SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures
Sea-ice contamination in the antenna field of view constitutes a large error source in retrieving sea-surface salinity (SSS) with the spaceborne Soil Moisture Active Passive (SMAP) L-band radiometer. This is a major obstacle in the current NASA/Remote Sensing Systems (RSS) SMAP SSS retrieval algorit...
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ftmdpi:oai:mdpi.com:/2072-4292/13/24/5120/ 2023-10-09T21:55:50+02:00 SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures Thomas Meissner Andrew Manaster agris 2021-12-16 application/pdf https://doi.org/10.3390/rs13245120 eng eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs13245120 https://creativecommons.org/licenses/by/4.0/ Remote Sensing Volume 13 Issue 24 Pages: 5120 SMAP AMSR2 sea surface salinity sea-ice cold water Text 2021 ftmdpi https://doi.org/10.3390/rs13245120 2023-09-10T23:55:40Z Sea-ice contamination in the antenna field of view constitutes a large error source in retrieving sea-surface salinity (SSS) with the spaceborne Soil Moisture Active Passive (SMAP) L-band radiometer. This is a major obstacle in the current NASA/Remote Sensing Systems (RSS) SMAP SSS retrieval algorithm in regards to obtaining accurate SSS measurements in the polar oceans. Our analysis finds a strong correlation between 8-day averaged SMAP L-band brightness temperature (TB) bias and TB measurements from the Advanced Microwave Scanning Radiometer (AMSR2) in the C-through Ka-band frequency range for sea-ice contaminated ocean scenes. We show how this correlation can be employed to develop: (1) a discriminant analysis that is able to reliably flag the SMAP observations for sea-ice contamination and (2) subsequently remove the sea-ice contamination from the SMAP observations, which results in significantly more accurate SMAP SSS retrievals near the sea-ice edge. We provide a case study that evaluates the performance of the proposed sea-ice flagging and correction algorithm. Our method is also able to detect drifting icebergs, which go often undetected in many available standard sea-ice products and thus result in spurious SMAP SSS retrievals. Text Sea ice MDPI Open Access Publishing Remote Sensing 13 24 5120 |
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Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
SMAP AMSR2 sea surface salinity sea-ice cold water |
spellingShingle |
SMAP AMSR2 sea surface salinity sea-ice cold water Thomas Meissner Andrew Manaster SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
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SMAP AMSR2 sea surface salinity sea-ice cold water |
description |
Sea-ice contamination in the antenna field of view constitutes a large error source in retrieving sea-surface salinity (SSS) with the spaceborne Soil Moisture Active Passive (SMAP) L-band radiometer. This is a major obstacle in the current NASA/Remote Sensing Systems (RSS) SMAP SSS retrieval algorithm in regards to obtaining accurate SSS measurements in the polar oceans. Our analysis finds a strong correlation between 8-day averaged SMAP L-band brightness temperature (TB) bias and TB measurements from the Advanced Microwave Scanning Radiometer (AMSR2) in the C-through Ka-band frequency range for sea-ice contaminated ocean scenes. We show how this correlation can be employed to develop: (1) a discriminant analysis that is able to reliably flag the SMAP observations for sea-ice contamination and (2) subsequently remove the sea-ice contamination from the SMAP observations, which results in significantly more accurate SMAP SSS retrievals near the sea-ice edge. We provide a case study that evaluates the performance of the proposed sea-ice flagging and correction algorithm. Our method is also able to detect drifting icebergs, which go often undetected in many available standard sea-ice products and thus result in spurious SMAP SSS retrievals. |
format |
Text |
author |
Thomas Meissner Andrew Manaster |
author_facet |
Thomas Meissner Andrew Manaster |
author_sort |
Thomas Meissner |
title |
SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
title_short |
SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
title_full |
SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
title_fullStr |
SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
title_full_unstemmed |
SMAP Salinity Retrievals near the Sea-Ice Edge Using Multi-Channel AMSR2 Brightness Temperatures |
title_sort |
smap salinity retrievals near the sea-ice edge using multi-channel amsr2 brightness temperatures |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13245120 |
op_coverage |
agris |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing Volume 13 Issue 24 Pages: 5120 |
op_relation |
Ocean Remote Sensing https://dx.doi.org/10.3390/rs13245120 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs13245120 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
24 |
container_start_page |
5120 |
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1779320018652102656 |