4.7 Article

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

Journal

REMOTE SENSING
Volume 13, Issue 16, Pages -

Publisher

MDPI
DOI: 10.3390/rs13163224

Keywords

GNSS-R; L-band microwave radiometry; CubeSat; ocean salinity; wind speed

Funding

  1. ESA S3 Challenge and Copernicus Masters Overall Winner award (FSSCat project)
  2. SPOT: Sensing with Pioneering Opportunistic Techniques [RTI2018-099008-B-C21/AEI/10.13039/501100011033]
  3. Unidad de Excelencia Maria de Maeztu [MDM-2016-0600]
  4. AGAUR-Generalitat de Catalunya (FEDER), Spain

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The FSSCat mission, a winner of the Copernicus Masters Competition in 2017, was the first ESA third-party mission based on CubeSats with the aim of providing soil moisture and sea ice concentration information through passive microwave measurements. The study utilized FMPL-2 data for sea surface salinity estimation, achieving accurate wind speed and sea surface salinity estimates by combining FMPL-2 data with sea surface temperature using various artificial neural network algorithms.
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.

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