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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doaj-56df12061e1f4254bd96e71f8efbb62f2020-11-25T00:23:59ZengMDPI AGRemote Sensing2072-42922018-11-011011179510.3390/rs10111795rs10111795Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager MeasurementsSang-Moo Lee0Byung-Ju Sohn1Christian D. Kummerow2School of Earth and Environmental Sciences, Seoul National University, Seoul 08826, KoreaSchool of Earth and Environmental Sciences, Seoul National University, Seoul 08826, KoreaDepartment of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USAThe 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.https://www.mdpi.com/2072-4292/10/11/1795snow/ice interface temperatureSSM/Imicrowave measurementfundamental climate data recordapparent emissivityArctic sea ice |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow |
spellingShingle |
Sang-Moo Lee Byung-Ju Sohn Christian D. Kummerow Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements Remote Sensing snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice |
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 |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-11-01 |
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. |
topic |
snow/ice interface temperature SSM/I microwave measurement fundamental climate data record apparent emissivity Arctic sea ice |
url |
https://www.mdpi.com/2072-4292/10/11/1795 |
work_keys_str_mv |
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