Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission

Abstract

The Federated Satellite System mission (FSSCat), winner of the 2017 Copernicus Masters Competition and the first ESA third-party mission based on CubeSats, aimed to provide coarse-resolution soil moisture estimations and sea ice concentration maps by means of the passive microwave measurements collected by the Flexible Microwave Payload-2 (FMPL-2). The mission was successfully launched on 3 September 2020. In addition to the primary scientific objectives, FMPL-2 data are used in this study to estimate sea surface salinity (SSS), correcting for the sea surface roughness using a wind speed estimate from the L-band microwave radiometer and GNSS-R data themselves. FMPL-2 was executed over the Arctic and Antarctic oceans on a weekly schedule. Different artificial neural network algorithms have been implemented, combining FMPL-2 data with the sea surface temperature, showing a root-mean-square error (RMSE) down to 1.68 m/s in the case of the wind speed (WS) retrieval algorithms, and RMSE down to 0.43 psu for the sea surface salinity algorithm in one single pass.

DDM-Former: Transformer networks for GNSS reflectometry global ocean wind speed estimation

“…In addition, they perform a feature selection procedure based on variables that decrease the RMSE values for a validation set. The advantages of utilizing MLPs are also demonstrated in [20,21,22]. Furthermore, a hybrid neural network model, named FA-RDN, achieves enhanced wind speed estimation performance in [23].…”

Sensitivity of Delay Doppler Map in Spaceborne GNSS-R to Geophysical Variables of the Ocean

“…This effect is indeed very small, but it can be reduced using current SSS maps obtained for example, from ESA SMOS and NASA SMAP missions [31], which offer errors of a fraction of 1 psu. In any case, even without this correction, it has already been proven that the combination of GNSS-R and L-band microwave radiometry data can produce single-pass SSS retrievals with a 0.43 psu error [32].…”

Awards Presented at the IGARSS 2022 Banquet [Conference Reports]

“…T he IEEE Geoscience and Remote Sensing Society's (GRSS's) 2022 publications, symposium, and special awards were presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) awards banquet held at the Grand Hyatt, Kuala Lumpur on 21 1).…”