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Chi Hao,Zhang Youguang,Lin Jing. Research of sea surface gust calculation method based on dual-frequency precipitation radar data[J]. Haiyang Xuebao,2025, 47(6):1–9 doi: 10.12284/hyxb2025067
Citation: Chi Hao,Zhang Youguang,Lin Jing. Research of sea surface gust calculation method based on dual-frequency precipitation radar data[J]. Haiyang Xuebao,2025, 47(6):1–9 doi: 10.12284/hyxb2025067

Research of sea surface gust calculation method based on dual-frequency precipitation radar data

doi: 10.12284/hyxb2025067
  • Received Date: 2025-01-22
  • Rev Recd Date: 2025-05-09
  • Available Online: 2025-06-03
  • Sea surface gusts play a critical role in the utilization of ocean resources, marine research, and the safety of maritime transportation and offshore construction. However, current observation methods are limited, resulting in significant data gaps in surface gust measurements. Lin Jing et al. corrected sea surface wind speeds based on the difference in backscattering coefficients between the C and Ku bands observed by the HY-2B radar altimeter, thereby deriving gust wind speeds at nadir points, although the spatial coverage remained relatively limited. Building upon this approach, the present study employs the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) mission, whose observational principles are similar to those of radar altimeters. By utilizing the difference in Ku- and Ka-band backscattering coefficients and using ERA5 sea surface wind speed as a reference, surface wind speeds are corrected to retrieve gust speeds, aiming to expand observation coverage and improve observational efficiency. Validation against ERA5 gust data yields a correlation coefficient (r) of 0.96, a root mean square error (RMSE) of 1.79 m/s, a mean bias (Bias) of 0.73 m/s, and a standard deviation (Std) of 1.64 m/s. Comparison with simultaneous NDBC buoy observations shows an r of 0.91, an RMSE of 1.50 m/s, a Bias of −0.15 m/s, and a Std of 1.50 m/s, indicating that gust wind speeds retrieved from DPR data demonstrate good reliability. Furthermore, by replacing ERA5 sea surface wind speeds with NDBC buoy measurements, the r increases to 0.95, the RMSE decreases to 1.10 m/s, the Bias is −0.07 m/s, and the Std remains at 1.50 m/s, further improving the retrieval results. These findings highlight that accurate sea surface wind speeds have a significant positive impact on the accuracy of gust wind retrievals.
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