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Articles | Volume 14, issue 12
https://doi.org/10.5194/amt-14-7435-2021
https://doi.org/10.5194/amt-14-7435-2021
Research article
 | 
30 Nov 2021
Research article |  | 30 Nov 2021

Support vector machine tropical wind speed retrieval in the presence of rain for Ku-band wind scatterometry

Xingou Xu and Ad Stoffelen

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Cited articles

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Chelton, D. B., Schlax, M. G., Samelson, R. M., Farrar, J. T., Molemaker, M. J., McWilliams, J. C., and Gula, J.: Prospects for future satellite estimation of small-scale variability of ocean surface velocity and vorticity, Prog. Oceanogr., 173, 256–350, https://doi.org/10.1016/j.pocean.2018.10.012, 2019. 
Cornford, D., Nabney, I. T., and Bishop, C. M.: Neural network-based wind vector retrieval from satellite scatterometer data, Neural Comput. Appl., 8, 206–217, https://doi.org/10.1007/s005210050023, 1999. 
Courtier, P., Thépaut, J. N., and Hollingsworth, A.: A strategy for operational implementation of 4D-Var, using an incremental approach, Q. J. Roy. Meteor. Soc., 120, 1367–1387, https://doi.org/10.1002/qj.49712051912, 1994. 
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The support vector machine can effectively represent the increasing effect of rain affecting...
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