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.     

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

Abstract

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.     

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.     

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.     

The role of temperature in drought projections over North America

The effects of future temperature and hence evapotranspiration increases on drought risk over North America, based on ten current (1970–1999) and ten corresponding future (2040–2069) Regional Climate Model (RCM) simulations from the North American Regional Climate Change Assessment Program, are presented in this study. The ten pairs of simulations considered in this study are based on six RCMs and four driving Atmosphere Ocean Coupled Global Climate Models. The effects of temperature and evapotranspiration on drought risks are assessed by comparing characteristics of drought events identified on the basis of Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspration Index (SPEI). The former index uses only precipitation, while the latter uses the difference (DIF) between precipitation and potential evapotranspiration (PET) as input variables. As short- and long-term droughts impact various sectors differently, multi-scale (ranging from 1- to 12-month) drought events are considered. The projected increase in mean temperature by more than 2 °C in the future period compared to the current period for most parts of North America results in large increases in PET and decreases in DIF for the future period, especially for low latitude regions of North America. These changes result in large increases in future drought risks for most parts of the USA and southern Canada. Though similar results are obtained with SPI, the projected increases in the drought characteristics such as severity and duration and the spatial extent of regions susceptible to drought risks in the future are considerably larger in the case of SPEI-based analysis. Both approaches suggest that long-term and extreme drought events are affected more by the future increases in temperature and PET than short-term and moderate drought events, particularly over the high drought risk regions of North America.     

Singular vector decomposition of the internal variability of the Canadian Regional Climate Model

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.     

Climate change impacts on water management in the Puget Sound region, Washington State, USA

Climate change is projected to result, on average, in earlier snowmelt and reduced summer flows in the Pacific Northwest, patterns not well represented in historical observations used in water planning. We evaluate the sensitivities of water supply systems in the Puget Sound basin cities of Everett, Seattle, and Tacoma to historical and projected future streamflow variability and water demands. We simulate streamflow for the 2020s, 2040s, and 2080s using the distributed hydrology–soil–vegetation model (DHSVM), driven by downscaled ensembles of climate simulations archived from the 2007 IPCC Fourth Assessment Report. We use these streamflow predictions as inputs to reservoir system models for the three water supply systems. Over the next century, under average conditions all systems are projected to experience declines and eventual disappearance of the springtime snowmelt peak. How these shifts affect management depends on physical characteristics, operating objectives, and the adaptive capacity of each system. Without adaptations, average seasonal drawdown of reservoir storage is projected to increase in all three systems throughout the 21st century. Reliability of all systems in the absence of demand increases is robust through the 2020s however, and remains above 98% for Seattle and Everett in the 2040s and 2080s. With demand increases, however, reliability of the systems in their current configurations and with current operating policies progressively declines through the century.     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

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.     

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution part 2: historical and future simulations of precipitation

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer-scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet-day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.

     

Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900–2099

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5 °C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.     

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. II: Basin-Scale Results

We evaluate the capacity of a regional climate model to simulate the statistics of extreme events, and also examine the effect of differing horizontal resolution, at the scale of individual hydrological basins in the topographically complex province of British Columbia, Canada. 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 global reanalysis over the period 1973–1995. The simulations were evaluated with ANUSPLIN, a daily observational gridded surface temperature and precipitation product and with meteorological data recorded at 28 stations within the upper Peace, Nechako, and upper Columbia River basins. In this work, we focus largely on a comparison of the skill of each model configuration in simulating the 90th percentile of daily precipitation (PR90). The companion paper describes the results for a wider range of temperature and precipitation extremes over the entire WCan domain.

Over all three watersheds, both simulations exhibit cold biases compared with observations, with the bias exacerbated at higher resolution. Although both simulations generally display wet biases in median precipitation, CRCM15 features a reduced bias in PR90 in all three basins in summer and throughout the year in the upper Columbia River basin. However, the higher resolution model is inferior to CRCM45 with respect to rarer heavy precipitation events and also displays high spatial variability and lower spatial correlations with ANUSPLIN compared with the coarser resolution model. A reduction in the range of PR90 biases over the upper Columbia basin is noted when the 15?km results are averaged to the 45?km grid. This improvement is partly attributable to the averaging of errors between different elevation data used in the gridded observations and CRCM, but the sensitivity of CRCM15 to resolved topography is also clear from spatial maps of seasonal extremes. At the station scale, modest but systematic reductions in the bias of PR90 relative to ANUSPLIN are again found when the CRCM15 results are averaged to the 45?km grid. Furthermore, the annual cycle of inter-station spatial variance in the upper Columbia River basin is well reproduced by CRCM15 but not by ANUSPLIN or CRCM45. The former result highlights the beneficial effect of spatial averaging of small-scale climate variability, whereas the latter is evidently a demonstration of the added value at high resolution vis-à-vis the improved simulation of precipitation at the resolution limit of the model.     

Combining climatological and participatory approaches for assessing changes in extreme climatic indices at regional scale

This paper combines the climatological and societal perspectives for assessing future climatic extremes over Kangasabati River basin in India using an ensemble of four high resolution (25 km) regional climate model (RCM) simulations from 1970 to 2050. The relevant extreme indices and their thresholds are defined in consultation with stakeholders and are then compared using RCM simulations. To evaluate the performance of RCM in realistically representing atmospheric processes in the basin, model simulations driven with ERAInterim global re-analysis data from 1989 to 2008 are compared with observations. The models perform well in simulating seasonality, interannual variability and climatic extremes. Future climatic extremes are evaluated based on RCM simulations driven by GCMs, for present (1970–1999) and for the SRES A1B scenario for future (2021–2050) period. The analysis shows an intensification of majority of extremes as projected by future ensemble mean. The study suggests that there is a marked consistency in stakeholder observed changes in climate extremes and future predicted trends.     

Evaluation of Precipitation Indices over North America from Various Configurations of Regional Climate Models

This study presents the evaluation of simulations from two new Canadian regional climate models (RCMs), CanRCM4 and CRCM5, with a focus on the models’ skill in simulating daily precipitation indices and the Standardized Precipitation Index (SPI). The evaluation was carried out over the past two decades using several sets of gridded observations that partially cover North America. The new Canadian RCMs were also compared with four reanalysis products and six other RCMs. The different configurations of the Canadian RCM simulations also permit evaluation of the impact of different spatial resolutions, atmospheric drivers, and nudging conditions. The results from the new Canadian models show some improvement in precipitation characteristics over the previous Canadian RCM (CRCM4), but these differ with the seasons. For winter, CanRCM4 and CRCM5 have better skill than most other models over all of North America. For the summer, CRCM5 0.44° performs best over the United States, while CRCM4 has the best skill over Canada. Good skill is exhibited by CanRCM4 and CRCM4 in simulating the 6-month SPI over the Prairies and the western US Corn Belt. In general, differences are small between runs with or without large-scale spectral nudging; differences are small when different boundary conditions are used.     

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.     

Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California, under two emissions scenarios

A hydrologic model was driven by the climate projected by 11 GCMs under two emissions scenarios (the higher emission SRES A2 and the lower emission SRES B1) to investigate whether the projected hydrologic changes by 2071–2100 have a high statistical confidence, and to determine the confidence level that the A2 and B1 emissions scenarios produce differing impacts. There are highly significant average temperature increases by 2071–2100 of 3.7°C under A2 and 2.4°C under B1; July increases are 5°C for A2 and 3°C for B1. Two high confidence hydrologic impacts are increasing winter streamflow and decreasing late spring and summer flow. Less snow at the end of winter is a confident projection, as is earlier arrival of the annual flow volume, which has important implications on California water management. The two emissions pathways show some differing impacts with high confidence: the degree of warming expected, the amount of decline in summer low flows, the shift to earlier streamflow timing, and the decline in end-of-winter snow pack, with more extreme impacts under higher emissions in all cases. This indicates that future emissions scenarios play a significant role in the degree of impacts to water resources in California.     

Surface‐absorbed and top‐of‐atmosphere radiation fluxes for the Mackenzie River basin from satellite observations and a regional climate model and an evaluation of the model

Abstract

Both the earth‐reflected shortwave and outgoing longwave radiation (OLR) fluxes at the top of the atmosphere (TOA) as well as surface‐absorbed solar fluxes from Canadian Regional Climate Model (CRCM) simulations of the Mackenzie River Basin for the period March 2000 to September 2003 are compared with the radiation fluxes deduced from satellite observations. The differences between the model and satellite solar fluxes at the TOA and at the surface, which are used in this paper to evaluate the CRCM performance, have opposite biases under clear skies and overcast conditions, suggesting that the surface albedo is underestimated while cloud albedo is overestimated. The slightly larger differences between the model and satellite fluxes at the surface compared to those at the TOA indicate the existence of a small positive atmospheric absorption bias in the model. The persistent overestimation of TOA reflected solar fluxes and underestimation of the surface‐absorbed solar fluxes by the CRCM under all sky conditions are consistent with the overestimation of cloud fraction by the CRCM. This results in a larger shortwave cloud radiative forcing (CRF) both at the TOA and at the surface in the CRCM simulation. The OLR from the CRCM agrees well with the satellite observations except for persistent negative biases during the winter months under all sky conditions. Under clear skies, the OLR is slightly underestimated by the CRCM during the winter months and overestimated in the other months. Under overcast conditions the OLR is underestimated by the CRCM, suggesting an underestimation of cloud‐top temperature by the CRCM. There is an improvement in differences between model and satellite fluxes compared to previously reported results largely because of changes to the treatment of the surface in the model.     

Implementation of a large‐scale variable velocity river flow routing algorithm in the Canadian Regional Climate Model (CRCM)

Abstract

Implementation and validation of a flow routing scheme for the North American domain of the Canadian Regional Climate Model (CRCM) is described. A variable velocity flow routing algorithm is used to transport runoff from the land surface to the continental edges and provide freshwater flux forcing for the oceans. The flow routing scheme uses Manning's equation to estimate flow velocities for river channels whose cross‐sections are assumed to be rectangular. Discretization of major North American river basins and their flow directions are obtained at the polar stereographic resolution of the CRCM using 5‐minute global river flow direction data as a template. In the absence of observation‐based gridded estimates of runoff, model runoff estimates from a global simulation of the Variable Infiltration Capacity (VIC) hydrological model (forced with observationbased meteorological data) are used to validate the flow routing scheme. Model results show that the inclusion of flow routing improves the comparison with observation‐based streamflow estimates when compared to the unrouted runoff. Monthly comparison of simulated streamflow with observation‐based estimates, and basin‐wide averaged flow velocities, suggests that the flow routing scheme performs satisfactorily.     

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.