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1.
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.  相似文献   

2.
This study analyzes the uncertainty of seasonal (winter and summer) precipitation extremes as simulated by a recent version of the Canadian Regional Climate Model (CRCM) using 16 simulations (1961–1990), considering four sources of uncertainty from: (a) the domain size, (b) the driving Atmosphere–Ocean Global Climate Models (AOGCM), (c) the ensemble member for a given AOGCM and (d) the internal variability of the CRCM. These 16 simulations are driven by 2 AOGCMs (i.e. CGCM3, members 4 and 5, and ECHAM5, members 1 and 2), and one set of re-analysis products (i.e. ERA40), using two domain sizes (AMNO, covering all North America and QC, a smaller domain centred over the Province of Québec). In addition to the mean seasonal precipitation, three seasonal indices are used to characterize different types of variability and extremes of precipitation: the number of wet days, the maximum number of consecutive dry days, and the 95th percentile of daily precipitation. Results show that largest source of uncertainty in summer comes from the AOGCM selection and the choice of domain size, followed by the choice of the member for a given AOGCM. In winter, the choice of the member becomes more important than the choice of the domain size. Simulated variance sensitivity is greater in winter than in summer, highlighting the importance of the large-scale circulation from the boundary conditions. The study confirms a higher uncertainty in the simulated heavy rainfall than the one in the mean precipitation, with some regions along the Great Lakes—St-Lawrence Valley exhibiting a systematic higher uncertainty value.  相似文献   

3.
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.  相似文献   

4.
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.  相似文献   

5.
An updated version of the Canadian Regional Climate Model (CRCM-II) has been used to perform time-slice simulations over northwestern North America, nested in the coupled Canadian General Circulation Model (CGCM2). Both driving and driven models are integrated in a scenario of transient greenhouse gases (GHG) and aerosols. The time slices span three decades that were chosen to correspond roughly to single, double and triple current GHG concentration levels. Several enhancements have been implemented in CRCM-II since the CRCM-I climate-change simulations reported upon earlier. The larger computational domain, extending further to the west, north and south, allows for a better spin-up of weather systems as they enter the regional domain. The increased length of the simulations, from 5 to 10 years, strengthens the statistical robustness of the results. The improvements to the physical parameterisation, notably the moist convection scheme and the diagnostic cloud formulation, cure the excessive cloud cover problem present in CRCM-I, reduce the warm surface bias and prevent the occurrence of grid-point precipitation storms that occurred with CRCM-I in summer. The dynamical ocean and sea-ice components of CGCM2 that is used to provide atmospheric lateral and surface boundary conditions to CRCM-II, as well as the use of transient rather than equilibrium conditions of GHG and the inclusion of direct aerosols forcing, in both CGCM2 and CRCM-II, increase the realism of the CRCM-II climate-change simulation.  相似文献   

6.
Evaluation of uncertainties in the CRCM-simulated North American climate   总被引：2，自引：2，他引：0  
This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US.  相似文献   

7.
The scaled-decomposed atmospheric water budget over North America is investigated through the analysis of 25 years of simulation by the Canadian Regional Climate Model (CRCM) driven by the NCEP–NCAR reanalyses for the period 1975–1999. The time average and time variability of the atmospheric water budget for the winter and summer seasons are decomposed into their large-scale and small-scale components to identify the added value of the regional model. For the winter season, the intra-seasonal transient-eddy variance is the main temporal variability. The large- and small-scale terms are of the same order of magnitude, and are large over both coasts and weak over the continent. For the summer season, the time–mean atmospheric water budget is rather different to that of winter, with maximum values over the south-eastern part of the continent. The summer intra-seasonal variance is about twice stronger than in winter and also dominates the variability, but the inter-monthly variance is non-negligible and can be in part associated to North American Monsoon System. Over the continent, the intra-seasonal climatological variance is dominated by the variability of the small scales. The small scales, that is those scales that are only resolved in the regional model but not in the reanalyses, contribute to the added value in a regional climate simulation. In the winter season, the added value of the CRCM is large and dominated by oceanic forcing, while in summer, it is dominant (larger than the large scales) and controlled mainly by convective processes.  相似文献   

8.
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.  相似文献   

9.
The Climate System Model (CSM) and the Parallel Climate Model (PCM), two coupled global climate models without flux adjustments recently developed at NCAR, were used to simulate the 20th century climate using historical greenhouse gas and sulfate aerosol forcing. These simulations were extended through the 21st century under two newly developed scenarios, a business-as-usual case (BAU, CO2≈710 ppmv in 2100) and a CO2 stabilization case (STA550, CO2≈540 ppmv in 2100). The simulated changes in temperature, precipitation, and soil moisture over the Asia-Pacific region (10°-60°N, 55°-155°E) are analyzed, with a focus on the East Asian summer monsoon rainfall and climate changes over the upper reaches of the Yangtze River. Under the BAU scenario, both the models produce surface warming of about 3-5℃ in winter and 2-3℃ in summer over most Asia. Under the STA550 scenario, the warming is reduced by 0.5-1.0℃ in winter and by 0.5℃ in summer. The warming is fairly uniform at the low latitudes and does not induce significant changes in the zonal mean Hadley circulation over the Asia-Pacific do main. While the regional precipitation changes from single CSM integrations are noisy, the PCM ensemble mean precipitation shows 10%-30% increases north of ～ 30°N and ～ 10% decreases south of ～ 30°N over the Asia-Pacific region in winter and 10%-20% increases in summer precipitation over most of the region. Soil moisture changes are small over most Asia. The CSM single simulation suggests a 30% increase in river runoff into the Three Gorges Dam, but the PCM ensemble simulations show small changes in the runoff.  相似文献   

10.
Climate change caused by anthropogenic activities has generated a variety of research focusing on investigating the past climate, predicting the future climate and quantifying the change in climate extreme events by using different climate models. Climate extreme events are valuable to evaluate the potential impact of climate change on human activities, agriculture and economy and are also useful to monitor the climate change on global scale. Here, a Regional Climate Model (RCM) simulation is used to study the future variations in the temperature extreme indices, particularly change in frequency of warm and cold spells duration over Pakistan. The analyses are done on the basis of simulating two 30 years simulations with the Hadley Center’s RCM PRECIS, at a horizontal resolution of 50 km. Simulation for the period 1961–1990 represents the recent climate and simulation for the period 2071–2100 represents the future climate. These simulations are driven by lateral boundary conditions from HadAM3P GCM of Hadley centre UK. For the validation of model, observed mean, maximum and minimum temperatures for the period 1961–1990 at all the available stations in Pakistan are first averaged and are then compared with the PRECIS averaged grid-box data. Also the observed monthly gridded data set of Climate Research Unit (UK) data is used to validate the model. Temperature indices in the base period as well as in future are then calculated and the corresponding change is observed. Percentile based spatial change of temperature shows that in summer, increase in daily minimum temperature is more as compared to the increase of daily maximum temperature whereas in winter, the change in maximum temperature is high. The occurrence of annual cold spells shows significantly decreasing trend while for warm spells there is slight increasing trend over Pakistan.  相似文献   

11.
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.  相似文献   

12.
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.  相似文献   

13.
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.  相似文献   

14.
Given the coarse resolution of global climate models, downscaling techniques are often needed to generate finer scale projections of variables affected by local-scale processes such as precipitation. However, classical statistical downscaling experiments for future climate rely on the time-invariance assumption as one cannot know the true change in the variable of interest, nor validate the models with data not yet observed. Our experimental setup involves using the Canadian regional climate model (CRCM) outputs as pseudo-observations to estimate model performance in the context of future climate projections by replacing historical and future observations with model simulations from the CRCM, nested within the domain of the Canadian global climate model (CGCM). In particular, we evaluated statistically downscaled daily precipitation time series in terms of the Peirce skill score, mean absolute errors, and climate indices. Specifically, we used a variety of linear and nonlinear methods such as artificial neural networks (ANN), decision trees and ensembles, multiple linear regression, and k-nearest neighbors to generate present and future daily precipitation occurrences and amounts. We obtained the predictors from the CGCM 3.1 20C3M (1971–2000) and A2 (2041–2070) simulations, and precipitation outputs from the CRCM 4.2 (forced with the CGCM 3.1 boundary conditions) as predictands. Overall, ANN models and tree ensembles outscored the linear models and simple nonlinear models in terms of precipitation occurrences, without performance deteriorating in future climate. In contrast, for the precipitation amounts and related climate indices, the performance of downscaling models deteriorated in future climate.  相似文献   

15.
This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23?years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates that the proposed weighting factors reflect well all five attributes and the performances of weighted averaged references are better than that of the best single model. This study also found that the improvement of WARs’ performance is due to the reliability (accuracy) of RCMs rather than the ensemble size.  相似文献   

16.
Under recent Arctic warming, boreal winters have witnessed severe cold surges over both Eurasia and North America, bringing about serious social and economic impacts. Here, we investigated the changes in daily surface air temperature (SAT) variability during the rapid Arctic warming period of 1988/89–2015/16, and found the daily SAT variance, mainly contributed by the sub-seasonal component, shows an increasing and decreasing trend over eastern Eurasia and North America, respectively. Increasing cold extremes (defined as days with daily SAT anomalies below 1.5 standard deviations) dominated the increase of the daily SAT variability over eastern Eurasia, while decreasing cold extremes dominated the decrease of the daily SAT variability over North America. The circulation regime of cold extremes over eastern Eurasia (North America) is characterized by an enhanced high-pressure ridge over the Urals (Alaska) and surface Siberian (Canadian) high. The data analyses and model simulations show the recent strengthening of the high-pressure ridge over the Urals was associated with warming of the Barents–Kara seas in the Arctic region, while the high-pressure ridge over Alaska was influenced by the offset effect of Arctic warming over the East Siberian–Chukchi seas and the Pacific decadal oscillation (PDO)–like sea surface temperature (SST) anomalies over the North Pacific. The transition of the PDO-like SST anomalies from a positive to negative phase cancelled the impact of Arctic warming, reduced the occurrence of extreme cold days, and possibly resulted in the decreasing trend of daily SAT variability in North America. The multi-ensemble simulations of climate models confirmed the regional Arctic warming as the driver of the increasing SAT variance over eastern Eurasia and North America and the overwhelming effect of SST forcing on the decreasing SAT variance over North America. Therefore, the regional response of winter cold extremes at midlatitudes to the Arctic warming could be different due to the distinct impact of decadal SST anomalies.  相似文献   

17.
The projected temperature and precipitationchange under different emissions scenarios using Coupled Model Intercomparison Project Phase 5 models over the northwestern arid regions of China(NWAC) were analyzed using the ensemble of three high-resolution dynamical downscaling simulations: the simulation of the Regional Climate Model version 4.0(Reg CM4) forced by the Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1); the Hadley Centre Global Environmental Model version 3 regional climate model(Had GEM3-RA) forced by the Atmosphere-Ocean coupled Had GEM version 2(Had GEM2-AO); and the Weather Research and Forecasting(WRF) model forced by the Norwegian community Earth System Model(Nor ESM1-M). Model validation indicated that the multimodel simulations reproduce the spatial and temporal distribution of temperature and precipitation well. The temperature is projected to increase over NWAC under both the 4.5 and 8.5 Representative Concentration Pathways scenarios(RCP4.5 and RCP8.5, respectively) in the middle of the 21 st century, but the warming trend is larger under the RCP8.5 scenario. Precipitation shows a significant increasing trend in spring and winter under both RCP4.5 and RCP8.5; but in summer, precipitation is projected to decrease in the Tarim Basin and Junggar Basin. The regional averaged temperature and precipitation show increasing trends in the future over NWAC; meanwhile, the large variability of the winter mean temperature and precipitation may induce more extreme cold events and intense snowfall events in these regions in the future.  相似文献   

18.
Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.

The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.

The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes.  相似文献   


19.
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.  相似文献   

20.
Multiyear (1983?C2006) hindcast simulation of summer monsoon over South Asia has been carried out using the regional climate model of the Beijing Climate Centre (BCC_RegCM1.0). The regional climate model (hereafter BCC RCM) is nested into the global climate model of the Beijing Climate Centre BCC_CGCM1.0 (here after CGCM). The regional climate model is initialized on 01 May and integrated up to the end of the September for 24?years. Compared to the driving CGCM the BCC RCM reproduces reasonably well the intensity and magnitude of the large-scale features associated with the South Asia summer monsoon such as the upper level anticyclone at 200?hPa, the mid-tropospheric warming over the Tibetan plateau, the surface heat low and the 850?hPa moisture transport from ocean to the land. Both models, i.e., BCC RCM and the driving CGCM overestimates (underestimates) the 850?hPa southwesterly flow over the northern (southern) Arabian Sea. Moreover, both models overestimate the seasonal mean precipitation over much of the South Asia region compared to the observations. However, the precipitation biases are significantly reduced in the BCC RCM simulations. Furthermore, both models simulate reasonably the interannual variability of the summer monsoon over India. The precipitation index simulated by BCC RCM shows significant correlation (0.62) with the observed one. The BCC RCM simulates reasonably well the spatial and temporal variation of the precipitation and surface air temperature compared to the driving CGCM. Further, the temperature biases are significantly reduced (1?C4°C) in the BCC RCM simulations. The simulated vertical structure of the atmosphere show biases above the four sub-regions, however, these biases are significantly reduced in the BCC RCM simulations compared to the driving CGCM. Compared to the driving CGCM, the evolution processes of the onset of summer monsoon, e.g., the meridional temperature gradient and the vertical wind shear are well simulated by the BCC RCM. The 24-year simulations also show that with a little exception the BCC RCM is capable to reproduce the monsoon active and break phases and the intraseasonal precipitation variation over the Indian subcontinent.  相似文献   

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