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1.
An overview of the PRUDENCE fine resolution climate model experiments for Europe is presented in terms of their climate change signals, in particular 2-meter temperature and precipitation. A comparison is made with regard to the seasonal variation in climate change response of the different models participating in the project. In particular, it will be possible to check how representative a particular PRUDENCE regional experiment is of the overall set in terms of seasonal values of temperature and precipitation. This is of relevance for such further studies and impact models that for practical reasons cannot use all the PRUDENCE regional experiments. This paper also provides some guidelines for how to select subsets of the PRUDENCE regional experiments according to such main sources of uncertainty in regional climate simulations as the choice of the emission scenario and of the driving global climate model.  相似文献   

2.
A regional ocean circulation model was used to project Baltic Sea climate at the end of the twenty-first century. A set of four scenario simulations was performed utilizing two global models and two forcing scenarios. To reduce model biases and to spin up future salinity the so-called Δ-change approach was applied. Using a regional coupled atmosphere–ocean model 30-year climatological monthly mean changes of atmospheric surface data and river discharge into the Baltic Sea were calculated from previously conducted time slice experiments. These changes were added to reconstructed atmospheric surface fields and runoff for the period 1903–1998. The total freshwater supply (runoff and net precipitation) is projected to increase between 0 and 21%. Due to increased westerlies in winter the annual mean wind speed will be between 2 and 13% larger compared to present climate. Both changes will cause a reduction of the average salinity of the Baltic Sea between 8 and 50%. Although salinity in the entire Baltic might be significantly lower at the end of the twenty-first century, deep water ventilation will very likely only slightly change. The largest change is projected for the secondary maximum of sea water age within the halocline. Further, the average temperature will increase between 1.9 and 3.2°C. The temperature response to atmospheric changes lags several months. Future annual maximum sea ice extent will decrease between 46 and 77% in accordance to earlier studies. However, in contrast to earlier results in the warmest scenario simulation one ice-free winter out of 96 seasons was found. Although wind speed changes are uniform, extreme sea levels may increase more than the mean sea level. In two out of four projections significant changes of 100-year surge heights were found.  相似文献   

3.
PRUDENCE simulations of the climate in Central Europe are analysed with respect to mean temperature, mean precipitation and three monthly mean geostrophic circulation indices. The three global models show important circulation biases in the control climate, in particular in the strength of the west-circulations in winter and summer. The nine regional models inherit much of the circulation biases from their host model, especially in winter. In summer, the regional models show a larger spread in circulation statistics, depending on nesting procedures and other model characteristics. Simulated circulation biases appear to have a significant inluence on simulated temperature and precipitation. The PRUDENCE ensemble appears to be biased towards warmer and wetter than observed circulations in winter, and towards warmer and dryer circulations in summer. A2-scenario simulations show important circulation changes, which have a significant impact on changes in the distributions of monthly mean temperature and precipitation. It is likely that interactions between land–surface processes and atmospheric circulation play an important role in the simulated changes in the summer climate in Central Europe.  相似文献   

4.
This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.  相似文献   

5.
Summary Efforts to understand and simulate the global climate in numerical models have led to regional studies of the energy and water balance. The Baltic Basin provides a continental scale test basin where meteorology, oceanography and hydrology all can meet. Using a simple conceptual approach, a large-scale hydrological model of the water balance of the total Baltic Sea Drainage Basin (HBV-Baltic) was used to simulate the basinwide water balance components for the present climate and to evaluate the land surface components of atmospheric climate models. It has been used extensively in co-operative BALTEX (The Baltic Sea Experiment) research and within SWECLIM (Swedish Regional Climate Modelling Programme) to support continued regional climate model development. This helps to identify inconsistencies in both meteorological and hydrological models. One result is that compensating errors are evident in the snow routines of the atmospheric models studied. The use of HBV-Baltic has greatly improved the dialogue between hydrological and meteorological modellers within the Baltic Basin research community. It is concluded that conceptual hydrological models, although far from being complete, play an important role in the realm of continental scale hydrological modelling. Atmospheric models benefit from the experience of hydrological modellers in developing simpler, yet more effective land surface parameterisations. This basic modelling tool for simulating the large-scale water balance of the Baltic Sea drainage basin is the only existing hydrological model that covers the entire basin and will continue to be used until more detailed models can be successfully applied at this scale. Received November 24, 2000 Revised April 4, 2001  相似文献   

6.
The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.  相似文献   

7.
Climate change impact on precipitation for the Amazon and La Plata basins   总被引：2，自引：0，他引：2  
We analyze the local and remote impacts of climate change on the hydroclimate of the Amazon and La Plata basins of South America (SA) in an ensemble of four 21st century projections (1970–2100, RCP8.5 scenario) with the regional climate model RegCM4 driven by the HadGEM, GFDL and MPI global climate models (GCMs) over the SA CORDEX domain. Two RegCM4 configurations are used, one employing the CLM land surface and the Emanuel convective schemes, and one using the BATS land surface and Grell (over land) convection schemes. First, we find considerable sensitivity of the precipitation change signal to both the driving GCM and the RegCM4 physics schemes (with the latter even greater than the first), highlighting the pronounced uncertainty of regional projections over the region. However, some improvements in the simulation of the annual cycle of precipitation over the Amazon and La Plata basins is found when using RegCM4, and some consistent change signals across the experiments are found. One is a tendency towards an extension of the dry season over central SA deriving from a late onset and an early retreat of the SA monsoon. The second is a dipolar response consisting of reduced precipitation over the broad Amazon and Central Brazil region and increased precipitation over the La Plata basin and central Argentina. An analysis of the relative influence on the change signal of local soil-moisture feedbacks and remote effects of Sea Surface Temperature (SST) over the Niño 3.4 region indicates that the former is prevalent over the Amazon basin while the latter dominates over the La Plata Basin. Also, the soil moisture feedback has a larger role in RegCM4 than in the GCMs.  相似文献   

8.
Anthropogenic greenhouse gas emissions are expected to lead to more frequent and intense summer temperature extremes, not only due to the mean warming itself, but also due to changes in temperature variability. To test this hypothesis, we analyse daily output of ten PRUDENCE regional climate model scenarios over Europe for the 2071–2100 period. The models project more frequent temperature extremes particularly over the Mediterranean and the transitional climate zone (TCZ, between the Mediterranean to the south and the Baltic Sea to the north). The projected warming of the uppermost percentiles of daily summer temperatures is found to be largest over France (in the region of maximum variability increase) rather than the Mediterranean (where the mean warming is largest). The underlying changes in temperature variability may arise from changes in (1) interannual temperature variability, (2) intraseasonal variability, and (3) the seasonal cycle. We present a methodology to decompose the total daily variability into these three components. Over France and depending upon the model, the total daily summer temperature variability is projected to significantly increase by 20–40% as a result of increases in all three components: interannual variability (30–95%), seasonal variability (35–105%), and intraseasonal variability (10–30%). Variability changes in northern and southern Europe are substantially smaller. Over France and parts of the TCZ, the models simulate a progressive warming within the summer season (corresponding to an increase in seasonal variability), with the projected temperature change in August exceeding that in June by 2–3 K. Thus, the most distinct warming is superimposed upon the maximum of the current seasonal cycle, leading to a higher intensity of extremes and an extension of the summer period (enabling extreme temperatures and heat waves even in September). The processes driving the variability changes are different for the three components but generally relate to enhanced land–atmosphere coupling and/or increased variability of surface net radiation, accompanied by a strong reduction of cloudiness, atmospheric circulation changes and a progressive depletion of soil moisture within the summer season. The relative contribution of these processes differs substantially between models.  相似文献   

9.
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10.
For the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), the recent version of the coupled atmosphere/ocean general circulation model (GCM) of the Max Planck Institute for Meteorology has been used to conduct an ensemble of transient climate simulations These simulations comprise three control simulations for the past century covering the period 1860–2000, and nine simulations for the future climate (2001–2100) using greenhouse gas (GHG) and aerosol concentrations according to the three IPCC scenarios B1, A1B and A2. For each scenario three simulations were performed. The global simulations were dynamically downscaled over Europe using the regional climate model (RCM) REMO at 0.44° horizontal resolution (about 50 km), whereas the physics packages of the GCM and RCM largely agree. The regional simulations comprise the three control simulations (1950–2000), the three A1B simulations and one simulation for B1 as well as for A2 (2001–2100). In our study we concentrate on the climate change signals in the hydrological cycle and the 2 m temperature by comparing the mean projected climate at the end of the twenty-first century (2071–2100) to a control period representing current climate (1961–1990). The robustness of the climate change signal projected by the GCM and RCM is analysed focussing on the large European catchments of Baltic Sea (land only), Danube and Rhine. In this respect, a robust climate change signal designates a projected change that sticks out of the noise of natural climate variability. Catchments and seasons are identified where the climate change signal in the components of the hydrological cycle is robust, and where this signal has a larger uncertainty. Notable differences in the robustness of the climate change signals between the GCM and RCM simulations are related to a stronger warming projected by the GCM in the winter over the Baltic Sea catchment and in the summer over the Danube and Rhine catchments. Our results indicate that the main explanation for these differences is that the finer resolution of the RCM leads to a better representation of local scale processes at the surface that feed back to the atmosphere, i.e. an improved representation of the land sea contrast and related moisture transport processes over the Baltic Sea catchment, and an improved representation of soil moisture feedbacks to the atmosphere over the Danube and Rhine catchments.  相似文献   

11.
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   

12.
Regional climate model simulations with RegCM3 were performed to investigate how future land-cover/land-use (LCLU) change in Montane Mainland Southeast Asia (MMSEA) could affect regional climate. Simulation land-surface parameterizations included present day and plausible 2050 land-covers, as well as two extreme deforestation simulations. In the simulations, the original land cover map of RegCM3, based on AVHRR 1992–93 observations, was replaced with one obtained from MODIS 2001 observations; and the model was set to work at two different spatial resolutions using the sub-grid feature of the land surface model: 27.79 km for the atmosphere and 9.26 km for the land surface. During validation, modeled precipitation closely matched observed precipitation over southern China, but underestimated precipitation in the Indochina Peninsula. The plausible 2050 LCLU simulation predicted little change in regional climate. However, an extreme irrigated crop parameterization caused precipitation to increase slightly in the Indochina Peninsula, decrease substantially in southeastern China, and increase significantly in the South China Sea. The extreme short-grass parameterization caused substantial precipitation decreases in MMSEA, but few changes elsewhere. These simulations indicate in order for significant climatological changes to occur, substantially more LCLU conversion is required than the 16 % change we incorporated into the plausible 2050 land-cover scenario.  相似文献   

13.
A subgrid parameterization of orographic precipitation   总被引：6，自引：0，他引：6  
Summary Estimates of the impact of global climate change on land surface hydrology require climate information on spatial scales far smaller than those explicitly resolved by global climate models of today and the foreseeable future. To bridge the gap between what is required and what is resolved, we propose a subgrid-scale parameterization of the influence of topography on clouds, precipitation, and land surface hydrology. The parameterization represents subgrid variations in surface elevation in terms of probability distributions of discrete elevation classes. Separate cloud, radiative, and surface processes are calculated for each elevation class. Rainshadow effects are not treated by the parameterization; they have to be explicitly resolved by the host model. The simulated surface temperature, precipitation, and snow cover for each elevation class are distributed to different geographical locations according to the spatial distribution of surface elevation within each grid cell.The subgrid parameterization has been implemented in the Pacific Northwest Laboratory's climate version of the Penn State/NCAR Mesoscale Model. The scheme is evaluated by driving the regional climate model with observed lateral boundary conditions for the Pacific Northwest and comparing simulated fields with surface observations. The method yields more realistic spatial distributions of precipitation and snow cover in mountainous areas and is considerably more computationally efficient than achieving high resolution by the use of nesting in the regional climate model.With 17 Figures  相似文献   

14.
In order to perform hydrological studies on the PRUDENCE regional climate model (RCM) simulations, a special focus was put on the discharge from large river catchments located in northern and central Europe. The discharge was simulated with a simplified land surface (SL) scheme and the Hydrological Discharge (HD) model. The daily fields of precipitation, 2 m temperature and evapotranspiration from the RCM simulations were used as forcing. Therefore the total catchment water balances are constrained by the hydrological cycle of the different RCMs. The validation of the simulated hydrological cycle from the control simulations shows that the multi-model ensemble mean is closer to the observations than each of the models, especially if different catchments and hydrological variables are considered. Therefore, the multi-model ensemble mean can be used to largely reduce the uncertainty that is introduced by a single RCM. This also provides more confidence in the future projections for the multi-model ensemble means. The scenario simulations predict a gradient in the climate change signal over Northern and Central Europe. Common features are the overall warming and the general increase of evapotranspiration. But while in the northern parts the warming will enhance the hydrological cycle leading to an increased discharge, the large warming, especially in the summer, will slow down the hydrological cycle caused by a drying in the central parts of Europe which is accompanied by a reduction of discharge. The comparison of the changes predicted by the multi-model ensemble mean to the changes predicted by the driving GCM indicates that the RCMs can compensate problems that a driving GCM may have with local scale processes or parameterizations.  相似文献   

15.
Present and future climatologies in the phase I CREMA experiment   总被引：1，自引：0，他引：1  
We provide an overall assessment of the surface air temperature and precipitation present day (1976–2005) and future (2070–2099) ensemble climatologies in the Phase I CREMA experiment. This consists of simulations performed with different configurations (physics schemes) of the ICTP regional model RegCM4 over five CORDEX domains (Africa, Mediterranean, Central America, South America, South Asia), driven by different combinations of three global climate models (GCMs) and two greenhouse gas (GHG) representative concentration pathways (RCP8.5 and RCP4.5). The biases (1976–2005) in the driving and nested model ensembles compared to observations show a high degree of spatial variability and, when comparing GCMs and RegCM4, similar magnitudes and more similarity for precipitation than for temperature. The large scale patterns of change (2070–2099 minus 1976–2005) are broadly consistent across the GCM and RegCM4 ensembles and with previous analyses of GCM projections, indicating that the GCMs selected in the CREMA experiment are representative of the more general behavior of current GCMs. The RegCM4, however, shows a lower climate sensitivity (reduced warming) than the driving GCMs, especially when using the CLM land surface scheme. While the broad patterns of precipitation change are consistent across the GCM and RegCM4 ensembles, greater differences are found at sub-regional scales over the various domains, evidently tied to the representation of local processes. This paper serves to provide a reference view of the behavior of the CREMA ensemble, while more detailed and process-based analysis of individual domains is left to companion papers of this special issue.  相似文献   

16.
土地利用变化对我国区域气候影响的数值试验   总被引：29，自引：0，他引：29  
使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,通过将中国区域植被覆盖由理想状况改变为实际状况的数值试验对比分析,探讨了当代中国土地利用变化对中国区域气候的影响,并对结果进行了统计显著性检验。研究表明,土地利用的变化,会导致我国西北等地区年平均降水减少,导致年平均气温在内陆部分地区升高和在沿海个别地区降低,引起许多地方夏季日平均最高气温升高,而冬季日平均最低气温则在我国东部部分地区降低的同时在西北地区升高,土壤湿度的变化表现为大范围的降低。研究同时表明,相同的土地变化在不同的地理环境下引起的气候要素变化有一定的不一致性。  相似文献   

17.
Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.  相似文献   

18.
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.  相似文献   

19.
An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.  相似文献   

20.
Storm surges in the Western Baltic Sea: the present and a possible future   总被引：3，自引：1，他引：2  
Globally-coupled climate models are generally capable of reproducing the observed trends in the globally averaged atmospheric temperature or mean sea level. However, the global models do not perform as well on regional/local scales. Here, we present results from four 100-year ocean model experiments for the Western Baltic Sea. In order to simulate storm surges in this region, we have used the General Estuarine Transport Model (GETM) as a high-resolution local model (spatial resolution ≈ 1?km), nested into a regional atmospheric and regional oceanic model in a fully baroclinic downscaling approach. The downscaling is based on the global model ECHAM5/MPI-OM. The projections are imbedded into two greenhouse-gas emission scenarios, A1B and B1, for the period 2000–2100, each with two realisations. Two control runs from 1960 to 2000 are used for validation. We use this modelling system to statistically reproduce the present distribution of surge extremes. The usage of the high-resolution local model leads to an improvement in surge heights of at least 10% compared to the driving model. To quantify uncertainties associated with climate projections, we investigate the impact of enhanced wind velocities and changes in mean sea levels. The analysis revealed a linear dependence of surge height and mean sea level, although the slope parameter is spatially varying. Furthermore, the modelling system is used to project possible changes within the next century. The results show that the sea level rise has greater potential to increase surge levels than does increased wind speed. The simulations further indicate that the changes in storm surge height in the scenarios can be consistently explained by the increase in mean sea level and variation in wind speed.  相似文献   

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