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1.
Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (?22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.  相似文献   

2.
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   

3.
Although uncertainties are still large, many potentially dangerous effects have already been identified concerning the impacts of global warming on human societies. For example, the record-breaking 2003 summer heat wave in Europe has given a glimpse of possible future European climate conditions. Here we use an ensemble of regional climate simulations for the end of the twentieth and twenty-first centuries over Europe to show that frequency, length and intensity changes in warm and cold temperature extremes can be derived to a close approximation from the knowledge of changes in three central statistics, the mean, standard deviation and skewness of the Probability Distribution Function, for which current climate models are better suited. In particular, the effect of the skewness parameter appears to be crucial, especially in the case of cold extremes, since it mostly explains the relative warming of these events compared to the whole distribution. An application of this finding is that the future impacts of extreme heat waves and cold spells on non-climatological variables (e.g., mortality) can be estimated to a first-order approximation from observed time series of daily temperature transformed in order to account for simulated changes in these three statistics.  相似文献   

4.
In the field of climate change impact analysis, bidirectional changes in projections of future wind regimes varying among studies, locations, and models have been described in the literature, which is understandable from a global perspective. However, we should attempt to find evidence in the historical record to support these projections. This paper attempts to address this issue by analyzing historical wind gust observations for up to 57 years (1953–2009) over Canada. Two wind gust analysis techniques were used: the speed of daily wind gust events ≥50?km?h?1 was compared with (1) the climatological daily temperature anomaly and (2) the climatological daily sea level air pressure anomaly. In addition, the frequency of daily wind gust events ≥90?km?h?1 was compared with both daily temperature and pressure anomalies. The results indicate that during the past five decades gust wind speed over Canada increased significantly as the daily temperature anomaly increased and the daily pressure anomaly decreased. About 50–60% of daily wind gust events ≥90?km?h?1 occurred with positive daily temperature anomalies and negative daily pressure anomalies. One major conclusion is that the methods used in and results derived from this study might be applied to climate change impact analysis to support projections of future wind regimes.  相似文献   

5.
This study compares the surface wind speed and forest damage data of two exceptionally severe winter storms, Vivian 1990 and Lothar 1999. The study area comprises the region that suffered damage in Switzerland. The wind speed data were derived from simulations of MeteoSwiss (Federal Office of Meteorology and Climatology), measurements during the storm periods and expert analyses of the data. The remotely sensed forest damage data were provided by the Federal Office for the Environment and the forest cover data by Swiss Federal Statistical Office. We compared data on the peak gust and maximum average wind speed, with data on the spatially related forest area and forest damage area, and found some clear differences in the correlations between the different wind data and forest damage. Our results point generally to the damage-causing role of near-surface gusts at maximum wind speeds during the storm. These tended to be spatially distributed on a fine scale. In only a few cases were the results statistically significant. However, these results could probably be improved with better wind data. For example, gust measurements spatially closer to forests or simulations of gusts at maximum wind speed could be produced with a spatially higher resolution.  相似文献   

6.
近50年中国风速变化多气候模式模拟检验   总被引：3，自引：0，他引：3  
江滢  罗勇  赵宗慈 《气象学报》2009,67(6):923-934
近年来,随着气候模式研究的快速发展,全球气候模式在模拟20世纪气候和气候变化特征,尤其是在模拟温度、降水等要素特征和变化及其人类活动对这些要素的影响等方面取得了丰硕的成果.然而,全球气候模式对近地层风速的模拟情况如何,目前仍缺少分析和检验.本文利用中国区域近地层风速观测资料,检验评估了参与IPCC AR4"20世纪气候耦合模式模拟"(20C3M)的19个伞球气候模式和国家气候中心新一代伞球气候模式(BCC_CSM1.0.1)模拟的1956-1999年中国近地层(10m)风速及其变化的模拟能力.研究发现,20个伞球气候模式基本上都能模拟出中国多年年(或季)平均风速分布状况,但模式模拟的平均风速一般小于观测值,尤以观测风速较大的北部和西北部地区模拟值偏小显著.气候模式模拟秋冬季风速分布的能力强于模拟夏春季的能力.模式基本上能模拟出冬、春季平均风速大于夏、秋季平均风速,但是模拟不出春、冬、夏、秋季平均风速依次减小的季节变化特征.模式及模式集成难以模拟出观测到的近50年中国年(或季)平均风速明显减小的变化趋势,少数模式能模拟出年(或季)平均风速略呈减小的变化趋势,但与观测值比相差约一个量级.模式对北部和西南部地区平均风速的变化模拟效果较好,而模式难以模拟东南-南部地区风速变化特征.  相似文献   

7.
This paper reports on a method using composites for studying synoptic conditions of a series of windstorm events selected on the basis of maximum wind speeds in Switzerland. The composite storm-averaged conditions indicate how flow fields, as well as related surface conditions, are organised so as to produce high wind speeds near the surface. On average, high winds in Switzerland, mainly generated by transient synoptic-scale eddies, are characterised by a minimum in the mean sea level pressure field over southern Norway, anticyclonic conditions south of 35°N and a steep pressure gradient over continental western Europe. The geopotential aloft has a predominant zonal structure, producing high winds between 45°N and 50°N over the eastern Atlantic and further inland; the jet stream has its maximum speed at 50°N over the Celtic Sea and Brittany at 250?hPa. Close to the surface, large temperature contrasts between the warm waters of the Atlantic Ocean and Mediterranean Sea and the cooler continent are diagnosed. The results thus obtained differ to those produced by other methods based on the analysis of deep cyclones or of strong vorticity in the northern North Atlantic Ocean basin. Differences of the composite mean synoptic conditions for current (1961?C1990) and future climate (2071?C2100) as simulated by the Global Climate Model HadAM3H in the context of the EU PRUDENCE project indicate that windstorms in a warmer world are generated by a subtle modification of the atmospheric baroclinicity, especially over the ocean and where greater ocean-continent temperature contrasts are simulated during winters. However, there are no signs of reduced storm activity as the climate warms by the end of the twenty-first century.  相似文献   

8.
Fine-resolution regional climate simulations of tropical cyclones (TCs) are performed over the eastern Australian region. The horizontal resolution (30 km) is fine enough that a good climatological simulation of observed tropical cyclone formation is obtained using the observed tropical cyclone lower wind speed threshold (17 m s–1). This simulation is performed without the insertion of artificial vortices (bogussing). The simulated occurrence of cyclones, measured in numbers of days of cyclone activity, is slightly greater than observed. While the model-simulated distribution of central pressures resembles that observed, simulated wind speeds are generally rather lower, due to weaker than observed pressure gradients close to the centres of the simulated storms. Simulations of the effect of climate change are performed. Under enhanced greenhouse conditions, simulated numbers of TCs do not change very much compared with those simulated for the current climate, nor do regions of occurrence. There is a 56% increase in the number of simulated storms with maximum winds greater than 30 m s–1 (alternatively, a 26% increase in the number of storms with central pressures less than 970 hPa). In addition, there is an increase in the number of intense storms simulated south of 30°S. This increase in simulated maximum storm intensity is consistent with previous studies of the impact of climate change on tropical cyclone wind speeds.  相似文献   

9.
The possible change in the characteristics of weather in the future should be considered as important as the mean climate change because the increasing risk of extremes is related to the variability on daily time scales. The weather characteristics can be represented by the climatological mean interdiurnal (day-to-day) variability (MIDV). This paper first assessed the phase five of the Coupled Model Intercomparison Project coupled climate models’ capability to represent MIDV for the surface maximum and minimum temperature, surface wind speed and precipitation under the present climate condition. Based on the assessment, we selected three best models for projecting future change. We found that the future changes in MIDV are characterized by: (a) a marked reduction in surface maximum and minimum temperature over high latitudes during the cold season; (b) a stronger reduction in the surface minimum temperature than in the maximum temperature; (c) a reduction in surface wind speed over large parts of lands in Northern Hemisphere (NH) during NH spring; (d) a noticeable increase in precipitation in NH mid-high latitudes in NH spring and winter, and in particular over East Asia throughout most of the year.  相似文献   

10.
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   

11.
浙江省几种灾害性大风近地面阵风系数特征   总被引：1，自引：1，他引：0       下载免费PDF全文
阵风特性研究是大风预报和服务的基础。基于2011-2013年浙江省自动气象站逐日逐10 min测风资料,分析了浙江省陆地和近海海面冷空气、热带气旋和强对流大风的阵风系数特征。结果表明:冷空气和热带气旋大风阵风系数空间分布基本相同,大风主要发生在近海海面和沿海地区,海面阵风系数一般小于1.5,等值线平行于海岸线且自西向东逐渐减小,陆地阵风系数一般大于2.0,山区可超过3.0,表现出地形对阵风系数的增强作用。强对流大风阵风系数明显高于业务规范平均值,发生地点遍及浙江省各地,但发生概率超过10%的站点主要位于沿海地区和近海海面。风向基本不影响阵风系数空间分布。冷空气和热带气旋站点阵风系数与海拔高度有较高正相关性。模糊聚类分析发现:浙江省400 m以上山区站与70 m以下的低海拔站点在阵风系数特征上分属不同空间类型;基于逐步回归建立站点阵风系数预报模型,检验表明:模糊聚类可帮助提高模型阵风系数预报能力。  相似文献   

12.
对2017年春季黑龙江省大、小兴安岭林区的6个代表站点10 m风场进行降尺度分析,并结合观测数据对比分析了WRF模式和CALMET降尺度模式的10 m风速、风向预报结果。结果表明：两模式逐小时风速预报与观测的相关系数为0.5-0.7,且随着风速的增加,模式的预报准确率逐渐提高,夜间的风速预报偏差较大,进入白天后,偏差明显减小。WRF模式对风速变化趋势的预报效果优于CALMET模式,与观测的风速相关性更高,而CALMET模式对较大风速的预报效果优于WRF模式。在风向预报方面,WRF和CALMET的风向模拟与观测风向均有较好的一致性,模式预报准确率较高的两个风向也刚好对应各站的盛行风向。同时,本文用回归方法对日平均风速进行订正发现,订正后各站的日平均风速预报准确率平均提高了50%,具有较好的业务应用价值。  相似文献   

13.
采用分位数映射（Quantile Mapping, QM）和delta分位数映射（Quantile Delta Mapping, QDM）两种误差订正方法对区域气候模式RegCM4在中国区域内模拟的逐日气温和降水数据进行订正。模式数据是5种不同全球气候模式驱动下的区域模式气候变化模拟结果。计算订正前后的极端气候指数进行对比分析,包括日最高气温极大值（TXx）、日最低气温极小值（TNn）、连续干旱日数（CDD）和最大日降水量（RX1day）。结果表明,5组模拟结果和其集合平均（ensR）都显示气温指数的模拟效果高于降水指数,其中对TXx模拟最好,对CDD的模拟最差;经过订正后,针对不同模式的两种订正结果都能够有效地减小模式与观测的偏差并提高了空间相关系数,且两种方法的订正效果无明显差别。对RCP4.5情景下未来变化的分析中,QM在一定程度上改变了模式模拟的未来变化幅度和空间分布特征,QDM则能够有效地保留所有极端指数的气候变化信号。从全国平均来看,除CDD外,所有指数未来都呈现增加趋势,且QDM订正结果与订正前模式模拟的变化趋势更为接近。建议在气候变化模拟的误差订正中采用QDM方法。  相似文献   

14.
Wind climate in Northwest Europe is subject to long-term persistence (LTP), also called the Hurst phenomenon. Ignorance of LTP causes underestimation of climatic variability. The quantification of multi-year variability is important for the assessment of the uncertainty of future multi-year wind yields. Estimating LTP requires long homogeneous time series. Such series of wind observations are rare, but annual mean geostrophic wind speed (U) can be used instead. This study demonstrates a method to estimate the 10-year aggregated mean U for the near and the far future and its uncertainty in Northwest Europe. Time series of U were derived from daily sea level pressure from the European Climate Assessment Dataset. Minor inhomogeneities cannot be ruled out, but were shown to hardly affect the estimated Hurst exponent $(\hat{H})$ . A maximum likelihood method was adjusted to remove the biases in $\hat{H}$ . The geostrophic wind speed over the North Sea, the British Isles and along the Scandinavian coast are characterised by statistically significant H between 0.58 and 0.74, (H?=?0.5 implies no LTP). The additional affect of the parameter uncertainty is estimated in a Bayesian way and is highly dependent on the record length. The assessment of structural changes in future wind fields requires general circulation models. An ensemble of seventeen simulations (ESSENCE) with one single climate model (ECHAM5/MPI-OM) was used to evaluate structural trends and LTP. The estimated $\hat{H}$ in the ESSENCE simulations are generally close to 0.5 and not significant. Significant trends in U are found over large parts of the investigated domain, but the trends are small compared to the multi-year variability. Large decreasing trends are found in the vicinity of Iceland and increasing trends near the Greenland coast. This is likely related to the sea ice retreat within the ESSENCE simulations and the associated change in surface temperature gradients.  相似文献   

15.
A regional climate model (RCM) constrained by future anomalies averaged from atmosphere–ocean general circulation model (AOGCM) simulations is used to generate mid-twenty-first century climate change predictions at 30-km resolution over the central U.S. The predictions are compared with those from 15 AOGCM and 7 RCM dynamic downscaling simulations to identify common climate change signals. There is strong agreement among the multi-model ensemble in predicting wetter conditions in April and May over the northern Great Plains and drier conditions over the southern Great Plains in June through August for the mid-twenty-first century. Projected changes in extreme daily precipitation are statistically significant over only a limited portion of the central U.S. in the RCM constrained with future anomalies. Projected changes in monthly mean 2-m air temperature are generally consistent across the AOGCM ensemble average, North American Regional Climate Change Assessment Program RCM ensemble average, and RCM constrained with future anomalies, which produce a maximum increase in August of 2.4–2.9 K over the northern and southern Great Plains and Midwest. Changes in extremes in daily 2-m air temperature from the RCM downscaled with anomalies are statistically significant over nearly the entire Great Plains and Midwest and indicate a positive shift in the warm tail of the daily 2-m temperature distribution that is larger than the positive shift in the cold tail.  相似文献   

16.
Here we investigate simulated changes in the precipitation climate over the Baltic Sea and surrounding land areas for the period 2071–2100 as compared to 1961–1990. We analyze precipitation in 10 regional climate models taking part in the European PRUDENCE project. Forced by the same global driving climate model, the mean of the regional climate model simulations captures the observed climatological precipitation over the Baltic Sea runoff land area to within 15% in each month, while single regional models have errors up to 25%. In the future climate, the precipitation is projected to increase in the Baltic Sea area, especially during winter. During summer increased precipitation in the north is contrasted with a decrease in the south of this region. Over the Baltic Sea itself the future change in the seasonal cycle of precipitation is markedly different in the regional climate model simulations. We show that the sea surface temperatures have a profound impact on the simulated hydrological cycle over the Baltic Sea. The driving global climate model used in the common experiment projects a very strong regional increase in summertime sea surface temperature, leading to a significant increase in precipitation. In addition to the common experiment some regional models have been forced by either a different set of Baltic Sea surface temperatures, lateral boundary conditions from another global climate model, a different emission scenario, or different initial conditions. We make use of the large number of experiments in the PRUDENCE project, providing an ensemble consisting of more than 25 realizations of climate change, to illustrate sources of uncertainties in climate change projections.  相似文献   

17.
We present an analysis of climate change over Europe as simulated by a regional climate model (RCM) nested within time-slice atmospheric general circulation model (AGCM) experiments. Changes in mean and interannual variability are discussed for the 30-year period of 2071–2100 with respect to the present day period of 1961–1990 under forcing from the A2 and B2 IPCC emission scenarios. In both scenarios, the European region undergoes substantial warming in all seasons, in the range of 1–5.5°C, with the warming being 1–2°C lower in the B2 than in the A2 scenario. The spatial patterns of warming are similar in the two scenarios, with a maximum over eastern Europe in winter and over western and southern Europe in summer. The precipitation changes in the two scenarios also show similar spatial patterns. In winter, precipitation increases over most of Europe (except for the southern Mediterranean regions) due to increased storm activity and higher atmospheric water vapor loadings. In summer, a decrease in precipitation is found over most of western and southern Europe in response to a blocking-like anticyclonic circulation over the northeastern Atlantic which deflects summer storms northward. The precipitation changes in the intermediate seasons (spring and fall) are less pronounced than in winter and summer. Overall, the intensity of daily precipitation events predominantly increases, often also in regions where the mean precipitation decreases. Conversely the number of wet days decreases (leading to longer dry periods) except in the winter over western and central Europe. Cloudiness, snow cover and soil water content show predominant decreases, in many cases also in regions where precipitation increases. Interannual variability of both temperature and precipitation increases substantially in the summer and shows only small changes in the other seasons. A number of statistically significant regional trends are found throughout the scenario simulations, especially for temperature and for the A2 scenario. The results from the forcing AGCM simulations and the nested RCM simulations are generally consistent with each other at the broad scale. However, significant differences in the simulated surface climate changes are found between the two models in the summer, when local physics processes are more important. In addition, substantial fine scale detail in the RCM-produced change signal is found in response to local topographical and coastline features.  相似文献   

18.
The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.  相似文献   

19.
The MM5 modelling system has been used to perform regional climate simulations over Western Europe on a 45-km grid for the years 1971 to 2000. We focus our analysis on the impact of the driving input data on simulated precipitation in the Alpine area. Using ERA40 reanalysis data, the MM5 climatology of precipitation compares reasonably well with an observational climatology for the Alpine region. Switching to an ECHAM5 climate simulation as driving data induces excessive overprediction by up to 80% in the colder seasons there, primarily over the Alpine slopes. The large-scale flow provided by the global datasets revealed moderate differences indicating an increased number of low-pressure systems travelling from the Atlantic into the Alpine region for ECHAM5 compared with ERA40. Mean seasonal 700-hPa wind speeds correspondingly showed higher values for the ECHAM5 driven simulation in the central Alps. Partitioning three-hourly 700-hPa winds according to direction and speed in the central Alps specifically revealed a distinct shift to stronger westerly and north-westerly winds. Furthermore, aggregating three-hourly rainfall amounts to the same wind direction and wind speed intervals as for the wind statistics revealed strongly intensified precipitation due to the overly intense westerly winds, implying too intense orographic precipitation enhancement.  相似文献   

20.
Regional climate projections using climate models commonly use an “all-model” ensemble based on data sets such as the Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment (AR4). Some regional assessments have omitted models based on specific criteria. We use a criteria based on the capacity of climate models to simulate the observed probability density function calculated using daily data, model-by-model and region-by-region for each of the AR4 models over Australia. We demonstrate that by omitting those climate models with relatively weak skill in simulating the observed probability density functions of maximum and minimum temperature and precipitation, different regional projections are obtained. Differences include: larger increases in the mean maximum and mean minimum temperatures, but smaller increases in the annual maximum and minimum temperatures. There is little impact on mean precipitation but the better models simulate a larger increase in the annual rainfall event combined with a larger decrease in the number of rain days. The weaker models bias the amount of mean warming towards lower increases, bias annual maximum temperatures to excessive warming and bias precipitation such that the amount of the annual rainfall event is under-estimated. We suggest that omitting weak models from regional scale estimates of future climate change helps clarify the nature and scale of the projected impacts of global warming.  相似文献   

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