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Infrastructure and transportation systems on which northern communities rely are exposed to a variety of climatic hazards over a broad range of scales. Efforts to adapt these systems to the rapidly warming Arctic climate require high-quality climate projections. Here, a state-of-the-art regional climate model is used to perform simulations at 4-km resolution over the eastern and central Canadian Arctic. These include, for the first time over this region, high-resolution climate projections extending to the year 2040. Validation shows that the model adequately simulates base climate variables, as well as variables hazardous to northern engineering and transportation systems, such as degrading permafrost, extreme rainfall, and extreme wind gust. Added value is found over coarser resolution simulations. A novel approach integrating climate model output and machine learning is used for deriving fog—an important, but complex hazard. Hotspots of change to climatic hazards over the next two decades (2021–2040) are identified. These include increases to short-duration rainfall intensity extremes exceeding 50%, suggesting Super–Clausius–Clapeyron scaling. Increases to extreme wind gust pressure are projected to reach 25% over some regions, while widespread increases in active layer thickness and ground temperature are expected. Overall fog frequency is projected to increase by around 10% over most of the study region by 2040, due to increasing frequency of high humidity conditions. Given that these changes are projected to be already underway, urgent action is required to successfully adapt northern transportation and engineering systems located in regions where the magnitude of hazards is projected to increase. [ABSTRACT FROM AUTHOR]

Recent studies indicated that the internal climate variability plays an important role in various aspects of projected climate changes on regional and local scales. Here we present results of the spreads in projected trends of wintertime North American surface air temperature and extremes indices of warm and cold days over the next half-century, by analyzing a 50-member large ensemble of climate simulations conducted with CanESM2. CanESM2 simulations confirm the important role of internal variability in projected surface temperature trends as demonstrated in previous studies. Yet the spread in North American warming trends in CanESM2 is generally smaller than those obtained from CCSM3 and ECHAM5 large ensemble simulations. Despite this, large spreads in the climate means as well as climate change trends of North American temperature extremes are apparent in CanESM2, especially in the projected cold day trends. The ensemble mean of forced climate simulations reveals high risks of warm days over the western coast and northern Canada, as well as a weakening belt of cold days extending from Alaska to the northeast US. The individual ensemble members differ from the ensemble mean mainly in magnitude of the warm day trends, but depart considerably from the ensemble mean in spatial pattern and magnitude of the cold day trends. The signal-to-noise ratio pattern of the warm day trend resembles that of the surface air temperature trend, with stronger signals over northern Canada, Alaska, and the southwestern US than the midsection of the continent. The projected cold day patterns reveal strong signals over the southwestern US, northern Canada, and the northeastern US. In addition, the internally generated components of mean and extreme temperature trends exhibit spatial coherences over North America, and are comparable to their externally forced trends. The large-scale atmospheric circulation-induced temperature variability influences these trends. Overall, our results suggest that climate change trends of North American temperature extremes are likely very uncertain and need to be applied with caution. [ABSTRACT FROM AUTHOR]

Short-duration precipitation extremes are widely used in the design of engineering infrastructure systems and they also lead to high impact flash flood events and landslides. Better understanding of these events in a changing climate is therefore critical. This study assesses characteristics of short-duration precipitation extremes of 1-, 3-, 6- and 12-h durations in terms of the precipitation-temperature (P–T) relationship in current and future climates for ten Canadian climatic regions using the limited area version of the global environment multiscale (GEM) model. The GEM simulations, driven by ERA-Interim reanalysis and two coupled global climate models (CanESM2 and MPI-ESM), reproduce the general observed regional P–T relationship characteristics in current climate (1981–2010), such as sub-CC (Clausius–Clapeyron) and CC scalings for the coastal and northern, and inland regions, respectively, albeit with some underestimation. Analysis of the transient climate change simulations suggests important shifts and/or extensions of the P–T curve to higher temperature bins in future climate (2071–2100) for RCP4.5 and 8.5 scenarios, particularly for 1-h duration. Analysis of the spatial patterns of dew point depression (temperature minus dew point temperature) and convective available potential energy (CAPE) corresponding to short-duration precipitation extremes for different temperature bins show their changing relative importance from low to high temperature bins. For the low-temperature bins, short-duration precipitation extremes are largely due to high relative humidity, while for high-temperature bins, strong convection due to atmospheric instability brought by surface warming is largely responsible. The analysis thus addresses some of the key knowledge gaps related to the behavior of P–T relationship and associated mechanisms for the Canadian regions. [ABSTRACT FROM AUTHOR]

Climate-impact projections are subject to uncertainty arising from climate models, greenhouse gases emission scenarios, bias correction and downscaling methods (BCDS), and the impact models. We studied the effects of hydrological model parameterization and regionalization (HM-P and HM-R) on the cascade of uncertainty. We developed a new, widely-applicable approach that improves our understanding of how HM-P and HM-R along with other uncertainty drivers contribute to the overall uncertainty in climate-impact projections. We analyzed uncertainties arising from general circulation models (GCMs), representative concertation pathways, BCDS, evapotranspiration calculation methods, and specifically HM-P and HM-R. We used the Soil and Water Assessment Tool, a semi-physical process-based hydrologic model with a high capability of parameterization, to project blue and green water resources for historical (1983–2007), near future (2010–2035) and far future (2040–2065) periods in Alberta, a western province of Canada. We developed an Analysis of Variance (ANOVA)-Sequential Uncertainty Fitting Program approach, to decompose the overall uncertainty into contributions of single drivers using the projected blue and green water resources. The monthly analyses of projected water resources showed that HM-P and HM-R contribute 21–51% and 15–55% to the blue water, and 20–48% and 15–50% to the green water overall uncertainty in near future and far future, respectively. Overall, we found that in spring and summer seasons uncertainty arising from HM-P and HM-R dominates other uncertainty sources, e.g. GCMs. We also found that global climate models are another dominant source of uncertainty in future impact projections. [ABSTRACT FROM AUTHOR]

Winter weather events with temperatures near 0 ∘ C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0. 11 ∘ grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980–2009) are found to be comparable to observations. The projections for the future scenario (2070–2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events ( ≥ 6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study evaluates projected changes to rain-on-snow (ROS) characteristics (i.e., frequency, rainfall amount, and runoff) for the future 2041-2070 period with respect to the current 1976-2005 period over North America using six simulations, based on two Canadian RCMs, driven by two driving GCMs for RCP4.5 and 8.5 emission pathways. Prior to assessing projected changes, the two RCMs are evaluated by comparing ERA-Interim driven RCM simulations with available observations, and results indicate that both models reproduce reasonably well the observed spatial patterns of ROS event frequency and other related features. Analysis of current and future simulations suggest general increases in ROS characteristics during the November-March period for most regions of Canada and for northwestern US for the future period, due to an increase in the rainfall frequency with warmer air temperatures in future. Future ROS runoff is often projected to increase more than future ROS rainfall amounts, particularly for northeastern North America, during snowmelt months, as ROS events usually accelerate snowmelt. The simulations show that ROS event is a primary flood generating mechanism over most of Canada and north-western and -central US for the January-May period for the current period and this is projected to continue in the future period. More focused analysis over selected basins shows decreases in future spring runoff due to decreases in both snow cover and ROS runoff. The above results highlight the need to take into consideration ROS events in water resources management adaptation strategies for future climate. [ABSTRACT FROM AUTHOR]

Lakes influence the regional climate and hydrology in a number of ways and therefore they should be represented in climate models in a realistic manner. Lack of representation of lakes in models can lead to errors in simulated energy and water fluxes, for lake-rich regions. This study focuses on the assessment of the impact of climate change on lakes and hydrology as well as on the influence of lakes on projected changes to regional climate and surface hydrology, particularly streamflows, for Northeast Canada. To this end, transient climate change simulations spanning the 1950-2100 period are performed, with and without lakes, with the fifth generation of the Canadian Regional Climate Model (CRCM5), driven by the Canadian Earth System Model (CanESM2) at the lateral boundaries for Representative Concentration Pathway 8.5. An additional CRCM5 simulation, driven by European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-Interim) for the 1980-2010 period, is performed in order to assess performance and boundary forcing errors. Performance errors are assessed by comparing the ERA-Interim-driven simulation with available observation datasets, for the 1980-2010 period, for selected variables: 2-m air temperature, total precipitation, snow water equivalent and streamflow. The validation results indicate reasonable model performance over the study region. Boundary forcing errors are studied by comparing ERA-Interim-driven simulation with the one driven by CanESM2 for the current 1980-2010 period, to identify regions and seasons for which projected changes should be interpreted with extra caution. Comparison of projected changes from the CRCM5 simulations with and without lakes suggest that the presence of lakes results in a dampening of projected increases to 2-m air temperature for all seasons almost everywhere in the study domain, with maximum dampening of the order of 2 °C occurring during winter, mostly in the vicinity of the lakes. As for streamflows, projected increases to spring streamflows, based on the simulation with lakes, are found to be smaller than that without lakes and this is due to the storage effect of lakes. Similarly, lower decreases in summer streamflows in future climate are noted in the simulation with lakes due to the gradual release of snowmelt water stored in lakes. An additional CRCM5 transient climate change simulation with lakes and interflow, i.e. lateral flow in the soil layers, is compared with the simulation with lakes, but without interflow, to assess the impact of interflow on projected changes to regional climate and hydrology. Maximum interflow is projected to shift earlier in spring and the maximum interflow rate is expected to decrease by around 25 % in future. Results suggest that the impact of interflow on projected changes to precipitation, soil moisture and humidity are modest, even though the interflow intensity is changing noticeably in future climate. The impact of the interflow on projected changes to streamflows is in the range of ±50 m/s. This study thus for the first time demonstrates the impact of lakes and interflow on projected changes to the regional climate and hydrology for the study region using a single regional modelling system. [ABSTRACT FROM AUTHOR]

Cold temperature and associated extremes often impact adversely human health and environment and bring disruptions in economic activities during winter over Canada. This study investigates projected changes in winter (December to March) period cold extreme days (i.e., cold nights, cold days, frost days, and ice days) and cold spells over Canada based on 11 regional climate model (RCM) simulations for the future 2040-2069 period with respect to the current 1970-1999 period. These simulations, available from the North American Regional Climate Change Assessment Program, were obtained with six different RCMs, when driven by four different Atmosphere-Ocean General Circulation Models, under the Special Report on Emissions Scenarios A2 scenario. Based on the reanalysis boundary conditions, the RCM simulations reproduce spatial patterns of observed mean values of the daily minimum and maximum temperatures and inter-annual variability of the number of cold nights over different Canadian climatic regions considered in the study. A comparison of current and future period simulations suggests decreases in the frequency of cold extreme events (i.e., cold nights, cold days and cold spells) and in selected return levels of maximum duration of cold spells over the entire study domain. Important regional differences are noticed as the simulations generally indicate smaller decreases in the characteristics of extreme cold events over western Canada compared to the other regions. The analysis also suggests an increase in the frequency of midwinter freeze-thaw events, due mainly to a decrease in the number of frost days and ice days for all Canadian regions. Especially, densely populated southern and coastal Canadian regions will require in depth studies to facilitate appropriate adaptation strategies as these regions are clearly expected to experience large increases in the frequency of freeze-thaw events. [ABSTRACT FROM AUTHOR]

Extreme hot spells can have significant impacts on human society and ecosystems, and therefore it is important to assess how these extreme events will evolve in a changing climate. In this study, the impact of climate change on hot days, hot spells, and heat waves, over 10 climatic regions covering Canada, based on 11 regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program for the June to August summer period is presented. These simulations were produced with six RCMs driven by four Atmosphere-Ocean General Circulation Models (AOGCM), for the A2 emission scenario, for the current 1970-1999 and future 2040-2069 periods. Two types of hot days, namely HD-1 and HD-2, defined respectively as days with only daily maximum temperature (Tmax) and both Tmax and daily minimum temperature (Tmin) exceeding their respective thresholds (i.e., period-of-record 90th percentile of Tmax and Tmin values), are considered in the study. Analogous to these hot days, two types of hot spells, namely HS-1 and HS-2, are identified as spells of consecutive HD-1 and HD-2 type hot days. In the study, heat waves are defined as periods of three or more consecutive days, with Tmax above 32 °C threshold. Results suggest future increases in the number of both types of hot days and hot spell events for the 10 climatic regions considered. However, the projected changes show high spatial variability and are highly dependent on the RCM and driving AOGCM combination. Extreme hot spell events such as HS-2 type hot spells of longer duration are expected to experience relatively larger increases compared to hot spells of moderate duration, implying considerable heat related environmental and health risks. Regionally, the Great Lakes, West Coast, Northern Plains, and Maritimes regions are found to be more affected due to increases in the frequency and severity of hot spells and/or heat wave characteristics, requiring more in depth studies for these regions to facilitate appropriate adaptation measures. [ABSTRACT FROM AUTHOR]

A new method is developed to evaluate the wave climate in the Gulf of St. Lawrence (GSL) with the consideration of wave attenuation by sea ice. Ice concentrations outputs from a regional oceanic model are used to attenuate, in post-processing, significant wave height ( H) time-series simulated with a parametric wave model for ice-free conditions. Reanalysis data is used to compute GSL wave climate for the 1981-2010 period with and without wave attenuation by sea ice. Outputs from two simulations from the Canadian Regional Climate Model are also used to evaluate how GSL wave climate should evolve during the twenty first century according to the SRES-A2 greenhouse gases emission scenario. Results show that sea ice has reduced extreme H on the GSL by about 12 % on average over the 1981-2010 period but its impact on wave climate should become negligible by 2100 except in the St. Lawrence Estuary. Over the twenty first century, an increase of extreme H on the GSL should be expected mostly because of the reduction of sea ice. On the other hand, little changes in the extreme wave climate should be expected as a response to changes in the wind regime over the GSL. For future coastal engineering applications, the GSL wave climate could be evaluated by supposing an ice-free sea to integrate the likely impact of future climate change. [ABSTRACT FROM AUTHOR]

In an ensemble of Regional Climate Model (RCM) simulations where different members are initialised at different times but driven by identical lateral boundary conditions, the individual members provide different, but equally acceptable, weather sequences. In others words, RCM simulations exhibit the phenomenon of Internal Variability (or inter-member variability-IV), defined as the spread between members in an ensemble of simulations. Our recent studies reveal that RCM's IV is associated with energy conversions similar to those taking place in weather systems. By analogy with the classical work on global energetics of weather systems, a formulation of an energy cycle for IV has been developed that is applicable over limited-area domains. Prognostic equations for ensemble-mean kinetic energy and available enthalpy are decomposed into contributions due to ensemble-mean variables and those due to deviations from the ensemble mean (IV). Together these equations constitute an energy cycle for IV in ensemble simulations of an RCM. A 50-member ensemble of 1-year simulations that differ only in their initial conditions was performed with the fifth-generation Canadian RCM (CRCM5) over an eastern North America domain. The various energy reservoirs of IV and exchange terms between reservoirs were evaluated; the results show a remarkably close parallel between the energy conversions associated with IV in ensemble simulations of RCM and the energy conversions taking place in weather systems in the real atmosphere. [ABSTRACT FROM AUTHOR]

In the present work, climate change impacts on three spring (March-June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak-volume, peak-duration and volume-duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970-1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970-1999) and future (2041-2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties. [ABSTRACT FROM AUTHOR]

Within Canada, the Canadian Prairies are particularly drought-prone mainly due to their location in the lee of the western cordillera and distance from large moisture sources. Although previous studies examined the occurrence of Canadian Prairie droughts during instrumental, pre-instrumental and to a lesser extent, future periods, none have specifically focused on all time three scales. Using two different drought indicators, namely the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI), this investigation assesses the variability of summer drought duration and intensity over a core region of the Prairies during (a) the pre-instrumental record extending back several centuries (inferred from tree rings), (b) the instrumental record (1901-2005), and (c) the twenty-first century using statistically downscaled climate variables from several Atmosphere-Ocean Global climate models with multiple emission scenarios. Results reveal that observed twentieth century droughts were relatively mild when compared to pre-settlement on the Prairies, but these periods are likely to return (and even worsen) in the future due to the anticipated warming during the course of the twenty-first century. However, future drought projections are distinctly different between the two indices. All PDSI-related model runs show greater drought frequency and severity mainly due to increasing temperatures. Conversely, the precipitation-based SPI indicates no significant changes to future summer drought frequency although there tends to be a higher persistence of multi-year droughts in central and southern portions of Canadian Prairies. These findings therefore stress the importance of considering anticipated warming trends when assessing future regional-scale drought, especially given the uncertainties and lack of consistency in future precipitation signals among climate models. This study can be considered an initial step toward quantifying and understanding Canadian Prairie drought occurrence and severity over several centuries as determined from paleo, instrumental, and climate model data sources. [ABSTRACT FROM AUTHOR]

An analysis of streamflow characteristics (i.e. mean annual and seasonal flows and extreme high and low flows) in current and future climates for 21 watersheds of north-east Canada covering mainly the province of Quebec is presented in this article. For the analysis, streamflows are derived from a 10-member ensemble of Canadian Regional Climate Model (CRCM) simulations, driven by the Canadian Global Climate Model simulations, of which five correspond to current 1970-1999 period, while the other five correspond to future 2041-2070 period. For developing projected changes of streamflow characteristics from current to future periods, two different approaches are used: one based on the concept of ensemble averaging while the other approach is based on merged samples of current and similarly future simulations following multiple comparison tests. Verification of the CRCM simulated streamflow characteristics for the 1970-1999 period suggests that the model simulated mean hydrographs and high flow characteristics compare well with those observed, while the model tends to underestimate low flow extremes. Results of projected changes to mean annual streamflow suggest statistically significant increases nearly all over the study domain, while those for seasonal streamflow show increases/decreases depending on the season. Two- and 5-year return levels of 15-day low flows are projected to increase significantly over most part of the study domain, though the changes are small in absolute terms. Based on the ensemble averaging approach, changes to 10- and 30-year return levels of high flows are not generally found significant. However, when a similar analysis is performed using longer samples, significant increases to high flow return levels are found mainly for northernmost watersheds. This study highlights the need for longer samples, particularly for extreme events in the development of robust projections. [ABSTRACT FROM AUTHOR]

Previous studies have shown that Regional Climate Models (RCM) internal variability (IV) fluctuates in time depending on synoptic events. This study focuses on the physical understanding of episodes with rapid growth of IV. An ensemble of 21 simulations, differing only in their initial conditions, was run over North America using version 5 of the Canadian RCM (CRCM). The IV is quantified in terms of energy of CRCM perturbations with respect to a reference simulation. The working hypothesis is that IV is arising through rapidly growing perturbations developed in dynamically unstable regions. If indeed IV is triggered by the growth of unstable perturbations, a large proportion of the CRCM perturbations must project onto the most unstable singular vectors (SVs). A set of ten SVs was computed to identify the orthogonal set of perturbations that provide the maximum growth with respect to the dry total-energy norm during the course of the CRCM ensemble of simulations. CRCM perturbations were then projected onto the subspace of SVs. The analysis of one episode of rapid growth of IV is presented in detail. It is shown that a large part of the IV growth is explained by initially small-amplitude unstable perturbations represented by the ten leading SVs, the SV subspace accounting for over 70% of the CRCM IV growth in 36 h. The projection on the leading SV at final time is greater than the projection on the remaining SVs and there is a high similarity between the CRCM perturbations and the leading SV after 24-36 h tangent-linear model integration. The vertical structure of perturbations revealed that the baroclinic conversion is the dominant process in IV growth for this particular episode. [ABSTRACT FROM AUTHOR]