利用无雨条件下亮度温度统计资料进行陆地微波辐射计观测的雨/无雨分类方法

S. Seto, N. Takahashi, T. Iguchi
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引用次数: 59

摘要

全球降水测量项目是热带降雨测量任务(TRMM)的继任者,其目标之一是利用几个星载微波辐射计制作3小时全球雨量图。将陆地上的辐射计观测分为“下雨”或“不下雨”是很重要的,尽管往往很困难,因为地面背景条件随时间和地点的变化很大。利用TRMM微波成像仪(TMI)和降水雷达(PR)同时观测的1个月、1°纬度1°经度数据,建立了无雨亮度温度数据库。本文提出了一种利用数据库确定背景亮度温度的雨/无雨分类方法。提出的RNC方法和为Goddard profiling算法(GPROF;对2000年全年的所有TMI观测结果应用了TMI标准雨率检索算法,并将结果与PR的RNC作为“真实值”进行了评估。第一种方法(M1)简单地将无雨条件下85- ghz垂直极化下的平均亮度温度[记为TB (85 V)]作为85- ghz垂直极化下的背景亮度温度[记为TBe (85 V)]。第二种方法(M2)使用数据库中无雨条件下TB (85 V)和TB (22 V)之间的回归方程。在这里,TBe (85 V)是通过将观测到的TB (22 V)代入回归方程来计算的。GPROF对降雨的准确探测与PR对所有降雨的探测之比为59%。M1和M2的比值分别为57%和63%。M1与雨率的比值为81%,M2为86%;GPROF是80%。这些比较是通过使用常数系数k0设置阈值来进行的,以使所有三种方法的假雨检测与PR检测到的所有无雨事件的比率几乎相同(约0.85%)。并对各种方法进行了进一步的比较,探讨了产生差异的原因。
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Rain/No-Rain Classification Methods for Microwave Radiometer Observations over Land Using Statistical Information for Brightness Temperatures under No-Rain Conditions
One of the goals of the Global Precipitation Measurement project, the successor to the Tropical Rainfall Measuring Mission (TRMM), is to produce a 3-hourly global rainfall map using several spaceborne microwave radiometers. It is important, although often difficult, to classify radiometer observations over land as either “rain” or “no rain” because background land surface conditions change significantly with time and location. In this study, a no-rain brightness temperature database was created to infer land surface conditions using simultaneous observations by TRMM Microwave Imager (TMI) and precipitation radar (PR) with a resolution of 1 month and 1° latitude 1° longitude. This paper proposes new rain/no-rain classification (RNC) methods that use the database to determine the background brightness temperature. The proposed RNC methods and the RNC method developed for the Goddard profiling algorithm (GPROF; the standard rain-rate retrieval algorithm for TMI) are applied to all TMI observations for the entire year of 2000, and the results are evaluated against the RNC made by PR as the “truth.” The first method (M1) simply uses the average brightness temperature at 85-GHz vertical polarization [denoted as TB (85 V)] under no-rain conditions as the background brightness temperature at 85-GHz vertical polarization [denoted as TBe (85 V)]. The second method (M2) uses a regression equation between TB (85 V) and TB (22 V) under no-rain conditions from the database. Here, TBe (85 V) is calculated by substituting the observed TB (22 V) into the regression equation. The ratio of accurate rain detection by GPROF to all rain occurrences detected by PR was 59%. This ratio was 57% for M1 and 63% for M2. The ratio with the weight of the rain rate was 81% for M1 and 86% for M2; it was 80% for GPROF. These comparisons were made by setting a threshold using a constant coefficient k0 to make the ratio of false rain detection to all no-rain occurrences detected by PR almost the same (approximately 0.85%) for all three methods. Further comparisons among the methods are made, and the reasons for the differences are investigated herein.
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