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Detailed Reference Information |
Stogryn, A.P., Butler, C.T. and Bartolac, T.J. (1994). Ocean surface wind retrievals from special sensor microwave imager data with neural networks. Journal of Geophysical Research 99: doi: 10.1029/93JC03042. issn: 0148-0227. |
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Several fully connected, feed forward neural networks trained on a set of special sensor microwave imager examples matched with buoy winds have yielded retrieval accuracies considerably better than those achieved by the current operational method. Equations and coefficients for using two of these networks, each with four input brightness temperatures and a hidden layer containing two neurodes, are given for implementation in wind retrieval codes. The first demonstrated an rms retrieval error of 1.41 m/s at a reference height of 19.5 m using an independent data set representing clear sky conditions. The second network yielded rms retrieval accuracies of 2.39 m/s under adverse weather conditions. This represents a factor of more than 2 improvement over the alternate algorithms that were examined for nonclear conditions. ¿ American Geophysical Union 1994 |
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Abstract |
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Keywords
Oceanography, General, Remote sensing and electromagnetic processes, Radio Science, Remote sensing |
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Publisher
American Geophysical Union 2000 Florida Avenue N.W. Washington, D.C. 20009-1277 USA 1-202-462-6900 1-202-328-0566 service@agu.org |
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