Canadian Regional Climate Model Simulations Research Articles

Evaluation and joint projection of temperature and precipitation extremes across Canada based on hierarchical Bayesian modelling and large ensembles of regional climate simulations

Individual and joint variations of extreme temperature and precipitation are assessed across Canada using the large ensemble of Canadian Regional Climate Model simulations (CanRCM4-LE) and two corresponding multivariate bias-corrected datasets (Canadian Large Ensembles Adjusted Datasets, CanLEAD-E & S). The overall performance of the three 50-member ensembles is evaluated against the NRCANmet gridded observation for 1951–2000. A hierarchical Bayesian framework is then applied to analyze the biases of each ensemble member, characterize the ensemble uncertainties associated with internal climate variability, and assess the trends and the joint distributions of temperature and precipitation. Further, projected changes of extreme climate indices are assessed across the three ensembles in the historical period and four future scenarios corresponding to +1.5 °C to +4.0 °C warming above the pre-industrial level of 1850–1900. Results show that the CanLEAD products have lower warm and wet biases compared to CanRCM4-LE over most regions and in all seasons except in winter. CanLEAD-S significantly reduces precipitation biases and represents the behaviour of extreme climate indices better than the other two ensembles. All ensembles consistently project strong warming and wetting trends over most parts of southern Canada excluding the Canadian Prairies in summer, which shows a drying trend towards the end of the 21st century. The ensembles show increases in hot extremes in central and southeastern Canada and increases in wet extremes in western coastal regions. The results of the study suggest that CanLEAD-E&S can be used as reliable products for climate change impact assessments at regional scales particularly for the analysis of nonstationary compound events.

Projected changes to wind loads coinciding with rainfall for building design in Canada based on an ensemble of Canadian regional climate model simulations

Strong wind coinciding with rainfall is an important weather phenomenon in many science and engineering fields. This study investigates changes in hourly extreme driving rain wind pressure (DRWP)—a climatic variable used in building design in Canada—for future periods of specified global mean temperature change using an ensemble of a Canadian regional climate model (CanRCM4) driven by the Canadian Earth system model (CanESM2) under the Representative Concentration Pathway 8.5 scenario. Evaluation of the model shows that the CanRCM4 ensemble reproduces hourly extreme wind speeds and rainfall (> 1.8 mm/h) occurrence frequency and the associated design (5-year return level) DRWP across Canada well when compared with 130 meteorological stations. Significant increases in future design DRWP are projected over western, eastern, and northern Canada, with the areal extent and relative magnitude of the increases scaling approximately linearly with the amount of global warming. Increases in future rainfall occurrence frequency are driven by the combined effect of increases in precipitation amount and changes in precipitation type from solid to liquid due to increases in air temperature; these are identified as the main factors leading to increases in future design DRWP. Future risk ratios of the design DRWP are highly dependent on those of the rainfall occurrence, which shows large increases over the three regions, while they are partly affected by the increases in future extreme wind speeds over western and northeastern Canada. Increases in DRWP can be an emerging risk for existing buildings, particularly in western, eastern, and northern Canada, and a consideration for managing and designing buildings across Canada.

Projected changes to extreme freezing precipitation and design ice loads over North America based on a large ensemble of Canadian regional climate model simulations

Abstract. Atmospheric ice accretion caused by freezing precipitation (FP) can lead to severe damage and the failure of buildings and infrastructure. This study investigates projected changes to extreme ice loads – those used to design infrastructure over North America (NA) – for future periods of specified global mean temperature change (GMTC), relative to the recent 1986–2016 period, using a large 50-member initial-condition ensemble of the CanRCM4 regional climate model, driven by CanESM2 under the RCP8.5 scenario. The analysis is based on 3-hourly ice accretions on horizontal, vertical and radial surfaces calculated based on FP diagnosed by the offline Bourgouin algorithm and wind speed during FP. The CanRCM4 ensemble projects an increase in future design ice loads for most of northern NA and decreases for most of southern NA and some northeastern coastal regions. These changes are mainly caused by regional increases in future upper-level and surface temperatures associated with global warming. Projected changes in design ice thickness are also affected by changes in future precipitation intensity and surface wind speed. Changes in upper-level and surface temperature conditions for FP occurrence in CanRCM4 are in broad agreement with those from nine global climate models but display regional differences under the same level of global warming, indicating that a larger multi-model, multi-scenario ensemble may be needed to better account for additional sources of structural and scenario uncertainty. Increases in ice accretion for latitudes higher than 40∘ N are substantial and would have clear implications for future building and infrastructure design.

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4 m s−1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4 m s−1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4 m s−1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.

Projected changes in characteristics of precipitation spatial structures over North America

ABSTRACTSpatial structures of hourly precipitation fields were studied from three simulations of the Canadian Regional Climate Model (CRCM) and observations of the National Centers for Environmental Prediction (NCEP) Stage IV analysis. Each precipitation structure, defined as a contiguous area of precipitation above a given threshold, was analysed through geometric characteristics (position, area, major and minor axes, eccentricity, orientation) and intensity characteristics (volume, mean and maximum intensities, precipitation distribution within the structure) for 16 climatic regions covering North America. While providing new insights on the spatial facet of precipitation, this study aimed to: (1) assess the performance of the CRCM to reproduce observed precipitation structures and (2) analyse the changes in precipitation structures between historical (1961–1990) and future (2071–2100) periods. In addition, the effect of internal variability was investigated using two CGCM‐driven CRCM simulations. In order to assess the CRCM performance, a reanalysis‐driven CRCM simulation was first compared with observations and then with CGCM‐driven CRCM simulations. Results suggest that reanalysis‐driven CRCM precipitation structures displayed intensities spatially more homogeneous than observed ones for the central and eastern United States and showed significantly lower precipitation volumes, intensities and areas. However, annual cycles of characteristic values were well reproduced. In addition, CGCM‐driven CRCM showed significantly lower precipitation volumes and intensities during summer months for southeastern regions when compared to reanalysis‐driven CRCM. Precipitation structures were also larger and shifted further north. Boundary conditions seemed to influence mainly central and eastern regions of North America. In future climate, results suggest more convective summer precipitations for central and eastern regions (increases in volumes, intensities and heterogeneity of structures), drier spring and summer conditions for southwestern regions (decreases in numbers of structures), wetter winter and spring conditions for northern regions (increases in numbers of structures) and wetter autumn conditions for southeastern regions (increases in volumes and intensities).