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Sea Surface Wind Speed Retrieval from MTVZA-GYa Data

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Abstract

A neural network (NN) algorithm for the sea surface wind speed retrieval from the MTVZA-GYa Russian satellite microwave radiometer measurements is presented. The algorithm is based on the physical modeling of the brightness temperature of microwave radiation in the ocean–atmosphere system using new theoretical geophysical model functions of the dependence of ocean radiation on wind speed. The algorithm is validated by comparing the wind fields retrieved from the MTVZA-GYa data with those obtained from the AMSR2 radiometer (Japan) for different areas of the World Ocean with a difference in measurement time not exceeding five minutes. The validation has shown that the NNs with a number of neurons \(n\) from 3 to 8 provide the smallest root-mean-square difference between the AMSR2 and MTVZA-GYa retrieved wind speeds, namely 1.6 m/s. When mapping the wind speed in tropical cyclones, the best fit to the wind fields from the AMSR2 data is obtained using the NN with \(n=4\).

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Authors and Affiliations

  1. Russian State Hydrometeorological University, 195196, St. Petersburg, Russia

    E. V. Zabolotskikh, S. M. Azarov & M. A. Zhivotovskaya

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  1. E. V. Zabolotskikh
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  2. S. M. Azarov
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  3. M. A. Zhivotovskaya
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Correspondence to E. V. Zabolotskikh.

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Translated from Meteorologiya i Gidrologiya, 2023, No. 8, pp. 24-34. https://doi.org/10.52002/0130-2906-2023-8-24-34.

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Zabolotskikh, E.V., Azarov, S.M. & Zhivotovskaya, M.A. Sea Surface Wind Speed Retrieval from MTVZA-GYa Data. Russ. Meteorol. Hydrol. 48, 658–665 (2023). https://doi.org/10.3103/S1068373923080022

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