Applications of satellite passive microwave data to rainfall estimation and FOG detection

Nan Ching Yeh, Jian Liang Wang, Wann Jin Chen, Gin Rong Liu, James Yu Chen Yaung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The torrential rainfall from typhoon caused the damage and loss of lives and properties. The low visibility produced by heavy fog always has a significant impact on transportation and military mission. The above-mentioned atmospheric parameters are the requirements of operational organizations. The aim of this study is rainfall estimation and fog detection by passive microwave data. Satellite passive microwave observations have potential to provide rainfall estimation and fog detection for wide oceans. The rainfall estimation for typhoons over ocean is using Bayesian approach. The fog detection over sea is based on the difference of brightness temperatures of TMI channels between heavy fog and clear weather conditions. The preliminary analysis shows the difference of brightness temperature is obvious in high frequency channels, especially in 85 GHz. In addition, we compare retrieved rain rate with that obtained from Precipitation Radar. Their correlation coefficients are 0.68 and 0.75 for the convection and stratiform rainfall patterns, respectively.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages1042-1046
Number of pages5
StatePublished - 2011
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 3 Oct 20117 Oct 2011

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume2

Conference

Conference32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Country/TerritoryTaiwan
CityTapei
Period3/10/117/10/11

Keywords

  • Brightness temperature
  • Heavy fog
  • Passive microwave
  • Rain rate

Fingerprint

Dive into the research topics of 'Applications of satellite passive microwave data to rainfall estimation and FOG detection'. Together they form a unique fingerprint.

Cite this