Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission
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 colle...
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ftmdpi:oai:mdpi.com:/2072-4292/13/16/3224/ 2023-08-20T04:01:07+02:00 Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission Joan Francesc Munoz-Martin Adriano Camps agris 2021-08-13 application/pdf https://doi.org/10.3390/rs13163224 EN eng Multidisciplinary Digital Publishing Institute Earth Observation Data https://dx.doi.org/10.3390/rs13163224 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 16; Pages: 3224 GNSS-R L-band microwave radiometry CubeSat ocean salinity wind speed Text 2021 ftmdpi https://doi.org/10.3390/rs13163224 2023-08-01T02:26:02Z 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. Text Antarc* Antarctic Arctic Sea ice MDPI Open Access Publishing Arctic Antarctic Remote Sensing 13 16 3224 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
GNSS-R L-band microwave radiometry CubeSat ocean salinity wind speed |
spellingShingle |
GNSS-R L-band microwave radiometry CubeSat ocean salinity wind speed Joan Francesc Munoz-Martin Adriano Camps Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
topic_facet |
GNSS-R L-band microwave radiometry CubeSat ocean salinity wind speed |
description |
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. |
format |
Text |
author |
Joan Francesc Munoz-Martin Adriano Camps |
author_facet |
Joan Francesc Munoz-Martin Adriano Camps |
author_sort |
Joan Francesc Munoz-Martin |
title |
Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
title_short |
Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
title_full |
Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
title_fullStr |
Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
title_full_unstemmed |
Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission |
title_sort |
sea surface salinity and wind speed retrievals using gnss-r and l-band microwave radiometry data from fmpl-2 onboard the fsscat mission |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13163224 |
op_coverage |
agris |
geographic |
Arctic Antarctic |
geographic_facet |
Arctic Antarctic |
genre |
Antarc* Antarctic Arctic Sea ice |
genre_facet |
Antarc* Antarctic Arctic Sea ice |
op_source |
Remote Sensing; Volume 13; Issue 16; Pages: 3224 |
op_relation |
Earth Observation Data https://dx.doi.org/10.3390/rs13163224 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs13163224 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
16 |
container_start_page |
3224 |
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1774722843002535936 |