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Shipborne GNSS reflectometry for monitoring along-track significant wave height and wind speed

  • National Marine Environment Prediction Center
  • Beihang University
  • SINOPEC

Research output: Contribution to journalArticlepeer-review

Abstract

Shipborne Global Navigation Satellite System-Reflectometry (GNSS-R) for measuring along-track significant wave height (SWH) and wind speed are first investigated in this article. A real-time shipborne GNSS-R instrument was carried on the XUELONG-2 for the 38th Antarctic Scientific Expedition. The collected dataset covered the entire expedition of the XUELONG-2. The dependencies of the correlation time, normalized area, ratio of reflected-to-direct signal-to-noise ratio (SNR), spectral width, and peak frequency on SWH and wind speed are explored. It is found that the correlation time, spectral width, and peak frequency better depend on SWH and wind speed than other two observables, therefore, they are used to measure the SWH and wind speed. The elevation angle, SNR and ship velocity, also impact on the observables, thus their influences should be corrected. The geophysical model function (GMF) and neural network are used to develop retrieval models of SWH and wind speed. Neural networks provide better retrieval performances. The best root mean square errors (RMSEs) of the retrieved SWH and wind speed are 0.38 m and 2.49 m/s, with a temporal and spatial resolutions of 1 min and 600 m, respectively. The measurements from the shipborne GNSS-R also agree with the co-located European Centre for Medium-Range Weather Forecasts (ECMWF) and Jason-3 altimeter data.

Original languageEnglish
Article number114935
JournalOcean Engineering
Volume281
DOIs
StatePublished - 1 Aug 2023

Keywords

  • Geophysical model function (GMF)
  • Neural network (NN)
  • Shipborne GNSS reflectometry
  • Significant wave height (SWH)
  • Wind speed

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