用GPROF算法反演降水强度和水凝物垂直结构

对NASA应用于TMI的业务降水反演算法(GPROF算法)作了简单分析，并对采用该算法反演的2002年夏季我国湖南常德地区的暴雨结构和2001年7月上旬袭击中国香港地区的尤特台风结构进行了分析。对常德暴雨个例，用地面雷达数据作为实况资料进行了真实性检验。检验结果表明:该算法的整体反演效果较好，可较好地反演常德地区的地面雨强及降水结构，雨区的反演精度与降水性质有关。对尤特台风个例，将反演结果与测雨雷达的反演产品进行了定性比较，结果表明:二者反映的降水结构基本一致；GPROF算法反演的潜热垂直结构也较好地反映了台风的热力结构。最后对算法可能的改进方向进行了讨论。     

Comparison of TRMM and water district rain rates over New Mexico

This paper compares monthly and seasonal rain rates derived from the Version 5 (V5) and Version 6 (V6) TRMM Precipitation Radar (TPR, TSDIS reference 2A25), TRMM Microwave Imager (TMI, 2A12), TRMM Combined Instrument (TCI, 2B31), TRMM calibrated IR rain estimates (3B42) and TRMM merged gauge and satellite analysis (3B43) algorithms over New Mexico (NM) with rain gauge analyses provided by the New Mexico water districts (WD). The average rain rates over the NM region for 1998–2002 are 0.91mmd?1 for WD and 0.75, 1.38, 1.49, 1.27, and 1.07mmd?1 for V5 3B43, 3B42, TMI, PR and TCA; and 0.74, 1.38, 0.87 and 0.97 mm d?1 for V6 3B43, TMI, TPR and TCA, respectively. Comparison of V5 3B43 with WD rain rates and the daily TRMM mission index (TPR and TMI) suggests that the low bias of V5 3B43 for the wet months (summer to early fall) may be due to the non-inclusion of some rain events in the operational gauge analyses that are used in the production of V5 3B43. Correlation analyses show that the WD rain rates vary in phase, with higher correlation between neighboring WDs. High temporal correlations (>0.8) exist between WD and the combined algorithms (3B42, 3B43 and TCA for both V5 and V6) while satellite instrument algorithms (PR, TMI and TCI) are correlated best among themselves at the monthly scale. Paired t-tests of the monthly time series show that V5 3B42 and TMI are statistically different from the WD rain rates while no significant difference exists between WD and the other products. The agreements between the TRMM satellite and WD gauge estimates are best for the spring and fall and worst for winter and summer. The reduction in V6 TMI (?7.4%) and TPR (?31%) rain rates (compared to V5) results in better agreement between WD estimates and TMI in winter and TPR during summer.     

利用热带降雨测量卫星的微波成像仪观测资料反演陆地降水

利用热带降雨测量卫星的微波成像仪资料，结合淮河流域试验加密观测期的阜阳地面天 气雷达雨量资料，建立了以散射指数和极化订正温度为主要参数的降水反演算法。对文 中所做反演试验与日本ＮＡＳＤＡ用微波成像仪和星载测雨雷达反演的雨强进行了比较。结果表明 ，文中所用的方法在反演陆地下垫面的降雨强度的分布和降雨区域的确定是比较成功的。     

Physical retrievals of over-ocean rain rate from multichannel microwave imagery. Part II: Algorithm implementation

Summary A new physical inversion-based algorithm for retrieving rain rate over the ocean with the Special Sensor Microwave Imager (SSM/I) is described. In a departure from other rain rate retrieval algorithms, the satellite observables inverted in the present algorithm are not the raw brightness temperatures but rather normalized polarizations for 19.35, 37.0, and 85.5 GHz, plus an 85.5 GHz scattering index which is sensitive primarily to ice particles aloft. The normalized polarizations are interpreted as footprint-averages of theoretically derived analytic functions of the column optical depth associated primarily with liquid water. The effective vertical depth of the rain layer is specified as a function of the SSM/I estimated column water vapor.The retrieval algorithm performs an iterative search for a high resolution (12.5 km) rain field which is simultaneously consistent with the 19.35 and 37.0 GHz normalized polarizations. The first-guess rain rate field is supplied by the 85.5 GHz scattering index. At gridpoints for which the rain column optical depth exceeds the dynamic range of the attenuation-based indices, the first-guess field is left essentially unmodified; elsewhere, the required consistency with the 19 and 37 GHz indices usually results in significant modification of the scattering-based rain rate estimates.The algorithm as described here is a prototype implementation which was developed with reference only to idealized theoretical models; empirical improvements to the numerical scheme and the model coefficients will be made in the future as results from the first Precipitation [algorithm] Intercomparison Project 1 (PIP-1) and the second phase of the GPCP (Global Precipitation Climatology Project) algorithm Intercomparison Project (AIP/2) are analyzed, as well as data from individual validation efforts. Although the algorithm is physically based and uses all SSM/I channels, it is computationally much less demanding than cloud/radiative transfer model-based inversion algorithms published else-where.With 9 Figures     

Sensitivity of hurricane intensity forecasts to physical initialization

Summary Intensity forecasts of a hurricane are shown to be quite sensitive to the initial meso-convective scale precipitation distributions. These are included within the data assimilation using a physical initialization that was developed at Florida State University. We show a case study of a hurricane forecast where the inclusion of the observed precipitation did provide reasonable intensity forecasts. Further experimentation with the inclusion or exclusion of individual meso-convective rainfall elements, around and over the storm, shows that the intensity forecasts were quite sensitive to these initial rainfall distributions. The exclusion of initial rain in the inner rain area of a hurricane leads to a much reduced intensity forecast, whereas that impact is less if the rainfall of an outer rain band was initially excluded.Intensity forecasts of hurricanes may be sensitive to a number of factors such as sea surface temperature anomalies, presence or absence of concentric eye walls, potential vorticity interactions in the upper troposphere and other environmental factors.This paper is a sequel to a recent study, Krishnamurti et al., 1997, on the prediction of hurricane OPAL of 1995 that was a category III storm over the Gulf of Mexico. In that study we showed successful forecasts of the storm intensity from the inclusion of observed rainfall distributions within physical initialization. In that paper we examined the issues of diabatic potential vorticity and the angular momentum in order to diagnose the storm intensity. All of the terms of the complete Ertel potential vorticity equation were evaluated and it was concluded that the diabatic contributions to the potential vorticity were quite important for the diagnosis of the storm's intensity. The present paper addresses some sensitivity issues related to the individual mesoconvective precipitating elements.With 4 Figures     

TRMM卫星与机载雷达在降雨反演中的数据对比个例研究

热带降水测量卫星（TRMM）上搭载的测雨雷达是第一部能够提供三维降水信息的星载雷达,机载雷达也能够对降雨进行实时观测。由于机载和星载雷达观测有很多共同点,所以选择机载、星载雷达数据进行对比。1998年8月26日NOAA/P3飞机对Bonnie飓风进行了一次观测飞行,与此同时TRMM卫星也同步扫过该区域,因此利用对Bonnie飓风的机、星观测数据对应点数值对比、差值对比、平均值对比等,对Bonnie飓风做了进一步分析。对比结果一致,印证了TRMM数据的可靠性,同时进一步验证了双束立体雷达算法的联合算法的可靠性。     

On the Tropical Rainfall Measuring Mission (TRMM)

Summary The importance of quantitative knowledge of tropical rainfall, its associated latent heating and variability is summarized in the context of climate change. Since the tropics are mainly covered with oceans, with some deserts and jungles, the monthly precipitation is not known within a factor of two. Hence the only way to measure it adequately for climate and general circulation models is from space. The paper describes the Tropical Rainfall Measuring Mission (TRMM). This joint Japan-U.S. cooperative Earth Probe satellite will be launched from Japan in 1997 for a three-year mission. The scientific basis of the instrument and orbit selection is explained. The precipitation instrument complement comprises the first rain radar to be flown in space (PR), and a multi-channel passive microwave sensor (TMI) improved relative to the SSM/I¹ by an additional channel at 10 GHz. The third rain instrument is a five-channel VIS/IR (VIRS) sensor. Progress in construction of instruments, observatory, data system, and the ground validation program is summarized. A report is also given concerning development of the algorithms by which rainfall and its associated latent heat release will be calculated from the several instruments, separately and in combination, and how the scientists will interact with the data system to obtain the 32 rain data products necessary to fulfill the science requirements.With 9 FiguresSSM/I stands for Special Sensor Microwave Imager.     

基于热带测雨卫星探测的东亚降水云结构特征的研究

利用热带测雨卫星的测雨雷达(TRMMPR)、微波成像仪(TMI)、可见光和红外辐射计(VIRS)、闪电成像仪(LIS)对降水云的综合探测结果,结合全球降水气候计划降水资料(GPCP)和中国气象台站雨量计观测资料,分析了东亚降水分布特点,并比较了TRMMPR与GPCP及地面雨量计观测结果的差异;揭示了中国中东部大陆、东海和南海对流降水和层云降水平均降水廓线的季节变化特征及物理意义,以及TMI高频和低频微波信号对地表降水率变化的响应特点;通过对中尺度强降水系统、锋面气旋降水系统和热对流降水系统的个例分析,探明了降水结构及其与闪电活动的关系、降水云顶部信息与地表雨强之间的关系。     

Physical initialization in the NMC Global Data Assimilation System

Summary The impact of assimilating Goes Precipitation Index (GPI) rain rates in the National Meteorological Center Global Data Assimilation System (NMC GDAS) via physical initialization is explored. Reverse algorithms of the simplified Arakawa-Schubert cumulus parameterization and the parameterized surface fluxes are developed in order to assimilate the GPI data over the tropics during the six hour forecasts linking successive GDAS analyses. Results from two experiments show improvements to both analyses and forecasts when GPI rain rates are assimilated.With 16 Figures     

Numerical weather prediction over the Eastern Caribbean using Florida State University (FSU) global and regional spectral models and multi-model/multi-analysis super-ensemble

Summary A month-long short-range numerical weather prediction experiment using the Florida State University’s (FSU) global and regional models and the multi-model/multi-analysis super-ensemble over the Eastern Caribbean domain is presented in this paper. The paper also investigates weather prediction capabilities of FSU global and regional models by examining the root mean square errors (RMSE) for the wind and precipitation fields. Super-ensemble forecasting, a new statistical approach to weather forecasting, is used over this domain. Here, forecasts from a number of numerical models provide the input and statistical combinations of these forecasts produce the super-ensemble forecast. A similar approach is used for the precipitation field where one model using different rain rate algorithms is used to generate different model outputs. The results show that the super-ensemble method produces forecasts that are superior to those obtained from the ensemble members. Received May 29, 2000/Revised February 15, 2001     

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。     

星载被动微波遥感反演降水算法回顾

根据不同的降水反演方法对多种利用SSM／I、TMI反演降水的算法进行归类总结，按下垫面检测和降水反演算法两大步骤进行简要描述，并分经验法、半经验(半物理)法、物理模式法及物理廓线法4类方法对多种算法作了回顾。     

The Challenges of Modeling Climate Variability and Change in West Africa

This paper overviews observations and examines modeling issues associated with the mean state, climate variability and climate change in West Africa. The Tropical Rain Measuring Mission (TRMM) satellite allows for the first time estimates of Unconditional, Convective and Stratiform rain rates in West Africa. The 1998 estimated TRMM rates are compared to long-term observed rain rates and a merged rain data set (CMAP) during 1998. Further, the TRMM estimates are compared to the simulated rain rates from the Community Climate Model Version 3.6. The TRMM Precipitation Radar rain estimates are generally lower than either the long-term observations or the CMAP rates during 1998. Moreover, the TRMM rain estimates show a significant fraction of the total rain (convective + stratiform) is characterized as stratiform rain (30–40%). The CCM3 simulates primarily convective rain and negligible amounts of non-convective rain for West Africa. Furthermore, the TRMM high-resolution rain patterns strongly imply that rain in West Africa occurs on mesoscales in association with mesoscale convective systems (squall lines, mesoscale convective complexes and non-squall tropical clusters). We demonstrate this by briefly examining two mesoscale convective systems during May 1998 with METEOSAT data. Regional climate models may offer the best solution to understanding climate change in West Africa because of their ability to capture mesoscale systems and better their representation of orographic features. Adequate boundary conditions from Global Climate Models are still necessary for regional climate model simulations to successfully reproduce mean climate conditions and provide understanding with respect to future climate change. Observations in West Africa should be maintained or increased for monitoring climate variability and possibility of climate change in West Africa, proper initialization of numerical weather prediction models and the validation of climate models.     

Rain rates based on SSM/I,OLR and raingauge data sets

Summary In this paper we present a methodology for evaluating rain rates from a mix of satellite and surface based observations. The component data sets include the outgoing longwave radiation (OLR), microwave radiometric data from the special sensor microwave imager (SSM/I) and surface raingauge data from the World Weather Watch. We have noted some deficiencies in the SSM/I algorithm-based rain rate over land areas; the OLR-based rain rates exhibit a larger lateral spread and lower intensities than the observed rainfall structures. The proposed combined method assimilates these three data sets to provide improved fields of global tropical rainfall.With 3 Figures     

Rain rate estimation from a synergetic use of SSM/I, AVHRR and meso-scale numerical model data

Summary In this paper a retrieval technique for estimating rainfall rates is introduced. The novel feature of this technique is the combination of two satellite radiometers — the Special Sensor Microwave/Imager (SSM/I) and the Advanced Very High-Resolution Radiometer (AVHRR) — with mesoscale weather prediction model data. This offers an adjustment of the model atmospheres to reality which is necessary for calculating brightness temperatures that can be compared with microwave satellite measurements.In sensitivity studies it was found that the estimation of precipitation is determined to a high degree by the particle size distribution of rain and snow, especially by the size distribution of solid hydrometeors. These studies also reveal the influence of the knowledge of the correct cloud coverage inside a SSM/I pixel and the importance of using a realistic temperature profile instead of using standard atmospheres.The retrieval technique is based on radiative transfer calculations using the model of Kummerow et al. (1989). The algorithm consists of two parts: First Guess (FG) brightness temperatures for the SSM/I frequencies are generated as a function of the cloud top height and the cloud coverage, derived from AVHRR data and predictions from a meso-scale model. The rainfall rate of different types of clouds containing raindrops, ice particles and coexisting ice and water hydrometeors is then calculated as a function of the cloud top height. As an example, a strong convective rain event over the western part of Europe and over the Alps is taken to evaluate the performance of this technique. Good agreement with radar data from the German Weather Service was achieved. Compared to statistical rainfall algorithms, the current algorithm shows a better performance of detecting rainfall areas.With 12 Figures     

Organization of convection and monsoon forecasts

Summary In this paper we address the issue of monsoon forecasts in relation to the organization of convection. Given a physical initialization procedure, within a data assimilation, it is possible to use the detailed distribution of rainfall from mesoconvective precipitating elements to define the initial state of a global model. If that is carried out using a very high resolution model then the initial state can carry within it an organization of convection within the resolvable scales. Then the impact of physical initialization on the maintenance and prediction of tropical weather such as the monsoon can be determined. Lacking such an initialization, one can expect the convectively driven energetics to be biased, and a slow degradation of the forecasts can follow. Several examples of forecasts at different resolutions are discussed here. The main findings of this study are that improved forecast results are obtained when physical initialization is invoked where the observed rain and the model resolution are comparable, i.e. the footprint of the highest resolutions rainfall estimates obtained from satellite based data sets (principally we use the SSM/I instrument over the oceans). At this resolution, we note that the model is able to carry an organization of convection in the initialization and in the forecasts through the medium-range time scale.We have compared our results of monsoon studies at a resolution T255 with those at resolution T62. The transform grid separation at the resolution T255 is approximately 50 km and at the resolution T62, it is approximately 200 km. We find that the model at the higher resolution (T255) performs better and has more realistic energy conversions for the convectively driven synoptic scale monsoon.An organization of convection, at the synoptic scales, is not seen in the forecasts at lower resolutions, T62, where the rainfall patterns are generally much broader and tend to be more zonal. Such organization appears more realistic at the resolution T255. Variances of the energy conversion, calculated in the two-dimensional spectral space, from physically initialized short range forecasts at the higher resolution are seen to be largest on the scales of the monsoon. Similar calculations for the reanalyzed fields at lower resolutions show the spectral distribution of variances to be biased towards local Hadley scale overturnings.With 12 Figures     

TRMM-retrieved Cloud Structure and Evolution of MCSs over the Northern South China Sea and Impacts of CAPE and Vertical Wind Shear

Cloud structure and evolution of Mesoscale Convective Systems(MCSs) retrieved from the Tropical Rainfall Measuring Mission Microwave Imager(TRMM TMI) and Precipitation Radar(PR) were investigated and compared with some pioneer studies based on soundings and models over the northern South China Sea(SCS).The impacts of Convective Available Potential Energy(CAPE) and environmental vertical wind shear on MCSs were also explored.The main features of MCSs over the SCS were captured well by both TRMM PR and TMI.However,the PR-retrieved surface rainfall in May was less than that in June,and the reverse for TMI.TRMM-retrieved rainfall amounts were generally consistent with those estimated from sounding and models.However,rainfall amounts from sounding-based and PR-based estimates were relatively higher than those retrieved from TRMM-TMI data.The Weather Research and Forecasting(WRF) modeling simulation underestimated the maximum rain rate by 22% compared to that derived from TRMM-PR,and underestimated mean rainfall by 10.4% compared to the TRMM-TMI estimate,and by 12.5% compared to the sounding-based estimate.The warm microphysical processes modeled from both the WRF and the Goddard Cumulus Ensemble(GCE) models were quite close to those based on TMI,but the ice water contents in the models were relatively less compared to that derived from TMI.The CAPE and wind shear induced by the monsoon circulation were found to play critical roles in maintaining and developing the intense convective clouds over SCS.The latent heating rate increased more than twofold during the monsoon period and provided favorable conditions for the upward transportation of energy from the ocean,giving rise to the possibility of inducing large-scale interactions.     

基于TMI产品资料对数值模式水凝物模拟能力的检验分析

本文利用热带测雨卫星(Tropical Rainfall Measuring Mission,TRMM)搭载微波成像仪(TRMM Microwave Imager,TMI)的探测及反演结果,结合微波辐射传输模式,就2004年17号台风暹芭(Chaba)过程,对AREM(Advanced Regional Eta-coo...     

Analyses of Orissa Super Cyclone using TRMM (TMI), DMSP (SSM/I) and OceanSat-I (MSMR) Derived Data

The super cyclone in October 1999 was the most intense tropical cyclone in the last century in Orissa, a coastal state in India. This state was battered for more than two days by strong winds and intense rain killing thousands of people. The main objective of this study is to examine the impact of total precipitable water content (TPWC) and surface wind speed data from sensors on board the Tropical Rainfall Measuring Mission (TRMM), Defense Meteorological Satellite Project (DMSP), and Indian Remote Sensing Satellite (OceanSat-I) satellites on the data assimilation system at NCMRWF, New Delhi during the Orissa cyclone period. Comparison of various assimilation experiments suggests that the utilization of TRMM Microwave Imager (TMI) data in the assimilation produced the best analyses. However, in all the forecasts, the storm was predicted to weaken and did not have a reasonably good track. Assimilation experiments with the other two satellite data showed the cyclone track much to the south of the observed track and also it was a weak storm. Biases in the data, when compared with each other, are evident in the analyses also. Better analyses are obtained when the satellite data are used in the originally obtained resolution than when reduced by averaging. A forecast experiment with assimilated data, utilizing the Cloud Motion Vectors (CMVs) from METEOSAT along with TMI data, produced the best forecast among all the experiments. However, the forecast quality was poor. A high-resolution data assimilation experiment was carried out to see the impact of model resolution on the analyses of the cyclone. The strength of the cyclone further increased when higher resolution TMI data were included. The study highlights the need for more satellite data over the Indian Ocean, where conventional data coverage is too poor to define the vertical structure of the atmosphere.     

Resolving SSM/I-ship radar rainfall discrepancies from AIP-3

The third algorithm intercomparison project （AIP-3） involved rain estimates from more than 50 satellite rainfall algorithms and ground radar measurements within the Intensive Flux Array （IFA） over the equatorial western Pacific warm pool region during the Tropical Ocean Global Atmosphere coupled Ocean-Atmosphere Response Experiment （TOGA COARE）. Early results indicated that there was a sys- tematic bias between rainrates from satellite passive microwave and ground radar measurements. The mean rainrate from radar measurements is about 50% underestimated compared to that from passive microwave-based retrieval algorithms. This paper is designed to analyze rain patterns from the Florida State University rain retrieval algorithm and radar measurements to understand physically the rain discrep- ancies. Results show that there is a clear range-dependent bias associated with the radar measurements. However, this range-dependent systematical bias is almost eliminated with the corrected radar rainrates. Results suggest that the effects from radar attenuation correction, calibration and beam filling are the major sources of rain discrepancies. This study demonstrates that rain retrievals based on satellite mea- surements from passive microwave radiometers such as the Special Sensor of Microwave Imager （SSM/I） are reliable, while rain estimates from ground radar measurements are correctable.