Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements
The Arctic sea ice region is the most visible area experiencing global warming-induced climate change. However, long-term measurements of climate-related variables have been limited to a small number of variables such as the sea ice concentration, extent, and area. In this study, we attempt to produ...
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ftmdpi:oai:mdpi.com:/2072-4292/10/11/1795/ 2023-08-20T04:03:50+02:00 Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow 2018-11-12 application/pdf https://doi.org/10.3390/rs10111795 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs10111795 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 11; Pages: 1795 snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice Text 2018 ftmdpi https://doi.org/10.3390/rs10111795 2023-07-31T21:50:16Z The Arctic sea ice region is the most visible area experiencing global warming-induced climate change. However, long-term measurements of climate-related variables have been limited to a small number of variables such as the sea ice concentration, extent, and area. In this study, we attempt to produce a long-term temperature record for the Arctic sea ice region using Special Sensor for Microwave Imager (SSM/I) Fundamental Climate Data Record (FCDR) data. For that, we developed an algorithm to retrieve the wintertime snow/ice interface temperature (SIIT) over the Arctic Ocean by counting the effect of the snow/ice volume scattering and ice surface roughness on the apparent emissivity (the total effect is referred to as the correction factor). A regression equation was devised to predict the correction factor from SSM/I brightness temperatures (TBs) only and then applied to SSM/I 19.4 GHz TB to estimate the SIIT. The obtained temperatures were validated against collocated Cold Regions Research and Engineering Laboratory (CRREL) ice mass balance (IMB) drifting buoy-measured temperatures at zero ice depth. It is shown that the SSM/I retrievals are in good agreement with the drifting buoy measurements, with a correlation coefficient of 0.95, bias of 0.1 K, and root-mean-square error of 1.48 K on a daily time scale. By applying the algorithm to 24-year (1988–2011) SSM/I FCDR data, we were able to produce the winter-time temperature at the sea ice surface for the 24-year period. Text Arctic Arctic Ocean Climate change Cold Regions Research and Engineering Laboratory Global warming Sea ice MDPI Open Access Publishing Arctic Arctic Ocean Remote Sensing 10 11 1795 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice |
spellingShingle |
snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
topic_facet |
snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice |
description |
The Arctic sea ice region is the most visible area experiencing global warming-induced climate change. However, long-term measurements of climate-related variables have been limited to a small number of variables such as the sea ice concentration, extent, and area. In this study, we attempt to produce a long-term temperature record for the Arctic sea ice region using Special Sensor for Microwave Imager (SSM/I) Fundamental Climate Data Record (FCDR) data. For that, we developed an algorithm to retrieve the wintertime snow/ice interface temperature (SIIT) over the Arctic Ocean by counting the effect of the snow/ice volume scattering and ice surface roughness on the apparent emissivity (the total effect is referred to as the correction factor). A regression equation was devised to predict the correction factor from SSM/I brightness temperatures (TBs) only and then applied to SSM/I 19.4 GHz TB to estimate the SIIT. The obtained temperatures were validated against collocated Cold Regions Research and Engineering Laboratory (CRREL) ice mass balance (IMB) drifting buoy-measured temperatures at zero ice depth. It is shown that the SSM/I retrievals are in good agreement with the drifting buoy measurements, with a correlation coefficient of 0.95, bias of 0.1 K, and root-mean-square error of 1.48 K on a daily time scale. By applying the algorithm to 24-year (1988–2011) SSM/I FCDR data, we were able to produce the winter-time temperature at the sea ice surface for the 24-year period. |
format |
Text |
author |
Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow |
author_facet |
Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow |
author_sort |
Sang-Moo Lee |
title |
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
title_short |
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
title_full |
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
title_fullStr |
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
title_full_unstemmed |
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements |
title_sort |
long-term arctic snow/ice interface temperature from special sensor for microwave imager measurements |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10111795 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Climate change Cold Regions Research and Engineering Laboratory Global warming Sea ice |
genre_facet |
Arctic Arctic Ocean Climate change Cold Regions Research and Engineering Laboratory Global warming Sea ice |
op_source |
Remote Sensing; Volume 10; Issue 11; Pages: 1795 |
op_relation |
https://dx.doi.org/10.3390/rs10111795 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10111795 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
11 |
container_start_page |
1795 |
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1774714271399149568 |