Preprints
https://doi.org/10.5194/amt-2021-279
https://doi.org/10.5194/amt-2021-279

  15 Sep 2021

15 Sep 2021

Review status: this preprint is currently under review for the journal AMT.

Wind Speed and Direction Estimation from Wave Spectra using Deep Learning

Haoyu Jiang1,2,3 Haoyu Jiang
  • 1Hubei Key Laboratory of Marine Geological Resources, China University of Geosciences, Wuhan, 430000, China
  • 2Laboratory for Regional Oceanography and Numerical Modeling, Pilot Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266000, China
  • 3Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

Abstract. High-frequency parts of ocean wave spectra are strongly coupled to the local wind. Measurements of ocean wave spectra can be used to estimate sea surface winds. In this study, two deep neural networks (DNNs) were used to estimate the wind speed and direction from the first five Fourier coefficients from buoys. The DNNs were trained by wind and wave measurements from more than 100 meteorological buoys during 2014–2018. It is found that the wave measurements can best represent the wind information ~1 h ago, because the wave spectra contain wind information a short period before. The overall root-mean-square error (RMSE) of estimated wind speed is ~1.1 m/s, and the RMSE of wind direction is ~14° when wind speed is 7~25 m/s. This model can not only be used for the wind estimation for compact wave buoys but also for the quality control of wind and wave measurements from meteorological buoys.

Haoyu Jiang

Status: open (until 21 Oct 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-279', Anonymous Referee #1, 26 Sep 2021 reply
    • AC1: 'Reply on RC1', Haoyu Jiang, 12 Oct 2021 reply
      • AC2: 'Reply on AC1', Haoyu Jiang, 12 Oct 2021 reply
  • RC2: 'Comment on amt-2021-279', Anonymous Referee #2, 27 Sep 2021 reply
  • RC3: 'Comment on amt-2021-279', Anonymous Referee #3, 12 Oct 2021 reply

Haoyu Jiang

Haoyu Jiang

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Short summary
Sea surface wind and waves are important ocean parameters that can be continuously observed by meteorological buoys. Meteorological buoys are sparse in the ocean due to their high cost of deployment & maintenance. In contrast, low-cost compact wave buoys are suited for deploying in large numbers. Although wave buoys are not designed for wind measurement, we found that deep learning can estimate wind from wave measurements accurately, making wave buoys a good-quality data source for sea wind.