Abstract
The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction.
Highlights
The bias of the joint inversion results based on Delay-Doppler Map Average (DDMA)
Three methods were proposed to estimate Significant wave height (SWH) from Cyclone Global Navigation Satellite System (CYGNSS) data based on polynomial function models
Through analysis of the data extracted for each month of 2018, the joint inversion results based on DDMA and Leading Edge Slope (LES) gave an average bias of −0.0040 m, an average RMSE
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. In 2016, NASA successfully launched the spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission, which consists of eight small satellites with an orbital inclination of 35◦ and provides large-scale measurements with high spatial and temporal resolution [25]. This mission provided the opportunity to estimate SWH at a near-global scale through spaceborne GNSS-R observations. A new SWH inversion method is presented using joint DDMA and LES measurements from CYGNSS This method, based on CYGNSS, can achieve a larger observation range, better accuracy, and higher temporal resolution than previous groundor air-based GNSS-R measurements.
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