Improved Weather Generator Algorithm for Multisite Simulation of Precipitation and Temperature - King, Leanna M.; McLeod, A. Ian; Simonovic, Slobodan P. (Journal of The American Water Resources Association, 2015)
The KnnCAD Version 4 weather generator algorithm for nonparametric, multisite simulations of temperature and precipitation data is presented. The K-nearest neighbor weather generator essentially reshuffles the historical data, with replacement. In KnnCAD Version 4, a block resampling scheme is introduced to preserve the temporal correlation structure in temperature data. Perturbation of the reshuffled variable data is also added to enhance the generation of extreme values. The Upper Thames River Basin in Ontario, Canada isused as a case study and the model is shown to simulate effectively the historical characteristics at the site. The KnnCAD Version 4 approach is shown to improve on the previous versions of the model and offers a major advantage over many parametric and semiparametric weather generators in that multisite use can be easily achieved without making statistical assumptions dealing with the spatial correlations and probability distributions of each variable.

Quantification of uncertainty in the assessment of future streamflow under changing climate conditions - Mandal, Sohom; Simonovic, Slobodan P. (Hydrological Processes, 2017)
Climate change has a significant influence on streamflow variation. The aim of this study is to quantify different sources of uncertainties in future streamflow projections due to climate change. For this purpose, 4 global climate models, 3 greenhouse gas emission scenarios (representative concentration pathways), 6 downscaling models, and a hydrologic model (UBCWM) are used. The assessment work is conducted for 2 different future time periods (2036 to 2065 and 2066 to 2095). Generalized extreme value distribution is used for the analysis of the flow frequency. Strathcona dam in the Campbell River basin, British Columbia, Canada, is used as a case study. The results show that the downscaling models contribute the highest amount of uncertainty to future streamflow predictions when compared to the contributions by global climate models or representative concentration pathways. It is also observed that the summer flows into Strathcona dam will decrease, and winter flows will increase in both future time periods. In addition to these, the flow magnitude becomes more uncertain for higher return periods in the Campbell River system under climate change.

A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models - Quilty, John; Adamowski, Jan; Boucher, Marie‐Amélie (Water Resources Research, 2019)
Abstract In water resources applications (e.g., streamflow, rainfall‐runoff, urban water demand [UWD], etc.), ensemble member selection and ensemble member weighting are two difficult yet important tasks in the development of ensemble forecasting systems. We propose and test a stochastic data‐driven ensemble forecasting framework that uses archived deterministic forecasts as input and results in probabilistic water resources forecasts. In addition to input data and (ensemble) model output uncertainty, the proposed approach integrates both ensemble member selection and weighting uncertainties, using input variable selection and data‐driven methods, respectively. Therefore, it does not require one to perform ensemble member selection and weighting separately. We applied the proposed forecasting framework to a previous real‐world case study in Montreal, Canada, to forecast daily UWD at multiple lead times. Using wavelet‐based forecasts as input data, we develop the Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, the first multiwavelet ensemble stochastic forecasting framework that produces probabilistic forecasts. For the considered case study, several variants of Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, produced using different input variable selection methods (partial correlation input selection and Edgeworth Approximations‐based conditional mutual information) and data‐driven models (multiple linear regression, extreme learning machines, and second‐order Volterra series models), are shown to outperform wavelet‐ and nonwavelet‐based benchmarks, especially during a heat wave (first time studied in the UWD forecasting literature). , Key Points A stochastic data‐driven ensemble framework is introduced for probabilistic water resources forecasting Ensemble member selection and weighting uncertainties are explicitly considered alongside input data and model output uncertainties Wavelet‐based model outputs are used as input to the framework for an urban water demand forecasting study outperforming benchmark methods

Human influence on Canadian temperatures - Wan, Hui; Zhang, Xuebin; Zwiers, Francis W. (Climate Dynamics, 2019)
Canada has experienced some of the most rapid warming on Earth over the past few decades with a warming rate about twice that of the global mean temperature since 1948. Long-term warming is observed in Canada’s annual, winter and summer mean temperatures, and in the annual coldest and hottest daytime and nighttime temperatures. The causes of these changes are assessed by comparing observed changes with climate model simulated responses to anthropogenic and natural (solar and volcanic) external forcings. Most of the observed warming of 1.7°C increase in annual mean temperature during 1948–2012 [90% confidence interval (1.1°, 2.2°C)] can only be explained by external forcing on the climate system, with anthropogenic influence being the dominant factor. It is estimated that anthropogenic forcing has contributed 1.0°C (0.6°, 1.5°C) and natural external forcing has contributed 0.2°C (0.1°, 0.3°C) to the observed warming. Up to 0.5°C of the observed warming trend may be associated with low frequency variability of the climate such as that represented by the Pacific decadal oscillation (PDO) and North Atlantic oscillation (NAO). Overall, the influence of both anthropogenic and natural external forcing is clearly evident in Canada-wide mean and extreme temperatures, and can also be detected regionally over much of the country.

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America - Diro, G. T.; Sushama, Laxmi; Huziy, O. (Climate Dynamics, 2018)
The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981–2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40–60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas - Diaconescu, Emilia Paula; Mailhot, Alain; Brown, Ross; Chaumont, Diane (Climate Dynamics, 2018)
This study focuses on the evaluation of daily precipitation and temperature climate indices and extremes simulated by an ensemble of 12 Regional Climate Model (RCM) simulations from the ARCTIC-CORDEX experiment with surface observations in the Canadian Arctic from the Adjusted Historical Canadian Climate Dataset. Five global reanalyses products (ERA-Interim, JRA55, MERRA, CFSR and GMFD) are also included in the evaluation to assess their potential for RCM evaluation in data sparse regions. The study evaluated the means and annual anomaly distributions of indices over the 1980–2004 dataset overlap period. The results showed that RCM and reanalysis performance varied with the climate variables being evaluated. Most RCMs and reanalyses were able to simulate well climate indices related to mean air temperature and hot extremes over most of the Canadian Arctic, with the exception of the Yukon region where models displayed the largest biases related to topographic effects. Overall performance was generally poor for indices related to cold extremes. Likewise, only a few RCM simulations and reanalyses were able to provide realistic simulations of precipitation extreme indicators. The multi-reanalysis ensemble provided superior results to individual datasets for climate indicators related to mean air temperature and hot extremes, but not for other indicators. These results support the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices.

The Role of Soil Moisture–Atmosphere Interaction on Future Hot Spells over North America as Simulated by the Canadian Regional Climate Model (CRCM5) - Diro, G. T.; Sushama, Laxmi (Journal of Climate, 2017)
AbstractSoil moisture–atmosphere interactions play a key role in modulating climate variability and extremes. This study investigates how soil moisture–atmosphere coupling may affect future extreme events, particularly the role of projected soil moisture in modulating the frequency and maximum duration of hot spells over North America, using the fifth-generation Canadian Regional Climate Model (CRCM5). With this objective, CRCM5 simulations, driven by two coupled general circulation models (MPI-ESM and CanESM2), are performed with and without soil moisture–atmosphere interactions for current (1981–2010) and future (2071–2100) climates over North America, for representative concentration pathways (RCPs) 4.5 and 8.5. Analysis indicates that, in future climate, the soil moisture–temperature coupling regions, located over the Great Plains in the current climate, will expand farther north, including large parts of central Canada. Results also indicate that soil moisture–atmosphere interactions will play an imp...

Influence of instrumentation on long temperature time series - Acquaotta, Fiorella; Fratianni, Simona; Aguilar, Enric; Fortin, Guillaume (Climatic Change, 2019)
In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspe Peninsula, a region of Canada. They have 6years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+10%) and extremely warm (+35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.

Extremal modeling of dependent and non-stationary series and joint modeling of extreme rainfall at multiple sites - Murphy, Orla A. (McGill University (Canada), 2018)

Development of a methodology to assess future trends in low flows at the watershed scale using solely climate data - Foulon, Étienne; Rousseau, Alain N.; Gagnon, Patrick (Journal of Hydrology, 2018)
Abstract Low flow conditions are governed by short-to-medium term weather conditions or long term climate conditions. This prompts the question: given climate scenarios, is it possible to assess future extreme low flow conditions from climate data indices (CDIs)? Or should we rely on the conventional approach of using outputs of climate models as inputs to a hydrological model? Several CDIs were computed using 42 climate scenarios over the years 1961–2100 for two watersheds located in Quebec, Canada. The relationship between the CDIs and hydrological data indices (HDIs; 7- and 30-day low flows for two hydrological seasons) were examined through correlation analysis to identify the indices governing low flows. Results of the Mann-Kendall test, with a modification for autocorrelated data, clearly identified trends. A partial correlation analysis allowed attributing the observed trends in HDIs to trends in specific CDIs. Furthermore, results showed that, even during the spatial validation process, the methodological framework was able to assess trends in low flow series from: (i) trends in the effective drought index (EDI) computed from rainfall plus snowmelt minus PET amounts over ten to twelve months of the hydrological snow cover season or (ii) the cumulative difference between rainfall and potential evapotranspiration over five months of the snow free season. For 80% of the climate scenarios, trends in HDIs were successfully attributed to trends in CDIs. Overall, this paper introduces an efficient methodological framework to assess future trends in low flows given climate scenarios. The outcome may prove useful to municipalities concerned with source water management under changing climate conditions.
Keywords: Rousseau_Alain

Integrated assessment of climate change impact on surface runoff contamination by pesticides - Gagnon, Patrick; Sheedy, Claudia; Rousseau, Alain N.; Bourgeois, Gaétan; Chouinard, Gérald (Integrated Environmental Assessment and Management, 2016)
Pesticide transport by surface runoff depends on climate, agricultural practices, topography, soil characteristics, crop type, and pest phenology. To accurately assess the impact of climate change, these factors must be accounted for in a single framework by integrating their interaction and uncertainty. This paper presents the development and application of a framework to assess the impact of climate change on pesticide transport by surface runoff in southern Quebec (Canada) for the 1981-2040 period. The crop enemies investigated were: weeds for corn (Zea mays); and for apple orchard (Malus pumila), three insect pests (codling moth (Cydia pomonella), plum curculio (Conotrachelus nenuphar) and apple maggot (Rhagoletis pomonella)) and two diseases (apple scab (Venturia inaequalis) and fire blight (Erwinia amylovora)). A total of 23 climate simulations, 19 sites, and 11 active ingredients were considered. The relationship between climate and phenology was accounted for by bioclimatic models of the Computer Centre for Agricultural Pest Forecasting (CIPRA) software. Exported loads of pesticides were evaluated at the edge-of-field scale using the Pesticide Root Zone Model (PRZM), simulating both hydrology and chemical transport. A stochastic model was developed to account for PRZM parameter uncertainty. Results of this study indicate that for the 2011-2040 period, application dates would be advanced from 3 to 7 days on average with respect to the 1981-2010 period. However, the impact of climate change on maximum daily rainfall during the application window is not statistically significant, mainly due to the high variability of extreme rainfall events. Hence for the studied sites and crop enemies considered, climate change impact on pesticide transported in surface runoff is not statistically significant throughout the 2011-2040 period.
Keywords: Rousseau_Alain

Simulation of aquifer-peatland-river interactions under climate change - Bourgault, M. A.; Larocque, M.; Roy, M. (Hydrology Research, 2014)
Wetlands play an important role in preventing extreme low flows in rivers and groundwater level drawdowns during drought periods. This hydrological function could become increasingly important under a warmer climate. Links between peatlands, aquifers, and rivers remain inadequately understood. The objective of this study was to evaluate the hydrologic functions of the Lanoraie peatland complex in southern Quebec, Canada, under different climate conditions. This peatland complex has developed in the beds of former fluvial channels during the final stages of the last deglaciation. The peatland covers a surface area of ~76 km2 and feeds five rivers. Numerical simulations were performed using a steady-state groundwater flow model. Results show that the peatland contributes on average to 77% of the mean annual river base flow. The peatland receives 52% of its water from the aquifer. Reduced recharge scenarios (−20 and −50% of current conditions) were used as a surrogate of climate change. With these scenarios, the simulated mean head decreases by 0.6 and 1.6 m in the sand. The mean river base flow decreases by 16 and 41% with the two scenarios. These results strongly underline the importance of aquifer-peatland-river interactions at the regional scale. They also point to the necessity of considering the entire hydrosystem in conservation initiatives.
Keywords: Ouvrage_Collectif_Numéro1

Quantitative and qualitative assessment of the impact of climate change on a combined sewer overflow and its receiving water body - Gooré Bi, Eustache; Monette, Frédéric; Gachon, Philippe; Gaspéri, Johnny; Perrodin, Yves (Environmental Science and Pollution Research, 2015)
Projections from the Canadian Regional Climate Model (CRCM) for the southern part of the province of Québec, Canada, suggest an increase in extreme precipitation events for the 2050 horizon (2041–2070). The main goal of this study consisted in a quantitative and qualitative assessment of the impact of the 20 % increase in rainfall intensity that led, in the summer of 2013, to overflows in the “Rolland-Therrien” combined sewer system in the city of Longueuil, Canada. The PCSWMM 2013 model was used to assess the sensitivity of this overflow under current (2013) and future (2050) climate conditions. The simulated quantitative variables (peak flow, QCSO, and volume discharged, VD) served as the basis for deriving ecotoxicological risk indices and event fluxes (EFs) transported to the St. Lawrence (SL) River. Results highlighted 15 to 500 % increases in VD and 13 to 148 % increases in QCSO by 2050 (compared to 2013), based on eight rainfall events measured from May to October. These results show that (i) the relationships between precipitation and combined sewer overflow variables are not linear and (ii) the design criteria for current hydraulic infrastructure must be revised to account for the impact of climate change (CC) arising from changes in precipitation regimes. EFs discharged into the SL River will be 2.24 times larger in the future than they are now (2013) due to large VDs resulting from CC. This will, in turn, lead to excessive inputs of total suspended solids (TSSs) and tracers for numerous urban pollutants (organic matter and nutrients, metals) into the receiving water body. Ecotoxicological risk indices will increase by more than 100 % by 2050 compared to 2013. Given that substantial VDs are at play, and although CC scenarios have many sources of uncertainty, strategies to adapt this drainage network to the effects of CC will have to be developed.
Keywords: Gachon_Philippe

Estimation of large wood budgets in a watershed and river corridor at interdecadal to interannual scales in a cold‐temperate fluvial system - Boivin, Maxime; Buffin‐Bélanger, Thomas; Piégay, Hervé (Earth Surface Processes and Landforms, 2017)
Abstract Large wood (LW) is a ubiquitous feature in rivers of forested watersheds worldwide, and its importance for river diversity has been recognized for several decades. Although the role of LW in fluvial dynamics has been extensively documented, there is a need to better quantify the most significant components of LW budgets at the river scale. The purpose of our study was to quantify each component (input, accumulation, and output) of a LW budget at the reach and watershed scales for different time periods (i.e. a 50‐year period, decadal cycle, and interannual cycle). The LW budget was quantified by measuring the volumes of LW inputs, accumulations, and outputs within river sections that were finally evacuated from the watershed. The study site included three unusually large but natural wood rafts in the delta of the Saint‐Jean River (SJR; Québec, Canada) that have accumulated all LW exported from the watershed for the last 50 years. We observed an increase in fluvial dynamics since 2004, which led to larger LW recruitment and a greater LW volume trapped in the river corridor, suggesting that the system is not in equilibrium in terms of the wood budget but is rather recovering from previous human pressures as well as adjusting to hydroclimatic changes. The results reveal the large variability in the LW budget dynamics during the 50‐year period and allow us to examine the eco‐hydromorphological trajectory that highlights key variables (discharge, erosion rates, bar surface area, sinuosity, wood mobility, and wood retention). Knowledge on the dynamics of these variables improves our understanding of the historical and future trajectories of LW dynamics and fluvial dynamics in gravel‐bed rivers. Extreme events (flood and ice‐melt) significantly contribute to LW dynamics in the SJR river system. Copyright © 2017 John Wiley & Sons, Ltd.
Keywords: Boivin_Maxime

Changes to flood peaks of a mountain river: implications for analysis of the 2013 flood in the Upper Bow River, Canada - Whitfield, Paul H.; Pomeroy, John W. (Hydrological Processes, 2016)
The mountain headwater Bow River at Banff, Alberta, Canada was subject to a large flood in June 2013, over which considerable debate has ensued regarding its probability of occurrence. It is therefore instructive to consider what information long term streamflow discharge records provide about environmental change in the Upper Bow River basin above Banff. Though protected as part of Banff National Park, since 1885, the basin has experienced considerable climate and land cover changes, each of which has the potential to impact observations, and hence the interpretations of flood probability. The Bow River at Banff hydrometric station is one of Canada's longest operating reference hydrological basin network stations and so has great value for assessing changes in flow regime over time. Furthermore, the station measures a river that provides an extremely important water supply for Calgary and irrigation district downstream and so is of great interest for assessing regional water security. These records were examined for changes in several flood attributes and to determine whether flow changes may have been related to landscape change within the basin as caused by forest fires, conversion from grasslands to forest with fire suppression, and regional climate variations and/or trends. Floods in the Upper Bow River are generated by both snowmelt and rain-on-snow (ROS) events, the latter type which include floods events generated by spatially and temporally large storms such as occurred in 2013. The two types of floods also have different frequency characteristics. Snowmelt and ROS flood attributes were not correlated significantly with any climate index or with burned area except that snowmelt event duration correlated negatively to the Pacific Decadal Oscillation. While there is a significant negative trend in all floods over the past 100years, when separated based on generating process, neither snowmelt floods nor large ROS floods associated with mesoscale storms show any trends over time. Despite extensive changes to the landscape of the basin and in within the climate system, the flood regime remains unchanged, something identified at smaller scales in the region but never at larger scales.

Historical Spatial and Temporal Climate Trends in Southern Ontario, Canada - Wazneh, Hussein; Arain, M. Altaf; Coulibaly, Paulin (Journal of Applied Meteorology and Climatology, 2017)
Abstract Spatial and temporal trends in historical temperature and precipitation extreme events were evaluated for southern Ontario, Canada. A number of climate indices were computed using observed and regional and global climate datasets for the area of study over the 1951–2013 period. A decrease in the frequency of cold temperature extremes and an increase in the frequency of warm temperature extremes was observed in the region. Overall, the numbers of extremely cold days decreased and hot nights increased. Nighttime warming was greater than daytime warming. The annual total precipitation and the frequency of extreme precipitation also increased. Spatially, for the precipitation indices, no significant trends were observed for annual total precipitation and extremely wet days in the southwest and the central part of Ontario. For temperature indices, cool days and warm night have significant trends in more than 90% of the study area. In general, the spatial variability of precipitation indices is much higher than that of temperature indices. In terms of comparisons between observed and simulated data, results showed large differences for both temperature and precipitation indices. For this region, the regional climate model was able to reproduce historical observed trends in climate indices very well as compared with global climate models. The statistical bias-correction method generally improved the ability of the global climate models to accurately simulate observed trends in climate indices.

Nonlinear response of precipitation to climate indices using a non-stationary Poisson-generalized Pareto model: case study of southeastern Canada. - Thiombiano, Alida Nadège; St-Hilaire, André; Adlouni, Salaheddine El; Ouarda, Taha B. M. J. (International Journal of Climatology, 2018)
Quantile estimates are generally interpreted in association with the return period concept in practical engineering. To do so with the peaks‐over‐threshold (POT) approach, combined Poisson‐generalized Pareto distributions (referred to as PD‐GPD model) must be considered. In this article, we evaluate the incorporation of non‐stationarity in the generalized Pareto distribution (GPD) and the Poisson distribution (PD) using, respectively, the smoothing‐based B‐spline functions and the logarithmic link function. Two models are proposed, a stationary PD combined to a non‐stationary GPD (referred to as PD0‐GPD1) and a combined non‐stationary PD and GPD (referred to as PD1‐GPD1). The teleconnections between hydro‐climatological variables and a number of large‐scale climate patterns allow using these climate indices as covariates in the development of non‐stationary extreme value models. The case study is made with daily precipitation amount time series from southeastern Canada and two climatic covariates, the Arctic Oscillation (AO) and the Pacific North American (PNA) indices. A comparison of PD0‐GPD1 and PD1‐GPD1 models showed that the incorporation of non‐stationarity in both POT models instead of solely in the GPD has an effect on the estimated quantiles. The use of the B‐spline function as link function between the GPD parameters and the considered climatic covariates provided flexible non‐stationary PD‐GPD models. Indeed, linear and nonlinear conditional quantiles are observed at various stations in the case study, opening an interesting perspective for further research on the physical mechanism behind these simple and complex interactions.

Sensitivity of seasonal precipitation extremes to model configuration of the Canadian Regional Climate Model over eastern Canada using historical simulations - Roy, Philippe; Gachon, Philippe; Laprise, René (Climate Dynamics, 2014)
This study analyzes the uncertainty of seasonal (winter and summer) precipitation extremes as simulated by a recent version of the Canadian Regional Climate Model (CRCM) using 16 simulations (1961–1990), considering four sources of uncertainty from: (a) the domain size, (b) the driving Atmosphere–Ocean Global Climate Models (AOGCM), (c) the ensemble member for a given AOGCM and (d) the internal variability of the CRCM. These 16 simulations are driven by 2 AOGCMs (i.e. CGCM3, members 4 and 5, and ECHAM5, members 1 and 2), and one set of re-analysis products (i.e. ERA40), using two domain sizes (AMNO, covering all North America and QC, a smaller domain centred over the Province of Québec). In addition to the mean seasonal precipitation, three seasonal indices are used to characterize different types of variability and extremes of precipitation: the number of wet days, the maximum number of consecutive dry days, and the 95th percentile of daily precipitation. Results show that largest source of uncertainty in summer comes from the AOGCM selection and the choice of domain size, followed by the choice of the member for a given AOGCM. In winter, the choice of the member becomes more important than the choice of the domain size. Simulated variance sensitivity is greater in winter than in summer, highlighting the importance of the large-scale circulation from the boundary conditions. The study confirms a higher uncertainty in the simulated heavy rainfall than the one in the mean precipitation, with some regions along the Great Lakes—St-Lawrence Valley exhibiting a systematic higher uncertainty value.
Keywords: Gachon_Philippe

Comparison of the temporal variability of winter daily extreme temperatures and precipitations in southern Quebec (Canada) using the Lombard and copula methods - Guerfi, Nadjet; Assani, Ali A.; Mesfioui, Mhamed; Kinnard, Christophe (International Journal of Climatology, 2015)
Although numerous studies have looked at the long-term trend of the temporal variability of winter temperature and precipitation in southern Quebec, no study has focused on the shifts in series means and the dependence between these two types of climate variables associated with this long-term trend. To fill these gaps, we used the Lombard method to detect the shifts in mean values and the copula method to detect any change in dependence between extreme (maximum and minimum) temperatures and precipitation (snow and rain) over the periods 1950–2000 (17 stations) and 1950–2010 (7 stations). During these two periods, the shifts in mean values of temperature and precipitation were recorded at less than half of the stations. The only significant change observed at the provincial scale is a decrease in the amount of snowfall, which occurred in many cases during the 1970s. This decrease affected stations on the north shore (continental temperate climate) more strongly than stations on the south shore (maritime temperate climate) of the St Lawrence River. However, this decrease in the amount of snowfall had no impact on the dependence over time between temperature and precipitation as snow.
Keywords: Kinnard_Christophe

Projected changes in the dynamics of flood hazard in the Grand River Basin, Canada. - Gaur, Abhishek; Simonovic, Slobodan P. (British Journal of Environment and Climate Change, 2015)
In this study future flooding frequencies have been estimated for the Grand River catchment located in south - western Ontario, Canada. Historical and future climatic projections made by fifteen Coupled Model Inter - comparison Project - 3 climate models are bias - corrected and downscaled before they are used to obtain mid - and end of 21 st century streamflow projections. By comparing the future projected and historically observed precipitation and temperature record s it is found that the mean and extreme temperature events will intensify in future across the catchment. The increase is more drastic in the case of extreme events than the mean events. The sign of change in future precipitation is uncertain. Further flow extremes are expected to increase in magnitude and frequency in future across the catchment. The confidence in the projection is more for low return period (<10 years) extreme events than higher return period (10 - 100 years) events. It can be expected that increases in temperature will play a dominant role in increasing the magnitude of low return period flooding events while precipitation seems to play an important role in shaping the high return period events.

Guide to identifying alert thresholds for heat waves in Canada based on evidence - Gachon, P.; Bussières, Louise; Gosselin, P.; Raphoz, M.; Bustinza, R.; Martin, Philippe H.; Dueymes, G.; Gosselin, Denis; Labrecque, Sylvain; Jeffers, S.; Yagouti, Abderrahmane (2016)
Among natural-disaster risks, heat waves are responsible for a large number of deaths, diseases and economic losses around the world. As they will increase in severity, duration and frequency over the decades to come within the context of climate change, these extreme events constitute a genuine danger to human health, and heat-warning systems are strongly recommended by public health authorities to reduce this risk of diseases and of excessive mortality and morbidity. Thus, evidence-based public alerting criteria are needed to reduce impacts on human health before and during persistent hot weather conditions. The goal of this guide is to identify alert thresholds for heat waves in Canada based on evidence, and to propose an approach for better defining heat waves in the Canadian context in order to reduce the risks to human health and contribute to the well-being of Canadians. This guide is the result of the collaboration among various research and public institutions working on: 1) meteorological and climate aspects, i.e. the Meteorological Service of Canada (MSC, Environment and Climate Change Canada), and the ESCER centre at the Universite du Quebec a Montreal, and 2) public health, i.e. Health Canada and the Institut National de Sante Publique du Quebec.
Keywords: Gachon_Philippe

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada - Eum, Hyung-Il; Gachon, Philippe; Laprise, René (Advances in Meteorology, 2016)
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.
Keywords: Gachon_Philippe

Extreme weather events in northeastern New Brunswick (Canada) for the period 1950–2012: Comparison of newspaper archive and weather station data - Mallet, Julie; Fortin, Guillaume; Germain, Daniel (Canadian Geographer, 2018)
In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co-occurring non-extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost-free days and extreme cold days was also found, in addition to a decline in the number of dry days.

Les impacts des changements climatiques sur la santé au Québec : l’exemple de l’Estrie - Petit, Geneviève; Lachance, Éric; Généreux, Mélissa; Barbeau-Meunier, Charles-Antoine; Pinsonneault, Linda; Dao, Huy Hao; Milot, Marie-Christine; Baron, Geneviève; Carignan, Alex (Université de Sherbrooke, 2019)
L’Organisation mondiale de la Santé (OMS) soutient que les changements climatiques représentent la plus grande menace pour la santé dans le monde au 21e siècle. Ceux-ci influencent négativement plusieurs déterminants sociaux et environnementaux de la santé comme l’accessibilité à la nourriture et la qualité de cette dernière, l’eau et l’air. Blessures, impacts psychosociaux, aggravation de maladies respiratoires, malnutrition, maladies infectieuses, décès : les conséquences sanitaires sont susceptibles d’affecter les populations sur tous les continents. Le Canada se réchauffe deux fois plus rapidement que la moyenne mondiale en raison de sa proximité au pôle Arctique, où le réchauffement est accéléré comparativement à l’équateur (Bush et Lemmen, 2019). Ainsi, le Québec n’est certainement pas à l’abri des changements climatiques. Dans le Sud de la province, les températures moyennes observées ont augmenté de plus d’un degré depuis 1970 et des répercussions se font déjà sentir dans notre environnement. Ce réchauffement, accompagné d’une plus grande variabilité du climat (augmentation du risque d’orages, de tempêtes et d’extrêmes hydrométéorologiques en général), représente un défi grandissant pour les professionnel.le.s de la santé. Dans la région de l’Estrie, les professionnel.le.s de santé publique ont effectué une analyse qui leur ont permis d’identifier quatre principaux problèmes environnementaux associés aux changements climatiques, soit : les vagues de chaleur; les inondations; les tiques à pattes noires; le pollen de l’herbe à poux. Ces problèmes ont des impacts importants sur la santé, c’est-à-dire potentiellement graves ou qui touchent un grand nombre de personnes. Le stress et les pertes (humaines et matérielles) engendrées par ces différents problèmes environnementaux peuvent aussi représenter une source majeure de problèmes psychologiques significatifs pouvant persister dans le temps. De plus, ces impacts sont variables selon les différents contextes sociaux des individus et des communautés, générant des inégalités sociales de santé.
Keywords: Généreux_Mélissa