New methods for retrieval of rainfall rate over ocean with SSM/I data

Daren Lu; Haibing Sun; Jianchun Bian; Hongbin Chen; Jinli Liu; Minzheng Duan; Zhigang Han

doi:10.1117/12.319455

19 August 1998 New methods for retrieval of rainfall rate over ocean with SSM/I data

Daren Lu, Haibing Sun, Jianchun Bian, Hongbin Chen, Jinli Liu, Minzheng Duan, Zhigang Han

Proceedings Volume 3503, Microwave Remote Sensing of the Atmosphere and Environment; (1998) https://doi.org/10.1117/12.319455
Event: Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space, 1998, Beijing, China

Abstract

Spaceborne microwave (MW) remote sensing of rainfall distribution with multi-channel radiometers has been proved as a powerful tool in past decade, in particular with DMSP's SSM/I data. Similar instruments but with different channel combinations, such as ADEOS-II/AMSR are being developed. Although there have been several retrieval schemes used for research and operational application, improvement of retrieval accuracy is still an important subject. As part of a NASDA project for ADEOS-II/AMSR retrieval algorithm development and Chinese National High-Tech R and D Program for Space Development, we proposed two kinds of retrieval algorithms for rainfall rate over ocean with SSM/I data. The first kind of algorithm is based on the probability pairing method, in which three different retrieval rain indices composed with different combination of SSM/I's channels are used as pairing indices with surface rainfall rate data provided by NASDA, Japan. Three different empirical rainfall rate--rain index relationship are produced. The second kind of algorithm is based on the method of self organization feature mapping (SOM), a kind of artificial neural network. SSM/I data and co-located surface rainfall data are put into SOM and clustering procedure is self-trained. After training, 154 clustering centers are formed and for each cluster a regressive relationship between retrieved rainfall rate and SSM/I data is established. In this paper, these two kinds of algorithm are briefly reviewed with their developments and validation. Their respective advantages and limitations are discussed.

Citation Download Citation

Daren Lu, Haibing Sun, Jianchun Bian, Hongbin Chen, Jinli Liu, Minzheng Duan, and Zhigang Han "New methods for retrieval of rainfall rate over ocean with SSM/I data", Proc. SPIE 3503, Microwave Remote Sensing of the Atmosphere and Environment, (19 August 1998); https://doi.org/10.1117/12.319455

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KEYWORDS

Clouds

Data modeling

Algorithm development

Medium wave

Remote sensing

Data centers

Radiometry

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