Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment
The FSSCat mission was the 2017 ESA Sentinel Small Satellite (S⌃3) Challenge winner and the Copernicus Masters competition overall winner. It was successfully launched on 3 September 2020 onboard the VEGA SSMS PoC (VV16). FSSCat aims to provide coarse and downscaled soil moisture data and over polar...
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Online Access: | http://hdl.handle.net/10261/225698 https://doi.org/10.3390/rs12244038 |
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ftcsic:oai:digital.csic.es:10261/225698 2024-02-11T09:55:04+01:00 Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment Muñoz-Martín, Joan Francesc Perez, Adrian Camps, Adriano Ribó, Serni Cardellach, Estel Stroeve, Julienne Nandan, Vishnu Itkin, Polona Tonboe, Rasmus Hendricks, Stefan Huntemann, Marcus Spreen, Gunnar Pastena, Massimiliano Ministerio de Ciencia, Innovación y Universidades (España) 2020-12-10 http://hdl.handle.net/10261/225698 https://doi.org/10.3390/rs12244038 unknown Multidisciplinary Digital Publishing Institute #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-099008-B-C22 Publisher's version Sí doi:10.3390/rs12244038 Remote Sensing 12(24): 4038 (2020) http://hdl.handle.net/10261/225698 2072-4292 open GNSS-R Sea-ice Arctic Snow artículo http://purl.org/coar/resource_type/c_6501 2020 ftcsic https://doi.org/10.3390/rs12244038 2024-01-16T11:00:50Z The FSSCat mission was the 2017 ESA Sentinel Small Satellite (S⌃3) Challenge winner and the Copernicus Masters competition overall winner. It was successfully launched on 3 September 2020 onboard the VEGA SSMS PoC (VV16). FSSCat aims to provide coarse and downscaled soil moisture data and over polar regions, sea ice cover, and coarse resolution ice thickness using a combined L-band microwave radiometer and GNSS-Reflectometry payload. As part of the calibration and validation activities of FSSCat, a GNSS-R instrument was deployed as part of the MOSAiC polar expedition. The Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition was an international one-year-long field experiment led by the Alfred Wegener Institute to study the climate system and the impact of climate change in the Arctic Ocean. This paper presents the first results of the PYCARO-2 instrument, focused on the GNSS-R techniques used to measure snow and ice thickness of an ice floe. The Interference Pattern produced by the combination of the GNSS direct and reflected signals over the sea-ice has been modeled using a four-layer model. The different thicknesses of the substrate layers (i.e., snow and ice) are linked to the position of the fringes of the interference pattern. Data collected by MOSAiC GNSS-R instrument between December 2019 and January 2020 for different GNSS constellations and frequencies are presented and analyzed, showing that under general conditions, sea ice and snow thickness can be retrieved using multiangular and multifrequency data. This work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project) and ESA project “FSSCat Validation Experiment in MOSAIC” (ESA CN 4000128320/19/NL/FF/ab). This work was also supported by ESA under the PO 5001025474. The PYCARO-2 instrument was developed within the SPOT project: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21/AEI/10.13039/501100011033 and RTI2018-099008-B-C22, and by EU EDRF funds ... Article in Journal/Newspaper Alfred Wegener Institute Arctic Arctic Ocean Climate change Sea ice Digital.CSIC (Spanish National Research Council) Arctic Arctic Ocean Remote Sensing 12 24 4038 |
institution |
Open Polar |
collection |
Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
unknown |
topic |
GNSS-R Sea-ice Arctic Snow |
spellingShingle |
GNSS-R Sea-ice Arctic Snow Muñoz-Martín, Joan Francesc Perez, Adrian Camps, Adriano Ribó, Serni Cardellach, Estel Stroeve, Julienne Nandan, Vishnu Itkin, Polona Tonboe, Rasmus Hendricks, Stefan Huntemann, Marcus Spreen, Gunnar Pastena, Massimiliano Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
topic_facet |
GNSS-R Sea-ice Arctic Snow |
description |
The FSSCat mission was the 2017 ESA Sentinel Small Satellite (S⌃3) Challenge winner and the Copernicus Masters competition overall winner. It was successfully launched on 3 September 2020 onboard the VEGA SSMS PoC (VV16). FSSCat aims to provide coarse and downscaled soil moisture data and over polar regions, sea ice cover, and coarse resolution ice thickness using a combined L-band microwave radiometer and GNSS-Reflectometry payload. As part of the calibration and validation activities of FSSCat, a GNSS-R instrument was deployed as part of the MOSAiC polar expedition. The Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition was an international one-year-long field experiment led by the Alfred Wegener Institute to study the climate system and the impact of climate change in the Arctic Ocean. This paper presents the first results of the PYCARO-2 instrument, focused on the GNSS-R techniques used to measure snow and ice thickness of an ice floe. The Interference Pattern produced by the combination of the GNSS direct and reflected signals over the sea-ice has been modeled using a four-layer model. The different thicknesses of the substrate layers (i.e., snow and ice) are linked to the position of the fringes of the interference pattern. Data collected by MOSAiC GNSS-R instrument between December 2019 and January 2020 for different GNSS constellations and frequencies are presented and analyzed, showing that under general conditions, sea ice and snow thickness can be retrieved using multiangular and multifrequency data. This work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project) and ESA project “FSSCat Validation Experiment in MOSAIC” (ESA CN 4000128320/19/NL/FF/ab). This work was also supported by ESA under the PO 5001025474. The PYCARO-2 instrument was developed within the SPOT project: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21/AEI/10.13039/501100011033 and RTI2018-099008-B-C22, and by EU EDRF funds ... |
author2 |
Ministerio de Ciencia, Innovación y Universidades (España) |
format |
Article in Journal/Newspaper |
author |
Muñoz-Martín, Joan Francesc Perez, Adrian Camps, Adriano Ribó, Serni Cardellach, Estel Stroeve, Julienne Nandan, Vishnu Itkin, Polona Tonboe, Rasmus Hendricks, Stefan Huntemann, Marcus Spreen, Gunnar Pastena, Massimiliano |
author_facet |
Muñoz-Martín, Joan Francesc Perez, Adrian Camps, Adriano Ribó, Serni Cardellach, Estel Stroeve, Julienne Nandan, Vishnu Itkin, Polona Tonboe, Rasmus Hendricks, Stefan Huntemann, Marcus Spreen, Gunnar Pastena, Massimiliano |
author_sort |
Muñoz-Martín, Joan Francesc |
title |
Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
title_short |
Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
title_full |
Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
title_fullStr |
Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
title_full_unstemmed |
Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment |
title_sort |
snow and ice thickness retrievals using gnss-r: preliminary results of the mosaic experiment |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
http://hdl.handle.net/10261/225698 https://doi.org/10.3390/rs12244038 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Alfred Wegener Institute Arctic Arctic Ocean Climate change Sea ice |
genre_facet |
Alfred Wegener Institute Arctic Arctic Ocean Climate change Sea ice |
op_relation |
#PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-099008-B-C22 Publisher's version Sí doi:10.3390/rs12244038 Remote Sensing 12(24): 4038 (2020) http://hdl.handle.net/10261/225698 2072-4292 |
op_rights |
open |
op_doi |
https://doi.org/10.3390/rs12244038 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
24 |
container_start_page |
4038 |
_version_ |
1790593683385483264 |