Stand-Alone Retrieval of Sea Ice Thickness From FY-3E GNOS-R Data

Arctic sea ice has long been a focal point of scientific research globally, with sea ice thickness (SIT) recognized as a critical parameter for predicting local marine environments, climate dynamics, and ensuring the safety of maritime transport. This study focuses on the retrieval of SIT, utilizing an established two-layer (sea ice-seawater) global navigation satellite system-reflectometry (GNSS-R) model and is extended to new data from Fengyun-3E (FY-3E) satellite. The research introduces an innovative empirical approach aimed at reducing reliance on ancillary data, allowing for stand-alone SIT retrieval solely based on GNSS-R data. This work underscores the potential for developing a practical semi-empirical model and parameterization scheme for SIT estimation through GNSS-R data. Furthermore, FY-3E has the capability to process signals from both the BeiDou Navigation Satellite System (BDS) and the global positioning system (GPS). Compared to the reference SIT, for the training set the root-mean-square error (RMSE) and correlation coefficient (
$r$
) between GPS-R SIT and reference are 0.1347 m and 0.8087, respectively, and for the test set, they are 0.1442 m and 0.7821. Based on BDS-R data, for the training set the RMSE and
$r$
are 0.1325 m and 0.8152, and for the test set, they are 0.1289 m and 0.8063, respectively. Experimental results indicate that BDS-based outcomes slightly outperform those obtained using GPS in the context of SIT retrieval.