The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006

The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.     

利用TRMM资料对热带气旋“威马逊”结构及其降水特征的研究

利用NASA提供的热带测雨卫星(TRMM)资料和NCEP/AVN模式的实况分析场研究了热带气旋“威马逊”(2002)的演变过程、结构和降水特征.对要素场及倾斜对流有效位能诊断分析发现,降水的分布和强度对热带气旋的发展有很好的指示作用.针对MM5的几种积云参数化方案进行了数值试验,初步研究了各方案在热带气旋定量降水预报(QPF)中的作用.     

Intercomparison of IRS-P4-MSMR derived geophysical products with DMSP-SSM/I and TRMM-TMI finished products

In this paper, MSMR geophysical products like Integrated Water Vapour (IWV), Ocean Surface Wind Speed (OWS) and Cloud Liquid Water (CLW) in different grids of 50, 75 and 150 kms are compared with similar products available from other satellites like DMSP-SSM/I and TRMMTMI. MSMR derived IWV, OWS and CLW compare well with SSM/I and TMI finished products. Comparison of MSMR derived CLW with that derived from TMI and SSM/I is relatively in less agreement. This is possibly due to the use of 37 GHz in SSM/I and TMI that is highly sensitive to CLW, while 37 GHz channels are not available on MSMR. Monthly comparison of MSMR geophysical products with those from TMI is all carried out for climatological purpose. The monthly comparisons were much better compared to instantaneous comparisons. In this paper, details of the data analysis and comparison results are presented. The usefulness of the MSMR vis-à-vis other sensors is also discussed.     

TRMM PR雷达与阜阳雷达降水资料的对比研究

选取了1998年与1999年HUBEX观测资料，将TRMM卫星上的星载降雨雷达PR与阜阳的713数字化天气雷达资料在以下3个方面做了比较：(1)强度场的分布；(2)平均反射率廓线；(3)灵敏度。分析、比较结果可知阜阳雷达在探测灵敏度和水平方向的分辨率要高于PR，但由于波束宽度、衰减和资料转化过程计算误差的原因，其远距离处的观测值与真实值有一定偏差。PR波长短，对衰减敏感，尤其是在垂直方向上经过强衰减后，订正值仍偏小。但由于探测方式的不同PR在水平方向上不存在衰减的问题，且其资料分布均匀，因此提出一种用PR资料来订正地基雷达资料的方法用以提高地基雷达探测的精确度。     

用TRMM资料研究江淮、华南降水的微波特性

热带测雨卫星TRMM (Tropical Rainfall Measuring Mission) 于1997年11月发射成功, 其首次携带了空载雷达, 有关资料已在网上对公众发布。利用热带测雨卫星上的微波成像仪TMI (TRMM Microw ave Imager) 资料以及其和测雨雷达TRMM/PR (Precipitation Radar) 资料联合反演的地面瞬时降水产品, 采用散射指数 (Is) 法从理论上探讨了我国江淮、华南降水尤其是暴雨的微波特性, 其中I_s表达式通过江淮、华南晴空TMI资料统计回归得到。以联合反演的地面瞬时降水产品为真值, 用面积相当法对14个降水个例求I_s降水阈值, 研究了阈值和降水面积以及85.5 GHz垂直通道最低亮温的关系, 并寻求了I_s和降水的相关特征。研究表明:I_s降水阈值随降水面积的增大或85.5 GHz垂直通道最低亮温的降低有增高的趋势; I_s与强对流性降水瞬时雨强对应很好, I_s≥60 K是一个好的暴雨指标。最后进行了初步的雨强反演试验研究, 由于TMI资料分辨率的提高以及时空配合较好的真值, 反演的地面瞬时降水与真值相关效果大大提高。     

反演寿县TMI微波频率的地表比辐射率

利用一个微波辐射传输模式，晴天下的大气探测廓线，地面的部分观测资料以及卫星观测的亮温，计算了淮河流域能量和水循环实验(HUBEx)中，寿县地区的热带降雨观测卫星微波成像仪(TRMM／TMI)微波频率的地表比辐射率。通过比较所计算的微波地表比辐射率随地表状况的改变，发现地表微波比辐射率随地表状况的变化存在敏感性，并且其变化是合理的。本中，地表肤温设定等于地表空气温度，并且仅计算了寿县的地表比辐射率，在HUBEx区域上的地表比辐射率的计算需要更多的观测资料。     

用TRMM/TMI估算HUBEX试验区的云中液态水

文中应用热带降雨测量卫星微波成像仪的微波遥感资料反演云中液态水。由于微波成像仪85.5 GHz通道对云中液态水非常敏感,通过离散纵坐标矢量辐射传输模式,运用迭代的方法可以有效地反演出陆地上空非降水云中的液态水路径。在淮河流域能量与水分循环试验中,分别运用微波成像仪85.5 GHz垂直极化单通道和微波成像仪85.5 GHz极化亮温差两种方法来估算陆地上空的云中液态水路径,反演结果与地基微波辐射计的测量结果是较为一致的。当地表比辐射率或地表温度误差较大时,用极化亮温差法估算云中液态水路径相对较好,尤其是对于低云,因为该方法对地表温度不敏感。     

TRMM卫星微波成像仪分级产品及其反演降水算法

文章叙述了获取定量降水信息的意义，简要介绍了对热带测雨卫星TRMM(Tropical Rainfall Measurement Mission)的仪器、美国国家宇航局提供的微波成像仪TMI(TRMM Microwave Imager)分级产品。对比了物理方法和经验方法反演降水的特点，并对一些经验方法以及倾斜对流系统对反演降水的影响、动态聚类分析、神经网络反演方法的研究成果进行了介绍。     

热带测雨卫星对淮河一次暴雨降水结构与闪电活动的研究

文中利用热带测雨卫星 (TRMM )搭载的测雨雷达 (PR)、闪电成像仪 (LIS)、GOES卫星红外通道辐射亮温(TBB)对 2 0 0 3年淮河汛期一锋面气旋系统的两个时次的探测结果 ,分析研究了降水结构及闪电活动 ,并与“98.7.2 0”武汉附近地区中尺度强降水的结构和闪电活动进行了比较。GOES的TBB、降水系统中的对流降水与层云降水比例、闪电活动频数随时间的变化均能表征锋面气旋系统的发展。TRMMPR探测结果表明 :冷锋降水狭窄细长 ,且均为强对流降水 (特别在冷锋加强时 ) ;暖锋宽广 ,且为大片层云降水 ,但其中存在面积不等的强对流降水云团 ;与“98.7.2 0”武汉附近地区中尺度强降水垂直结构的比较表明 ,锋面气旋降水的最大降水率出现在近地面 ,而中尺度强降水的最大降水率出现在低空 (3.0～ 3.5km) ,表明两者之间的降水微物理过程存在差别。TRMMLIS探测结果表明 :闪电活动均发生在冷锋的强对流降水云团中 ,暖锋中虽有强对流降水 ,但无闪电活动 ;闪电活动频数高所对应的降水廓线中、上部存在大量的冰相粒子。     

Tropical Precipitation Estimated by GPCP and TRMM PR Observations

In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project （GPCP） version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar （TRMM PR） are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d^-1 is larger than that of about 0.1 mm d^-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function （PDF） analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d^-1. When the TRMM PR rain rate is greater than 8 mm d^-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d^-1 compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d^-1 between the two datasets when the rain rate is less than 10 mm d^-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.