Improvement of microwave rainfall retrievals in Bayesian retrieval algorithms

被引：3
|
作者：
Seo, Eun-Kyoung [1 ]
Sohn, Byung-Ju [1 ]
Liu, Guosheng [2 ]
Ryu, Geun-Hyeok [1 ]
Han, Hyo-Jin [1 ]
机构：
[1] Seoul Natl Univ, Sch Earth & Environm Sci, Seoul, South Korea
[2] Florida State Univ, Dept Meteorol, Tallahassee, FL 32306 USA
来源：
JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN | 2008年 / 86卷 / 02期
关键词：
D O I：
10.2151/jmsj.86.405
中图分类号：
P4 [大气科学（气象学）];
学科分类号：
0706 ; 070601 ;
摘要：
This note describes a method to improve the current Tropical Rainfall Measuring Mission (TRMM) passive microwave rain rate estimates by adopting a modified probability density function (PDF) of rain rates in Bayesian retrieval algorithms. Unlike the original database that was generated from cloud model simulations mostly for more "eventful" cloud/rain cases, the modified PDF includes the probability of zero rain rates derived from actual observations. Based on analysis of one year TRMM data, this simple remedy lowers the passive microwave rain rate estimates by 3% and reduces the discrepancy between radiometer and radar estimates by 6%.
引用
收藏
页码：405 / 409
页数：5
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