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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Published in:Remote Sensing
Main Authors: Sang-Moo Lee, Byung-Ju Sohn, Christian D. Kummerow
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2018
Subjects:
Online Access:https://doi.org/10.3390/rs10111795
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spelling 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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