A New Integrated Method of CYGNSS DDMA and LES Measurements for Significant Wave Height Estimation
Jinwei Bu, Kegen Yu
Abstract
In this letter, we first propose two empirical models to retrieve significant wave height (SWH) using two GNSS Reflectometry (GNSS-R) observables derived from delay-Doppler map (DDM), namely DDM average (DDMA) and leading edge slope (LES). Then, we utilize minimum variance to establish a combined model to enhance the SWH estimation performance. Collocated ERA5 SWH data is utilized as the ground truth for the development and evaluation of the SWH models. The results show that the SWH estimates by the three models are highly consistent with ERA5 SWH data, with a root mean square error (RMSE) less than 0.502 m and a correlation coefficient (CC) higher than 0.88. In particular, the combined model has significantly smaller RMSE of 0.428 m and larger CC of 0.91; and compared with the combined model based on weighted average (WA) method and LES observable model based on integral delay waveform, the RMSE is improved by 20.15 % and 14.74 %, respectively. The performance of spaceborne GNSS-R SWH retrieval can be greatly enhanced by the construction of integrated model, as demonstrated by this letter.