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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Published in:Remote Sensing
Main Authors: 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
Other Authors: Ministerio de Ciencia, Innovación y Universidades (España)
Format: Article in Journal/Newspaper
Language:unknown
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:http://hdl.handle.net/10261/225698
https://doi.org/10.3390/rs12244038
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spelling 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

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
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