A neural network approach for wind retrieval from the ERS-1 scatterometer data. 1. Determination of the geophysical model function of ERS-1 scatterometer
- 17 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, I/76-I/80
- https://doi.org/10.1109/oceans.1994.363918
Abstract
Computes a new geophysical model function (GMF) for the ERS-1 scatterometer by the use of neural networks (NN). This NN-GMF is calibrated with ERS-1 scatterometer sigma0 collocated with ECMWF analysed wind vectors. In order to check the validity of the NN-GMF systematic comparisons with the ESA CMOD4-GMF (version 2) and the IFREMER CMOD2-I3-GMF are made. The GMF is used in many algorithms to retrieve the scatterometer wind.Keywords
This publication has 2 references indexed in Scilit:
- A neural network approach for modeling nonlinear transfer functions: Application for wind retrieval from spaceborne scatterometer dataJournal of Geophysical Research: Oceans, 1993
- Wind ambiguity removal by the use of neural network techniquesJournal of Geophysical Research: Oceans, 1991