Neural network wind retrieval from ERS-1/2 scatterometer data

LIN Mingsen; SONG Xingai; JIANG Xingwei

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Article Navigation > Acta Oceanologica Sinica > 2006 > (3): 35-39

LIN Mingsen, SONG Xingai, JIANG Xingwei. Neural network wind retrieval from ERS-1/2 scatterometer data[J]. Acta Oceanologica Sinica, 2006, (3): 35-39.

Citation:

LIN Mingsen, SONG Xingai, JIANG Xingwei. Neural network wind retrieval from ERS-1/2 scatterometer data[J]. Acta Oceanologica Sinica, 2006, (3): 35-39.

LIN Mingsen, SONG Xingai, JIANG Xingwei. Neural network wind retrieval from ERS-1/2 scatterometer data[J]. Acta Oceanologica Sinica, 2006, (3): 35-39.

Citation:

LIN Mingsen, SONG Xingai, JIANG Xingwei. Neural network wind retrieval from ERS-1/2 scatterometer data[J]. Acta Oceanologica Sinica, 2006, (3): 35-39.

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Neural network wind retrieval from ERS-1/2 scatterometer data

1.
National Satellite Ocean Application Service, Beijing 100081, China
2.
National Satellite Ocean Application Service, Beijing 100081, China;College of Physical and Environment Oceanography, Ocean University of China, Qingdao 266003, China

Received Date: 2005-10-22
Rev Recd Date: 2006-02-08

Abstract

Abstract

A neural network methodology is presented to retrieve wind vectors from ERS-1/2 scatterometer data. The wind directional ambiguities are eliminated by a circular median filter algorithm. All data come from ERS-1/2 scatterometer data collocated pairs with CMCD4 vector. Comparing the results with CMCD4 and ECMWF wind vector,they agree well, which indicates that it is possible to extract wind vector from the ERS-1/2 scatterometer with the neural network method.
- BP-NN,
- scatterometer,
- wind fields,
- retrieval,
- disambiguate