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An Algorithm for Retrieving the 2-D Distribution of Moderate Rain by X-SAR

  • Shuyuan Lu
  • , Yanan Xie
  • , Rui Wang*
  • , Ting Luo
  • , Zhenbin Xu
  • , Xueying Yu
  • *Corresponding author for this work
  • Shanghai University

Research output: Contribution to journalArticlepeer-review

Abstract

Synthetic aperture radar (SAR) can detect ground information with high precision, which provides another opportunity for the retrieval of rain. Rainfall intensities in East Asia are mainly moderate. The current retrieval algorithms have high accuracy in rainstorms, but they overestimate the rainfall intensity greatly in moderate rain. Therefore, it is very important to reduce the retrieval error of SAR in moderate rain. After analyzing the scattering model of precipitation, this paper proposes an algorithm for retrieving 2-D moderate rain distribution (MRA). Since the 2-D distribution of rain is related to the vertical and horizontal distributions, MRA combines the empirical regression equation with the directional model of rain rates at different levels to retrieve the vertical distribution of precipitation. Compared with the model-oriented statistical (MOS) algorithm, MRA reduces the root mean square error when retrieving the surface rain rate from 2.6 to 0.1. In addition, based on the high-precision rain parameters retrieved by MRA, the horizontal distribution is retrieved through the likelihood distance. This horizontal distribution retrieval method not only has less amount of calculation but also avoids the difficulties of mathematical analysis.

Original languageEnglish
Article number4081
JournalRemote Sensing
Volume14
Issue number16
DOIs
StatePublished - Aug 2022
Externally publishedYes

Keywords

  • rain distribution
  • surface rain rate
  • synthetic aperture radar

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