A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications
Passive microwave measurements at L-band from ESA’s Soil Moisture and Ocean Salinity (SMOS) mission can be used to retrieve sea ice thickness of up to 0.5–1.0 m. Since 2015, NASA’s Soil Moisture Active Passive (SMAP) mission provides brightness temperatures (TB) at the same frequency. Here, we explo...
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ftdoajarticles:oai:doaj.org/article:3114a811a85c4635af676edd597e99e5 2023-05-15T18:16:19+02:00 A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications Amelie U. Schmitt Lars Kaleschke 2018-04-01T00:00:00Z https://doi.org/10.3390/rs10040553 https://doaj.org/article/3114a811a85c4635af676edd597e99e5 EN eng MDPI AG http://www.mdpi.com/2072-4292/10/4/553 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10040553 https://doaj.org/article/3114a811a85c4635af676edd597e99e5 Remote Sensing, Vol 10, Iss 4, p 553 (2018) SMAP SMOS L-band brightness temperature sea ice thickness Science Q article 2018 ftdoajarticles https://doi.org/10.3390/rs10040553 2022-12-31T11:22:47Z Passive microwave measurements at L-band from ESA’s Soil Moisture and Ocean Salinity (SMOS) mission can be used to retrieve sea ice thickness of up to 0.5–1.0 m. Since 2015, NASA’s Soil Moisture Active Passive (SMAP) mission provides brightness temperatures (TB) at the same frequency. Here, we explore the possibility of combining SMOS and SMAP TBs for sea ice thickness retrieval. First, we compare daily TBs over polar ocean and sea ice regions. For this purpose, the multi-angular SMOS measurements have to be fitted to the SMAP incidence angle of 40 ∘ . Using a synthetical dataset for testing, we evaluate the performance of different fitting methods. We find that a two-step regression fitting method performs best, yielding a high accuracy even for a small number of measurements of only 15. Generally, SMOS and SMAP TBs agree very well with correlations exceeding 0.99 over sea ice but show an intensity bias of about 2.7 K over both ocean and sea ice regions. This bias can be adjusted using a linear fit resulting in a very good agreement of the retrieved sea ice thicknesses. The main advantages of a combined product are the increased number of daily overpasses leading to an improved data coverage also towards lower latitudes, as well as a continuation of retrieved timeseries if one of the sensors stops delivering data. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Remote Sensing 10 4 553 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
SMAP SMOS L-band brightness temperature sea ice thickness Science Q |
spellingShingle |
SMAP SMOS L-band brightness temperature sea ice thickness Science Q Amelie U. Schmitt Lars Kaleschke A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
topic_facet |
SMAP SMOS L-band brightness temperature sea ice thickness Science Q |
description |
Passive microwave measurements at L-band from ESA’s Soil Moisture and Ocean Salinity (SMOS) mission can be used to retrieve sea ice thickness of up to 0.5–1.0 m. Since 2015, NASA’s Soil Moisture Active Passive (SMAP) mission provides brightness temperatures (TB) at the same frequency. Here, we explore the possibility of combining SMOS and SMAP TBs for sea ice thickness retrieval. First, we compare daily TBs over polar ocean and sea ice regions. For this purpose, the multi-angular SMOS measurements have to be fitted to the SMAP incidence angle of 40 ∘ . Using a synthetical dataset for testing, we evaluate the performance of different fitting methods. We find that a two-step regression fitting method performs best, yielding a high accuracy even for a small number of measurements of only 15. Generally, SMOS and SMAP TBs agree very well with correlations exceeding 0.99 over sea ice but show an intensity bias of about 2.7 K over both ocean and sea ice regions. This bias can be adjusted using a linear fit resulting in a very good agreement of the retrieved sea ice thicknesses. The main advantages of a combined product are the increased number of daily overpasses leading to an improved data coverage also towards lower latitudes, as well as a continuation of retrieved timeseries if one of the sensors stops delivering data. |
format |
Article in Journal/Newspaper |
author |
Amelie U. Schmitt Lars Kaleschke |
author_facet |
Amelie U. Schmitt Lars Kaleschke |
author_sort |
Amelie U. Schmitt |
title |
A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
title_short |
A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
title_full |
A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
title_fullStr |
A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
title_full_unstemmed |
A Consistent Combination of Brightness Temperatures from SMOS and SMAP over Polar Oceans for Sea Ice Applications |
title_sort |
consistent combination of brightness temperatures from smos and smap over polar oceans for sea ice applications |
publisher |
MDPI AG |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10040553 https://doaj.org/article/3114a811a85c4635af676edd597e99e5 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing, Vol 10, Iss 4, p 553 (2018) |
op_relation |
http://www.mdpi.com/2072-4292/10/4/553 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10040553 https://doaj.org/article/3114a811a85c4635af676edd597e99e5 |
op_doi |
https://doi.org/10.3390/rs10040553 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
4 |
container_start_page |
553 |
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1766189856341360640 |