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Canadian climate service providers offer projections from the Coupled Model Intercomparison Project (CMIP6) to help inform climate change mitigation and adaptation decisions. CMIP6 includes several "hot" climate models whose sensitivity to greenhouse gas forcings exceeds the likely range inferred from multiple lines of evidence. Global warming estimates assessed in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) were reduced by applying observational constraints on the historical rate of warming to the CMIP6 ensemble. This study assesses whether globally constrained CMIP6 projections for Canada are appreciably different from unconstrained projections. Two constraints are considered: one that removes models whose transient climate response lies outside the AR6 assessed range (TCRlikely), and the other that weights models to match the assessed distribution of equilibrium climate sensitivity (ECSall). Both constraints lead to appreciably cooler and drier projections than the unconstrained ensemble, with the strongest reductions seen in the upper end of the ensemble range, high-emissions scenario, end-of-century time period, and northern regions of Canada. In this case, constrained projections of annual mean temperature are 2°–3°C cooler than the unconstrained projections, whereas projections of annual total precipitation are typically 20%–40% drier. Appreciable differences are also detected in the ensemble median of temperature extreme indices. Based on these results, it is recommended that a constrained ensemble be considered for regional projections to avoid the "hot model" problem. Alternatively, projections can be communicated conditional on a specified level of global warming, with global constraints then used to inform the timing of the warming level exceedance. [ABSTRACT FROM AUTHOR]

Climate extremes indices are evaluated for the northeast United States and adjacent Canada (Northeast) using gridded observations and twenty-three CMIP5 coupled models. Previous results have demonstrated observed increases in warm and wet extremes and decreases in cold extremes, consistent with changes expected in a warming world. Here, a significant shift is found in the distribution of observed total annual precipitation over 1981-2010. In addition, significant positive trends are seen in all observed wet precipitation indices over 1951-2010. For the Northeast region, CMIP5 models project significant shifts in the distributions of most temperature and precipitation indices by 2041-2070. By the late century, the coldest (driest) future extremes are projected to be warmer (wetter) than the warmest (wettest) extremes at present. The multimodel interquartile range compares well with observations, providing a measure of confidence in the projections in this region. Spatial analysis suggests that the largest increases in heavy precipitation extremes are projected for northern, coastal, and mountainous areas. Results suggest that the projected increase in total annual precipitation is strongly influenced by increases in winter wet extremes. The largest decreases in cold extremes are projected for northern and interior portions of the Northeast, while the largest increases in summer warm extremes are projected for densely populated southern, central, and coastal areas. This study provides a regional analysis and verification of the latest generation of CMIP global models specifically for the Northeast, useful to stakeholders focused on understanding and adapting to climate change and its impacts in the region. [ABSTRACT FROM AUTHOR]

Freshwater supplies in most western Canadian watersheds are threatened by the warming of temperatures because it alters the snow-dominated hydrologic patterns that characterize these cold regions. In this study, we used datasets from 12 climate simulations, which are associated with seven global climate models and four future scenarios and are participating in phase 6 of the Coupled Model Intercomparison Project, to calculate and assess the historical and future temporal patterns of 13 hydroclimate indicators relevant to water resources management. We conducted linear long-term trend and change analyses on their annual time series to provide insight into the potential regional impacts of the detected changes on water availability for all users. We implemented our framework on the Alberta oil sands region in Canada to support the monitoring of environmental changes in this region, relative to the established baseline 1985–2014. Our analysis indicates a persistent increase in the occurrence of extreme hot temperatures, fewer extreme cold temperatures, and an increase in warm spells and heatwaves, while precipitation-related indices show minor changes. Consequently, deficits in regional water availability during summer and water-year periods, as depicted by the standardized precipitation evapotranspiration indices, are expected. The combined effects of the strong climate warming signals and the small increases in precipitation annual amounts generally detected in this study suggest that drier conditions may become severe and frequent in the Alberta oil sands region. The challenging climate change risks identified for this region should therefore be continuously monitored, updated, and integrated to support a sustainable management for all water users. [ABSTRACT FROM AUTHOR]

With the objective of trying to understand the adaptability of agriculture across the Canadian Prairies under climate change, simple‐to‐use agroclimatic indices were calculated for the base climate period of 1981 to 2010 and for both the medium (RCP4.5) and high (RCP8.5) emission projections extending to the distant future (2071–2100). The agroclimatic indices included the Effective Growing Degree Days (EGDDs), Growing Season Length (GSL), the Climate Moisture Index (CMI), and the Temperature Humidity Index (THI). For climate change in 30‐year periods, these indices were calculated as multi‐model ensembles of six Global Climate Models recommended under the Coupled Model Intercomparison Project Phase 5 (CMIP5) for the study area. We found that the GSL, EGDDs, CMI, and THI were amplified above the values of the base climate period in the order of 40–50 days, 600–1200 heat units, −100 to −120 mm and 3–4 THI units by the close of the distant future (2071–2100) under the RCP4.5 and RCP8.5, respectively. This amplification has implications on where crop and livestock production could become more suitable or riskier in future. Opportunities include expanding crop and livestock production to more northerly regions which currently have insufficient heat units, a short growing season and unfavourable temperature humidity thresholds for livestock production. Moisture deficits will continue to be the greatest risk during the growing season under climate change scenarios but options exist to implement adaptive measures such as staggering seeding times to take advantage of moisture availability in the spring and autumn seasons and crop substitution. This study has relevance for policy and program formulation and implementation in Canada's agricultural regions and potentially, other areas of the world with similar climate change outcomes. [ABSTRACT FROM AUTHOR]

Representative subsets of global climate models (GCMs) are often used in climate change impact studies to account for uncertainty in ensemble climate projections. However, the effectiveness of such subsets has seldom been assessed for the estimations of either the mean or the spread of the full ensembles. We assessed two different approaches that were employed to select 5 GCMs from a 20-member ensemble of GCMs from the CMIP5 ensemble for projecting canola and spring wheat yields across Canada under RCP 4.5 and 8.5 emission scenarios in the periods 2040–2069 and 2070–2099, based on crop simulation models. Averages and spreads of the simulated crop yields using the 5-GCM subsets selected by T&P and KKZ approaches were compared with the full 20-GCM ensemble. Our results showed that the 5-GCM subsets selected by the two approaches could produce full-ensemble means with a relative absolute error of 2.9–4.7% for canola and 1.5–2.2% for spring wheat, and covers 61.8–91.1% and 66.1–80.8% of the full-ensemble spread for canola and spring wheat, respectively. Our results also demonstrated that both approaches were very likely to outperform a subset of randomly selected 5 GCMs in terms of a smaller error and a larger range. [ABSTRACT FROM AUTHOR]

The mountainous watersheds of western Canada are generally thought to be in a state of transition from snow‐dominated to hybrid regimes. In stream networks that are regulated, the effects of this transition on streamflow can have compelling operational consequences. Seasonal magnitude changes may impact spill‐risk management, while changes in the composition of summer runoff may increase its variability and reduce the forecasting capabilities of state variables like peak snow water equivalent. Though glacier loss can have a considerable impact on summer runoff, few studies explicitly model the ongoing glacier recession in conjunction with other primary hydrological processes. In this study, we incorporate glacier dynamics from a previous run of the Regional Glaciation Model into the University of British Columbia Watershed Model via the Raven modelling framework. We use this modelling system to explore potential changes under Representative Concentration Pathways 4.5 and 8.5 to the hydrology of the ∼20000km2 Mica Basin, a regulated watershed containing the headwaters of the Columbia River. Our results project statistically significant increases in spring flow in future eras, which may force lower reservoir drafting in late winter, creating potential for energy shortfalls in early spring. We project the coefficient of variation of summer runoff generally goes unchanged in future eras as does the summer runoff forecasting capability of April 1st SWE. Hence, despite modelled glacier loss and reduced snowmelt contribution, our study does not reject the null hypothesis that the predictability of the Mica Basin's summer runoff is unchanged in future eras. We explore these results in detail because they superficially appear to contrast the conventional conceptualization that reduced snowmelt negatively affects the predictive powers of snowpack and glacier loss increases the variability of runoff. We argue that our results' apparent discordance from convention displays the complexities inherent in isolating the effects of changes to a single water balance component when other components are also non‐stationary and highlights the benefits of using modelling to more explicitly explore such implications. [ABSTRACT FROM AUTHOR]

The warming climate can considerably affect socioeconomic activities and environmental health conditions in Canada. Climate models play a key role in evaluating the impact of climate change and developing adaption and mitigation strategies corresponding to Canadian regions. This study compares the behavior of climate models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6) with their CMIP5 predecessors in representing a set of climate indices relevant to Canada's agricultural productivity, infrastructure resilience, and environmental health. Our results show that although CMIP5 and CMIP6 multi‐model ensemble mean values for the considered indices are almost similar, the behavior of individual CMIP5 and CMIP6 models or even the model pairs of the same modeling center can be different across Canada. Moreover, the CMIP6 models do not necessarily outperform CMIP5 in comparison to NOAA and NCEP reanalysis datasets in simulating the annual mean and coefficient of variation values for the indices during the historical period. The comparisons between models' simulations also reveal that the envelope of estimated values based on individual CMIP6 models does not cover or overlap with their CMIP5 counterparts or even with other CMIP6 models. Therefore, the CMIP6 models with higher number of simulations do not necessarily provide a larger range of projections over Canadian regions. The divergence between CMIP5 and CMIP6 models' behavior is more obvious under the 8.5 W/m2 forcing in the long‐term horizon. Overall, the estimated sign, magnitude, and spatial pattern of changes in the climate indices depend on the considered climate model and forcing scenario. Plain Language Summary: Climatic conditions play an important role in shaping countries' society, economy, and environment. As Canada gets warmer, the country becomes more vulnerable to changes in temperature and precipitation. Particularly, agricultural production, infrastructure stability, and human and environmental health are at great risks of degradation. Climate models are the most credible tools to project future climate; therefore, their behavior is critical to evaluate the climate change impacts. In this study, the simulations of the state‐of‐the‐art Climate Model Intercomparison Project Phase 6 (CMIP6) and CMIP5 climate models are compared across Canadian regions. In total, 389 climate simulations are used to estimate a set of pertinent climate indices. Results reveal that there is no clear superiority of CMIP6 models over CMIP5 in representing estimated values by NOAA and NCEP reanalysis datasets during the historical period in Canada. Moreover, although the magnitude and spatial pattern of projections by CMIP5 and CMIP6 models are not necessarily similar, both of them show significant changes in temperature and precipitation in the future and considered climate indices, which can be alarming for Canada. Further analyses using bias‐corrected simulations are needed to assess the extent of climate change impacts on Canada's agriculture, infrastructure as well as environmental health. Key Points: Comparisons with NOAA and NCEP reanalysis datasets show that CMIP6 climate models do not necessarily outperform CMIP5 models in CanadaAlthough CMIP6 and CMIP5 multi‐model ensemble mean values are almost similar, the range of projections by individual models is differentThe divergence between CMIP5 and CMIP6 models' behavior is more obvious under the 8.5 W/m2 forcing in the long‐term horizon [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The interannual variability of wintertime North American surface temperature extremes and its generation and maintenance are analyzed in this study. The leading mode of the temperature extreme anomalies, revealed by empirical orthogonal function (EOF) analyses of December-February mean temperature extreme indices over North America, is characterized by an anomalous center of action over western-central Canada. In association with the leading mode of temperature extreme variability, the large-scale atmospheric circulation features an anomalous Pacific-North American (PNA)-like pattern from the preceding fall to winter, which has important implications for seasonal prediction of North American temperature extremes.A positive PNA pattern leads to more warm and fewer cold extremes over western-central Canada. The anomalous circulation over the PNA sector drives thermal advection that contributes to temperature anomalies over North America, as well as a Pacific decadal oscillation (PDO)-like sea surface temperature (SST) anomaly pattern in the midlatitude North Pacific. The PNA-like circulation anomaly tends to be supported by SST warming in the tropical central-eastern Pacific and a positive synoptic-scale eddy vorticity forcing feedback on the large-scale circulation over the PNA sector. The leading extreme mode--associated atmospheric circulation patterns obtained from the observational and reanalysis data, together with the anomalous SST and synoptic eddy activities, are reasonably well simulated in most CMIP5 models and in the multimodel mean. For most models considered, the simulated patterns of atmospheric circulation, SST, and synoptic eddy activities have lower spatial variances than the corresponding observational and reanalysis patterns over the PNA sector, especially over the North Pacific. [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]

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]

In this study, high‐resolution projections of temperature and precipitation changes over Canada were developed through the Providing Regional Climates for Impact Studies (PRECIS) model under Representative Concentration Pathways (RCPs). In detail, the PRECIS model was employed to conduct simulations for the historical period over the entirety of Canada, driven by the boundary conditions from both ERA‐Interim (1979–2011) and HadGEM2‐ES (1959–2005). The performance of PRECIS simulations in reproducing historical climatology of Canada was then validated through comparison with observed temperature and precipitation over the baseline period (1986–2005). The boundary conditions from HadGEM2‐ES under RCP4.5 and RCP8.5 was used to drive PRECIS for simulating climatic variables over Canada for the period of 2006–2099. Future climate projections of temperature and precipitation as well as their extreme indices over two time‐slices (i.e. 2046–2065 and 2076–2095) were extracted and analysed. The results could help investigate how the regional climate over Canada will respond to global warming as well as the spatio‐temporal characteristics of plausible climate changes in the Canadian context. The validation results demonstrate that the PRECIS model is effective in reproducing the historical climatological patterns of annual mean temperature and total precipitation across Canada. Projections of temperature and precipitation for the two future periods indicate that there will be an apparent increasing pattern over Canada. The projected changes derived in this study can provide decision‐makers with valuable information to evaluate possible impacts on economic, social and environmental sectors at regional and local scales. [ABSTRACT FROM AUTHOR]

ABSTRACT Precipitation, temperature, and evaporative demand are the most dominant factors affecting water availability in a region. This study examines projected changes in these hydro-climatic variables over western Canada under two greenhouse gas emissions scenarios using statistically downscaled, high resolution climate data generated by six Global Climate Models ( GCMs) from the latest Coupled Model Intercomparison Project ( CMIP5). Potential changes in the spatial and seasonal distributions of water availability over nine major western Canadian river basins are examined by computing the 3- and 12-month standardized precipitation and evapotranspiration indices ( SPEI-3 and SPEI-12). While individual GCM projections vary on the rate and seasonality of changes, they all indicate similar spatial and temporal patterns. The highest projected increases in precipitation and temperature are primarily in the northern basins, with some decreases in summer precipitation in the southern basins. The evolution of the SPEI-12 values for the southern basins such as Columbia, Saskatchewan, Fraser and Athabasca indicate a gradual increase in the magnitude and duration of water deficit, while the reverse was found for most of the northern basins such as Peel/Lower Mackenzie, Liard, and Northern Pacific that show a gradual increase in water surplus on an annual basis. The SPEI-3, however, shows that almost all river basins in western Canada, with the exception of Peel/Lower Mackenzie that are located in the extreme north of the study region, are projected to experience decreasing water availability in summer. In general, the study highlights the potential changes in the spatial and seasonal distribution of western Canadian water resources and sets the stage for a more detailed and process based hydro-climate modelling study to be conducted in the region. [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]

Copyright of Environmental Reviews is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)