Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models
Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Eart...
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ftdoajarticles:oai:doaj.org/article:095fb0997238410da1c9d8d05e80be01 2023-05-15T15:11:50+02:00 Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models F. Richter M. Drusch L. Kaleschke N. Maaß X. Tian-Kunze S. Mecklenburg 2018-03-01T00:00:00Z https://doi.org/10.5194/tc-12-921-2018 https://doaj.org/article/095fb0997238410da1c9d8d05e80be01 EN eng Copernicus Publications https://www.the-cryosphere.net/12/921/2018/tc-12-921-2018.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-12-921-2018 1994-0416 1994-0424 https://doaj.org/article/095fb0997238410da1c9d8d05e80be01 The Cryosphere, Vol 12, Pp 921-933 (2018) Environmental sciences GE1-350 Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.5194/tc-12-921-2018 2022-12-31T12:03:17Z Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously. Article in Journal/Newspaper Arctic Sea ice The Cryosphere Directory of Open Access Journals: DOAJ Articles Arctic The Cryosphere 12 3 921 933 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 F. Richter M. Drusch L. Kaleschke N. Maaß X. Tian-Kunze S. Mecklenburg Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously. |
format |
Article in Journal/Newspaper |
author |
F. Richter M. Drusch L. Kaleschke N. Maaß X. Tian-Kunze S. Mecklenburg |
author_facet |
F. Richter M. Drusch L. Kaleschke N. Maaß X. Tian-Kunze S. Mecklenburg |
author_sort |
F. Richter |
title |
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
title_short |
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
title_full |
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
title_fullStr |
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
title_full_unstemmed |
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models |
title_sort |
arctic sea ice signatures: l-band brightness temperature sensitivity comparison using two radiation transfer models |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-12-921-2018 https://doaj.org/article/095fb0997238410da1c9d8d05e80be01 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice The Cryosphere |
genre_facet |
Arctic Sea ice The Cryosphere |
op_source |
The Cryosphere, Vol 12, Pp 921-933 (2018) |
op_relation |
https://www.the-cryosphere.net/12/921/2018/tc-12-921-2018.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-12-921-2018 1994-0416 1994-0424 https://doaj.org/article/095fb0997238410da1c9d8d05e80be01 |
op_doi |
https://doi.org/10.5194/tc-12-921-2018 |
container_title |
The Cryosphere |
container_volume |
12 |
container_issue |
3 |
container_start_page |
921 |
op_container_end_page |
933 |
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