Abstract
Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s; the mean error was 3.57 m/s; the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.
Highlights
As an extreme weather phenomenon, the typhoon can bring severe storms and heavy rains, which can cause devastating damage to human life and property
In order to get more matching points of Cyclone Global Navigation Satellite System (CYGNSS) and European Centre for Medium-Range Weather Forecasts (ECMWF) for comparison, we had adopted the method of biharmonic spline interpolation for the CYGNSS and ECMWF reanalysis data and the spatial resolution after interpolation was unified to 0.1◦ × 0.1◦
When the wind speed is greater than 41.5 m/s, the root-mean-square error (RMSE) of CYGNSS and ECMWF reanalysis data is 5.07 m/s, the mean error is 3.57 m/s and the correlation coefficient was 0.52, the average relative error account 11.0%
Summary
As an extreme weather phenomenon, the typhoon can bring severe storms and heavy rains, which can cause devastating damage to human life and property. Optical remote sensing satellite signal are blocked by the cloud and heavy rainfall inside the typhoon, resulting in the absence of accurate and frequent observations of wind field in the typhoon inner core [4]. With the development of Global Navigation Satellite System (GNSS) [5], the GNSS-reflectometry (GNSS-R) technology has been widely used for various geophysical parameters remote sensing, including ocean wave height and speed estimation. GNSS L-band signals can penetrate clouds and heavy rainfall under any type of weather conditions so it is useful to monitor ocean wind speeds during a typhoon event [7]. Cyclone Global Navigation Satellite System (CYGNSS) uses the GPS signals reflected from the ocean surface to detect wind speed [8] at high-temporal resolution, which may improve the forecast of the tropical cyclone’s intensity [9]. Since the eight satellites of CYGNSS can work at the same time, CYGNSS can measure the ocean surface winds between 38◦N and 38◦S in latitude with high spatial resolution [10]
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