Climate Change on Newfoundland and Labrador Shelves: Results From a Regional Downscaled Ocean and Sea-Ice Model Under an A1B Forcing Scenario 2011–2069

Climate change may affect ocean and ice conditions in coastal oceans and thus have significant impacts on coastal infrastructure, marine navigation, and marine ecosystems. In this study a three-dimensional ice–ocean model is developed to examine likely changes of ocean and ice conditions over the Newfoundland and Labrador Shelves in response to climate change. The model is configured with a horizontal grid of approximately 7?km and a vertical grid of 46 levels and is run from 1979 to 2069. The projection period is 2011 to 2069 under a median emission scenario A1B used by the Intergovernmental Panel on Climate Change. For the projection period, the surface atmospheric forcing fields used are from the Canadian Regional Climate Model over the North Atlantic. The open boundary conditions come from the Canadian Global Climate Model, Version 3 (CGCM3), adjusted for the 1981–2010 mean of the Simple Ocean Data Assimilation model output. The simulated fields over the 1981–2010 period have patterns consistent with observations. Over the Newfoundland and Labrador Shelves during the projection period, the model shows general trends of warming, freshening, and decreasing ice. From 2011 to 2069, the model projects that under A1B sea surface temperature will increase by 1.4°C; bottom temperature will increase by 1.6°C; sea surface salinity will decrease by 0.7; bottom salinity will decrease by 0.3; and sea-ice extent will decrease by 70%. The sea level will rise by 0.11?m at the St. John's tide-gauge station because of oceanographic change, and the freshwater transport of the Labrador Current will double as a result of freshening. The regional ice–ocean model reproduces more realistic present climate conditions and projects considerably different future climate conditions than CGCM3.     

Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model

The fifth-generation Canadian Regional Climate Model (CRCM5) was used to dynamically downscale two Coupled Global Climate Model (CGCM) simulations of the transient climate change for the period 1950–2100, over North America, following the CORDEX protocol. The CRCM5 was driven by data from the CanESM2 and MPI-ESM-LR CGCM simulations, based on the historical (1850–2005) and future (2006–2100) RCP4.5 radiative forcing scenario. The results show that the CRCM5 simulations reproduce relatively well the current-climate North American regional climatic features, such as the temperature and precipitation multiannual means, annual cycles and temporal variability at daily scale. A cold bias was noted during the winter season over western and southern portions of the continent. CRCM5-simulated precipitation accumulations at daily temporal scale are much more realistic when compared with its driving CGCM simulations, especially in summer when small-scale driven convective precipitation has a large contribution over land. The CRCM5 climate projections imply a general warming over the continent in the 21st century, especially over the northern regions in winter. The winter warming is mostly contributed by the lower percentiles of daily temperatures, implying a reduction in the frequency and intensity of cold waves. A precipitation decrease is projected over Central America and an increase over the rest of the continent. For the average precipitation change in summer however there is little consensus between the simulations. Some of these differences can be attributed to the uncertainties in CGCM-projected changes in the position and strength of the Pacific Ocean subtropical high pressure.     

Climate projections over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5)

Following the CORDEX experimental protocol, climate simulations and climate-change projections for Africa were made with the new fifth-generation Canadian Regional Climate Model (CRCM5). The model was driven by two Global Climate Models (GCMs), one developed by the Max-Planck-Institut für Meteorologie and the other by the Canadian Centre for Climate Modelling and Analysis, for the period 1950–2100 under the RCP4.5 emission scenario. The performance of the CRCM5 simulations for current climate is discussed first and compared also with a reanalysis-driven CRCM5 simulation. It is shown that errors in lateral boundary conditions and sea-surface temperature from the GCMs have deleterious consequences on the skill of the CRCM5 at reproducing specific regional climate features such as the West African Monsoon and the annual cycle of precipitation. For other aspects of the African climate however the regional model is able to add value compared to the simulations of the driving GCMs. Climate-change projections for periods until the end of this century are also analysed. All models project a warming throughout the twenty-first century, although the details of the climate changes differ notably between model projections, especially for precipitation changes. It is shown that the climate changes projected by CRCM5 often differ noticeably from those of the driving GCMs.     

The Impacts of Climate Change on the Autumn North Atlantic Wave Climate

Abstract

In this study, we investigate the impact of global warming induced by possible climate change on the autumn winds, the related storm climate, and the wave climate over the North Atlantic Ocean. These analyses are based on a third-generation wave model, WAVEWATCHIII? and dynamically downscaled winds, obtained from the Canadian Regional Climate Model driven by the third version of the Coupled Global Climate Model (T47) from the Canadian Centre for Climate Modelling and Analysis following the A1B climate change scenario of the Special Report on Emission Scenarios from the Intergovernmental Panel on Climate Change. Compared with the present wave climate, represented as 1970–1999, the significant wave heights in the northeast North Atlantic will increase, whereas in other areas, such as the mid-latitudes, they will decrease, with associated changes in winds in the future climate (2040–2069). An analysis of inverse wave ages is used to suggest that wind-driven wave regimes tend to occur more frequently in the northeast North Atlantic and decrease in the mid-latitudes in the climate change scenario. The dominant North Atlantic storm-track region is estimated to shift northward, especially over the northern Northeast Atlantic, where the frequency of occurrence of the most intense cyclones is estimated to increase. We suggest that changes in storm densities are related to changes in the upper level steering flow in the atmosphere, which are the precursor to changes in the winds and ocean waves.     

Sensitivity of the CRCM atmospheric and the Gulf of St. Lawrence Ocean‐Ice models to each other

Abstract

The sensitivity of the Canadian Regional Climate Model (CRCM), developed at the Université du Québec à Montréal, and the Gulf of St. Lawrence Ocean Model (GOM), developed at the Institut Maurice‐ Lamontagne, to each other is tested with an ensemble of simulations over eastern Canada from 1 November 1989 to 31 March 1990. The goal of this study is to investigate the interaction of the CRCM and GOM with respect to each other's forcing fields. In the first part of the experiment, a series of simulations were performed using an iterative strategy, where both models run separately and alternately, using variables from the other model to supply the needed forcing fields for the computation of surface fluxes. The runs are iterated several times over the same period from the output of the previous run to allow the atmosphere and the ocean to interact several times with each other and to study the evolution of the solutions from one iteration to the next. In the second part of the experiment, a two‐way coupled simulation is performed over the same period. The results indicate that on a monthly or longer timescale, the CRCM is not very sensitive to the details of the oceanic fields from GOM, except locally over the Gulf of St. Lawrence (GSL). However, GOM is quite sensitive to the differences in atmospheric fields from the CRCM. The results of several iterations converge to a unique solution, suggesting that the CRCM and GOM reach equilibrium with respect to each other's forcing fields. Furthermore, the results of the coupled run also converge to this same solution.     

Sensitivity of Hudson Bay Sea ice and ocean climate to atmospheric temperature forcing

A regional sea-ice?Cocean model was used to investigate the response of sea ice and oceanic heat storage in the Hudson Bay system to a climate-warming scenario. Projections of air temperature (for the years 2041?C2070; effective CO₂ concentration of 707?C950?ppmv) obtained from the Canadian Regional Climate Model (CRCM 4.2.3), driven by the third-generation coupled global climate model (CGCM 3) for lateral atmospheric and land and ocean surface boundaries, were used to drive a single sensitivity experiment with the delta-change approach. The projected change in air temperature varies from 0.8°C (summer) to 10°C (winter), with a mean warming of 3.9°C. The hydrologic forcing in the warmer climate scenario was identical to the one used for the present climate simulation. Under this warmer climate scenario, the sea-ice season is reduced by 7?C9?weeks. The highest change in summer sea-surface temperature, up to 5°C, is found in southeastern Hudson Bay, along the Nunavik coast and in James Bay. In central Hudson Bay, sea-surface temperature increases by over 3°C. Analysis of the heat content stored in the water column revealed an accumulation of additional heat, exceeding 3?MJ?m^?3, trapped along the eastern shore of James and Hudson bays during winter. Despite the stratification due to meltwater and river runoff during summer, the shallow coastal regions demonstrate a higher capacity of heat storage. The maximum volume of dense water produced at the end of winter was halved under the climate-warming perturbation. The maximum volume of sea ice is reduced by 31% (592?km3) while the difference in the maximum cover is only 2.6% (32,350?km²). Overall, the depletion of sea-ice thickness in Hudson Bay follows a southeast?Cnorthwest gradient. Sea-ice thickness in Hudson Strait and Ungava Bay is 50% thinner than in present climate conditions during wintertime. The model indicates that the greatest changes in both sea-ice climate and heat content would occur in southeastern Hudson Bay, James Bay, and Hudson Strait.     

A projection of extreme climate events in the 21st century over east Asia using the community climate system model 3

A series of coupled atmosphere-ocean-land global climate model (GCM) simulations using the National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) has been performed for the period 1870–2099 at a T85 horizontal resolution following the GCM experimental design suggested in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). First, a hindcast was performed using the atmospheric concentrations of three greenhouse gases (CO₂, CH₄, N₂O) specified annually and globally on the basis of observations for the period 1870–1999. The hindcast results were compared with observations to evaluate the GCM’s reliability in future climate simulations. Second, climate projections for a 100-year period (2000–2099) were made using six scenarios of the atmospheric concentrations of the three greenhouse gases according to the A1FI, A1T, A1B, A2, B1, and B2 emission profiles of the Special Report on Emissions Scenarios. The present CCSM simulations are found to be consistent with IPCC’s AR4 results in the temporal and spatial distributions for both the present-day and future periods. The GCM results were used to examine the changes in extreme temperatures and precipitation in East Asia and Korea. The extreme temperatures were categorized into warm and cold events: the former includes tropical nights, warm days, and heat waves during summer (June–July–August) and the latter includes frost days, cold days, and cold surges during winter (December–January–February). Focusing on Korea, the results predict more frequent heat waves in response to future emissions: the projected percentage changes between the present day and the late 2090s range from 294% to 583% depending on the emission scenario. The projected global warming is predicted to decrease the frequency of cold extreme events; however, the projected changes in cold surge frequency are not statistically significant. Whereas the number of cold surges in the A1FI emission profile decreases from the present-day value by up to 24%, the decrease in the B1 scenario is less than 1%. The frequency and intensity of extreme precipitation events year-round were examined. Both the frequency and the intensity of these events are predicted to increase in the region around Korea. The present results will be helpful for establishing an adaptation strategy for possible climate change nationwide, especially extreme climate events, associated with global warming.     

两种不同减排情景下21世纪气候变化的数值模拟

利用国家气候中心最新发展的气候系统模式BCC-CSM1.0模拟了相对于B1排放情景,两种不同减排情景(De90和De07,表示按照B1情景排放到2012年,之后线性递减,至2050年时CO_2排放水平分别达到1990和2007年排放水平一半的情景)对全球和中国区域气候变化的影响.结果表明:两种减排情景下模式模拟的全球平均地表气温在21世纪40年代以后明显低于Bl情景,比减排情景浓度低于B1的时间延迟了20年左右;尽管De90减排情景在2050年所达到的稳定排放水平低于De07情景,但De90情景下的全球增温在2070年以后才一致低于De07情景,这种滞后町能与耦合系统(主要足海洋)的惯性有关;至21世纪末,De90和De07情景下的全球增温幅度分别比B1情景降低了0.4和0.2℃;从全球分布来看,B1情景下21世纪后30年的增温幅度在北半球高纬度和极地地区最大,减排情景能够显著减少这些地区的增温幅度,减排程度越大,则减少越多;在中国区域,B1情景下21世纪末平均增温比全球平均高约1.2℃,减排情景De90和De07分别比B1情景降低了0.4和0.3℃,中国北方地区增温幅度高于南方及沿海地区,减排情景能够显著减小中国西部地区的增温幅度;B1情景下21世纪后30年伞球增温在冬季最高,De90和De07情景分别能够降低各个季节全球升温幅度的17%和10%左右.     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Evaluation of Total Precipitable Water from CRCM4 using the NVAP-MEaSUREs Dataset and ERA-Interim Reanalysis Data

The fourth-generation Canadian Regional Climate Model’s (CRCM4) precipitable water is evaluated and compared with observational data and ERA-Interim reanalysis data over five Canadian basins with simulations driven by ERA-Interim (two) and global climate models (two). Considering the 22 years of data available in the observations, we analyze precipitable water’s behaviour through its annual cycle, its daily distribution, and its annual daily maxima. For the simulations driven by reanalyses, differences in annual daily maximum values and their correlations with observations are examined. In general, the values for precipitable water simulated by CRCM4 are similar to those observed, and the model reproduces both the interannual and inter-basin variabilities. The simulation at 15 km resolution produces higher extreme values than simulations performed at 45 km resolution and higher than the observations taken at coarser resolution (1°), without much influence on the mean behaviour. Some underestimation is found with the simulation driven by the Canadian Centre for Climate Modelling and Analysis Model, version 3, a sign of a cold and dry bias, whereas the run driven by the European Centre Hamburg Model, version 5, is much closer to the observations, pointing to the importance of closely considering the regional–global model combination. Overall, CRCM4's ability to reproduce the major characteristics of observed precipitable water makes it a possible tool for providing precipitable water data that could serve as a basis for probable maximum precipitation and probable maximum flood studies at the basin scale.     

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada

We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973–1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10?km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.

Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX?>?25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45?km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability.     

Potential Implications of PCM Climate Change Scenarios for Sacramento–San Joaquin River Basin Hydrology and Water Resources

The potential effects of climate change on the hydrology and water resources of the Sacramento–San Joaquin River Basin were evaluated using ensemble climate simulations generated by the U.S. Department of Energy and National Center for Atmospheric Research Parallel Climate Model (DOE/NCAR PCM). Five PCM scenarios were employed. The first three were ensemble runs from 1995–2099 with a `business as usual' global emissions scenario, eachwith different atmospheric initializations. The fourth was a `control climate'scenario with greenhouse gas emissions set at 1995 levels and run through 2099. The fifth was a historical climate simulation forced with evolving greenhouse gas concentrations from 1870–2000, from which a 50-yearportion is taken for use in bias-correction of the other runs. From these global simulations, transient monthly temperature and precipitation sequences were statistically downscaled to produce continuous daily hydrologic model forcings, which drove a macro-scale hydrology model of theSacramento–San Joaquin River Basins at a 1/8-degree spatial resolution, and produceddaily streamflow sequences for each climate scenario. Each streamflow scenario was used in a water resources system model that simulated current and predicted future performance of the system. The progressive warming of the PCM scenarios (approximately 1.2 °C at midcentury, and 2.2 °C by the 2090s), coupled with reductions in winter and spring precipitation (from 10 to 25%), markedly reduced late spring snowpack (by as much as half on average by the end of the century). Progressive reductions in winter, spring, and summer streamflow were less severe in the northern part of the study domain than in the south, where a seasonality shift was apparent. Results from the water resources system model indicate that achieving and maintaining status quo (control scenario climate) system performance in the future would be nearly impossible, given the altered climate scenario hydrologies. The most comprehensive of the mitigation alternatives examined satisfied only 87–96% of environmental targets in the Sacramento system, and less than 80% in the San Joaquin system. It is evident that demand modification and system infrastructure improvements will be required to account for the volumetric and temporal shifts in flows predicted to occur with future climates in the Sacramento–San JoaquinRiver basins.     

Evaluation and response of winter cold spells over Western Europe in CMIP5 models

This paper is dedicated to the analysis of winter cold spells over Western Europe in the simulations of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). Both model biases and responses in a warming climate are discussed using historical simulations and the 8.5 W/m² Representative Concentration Pathway (RCP8.5) scenario, respectively on the 1979–2008 and 2070–2099 periods. A percentile-based index (10th percentile of daily minimum temperature, Q10) with duration and spatial extent criteria is used to define cold spells. Related diagnostics (intensity, duration, extent, and severity as a combination of the former three statistics) of 13 models are compared to observations and suggest that models biases on severity are mainly due to the intensity parameter rather than to duration and extent. Some hypotheses are proposed to explain these biases, that involve large-scale dynamics and/or radiative fluxes related to clouds. Evolution of cold spells characteristics by the end of the century is then discussed by comparing RCP8.5 and historical simulations. In line with the projected rise of mean temperature, “present-climate” cold spells (computed with the 1979–2008 10th percentile, Q10P) are projected to be much less frequent and, except in one model, less severe. When cold spells are defined from the future 10th percentile threshold (“future-climate” cold spells, Q10F), all models simulate a decrease of their intensity linearly related to the seasonal mean warming. Some insights are given to explain the inter-model diversity in the magnitude of the cold spells response. In particular, the snow-albedo feedback is suggested to play an important role, while for some models changes in large-scale dynamics are also not negligible.     

Climate change projections for the Texas High Plains and Rolling Plains

Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

     

Twenty-first century Arctic climate change in the CCSM3 IPCC scenario simulations

Arctic climate change in the Twenty-first century is simulated by the Community Climate System Model version 3.0 (CCSM3). The simulations from three emission scenarios (A2, A1B and B1) are analyzed using eight (A1B and B1) or five (A2) ensemble members. The model simulates a reasonable present-day climate and historical climate trend. The model projects a decline of sea-ice extent in the range of 1.4–3.9% per decade and 4.8–22.2% per decade in winter and summer, respectively, corresponding to the range of forcings that span the scenarios. At the end of the Twenty-first century, the winter and summer Arctic mean surface air temperature increases in a range of 4–14°C (B1 and A2) and 0.7–5°C (B1 and A2) relative to the end of the Twentieth century. The Arctic becomes ice-free during summer at the end of the Twenty-first century in the A2 scenario. Similar to the observations, the Arctic Oscillation (AO) is the dominant factor in explaining the variability of the atmosphere and sea ice in the 1870–1999 historical runs. The AO shifts to the positive phase in response to greenhouse gas forcings in the Twenty-first century. But the simulated trends in both Arctic mean sea-level pressure and the AO index are smaller than what has been observed. The Twenty-first century Arctic warming mainly results from the radiative forcing of greenhouse gases. The 1st empirical orthogonal function (explains 72.2–51.7% of the total variance) of the wintertime surface air temperature during 1870–2099 is characterized by a strong warming trend and a “polar amplification”-type of spatial pattern. The AO, which plays a secondary role, contributes to less than 10% of the total variance in both surface temperature and sea-ice concentration.     

Climate and climate change in western canada as simulated by the Canadian regional climate model

Abstract

A þrst climate simulation performed with the novel Canadian Regional Climate Model (CRCM) is presented. The CRCM is based on fully elastic non‐hydrostatic þeld equations, which are solved with an efþcient semi‐implicit semi‐Lagrangian (SISL) marching algorithm, and on the parametrization package of subgrid‐scale physical effects of the second‐generation Canadian Global Climate Model (GCMII). Two 5‐year integrations of the CRCM nested with GCMII simulated data as lateral boundary conditions are made for conditions corresponding to current and doubled CO₂ scenarios. For these simulations the CRCM used a grid size of 45 km on a polar‐stereographic projection, 20 scaled‐height levels and a time step of 15 min; the nesting GCMII has a spectral truncation of T32, 10 hybrid‐pressure levels and a time step of 20 min. These simulations serve to document: (1) the suitability of the SISL numerical scheme for regional climate modelling, (2) the use of GCMII physics at much higher resolution than in the nesting model, (3) the ability of the CRCM to add realistic regional‐scale climate information to global model simulations, and (4) the climate of the CRCM compared to that of GCMII under two greenhouse gases (GHG) scenarios.     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

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.     

Analysis of streamflow characteristics over Northeastern Canada in a changing climate

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.     

Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model

Two 30-year simulations corresponding to 1960-1989 and 2070-2099 have been performed with a variable resolution atmospheric model. The model has a maximum horizontal resolution of 0.5° over the Mediterranean Sea. Simulations are driven by IPCC-B2 scenario radiative forcing. Sea surface temperatures (SSTs) are prescribed from monthly observations for the present climate simulation, and from a blend of observations and coupled simulations for the scenario. Another pair of forced atmospheric simulations has been run under these forcings with the same uniform low resolution as the coupled model. Comparisons with observations show that the variable resolution model realistically reproduces the main climate characteristics of the Mediterranean region. At a global scale, changes in latitudinal temperature profiles are similar for the forced and coupled models, justifying the time-slice approach. The 2 m temperature and precipitation responses predict a warming and drying of the Mediterranean region. A comparison with the coupled simulation and forced low-resolution simulation shows that this pattern is robust. The decrease in mean precipitation is associated with a significant decrease in soil wetness, and could involve considerable impact on water resources around the Mediterranean basin.     

Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.