A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS
Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combina...
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ftdoajarticles:oai:doaj.org/article:2bca8dc2538747f896ab1d9156e3ad5e 2023-05-15T14:28:56+02:00 A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS Andreas Preußer Günther Heinemann Lukas Schefczyk Sascha Willmes 2022-04-01T00:00:00Z https://doi.org/10.3390/rs14092036 https://doaj.org/article/2bca8dc2538747f896ab1d9156e3ad5e EN eng MDPI AG https://www.mdpi.com/2072-4292/14/9/2036 https://doaj.org/toc/2072-4292 doi:10.3390/rs14092036 2072-4292 https://doaj.org/article/2bca8dc2538747f896ab1d9156e3ad5e Remote Sensing, Vol 14, Iss 2036, p 2036 (2022) sea-ice polynyas leads ice thickness Arctic reanalysis Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14092036 2022-12-30T23:33:29Z Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020. Article in Journal/Newspaper Arctic Archipelago Arctic Arctic Ocean Canadian Arctic Archipelago laptev Laptev Sea Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Arctic Ocean Canadian Arctic Archipelago Laptev Sea Remote Sensing 14 9 2036 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea-ice polynyas leads ice thickness Arctic reanalysis Science Q |
spellingShingle |
sea-ice polynyas leads ice thickness Arctic reanalysis Science Q Andreas Preußer Günther Heinemann Lukas Schefczyk Sascha Willmes A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
topic_facet |
sea-ice polynyas leads ice thickness Arctic reanalysis Science Q |
description |
Knowledge of the wintertime sea-ice production in Arctic polynyas is an important requirement for estimations of the dense water formation, which drives vertical mixing in the upper ocean. Satellite-based techniques incorporating relatively high resolution thermal-infrared data from MODIS in combination with atmospheric reanalysis data have proven to be a strong tool to monitor large and regularly forming polynyas and to resolve narrow thin-ice areas (i.e., leads) along the shelf-breaks and across the entire Arctic Ocean. However, the selection of the atmospheric data sets has a large influence on derived polynya characteristics due to their impact on the calculation of the heat loss to the atmosphere, which is determined by the local thin-ice thickness. In order to overcome this methodical ambiguity, we present a MODIS-assisted temperature adjustment (MATA) algorithm that yields corrections of the 2 m air temperature and hence decreases differences between the atmospheric input data sets. The adjustment algorithm is based on atmospheric model simulations. We focus on the Laptev Sea region for detailed case studies on the developed algorithm and present time series of polynya characteristics in the winter season 2019/2020. It shows that the application of the empirically derived correction decreases the difference between different utilized atmospheric products significantly from 49% to 23%. Additional filter strategies are applied that aim at increasing the capability to include leads in the quasi-daily and persistence-filtered thin-ice thickness composites. More generally, the winter of 2019/2020 features high polynya activity in the eastern Arctic and less activity in the Canadian Arctic Archipelago, presumably as a result of the particularly strong polar vortex in early 2020. |
format |
Article in Journal/Newspaper |
author |
Andreas Preußer Günther Heinemann Lukas Schefczyk Sascha Willmes |
author_facet |
Andreas Preußer Günther Heinemann Lukas Schefczyk Sascha Willmes |
author_sort |
Andreas Preußer |
title |
A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
title_short |
A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
title_full |
A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
title_fullStr |
A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
title_full_unstemmed |
A Model-Based Temperature Adjustment Scheme for Wintertime Sea-Ice Production Retrievals from MODIS |
title_sort |
model-based temperature adjustment scheme for wintertime sea-ice production retrievals from modis |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14092036 https://doaj.org/article/2bca8dc2538747f896ab1d9156e3ad5e |
geographic |
Arctic Arctic Ocean Canadian Arctic Archipelago Laptev Sea |
geographic_facet |
Arctic Arctic Ocean Canadian Arctic Archipelago Laptev Sea |
genre |
Arctic Archipelago Arctic Arctic Ocean Canadian Arctic Archipelago laptev Laptev Sea Sea ice |
genre_facet |
Arctic Archipelago Arctic Arctic Ocean Canadian Arctic Archipelago laptev Laptev Sea Sea ice |
op_source |
Remote Sensing, Vol 14, Iss 2036, p 2036 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/9/2036 https://doaj.org/toc/2072-4292 doi:10.3390/rs14092036 2072-4292 https://doaj.org/article/2bca8dc2538747f896ab1d9156e3ad5e |
op_doi |
https://doi.org/10.3390/rs14092036 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
9 |
container_start_page |
2036 |
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1766303060930330624 |