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1.
Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km2) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.  相似文献   

2.
Regional climate simulation can generally be improved by using an RCM nested within a coarser-resolution GCM. However, whether or not it can also be improved by the direct use of a state-of-the-art GCM with very fine resolution, close to that of an RCM, and, if so, which is the better approach, are open questions. These questions are important for understanding and using these two kinds of simulation approaches, but have not yet been investigated. Accordingly, the present reported work compared simulation results over China from a very-fine-resolution GCM (VFRGCM) and from RCM dynamical downscaling. The results showed that: (1) The VFRGCM reproduces the climatologies and trends of both air temperature and precipitation, as well as inter-monthly variations of air temperature in terms of spatial pattern and amount, closer to observations than the coarse-resolution version of the GCM. This is not the case, however, for the inter-monthly variations of precipitation. (2) The VFRGCM captures the climatology, trend, and inter-monthly variation of air temperature, as well as the trend in precipitation, more reasonably than the RCM dynamical downscaling method. (3) The RCM dynamical downscaling method performs better than the VFRGCM in terms of the climatology and inter-monthly variation of precipitation. Overall, the results suggest that VFRGCMs possess great potential with regard to their application in climate simulation in the future, and the RCM dynamical downscaling method is still dominant in terms of regional precipitation simulation.  相似文献   

3.
This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate.  相似文献   

4.
Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel ClimateModel (PCM), and the implications of the comparison for a future(2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly(at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at 1/2-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.  相似文献   

5.
The fifth-generation Pennsylvania State University/NCAR Mesoscale Model Version 3 (MM5V3) was used to simulate extreme heavy rainfall events over the Yangtze River Basin in June 1999. The effects of model's horizontal and vertical resolution on the extreme climate events were investigated in detail. In principle, the model was able to characterize the spatial distribution of monthly heavy precipitation. The results indicated that the increase in horizontal resolution could reduce the bias of the modeled heavy rain and reasonably simulate the change of daily precipitation during the study period. A finer vertical resolution led to obviously improve rainfall simulations with smaller biases, and hence, better resolve heavy rainfall events. The increase in both horizontal and vertical resolution could produce better predictions of heavy rainfall events. Not only the rainfall simulation altered in the cases of different horizontal and vertical grid spacing, but also other meteorological fields demonstrated diverse variations in terms of resolution change in the model. An evident improvement in the simulated sea level pressure resulted from the increase of horizontal resolution, but the simulation was insensitive to vertical grid spacing. The increase in vertical resolution could enhance the simulation of surface temperature as well as atmospheric circulation at low levels, while the simulation of circulation at middle and upper levels were found to be much less dependent on changing resolution. In addition, cumulus parameterization schemes showed high sensitivity to horizontal resolution. Different convective schemes exhibited large discrepancies in rainfall simulations with regards to changing resolution. The percentage of convective precipitation in the Grell scheme increased with increasing horizontal resolution. In contrast, the Kain-Fritsch scheme caused a reduced ratio of convective precipitation to total rainfall accumulations corresponding to increasing horizontal resolution.  相似文献   

6.

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

  相似文献   

7.
Regional climate model projections for the State of Washington   总被引:3,自引:1,他引:2  
Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.  相似文献   

8.
Summary A regional climate model (RCM) is described which incorporates an improved scheme for soil moisture availability (SMA) compared to an earlier version. The improvement introduces a sensitivity of SMA to soil type, vegetation cover and ground albedo, making the model more adaptable to divers regions. In addition, the interactive SMA depends on past precipitation, ground temperature and terrain relief. Six RCM simulations of the monthly mean climate over southern Africa are performed at 0.5° grid spacing. Improvements in the RCM climate simulations compared to control runs are attributed to the newer SMA scheme. Only a slight improvement in skill results from driving the RCM with observational analyses as opposed to GCM “predicted” lateral boundary conditions. The high spatial resolution of the RCM provides a distinct advantage in the simulated spatial distribution of precipitation compared with a global model run at an effective grid spacing of 2.8°. The mesoscale precipitation signal in the RCM simulations is more dominant during the rather dry December 1982 than during December 1988. The improved SMA scheme contributed to a realistic partition between latent and sensible heat fluxes at the ground-atmosphere boundary and consequently a realistic diurnal cycle of ground temperature. Simulated differences in the spatial distribution of rainfall between December 1982 and December 1988 are more realistic with the improved scheme. Received June 28, 2001 Revised August 27, 2001  相似文献   

9.
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   

10.
分辨率对区域气候极端事件模拟的影响   总被引:13,自引:2,他引:13  
汤剑平  赵鸣  苏炳凯 《气象学报》2006,64(4):432-442
利用NCAR MM5V3对1999年6月长江流域的极端异常降水事件进行了模拟,主要研究不同水平和垂直分辨率对极端区域气候事件模拟的影响。数值模拟试验表明:模式能够模拟出极端强降水的主要分布特征;水平分辨率的提高降低了模式模拟的强降水偏差,对逐日降水变化的模拟更加合理,而垂直分辨率的提高基本上也都减小了模拟的强降水过程的偏差,改善对强降水的模拟能力;模式水平、垂直分辨率的提高在一定程度上增强了对强降水过程的模拟能力。水平分辨率的提高能够改善模式对海平面气压的模拟,而垂直分辨率的提高可以改善模式模拟的地面气温和低层环流。分辨率对中层大气环流的影响不是很敏感。不同积云对流参数化方案模拟的对流降水比率随水平分辨率的变化是不同的,Grell方案对流降水比例随分辨率的提高而增加,而Kain-Fritsch方案的结果相反。  相似文献   

11.
A 26-year simulation (1980–2005) was performed with the Weather Research and Forecast (WRF) model over the Volta Basin in West Africa. This was to investigate the ability of a climate version of WRF to reproduce present day temperature and precipitation over the Volta Basin. The ERA-Interim reanalysis and one realization of the ECHAM6 global circulation model (GCM) data were dynamically downscaled using two nested domains within the WRF model. The outer domain had a horizontal resolution of 50 km and covered the whole of West Africa while the inner domain had a horizontal resolution of 10 km. It was observed that biases in the respective forcing data were carried over to the RCM, but also the RCM itself contributed to the mean bias of the model. Also, the biases in the 50-km domain were transferred unchanged, especially in the case of temperature, to the 10-km domain, but, for precipitation, the higher-resolution simulations increased the mean bias in some cases. While in general, WRF underestimated temperature in both the outer (mean biases of ?1.6 and ?2.3 K for ERA-Interim and ECHAM6, respectively) and the inner (mean biases of ?0.9 K for the reanalysis and ?1.8 K for the GCM) domains, WRF slightly underestimated precipitation in the coarser domain but overestimated precipitation in the finer domain over the Volta Basin. The performance of the GCM, in general, is good, particularly for temperature with mean bias of ?0.7 K over the outer domain. However, for precipitation, the added value of the RCM cannot be overlooked, especially over the whole West African region on the annual time scale (mean biases of ?3% for WRF and ?8% for ECHAM6). Over the whole Volta Basin and the Soudano-Sahel for the month of April and spring (MAM) rainfall, respectively, mean bias close to 0% was simulated. Biases in the interannual variability in both temperature and precipitation over the basin were smaller in the WRF than the ECHAM6. High spatial pattern correlations between 0.7 and 0.8 were achieved for the autumn precipitation and low spatial correlation in the range of 0.0 and 0.2 for the winter season precipitation over the whole basin and all the three belts over the basin.  相似文献   

12.
A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations.  相似文献   

13.
An evaluation of RegCM3_CERES for regional climate modeling in China   总被引:1,自引:0,他引:1  
陈锋  谢正辉 《大气科学进展》2013,30(4):1187-1200
A 20-year simulation of regional climate over East Asia by the regional climate model RegCM3_CERES (Regional Climate Model version 3 coupled with the Crop Estimation through Resource and Environment Synthesis) was carried out and compared with observations and the original RegCM3 model to comprehensively evaluate its performance in simulating the regional climate over continental China. The results showed that RegCM3_CERES reproduced the regional climate at a resolution of 60 km over China by using ERA40 data as the boundary conditions, albeit with some limitations. The model captured the basic characteristics of the East Asian circulation, the spatial distribution of mean precipitation and temperature, and the daily characteristics of precipitation and temperature. However, it underestimated both the intensity of the monsoon in the monsoonal area and precipitation in southern China, overestimated precipitation in northern China, and produced a systematic cold temperature bias over most of continental China. Despite these limitations, it was concluded that the RegCM3_CERES model is able to simulate the regional climate over continental China reasonably well.  相似文献   

14.
High-resolution regional climate change simulations have proven to offer an added value compared to available global climate model simulations. However, over many regions of the globe, long-term high-resolution climate change projections are rather sparse. We present a transient high-resolution climate change projection with the regional climate model with the regional climate model REMO over the southern African region, following the SRES A1B emission scenario. The simulation was conducted at 18?km grid spacing for the period from 1960 to 2100, making it to the longest available climate change projection at such a high resolution for the region. In the first part of the study, we focus on the impact of the model setup on the simulated rainfall over the southern African region. In the standard setup, we used the output of the global climate model ECHAM5/MPIOM directly to force REMO. This setup led to a very strong wet bias over the region. Changing it to the double-nesting setup significantly reduced this bias, but a substantial wet bias still persists. The remaining bias could partly be attributed to a warm bias in the SST forcing over the southern Atlantic Ocean. Thus, we applied an SST correction based on the anomaly approach to the data, which led to a further improvement of the rainfall simulation. As the SST bias in the southern Atlantic is a common feature of all global climate models assessed by the IPCC, we recommend the chosen model setup, including the SST correction, as general procedure for dynamical downscaling studies over the southern African region. In the second part, we present the projected spatial and temporal changes of temperature and precipitation, including several rainfall characteristics, over the southern African region. Herby we compare the projections of the high-resolution REMO simulation to those of the forcing regional and global models. We generally find that for temperature the magnitude of the projected changes of the regional model only slightly differs from the GCM projection; however, the spatial patterns are much better resolved in the RCM projections. For precipitation, REMO shows a more intense drying toward the end of the twenty-first century than it is simulated by the global model. This can have a major influence when investigating the impacts of future climate change on a regional or even local scale. In combination with the improved spatial patterns, the application of high-resolution climate change information could therefore improve the results of such applications.  相似文献   

15.
A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.  相似文献   

16.
We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.  相似文献   

17.
于翡  黄丽萍  邓莲堂 《大气科学》2018,42(5):1146-1156
国家气象中心业务运行的中尺度数值预报系统GRAPES-MESO(Global/Regional Assimilation and Prediction System mesoscale model)在升级到4.0版本后采用了与以往版本不同的三维空间分辨率设置,本文通过计算精度分析、个例分析及统计分析的方法详细阐述了两者水平分辨率和不等距垂直分层的差异,并由此深入分析了不同模式三维空间分辨率对中国夏季汛期降水预报的影响。主要结论表明,GRAPES-MESO预报系统4.0版本在水平分辨率提高到10 km并同时使用更为合理的加密垂直分层设置后,不仅提高了计算精度和计算稳定性,同时仍能满足业务预报的时效要求。对个例降水特征的分析结果表明,提高模式空间分辨率可以在一定程度上改善对降水中心的预报,但对降水落区的预报改进较为有限。对2012年7月整月批量试验的统计检验结果表明,月平均技巧评分总体变化不大,但对逐日大到暴雨评分提高较大,通过各气象要素统计检验分析可以认为,模式空间分辨率提高的主要作用是通过降低了中低层高度场、温度场和水平风场的误差,改进了对流层中层环流背景场以及对流层低层降水直接触发系统的强度预报,从而能够提高大到暴雨的降水评分。  相似文献   

18.
不同区域气候模式对中国地区温度和降水的长期模拟比较   总被引:19,自引:9,他引:19  
冯锦明  符淙斌 《大气科学》2007,31(5):805-814
利用亚洲区域模式比较计划RMIP第二阶段五个区域模式和一个变网格全球模式,对中国地区1988年12月~1998年11月十年模拟的平均温度和降水结果,分析比较了不同区域气候模式对中国地区温度和降水的模拟能力。研究结果表明:几乎所有模式都能模拟出中国地区多年平均温度和降水的基本空间分布形态,但模式模拟的温度普遍偏低,在大部分区域,大多数模式模拟的降水偏多,而且不同模式之间存在较大差别。模式能较好地反映出中国地区温度的年际变化,对夏季降水的年际变化模拟较差,对冬季模拟较好。  相似文献   

19.
Regional Climate Models (RCMs) have been developed in the last two decades in order to produce high-resolution climate information by downscaling Atmosphere-Ocean General Circulation Models (AOGCMs) simulations or analyses of observed data. A crucial evaluation of RCMs worth is given by the assessment of the value added compared to the driving data. This evaluation is usually very complex due to the manifold circumstances that can preclude a fair assessment. In order to circumvent these issues, here we limit ourselves to estimating the potential of RCMs to add value over coarse-resolution data. We do this by quantifying the importance of fine-scale RCM-resolved features in the near-surface temperature, but disregarding their skill. The Reynolds decomposition technique is used to separate the variance of the time-varying RCM-simulated temperature field according to the contribution of large and small spatial scales and of stationary and transient processes. The temperature variance is then approximated by the contribution of four terms, two of them associated with coarse-scales (e.g., corresponding to the scales that can be simulated by AOGCMs) and two of them describing the original contribution of RCM simulations. Results show that the potential added value (PAV) emerges almost exclusively in regions characterised by important surface forcings either due to the presence of fine-scale topography or land-water contrasts. Moreover, some of the processes leading to small-scale variability appear to be related with relatively simple mechanisms such as the distinct physical properties of the Earth surface and the general variation of temperature with altitude in the Earth atmosphere. Finally, the article includes some results of the application of the PAV framework to the future temperature change signal due to anthropogenic greenhouse gasses. Here, contrary to previous studies centred on precipitation, findings suggest for surface temperature a relatively low potential of RCMs to add value over coarser resolution models, with the greatest potential located in coastline regions due to the differential warming occurring in land and water surfaces.  相似文献   

20.
黄安宁  张耀存  朱坚 《大气科学》2009,33(6):1212-1224
利用PσRCM9区域气候模式, 分析了中国夏季不同强度降水模拟对不同积云对流参数化方案的敏感性。结果表明, 采用四种积云对流参数化方案, 模式能够模拟出小雨、 大雨和暴雨的雨量百分比和雨日百分比空间分布的一致性特征, 但不能模拟出中雨雨量百分比和雨日百分比空间分布的相似性, 这是由于模式不能模拟中雨雨量百分比的空间分布形式所致。还发现模拟的我国夏季降水以小雨和中雨为主, 四种积云对流参数化方案均低估了中国夏季大雨和暴雨对总降水的贡献, 尤其是在我国西部、 东北和华北地区更明显。不同积云对流参数化方案下模拟的极端强降水阈值的空间分布形式基本与观测一致, 但强度与观测存在较大差异。相比较而言, Grell方案较Kuo、 Anthes-Kuo和Betts-Mille积云对流参数化方案更适合中国东南部地区夏季极端强降水的模拟。  相似文献   

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