基于卫星降水和WRF预报降水的“6.18”门头沟泥石流事件的回报检验研究

2017年6月18日北京门头沟地区突发泥石流,造成6人伤亡。短时强降水是这起事件的主要诱发因素,但常规气象观测并没有很好地观测到此次降水过程,可见降水数据的准确性对于滑坡泥石流的实时预警及预报至关重要。近年来,卫星遥感估算降水发展迅速,WRF（Weather Research and Forecasting Model）模式关于降水的预报技巧也逐渐提高。本文以自动站降水资料为参考,首先利用定性方法和泰勒图、TS（Threat Score）评分等定量的方法比较了CMORPH（CPC MORPHing technique）、GPM（Global Precipitation Measurement）和PERSIANN-CCS（Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System）三种卫星降水资料以及不同起报时间的WRF预报降水对此次降水过程的表现能力,然后利用降水数据驱动滑坡泥石流统计预报模型,对此次事件进行了回报,分析不同降水数据在模型中的实际应用效果,最终为滑坡泥石流实时预警和预报系统的构建提供参考。结果表明,三种卫星降水资料基本上能反映出此次降水过程东北—西南向的带状空间分布形态,其中,CMORPH与自动站资料的空间相关性最好,命中率也最高,但对降水量有一定的高估,GPM对平均降水量的时间变化有较好的反映,体现了卫星降水在观测较少地区的良好利用价值,PERSIANN-CCS的表现则相对差些。WRF模式能预报出此次降水的带状空间分布特征,但降水中心的位置与实际有所偏差;此外,预报的最大降水量的峰值出现时间比实际上晚。由于此次降水的强局地性,只有空间分辨率均匀且质量相对较好的CMORPH卫星降水驱动模型可以回报出此次事件,而自动站点资料由于空间分布不均,则没有回报出此次事件,这表明了卫星降水在滑坡泥石流实时预警系统的构建中具有一定的优势。WRF模式降水驱动模型可以提前做出预警,虽然预报的事件发生时间与实际相比偏晚3~5 h,但WRF可以较好地预报72 h内的降水,因而可以延长灾害的可预见期。WRF模式预报降水的时间和空间精度都需要进一步提高,但是仍具有很好的参考意义。     

WRF模式分辨率对新疆异常降雨天气要素模拟的影响

利用新一代中尺度气候数值模式WRF对中国西北干旱典型地区——新疆2000年10月的异常降雨事件进行模拟,主要研究了不同水平分辨率、垂直分辨率以及不同积云参数化过程对气温、降雨和土壤温度模拟的影响。结果表明：不同分辨率的模拟基本上均模拟出了地面气温的分布特征,且随着水平分辨率的提高,模式模拟能力显著提高,对地面气温值、分布范围的模拟渐趋合理,同时模式对于地形引起的温度分布变化的模拟更加趋近实际。水平分辨率、垂直分辨率的提高同样改善了模式对降水的模拟能力,分辨率的提高不仅改进了模式对降雨分布区模拟的精度,也增强了对于地形引起的降雨变异的模拟能力。在土壤温度模拟上,不同分辨率的试验均能模拟出土壤温度的分布特征,较高水平分辨率有利于描述土壤温度分布细节,但更容易出现“数值点风暴”现象。     

A Heavy Rainfall Event in Autumn over Beijing-Atmospheric Circulation Background and Hindcast Simulation Using WRF

Heavy rainfall events often occur in Beijing during summer but rarely in autumn. However,during 3-5 September2015, an exceptionally heavy rainfall event occurred in Beijing. Based on the reanalysis data and the Weather Research and Forecasting(WRF) model simulations, the main contributing factors and the predictability of this heavy rainfall event were examined through comprehensive analyses of vorticity advection and water vapor transport/budget. The results indicate that a "high-in-the-east-low-in-the-west" pattern of 500-hPa geopotential height over the Beijing area played an important role. The 850-hPa low-level jet(LLJ) provided a mechanism for rising motion and transported abundant water vapor into the Beijing area. Two-way nested hindcast experiments using WRF well reproduced the atmospheric circulation and LLJ. Quantitative analysis indicates that the WRF model with the rapid update cycle(RUC) land surface scheme and the single-moment 6-class(WSM6) microphysics scheme exhibited the best skill, and the model performance improved with a higher resolution. Further analysis indicates that the bias in the precipitation forecast was caused by the bias in water vapor transport.     

A Heavy Rainfall Event in Autumn over Beijing—Atmospheric Circulation Background and Hindcast Simulation Using WRF

Heavy rainfall events often occur in Beijing during summer but rarely in autumn. However, during 3–5 September 2015, an exceptionally heavy rainfall event occurred in Beijing. Based on the reanalysis data and the Weather Research and Forecasting (WRF) model simulations, the main contributing factors and the predictability of this heavy rainfall event were examined through comprehensive analyses of vorticity advection and water vapor transport/ budget. The results indicate that a “high-in-the-east–low-in-the-west” pattern of 500-hPa geopotential height over the Beijing area played an important role. The 850-hPa low-level jet (LLJ) provided a mechanism for rising motion and transported abundant water vapor into the Beijing area. Two-way nested hindcast experiments using WRF well reproduced the atmospheric circulation and LLJ. Quantitative analysis indicates that the WRF model with the rapid update cycle (RUC) land surface scheme and the single-moment 6-class (WSM6) microphysics scheme exhibited the best skill, and the model performance improved with a higher resolution. Further analysis indicates that the bias in the precipitation forecast was caused by the bias in water vapor transport.     

Impact of precipitating ice on the simulation of a heavy rainfall event with advanced research WRF using two bulk microphysical schemes

In this study, the Weather Research and Forecasting (WRF) model version 3.2 is used to examine the impact of precipitating ice and especially snow-graupel partitioning in the simulation of a heavy rainfall event over Chalkidiki peninsula in Northern Greece. This major precipitation event, associated with a case of cyclogenesis over the Aegean Sea, occurred on the 8th of October 2006 causing severe flooding and damage. Two widely used microphysical parameterizations, the Purdue Lin (PLIN) and WRF Single-Moment 6-class scheme (WSM6) are compared with available raingauge measurements over the complex topography of Chalkidiki. To further investigate the importance of snow and graupel relative mass content and the treatment of precipitating ice sedimentation velocity, two older versions of the WSM6 scheme were compiled and run with the current model. The verification results indicate that all simulations were found to match raingauge data more closely over the eastern mountainous Chalkidiki peninsula where maximum accumulations were observed. In other stations all schemes overestimate 24h accumulated rainfall except a station situated at the western part of the peninsula, where none of the simulations was able to reproduce observed rainfall. Graupel dominance in PLIN generates rapid precipitation fallout at the point of maximum predicted 24h accumulation. Similar behavior is shown in WSM6 from WRF version 2, but with significant less rainfall. Increasing snow amounts aloft, due to the unified treatment of precipitating ice in WSM6 from WRF version 3, modifies rain dynamics which decrease rainfall rates, but increases 24h accumulations. A sensitivity experiment where PLIN is used with snow accretion by graupel turned off, indicated that this process seems to be the most important factor controlling the differences in surface precipitation between PLIN and WSM6 from WRF version 3, determining the spatial and temporal distribution of this heavy precipitation event. The results also revealed that snow overestimation can lead to high rainfall accumulations, even though rain is more evenly distributed over the 24h period, deteriorating precipitation forecast.     

Spatial and temporal variations of aridity indices in Iraq

In this paper, a nonhydrostatic Weather Research and Forecasting (WRF) model has been used to simulate the extreme precipitation event of 25 November 2009, over Jeddah, Saudi Arabia. The model is integrated in three nested (27, 9, and 3 km) domains with the initial and boundary forcing derived from the NCEP reanalysis datasets. As a control experiment, the model integrated for 48 h initiated at 0000 UTC on 24 November 2009. The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results indicate that a strong low-level (850 hPa) wind over Jeddah and surrounding regions enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the mesoscale system. The influences of topography and heat exchange process in the atmosphere were investigated on the development of extreme precipitation event; two sensitivity experiments are carried out: one without topography and another without exchange of surface heating to the atmosphere. The results depict that both surface heating and topography played crucial role in determining the spatial distribution and intensity of the extreme rainfall over Jeddah. The topography favored enhanced uplift motion that further strengthened the low-level jet and hence the rainfall over Jeddah and adjacent areas. On the other hand, the absence of surface heating considerably reduced the simulated rainfall by 30% as compared to the observations.     

Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4

To study the prediction of the anomalous precipitation and general circulation for the summer(June–July–August) of1998, the Community Climate System Model Version 4.0(CCSM4.0) integrations were used to drive version 3.2 of the Weather Research and Forecasting(WRF3.2) regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.     

CMIP5多模式对东亚地区地面气温年际变率的回报研究

对CMIP5全球气候模式中年代际回报试验的气温资料及其简单集合平均(Multi-model ensemble mean,EMN)和贝叶斯模式平均的结果(Bayesian Model Averaging,BMA)进行经验正交函数(Empirical Orthogonal Function,EOF)分解和Morlet小波分析,检验评估各个模式及其EMN和BMA对东亚地面气温的方差、气温时空分布特征及周期变化的回报能力。结果表明,10个模式、EMN、BMA都能很好地回报出1981—2010年东亚地面气温的方差分布,其中BMA回报效果最好。EOF分析表明,BMA能较好地回报出东亚地面气温第一模态的时空分布。MIROC5能较好地回报出第二模态的趋势变化,但却不能回报出气温的年际变率。绝大多数模式和EMN、BMA虽然能回报出东亚地面气温的变化趋势,但是对气温年际变率的回报仍然是比较困难的。CMCC-CM对气温变化主模态的3~5 a的周期变化特征回报效果最好,和NCEP资料的结果最为接近。     

雷达热动力反演资料的高分辨率同化模拟试验

目前,北京地区的天气预报系统对局地对流性定量降水预报能力较弱,远不能满足人们生产、生活和防灾、减灾工作的需要。针对北京地区对提高0-12 h短时临近天气,尤其是夏季局地对流性降水预报能力的需求,基于中国气象局北京城市气象研究所变分多普勒雷达分析系统（VDRAS）的雷达热动力反演资料,建立了WRF模式初始化模块,采用四维资料同化（FDDA）方法,将VDRAS系统高时空分辨率三维热动力结构分析场资料同化到WRF模式中,实现了北京地区VDRAS分析场资料在WRF中尺度模式系统中的应用。通过降水个例的高分辨率同化模拟试验分析了雷达热动力反演资料同化对模式预报结果的影响。研究结果表明:雷达热动力反演资料的同化能够提高模式系统对近地面温、湿、风大气要素和降水过程的模拟能力,改善2 m比湿、降水落区、降水量级、降水时间的预报效果,减少降水漏报的现象。温度和比湿的同化比风的同化对模拟降水结果的改善更重要。虽然研究表明雷达热动力反演资料在WRF模式中的同化能够明显改善模式对选取降水个例的模拟效果,但其对模式尤其是数值业务模式系统预报效果的影响需要进一步更全面、更系统的检验,为业务化应用奠定更坚实的基础。      

A Modified Double-Moment Bulk Microphysics Scheme Geared toward the East Asian Monsoon Region

Representation of cloud microphysical processes is one of the key aspects of numerical models. An improved double-moment bulk cloud microphysics scheme (named IMY) was created based on the standard Milbrandt-Yau (MY) scheme in the Weather Research and Forecasting (WRF) model for the East Asian monsoon region (EAMR). In the IMY scheme, the shape parameters of raindrops, snow particles, and cloud droplet size distributions are variables instead of fixed constants. Specifically, the shape parameters of raindrop and snow size distributions are diagnosed from their respective shape-slope relationships. The shape parameter for the cloud droplet size distribution depends on the total cloud droplet number concentration. In addition, a series of minor improvements involving detailed cloud processes have also been incorporated. The improved scheme was coupled into the WRF model and tested on two heavy rainfall cases over the EAMR. The IMY scheme is shown to reproduce the overall spatial distribution of rainfall and its temporal evolution, evidenced by comparing the modeled results with surface gauge observations. The simulations also successfully capture the cloud features by using satellite and ground-based radar observations as a reference. The IMY has yielded simulation results on the case studies that were comparable, and in ways superior to MY, indicating that the improved scheme shows promise. Although the simulations demonstrated a positive performance evaluation for the IMY scheme, continued experiments are required to further validate the scheme with different weather events.     

基于WRF模式的云南短时强降水物理量特征

为了解云南短时强降水发生前本地化中尺度WRF(Weather Research Forecast)模式输出结果的物理量特征及其对短时强降水预报的作用,使用WRF模式对2016年云南主汛期(6—8月)5次短时强降水过程进行模拟,利用模式输出的高时空分辨率资料计算5次过程中85个样本在短时强降水发生前6 h水汽类、动力类及不稳定条件类的部分物理量值,使用箱线图分析各物理量的分布特征及其与短时强降水的关系,应用经验累积分布函数图确定各物理量的阈值。研究表明,水汽类物理量样本数据值分布较为集中,随着短时强降水的临近数值逐渐增大;动力类的6 km垂直风切变中位数值及平均值随时间变化很小,所有时次的6 km垂直风切变阈值均低于12 m/s,表明短时强降水发生前有弱垂直风切变;不稳定条件类中对流有效位能样本数据的离散程度较大,对短时强降水无指示意义;LI指数、K指数和700 hPa假相当位温样本数据离散度较小,其中K指数中位数值、平均值及阈值的上下限在短时强降水发生前1 h有显著增大的特征,且数据集中度达到最高,大的K指数值与短时强降水有较好的对应关系。使用物理量阈值推算短时强降水落点的方法对云南本地化WRF模式短时强降水的预报性能有改进作用。     

Impact of ECMWF,NCEP, and NCMRWF global model analysis on the WRF model forecast over Indian Region

The global model analysis has significant impact on the mesoscale model forecast as global model provides initial condition (IC) and lateral boundary conditions (LBC) for the mesoscale model. With this objective, four operational global model analyses prepared from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS), NCEP Global Forecasting System (GFS), and National Centre for Medium Range Weather Forecasting (NCMRWF) are used daily to generate IC and LBC of the mesoscale model during 13th December 2012 to 13th January 2013. The Weather Research and Forecasting (WRF) model version 3.4, broadly used for short-range weather forecast, is adopted in this study as mesoscale model. After initial comparison of global model analyses with Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles, daily WRF model forecasts initialized from global model analyses are compared with in situ observations and AIRS profiles. Results demonstrated that forecasts initialized from the ECMWF analysis are closer to AIRS-retrieved profiles and in situ observations compared to other global model analyses. No major differences are occurred in the WRF model forecasts when initialized from the NCEP GDAS and GFS analyses, whereas these two analyses have different spatial resolutions and observations used for assimilation. Maximum RMSD is seen in the NCMRWF analysis-based experiments when compared with AIRS-retrieved profiles. The rainfall prediction is also improved when WRF model is initialized from the ECMWF analysis compared to the NCEP and NCMRWF analyses.     

The Application of a Meteo-hydrological Forecasting System with Rainfall Bias Correction in a Small and Medium-sized Catchment

Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast. The quality of rainfall data in terms of both intensity and distribution is very important for establishing a reliable meteo-hydrological forecasting model. To improve the accuracy of rainfall data, the successive correction method is introduced to correct the bias of rainfall, and a meteo-hydrological forecasting model based on WRF and WRF-Hydro is applied for streamflow forecast over the Zhanghe River catchment in China. The performance of WRF rainfall is compared with the China Meteorological Administration Multi-source Precipitation Analysis System (CMPAS), and the simulated streamflow from the model is further studied. It shows that the corrected WRF rainfall is more similar to the CMPAS in both temporal and spatial distribution than the original WRF rainfall. By contrast, the statistical metrics of the corrected WRF rainfall are better. When the corrected WRF rainfall is used to drive the WRF-Hydro model, the simulated streamflow of most events is significantly improved in both hydrographs and volume than that of using the original WRF rainfall. Among the studied events, the largest improvement of the NSE is from -0.68 to 0.67. It proves that correcting the bias of WRF rainfall with the successive correction method can greatly improve the performance of streamflow forecast. In general, the WRF / WRF-Hydro meteo-hydrological forecasting model based on the successive correction method has the potential to provide better streamflow forecast in the Zhanghe River catchment.     

Evaluating rainfall patterns using physics scheme ensembles from a regional atmospheric model

This study evaluated the ability of Weather Research and Forecasting (WRF) multi-physics ensembles to simulate storm systems known as East Coast Lows (ECLs). ECLs are intense low-pressure systems that develop off the eastern coast of Australia. These systems can cause significant damage to the region. On the other hand, the systems are also beneficial as they generate the majority of high inflow to coastal reservoirs. It is the common interest of both hazard control and water management to correctly capture the ECL features in modeling, in particular, to reproduce the observed spatial rainfall patterns. We simulated eight ECL events using WRF with 36 model configurations, each comprising physics scheme combinations of two planetary boundary layer (pbl), two cumulus (cu), three microphysics (mp), and three radiation (ra) schemes. The performance of each physics scheme combination and the ensembles of multiple physics scheme combinations were evaluated separately. Results show that using the ensemble average gives higher skill than the median performer within the ensemble. More importantly, choosing a composite average of the better performing pbl and cu schemes can substantially improve the representation of high rainfall both spatially and quantitatively.     

华东地区极端降水动力降尺度模拟及未来预估

利用CMIP5（Coupled Model Intercomparison Project Phase 5）数据集中的全球模式IPSL-CM5A-LR及其嵌套的区域气候模式WRF（Weather Research and Forecasting）,分别评估了模式对1981~2000中国华东区域极端降水指标的模拟能力,并讨论了RCP8.5排放情景下21世纪中期（2041~2060年）中国华东极端降水指标的变化特征。相比驱动场全球气候模式,WRF模式更好地再现了各个极端指数空间分布及各子区域降水年周期变化。在模拟区域气候特点方面,WRF模拟结果有所改进,并在弥补全球模式对小雨日过多模拟的缺陷起到了明显的作用。21世纪中期,华东区域的降水将呈现明显的极端化趋势。WRF模拟结果显示年总降雨量、年大雨日数、平均日降雨强度在华东大部分区域的增幅在20%以上;年极端降雨天数、连续5 d最大降水量的增幅在华东北部部分区域分别超过了50%和35%,同时最长续干旱日在华东区域全面增加;且变化显著的格点主要位于增加幅度较大的区域。未来华东区域会出现强降水事件和干旱事件同时增加的情况,降水呈现明显的极端化趋势,且华东北部极端化强于华东南部。     

VALIDATION OF NEAR-SURFACE WINDS OBTAINED BY A HYBRID WRF/CALMET MODELING SYSTEM OVER A COASTAL ISLAND WITH COMPLEX TERRAIN

The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.     

台风海葵引发浙西山区大暴雨的成因

利用中尺度数值模式WRF,结合多普勒雷达资料、卫星TBB资料和自动站资料对2012年8月6—9日由台风海葵引发的杭州西部山区强暴雨洪涝灾害进行分析。结果表明,登陆台风内部的螺旋云带中有多个中尺度云团活动,云团不断从台风螺旋云带内部分裂生成,并有一个从加强发展到逐渐消亡的过程,正是在中尺度云团的直接作用下,给台风经过地区造成了一次又一次的强降水,导致了浙西北等地区持续不断发生暴雨,因此,中尺度系统是造成台风暴雨的直接原因;台风外围的东北风、西北风和偏西风在有利地形配合下,往往会汇合形成中尺度辐合线,未来强降水区域也基本落在中尺度辐合线附近区域,中尺度辐合线是触发暴雨对流发生、发展的重要系统;浙江杭州西北部山区地形对于台风暴雨主要体现在增幅作用,对台风路径、降水范围影响不大。     

持续性强降水的区域模式动力中期预报研究

持续性强降水及其次生灾害给人民的生产和生活造成严重影响, 延伸其模式动力预报能力对防灾、减灾具有重要意义。随着对持续性强降水过程形成机理及模式动力中期预报认识的不断提高, 以减小模式初始条件误差、边界条件误差以及内场预报误差为目标提出了一系列动力中期预报技术方法, 主要包括:针对边界条件提出低通滤波技术方案, 改进了5 d以上的环流及降水预报; 针对模式预报内场进行谱逼近技术试验, 对提前3—7 d的小雨以上量级的降水预报改进明显; 针对初始条件进行多尺度混合更新初值技术预报试验, 融合全球预报的大尺度场及区域模式预报的中小尺度场进行15 d预报, 明显提高了50及100 mm以上的持续性累积降水预报时效。      

Evaluating the performance of a WRF physics ensemble over South-East Australia

When using the Weather Research and Forecasting (WRF) modelling system it is necessary to choose between many parametrisations for each physics option. This study examines the performance of various physics scheme combinations on the simulation of a series of rainfall events near the south-east coast of Australia known as East Coast Lows. A thirty-six member multi-physics ensemble was created such that each member had a unique set of physics parametrisations. No single ensemble member was found to perform best for all events, variables and metrics. This is reflected in the fact that different climate variables are found to be sensitive to different physical parametrisations. While a standardised super-metric can be used to identify best performers, a step-wise decision approach described here, allows explicit recognition of the “robustness” of choosing one parameterisation over another, allowing the identification of a group of “equally robustly” performing physics combinations. These results suggest that the Mellor-Yamada-Janjic planetary boundary layer scheme and the Betts-Miller-Janjic cumulus scheme can be chosen with some robustness. Possibly with greater confidence, the results also suggest that the Yonsei University planetary boundary layer scheme, Kain-Fritsch cumulus scheme and RRTMG radiation scheme should not be used in combination in this region. Results further indicate that the selection of physics scheme options has larger impact on model performance during the more intensive rainfall events.     

WRF和MM5模式对辽宁暴雨模拟的对比分析

用近年开发的新一代中尺度预报模式WRF(Weather Research Forecast)和已被广泛应用的MM5模式分别模拟研究了2002年8月3~4日发生在辽宁的一次区域性暴雨过程。模拟结果显示WRF模式能够比较成功地反映出导致暴雨发生的高低空环流背景和暴雨的分布状况;WRF和MM5模拟结果的对比分析表明:由于WRF的动力框架具有一定的优越性使得模式结果得到改善,在前处理和所选物理过程相同的情况下,WRF模式对能够代表本次暴雨过程中中尺度天气系统的高度场、风场、散度场、水汽通量场以及垂直速度场等物理量的模拟效果要好于MM5。高空形势场的影响使WRF模拟的降水落区和强度更接近实况。