Numerical Simulations of Intense Meiyu Rainfall in 1991 over the Changjiang and Huaihe River Valleys by a Regional Climate Model with p-б Incorporated Coordinate System

Based on the primitive equation model with p-σincorporated coordinate system originally developed by Qian et al., a one-way nested fine mesh limited area model is developed. This model is nested with ECMWF T42 data to simulate the extra-intensive rainfall event occurring in the Changjiang and Huaihe River valleys in summer of 1991. The results show that the model has cer-tain capacity to fairly reproduce the regional distribution and the movement of the main rainfall belts. Therefore it can be used as a regional climate model to simulate and predict the short-range regional climate changes.     

Multi-year simulation of the East Asian Monsoon and Precipitation in China using a Regional Climate Model and Evaluation

1. Introduction As an important way to study the global climate change, because of its low resolution, GCM (general circulation model) shows obvious deficiency and uncer- tainty in capturing some regional features when used in the regional climate study, and the uncertainty is even serious in regional climate simulation over East Asia (Ding et al., 2000; Zhao and Luo, 1998; Qian et al., 1999). The high-resolution regional climate model (RegCM) developed in the 1980s can provide better simu…     

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC）. Part Ⅰ： Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.     

DEVELOPMENT OF A COUPLED REGIONAL AIR-SEA MODEL AND ITS NUMERICAL SIMULATION FOR SUMMER MONSOON IN 1998*

A coupled regional air-sea model is developed by using the regional climate model (P-σ RCM) and the regional ocean model (POM),which is used to simulate East Asian monsoon and oceanic elements in East Asian coastal waters.The simulated surface layer oceanic elements are basically consistent with the reality and can reflect the interaction between the monsoon and the surface layer currents.The great difference with the reality is "cold drift" of the simulated surface temperature.The coupled model has certain ability to simulate the atmosphere geopotential height fields,precipitation and low-level southwest wind from May to August in 1998.It can display the process of summer monsoon onset during the third dekad of May and the evolution features after the onset.The differences between the simulation results of the coupled model and that of the single P-σ RCM are shown mainly in the low-level atmosphere and the model internal regions.     

Notes of Numerical Simulation of Summer Rainfall in China with a Regional Climate Model REMO

Regional climate models are major tools for regional climate simulation and their output are mostly used for climate impact studies. Notes are reported from a series of numerical simulations of summer rainfall in China with a regional climate model. Domain sizes and running modes are major foci. The results reveal that the model in forecast mode driven by "perfect" boundaries could reasonably represent the inter-annual differences: heavy rainfall along the Yangtze River in 1998 and dry conditions in 1997. Model simulation in climate mode differs to a greater extent from observation than that in forecast mode. This may be due to the fact that in climate mode it departs further from the driving fields and relies more on internal model dynamical processes. A smaller domain in climate mode outperforms a larger one. Further development of model parameterizations including dynamic vegetation are encouraged in future studies.     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

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.     

EFFECTS OF THE ENVELOPE DEGREE OF OROGRAPHY ON THE SIMULATED CLIMATE PROPERTIES*

A primitive equation model with a zonal domain and a p-σ incorporated vertical coordinate system is used to study the effects of the envelope degree of orography on the simulated properties of both winter and summer climates.Results show that the orography with a larger envelope degree can improve the simulations to certain extent,especially in winter.It is found that the simulated properties of climate are mainly determined by the co-effects of the land-sea and the orographic distributions,and the envelope degree of orography has a secondary effect.However it should be taken properly in order to improve simulations:otherwise,it would be harmful.Different envelope degrees of orography can be adopted in different areas.     

Can Artificial Climate Trends in Global Reanalysis be Reduced by Dynamical Downscaling:A Case Study of China

In this study,the ability of dynamical downscaling for reduction of artificial climate trends in global reanalysis is tested in China.Dynamical downscaling is performed using a 60-km horizontal resolution Regional Integrated Environmental Model System (RIEMS) forced by the NCEP-Department of Energy (DOE) reanalysis II (NCEP-2).The results show that this regional climate model (RCM) can not only produce dynamically consistent fine scale fields of atmosphere and land surface in the regional domain,but it also has the ability to minimize artificial climate trends existing in the global reanalysis to a certain extent.As compared to the observed 2-meter temperature anomaly averaged across China,our model can simulate the observed inter-annual variation and variability as well as reduce artificial climate trends in the reanalysis by approximately 0.10 C decade 1 from 1980 to 2007.The RIEMS can effectively reduce artificial trends in global reanalysis for areas in western China,especially for regions with high altitude mountains and deserts,as well as introduce some new spurious changes in other local regions.The model simulations overestimated observed winter trends for most areas in eastern China with the exception of the Tibetan Plateau,and it greatly overestimated observed summer trends in the Sichuan Basin located in southwest China.This implies that the dynamical downscaling of RCM for long-term trends has certain seasonal and regional dependencies due to imperfect physical processes and parameterizations.     

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC） Part Ⅱ： The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center (NCC) since 2001. The NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM (CGCM) provides the boundary and initial conditions for driving the regional climate model (RegCM NCC). The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme (TKE) and an improved land process model (LPM). The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part I. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model’s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast (1991–2000) for summer (June–August), the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient (ACC) are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM NCC were made. The results are basically reasonable compared with the observations.     

SIMULATION OF MONTHLY CLIMATIC MEAN FIELD IN JANUARY AND JULY IN QINGHAI-XIZANG PLATEAU AND NORTHWESTERN CHINA

In this paper,we simulate the regional climate in summer and winter in northwestern part ofChina and the Qinghai-Xizang Plateau with regional climate model(MM4)nested with GFDLdata,and compare the simulated results with observed data and GFDL data.The results show thatthe regional model reproduces the regional climate systems,such as the high pressure on theplateau and the low pressure in the north of the plateau in winter,the warm-low pressure over theplateau and pressure ridge in south and north of the Qinghai-Xizang Plateau in summer.Theseregional climate features could not be distinguished by the GCM.The simulations of precipitationdistribution are reasonable.But differences between the simulated and observed precipitationvalues in some places are obvious.The precipitation in south of the Qinghai-Xizang Plateau isunderestimated,and in north of the Qinghai-Xizang Plateau,the precipitation is overestimated.The simulation of height field is better than temperature field.     

区域和全球模式的嵌套技术 及其长期积分试验

将区域模式嵌入澳大利亚CSIRO (Commonwealth Scientific and Industrial Research Organization）的全球模式中,并将其应用于区域模式的长期气候积分试验。模拟结果表明,当区域与全球模式嵌套时,边界吸收问题十分重要,由区域模式得到的高分辨率大尺度环流形式在边界上必须与全球模式提供的强迫一致,同时区域模式必须给出基于模式内部物理过程产生的高分辨信息。因此,在嵌套过程中,必须仔细考虑缓冲区的设置,使大尺度强迫与中尺度特征充分混合,既保持区域模式内外的一致性,又使区域内部中尺度强迫物理过程得到充分发展。将区域模式与澳大利亚CSIRO的9层21波三角形截断谱模式嵌套后,完成了连续3年的区域气候模式积分。模拟结果表明,由于区域模式较好地刻划了区域尺度的地形、下垫面和海岸线分布等的细节特征,模拟的区域气候特征比全球模式有较大的改进,尤其是对季风降水的模拟,区域模式明显改进了全球模式的模拟结果。     

Sources of systematic errors in the climatology of a regional climate model over Europe

 Two ten-year simulations made with a European regional climate model (RCM) are compared. They are driven by the same observed sea surface temperatures but use different lateral boundary forcing. For one simulation, RCM AMIP, this forcing is obtained from a standard integration of a global general circulation model (GCM AMIP), whereas for the other simulation, RCM ASSIM, it is derived from a time series of operational analyses. The archive of analysis fields (surface pressure plus winds and temperatures on various pressure levels) is not sufficiently comprehensive to provide directly the full set of driving fields required for the RCM (in particular, no moisture fields are present), so these are obtained via a GCM integration, GCM ASSIM, in which the model is continuously relaxed towards the analysis fields using a data assimilation technique. Errors in RCM AMIP can arise either from the internal RCM physics or from errors in the lateral boundary forcing inherited from GCM AMIP. Errors in RCM ASSIM can arise from the internal RCM physics or the boundary moisture forcing but not from the driving circulation. Although previous studies have considered RCM integrations driven either by output from standard GCM integrations or operational analyses, our study is the first to compare parallel integrations of each type. This allows the total systematic error in an RCM integration driven by standard GCM output to be partitioned into components arising from the driving circulation and the internal RCM physics. These components indicate the scope for reducing regional simulation biases by improving either the driving GCM or the RCM itself. The results relate mainly to elements of surface climate likely to be influenced by both the driving circulation and regional physical processes operating in the RCM. For cloud cover, errors are found to arise largely from the internal RCM physics. Values are too low despite a positive relative humidity bias, indicating shortcomings in the parametrisation scheme used to calculate cloud cover. In summer, surface temperature and precipitation errors are also explained principally by regional processes. For example excessive solar heating leads to anomalously high surface temperatures over southern Europe and excessive drying of the soil reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing also exerts some influence, mainly via a tropospheric cold bias which partially offsets the warming over southern Europe and also increases precipitation. In other seasons the lateral boundary forcing and the regional physics both contribute significantly to the errors in surface temperature and precipitation. In winter the boundary forcing (apart from moisture) is responsible for about 60% of the total error variance for temperature and about 40% for precipitation, due to the cold bias and circulation errors such as a southward shift in the storm track. The remaining errors arise from the regional physics, although for precipitation an excessive supply of moisture from the lateral boundaries also contributes. The skill of the mesoscale component of the surface temperature and precipitation distributions exceeds previous estimates, due to more realistic observed climatology. The mesoscale patterns are very similar in the two RCM simulations indicating that errors in the simulation of fine scale detail arise mainly from inadequate representations of local forcings rather than errors in the large-scale circulation. Circulation errors in RCM AMIP (e.g. cold bias, southward shift of storm track) are also present in GCM AMIP, but are largely absent in RCM ASSIM except in summer. This confirms evidence from previous work that the key to reducing most circulation errors in the RCM lies in improving the driving GCM. Regional processes only make a major contribution to circulation errors in summer, when reduced advection from the boundaries allows errors in surface temperature to be transmitted more effectively into the troposphere. Finally, we find evidence of error balances in the GCM which act to minimise biases in important climatological variables. This reflects tuning of the model physics at GCM resolution. In order to achieve simultaneous optimisation of the RCM and GCM at widely differing resolutions it may be necessary to introduce explicit scale dependences into some aspects of the physics. Received: 17 September 1997/Accepted: 10 March 1998     

月尺度区域气候数值预测试验

将９层全球气候谱模式与ＣＳＵ－ＲＡＭＳ中尺度数值式嵌套,进行了月尺度的短期区域气候预测试验。结果表明：ＧＣＭ模式的集合预报能够反映较大尺度的平均环流;在此基础上,被嵌套的ＣＳＵ－ＲＡＭＳ中尺度模式能够得到更为细致的区域环流特征以及它的短期气候尺度的演率。ＧＣＭ模式与中尺度模式相结合的“区域气候数据模式”是了解短期区域气候变化的有效方法之一。     

Testing the downscaling ability of a one-way nested regional climate model in regions of complex topography

The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment has been carried out for four winter months over the west coast of North America. The results show that complex topography and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings, found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility. Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution.     

A simple soil moisture scheme for regional climate simulations in the tropics

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     

High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions

To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections.     

Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs.     

Testing the downscaling ability of a one-way nested regional climate model in regions of complex topography

The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment has been carried out for four winter months over the west coast of North America. The results show that complex topography and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings, found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility. Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution. Figure legends were missing in original article. Climate Dynamics (2005) 23: 473-493. The complete article is given here. DOI: 10.1007/s00382-004-0438-5     

Simulation of South American wintertime climate with a nesting system

A numerical nesting system is developed to simulate wintertime climate of the eastern South Pacific-South America-western South Atlantic region, and preliminary results are presented. The nesting system consists of a large-scale global atmospheric general circulation model (GCM) and a regional climate model (RCM). The latter is driven at its boundaries by the GCM. The particularity of this nesting system is that the GCM itself has a variable horizontal resolution (stretched grid). Our main purpose is to assess the plausibility of such a technique to improve climate representation over South America. In order to evaluate how this nesting system represents the main features of the regional circulation, several mean fields have been analyzed. The global model, despite its relatively low resolution, could simulate reasonably well the more significant large-scale circulation patterns. The use of the regional model often results in improvements, but not universally. Many of the systematic errors of the global model are also present in the regional model, although the biases tend to be rectified. Our preliminary results suggest that nesting technique is a computationally low-cost alternative for simulating regional climate features. However, additional simulations, parametrizations tuning and further diagnosis are clearly needed to represent local patterns more precisely. Received: 18 February 1999 / Accepted: 31 May 2000     

初始条件和边界条件对区域模式模拟青藏高原区域气候的影响

用ＧＦＤＬ气候场及ＧＣＭ的模拟结果分别为区域模式（ＭＭ４）提供初始条件和边界条件,模拟了青藏高原地区夏季区域气候特征,通过比较不同初始条件和边界条件时区域模式的模拟结果,分析了初始条件和边界条件对模拟结果的影响,虽然这两种方法都模拟出青藏高原附近的主要区域气候特征,但ＧＦＤＬ提供初始条件和边界条件对ＭＭ４的模拟结果明显优于用ＧＣＭ提供初始条件和边界条件时的模拟结果,特别是高层,ＧＣＭ输出结果与实际