated for both catchments, which calls for renewed assessments of existing water supply and flood risk management strategies.

Abstract The objective of this study is to compare the spatiotemporal variability of seasonal daily mean flows measured in 17 watersheds, grouped into three homogeneous hydroclimatic regions, during the period 1930–2023 in southern Quebec. With regard to spatial variability, unlike extreme daily flows, seasonal daily mean flows are very poorly correlated with physiographic factors and land use and land cover. In fall, they are not correlated with any physiographic or climatic factor. In winter, they are positively correlated with the rainfall and winter daily mean maximum temperatures. In spring, they are strongly correlated positively with the snowfall but negatively with the spring daily mean maximum temperatures. However, in summer, they are better correlated with forest area and, to a lesser extent, with the rainfall. As for their temporal variability, the application of six different statistical tests revealed a general increase in daily mean flows in winter due to early snowmelt and increased rainfall in fall. In summer, flows decreased significantly in the snowiest hydroclimatic region on the south shore due to the decrease in the snowfall. In spring, no significant change in flows was globally observed in the three hydroclimatic regions despite the decrease in the snowfall due to the increase in the rainfall. In fall, flows increased significantly south of 47°N on both shores due to the increase in the rainfall. This study demonstrates that, unlike extreme flows, the temporal variability of seasonal daily average flows is exclusively influenced by climatic variables in southern Quebec. Due to this influence, seasonal daily mean flows thus appear to be the best indicator for monitoring the impacts of changes in precipitation regimes and seasonal temperatures on river flows in southern Quebec.

Rivers are sensitive to natural climate change as well as to human impacts such as flow modification and land-use change. Climate change could cause changes to precipitation amounts, the intensity of cyclonic storms, the proportion of precipitation falling as rain, glacier mass balance, and the extent of permafrost; all of which affect the hydrology and morphology of river systems. Changes to the frequency and magnitude of flood flows present the greatest threat. Historically, wetter periods are associated with significantly higher flood frequency and magnitude. These effects are reduced in drainage basins with large lakes or glacier storage. Alluvial rivers with fine-grained sediments are most sensitive, but all rivers will respond, except those flowing through resistant bedrock. The consequences of changes in flow include changes in channel dimensions, gradient, channel pattern, sedimentation, bank erosion rates, and channel migration rates. The most sensitive and vulnerable regions are in southern Canada, particularly those regions at risk of substantial increases in rainfall intensity and duration. In northern rivers, thawing of permafrost and changes to river-ice conditions are important concerns. The type and magnitude of effects will be different between regions, as well as between small and large river basins. Time scales of change will range from years to centuries. These changes will affect the use that we make of rivers and their floodplains, and may require mitigative measures. Radical change is also possible. Climatic impacts will be ubiquitous and will be in addition to existing and future direct human impact on streamflow and rivers.

This paper presents an integrated assessment model for use with climate policy decision making in Canada. The feedback based integrated assessment model ANEMI_CDN represents Canada within the global society-biosphere-climate-economy-energy system. The model uses a system dynamics simulation approach to investigate the impacts of climate change in Canada and policy options for adapting to changing global conditions. The disaggregation techniques allow ANEMI_CDN to show results with various temporal resolutions. Two Canadian policy scenarios are presented as illustrative examples to map policy impacts on key model variables, including population, water-stress, food production, energy consumption, and emissions under changing climate over this century. The main finding is a significant impact of a carbon tax on energy consumption. Two policy scenario simulations provide additional insights to policy makers regarding the choice of adaptation/mitigation options along with their implementation time.

The effects of wetlands on stream flows are well established, namely mitigating flow regimes through water storage and slow water release. However, their effectiveness in reducing flood peaks and sustaining low flows is mainly driven by climate conditions and wetland type with respect to their connectivity to the hydrographic network (i.e. isolated or riparian wetlands). While some studies have demonstrated these hydrological functions/services, few of them have focused on the benefits to the hydrological regimes and their evolution under climate change (CC) and, thus, some gaps persist. The objective of this study was to further advance our knowledge with that respect. The PHYSITEL/HYDROTEL modelling platform was used to assess current and future states of watershed hydrology of the Becancour and Yamaska watersheds, Quebec, Canada. Simulation results showed that CC will induce similar changes on mean seasonal flows, namely larger and earlier spring flows leading to decreases in summer and fall flows. These expected changes will have different effects on 20-year and 100-year peak flows with respect to the considered watershed. Nevertheless, conservation of current wetland states should: (i) for the Becancour watershed, mitigate the potential increase in 2-year, 20-year and 100-year peak flows; and (ii) for the Yamaska watershed, accentuate the potential decrease in the aforementioned indicators. However, any loss of existing wetlands would be detrimental for 7-day 2-year and 10-year as well as 30-day 5-year low flows.

Abstract The estimation of the Intensity–Duration–Frequency (IDF) relation is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change conditions. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4).