A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model

An analysis of ice thickness distribution is a challenge, particularly in a seasonal sea ice zone with a strongly dynamic ice motion field, such as the Gulf of St. Lawrence off Canada. We present a novel automated method for ice concentration and thickness analysis combining modeling of sea ice ther...

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Published in:The Cryosphere
Main Authors: Karvonen, J., Cheng, B., Vihma, T., Arkett, M., Carrieres, T.
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/tc-6-1507-2012
https://tc.copernicus.org/articles/6/1507/2012/
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spelling ftcopernicus:oai:publications.copernicus.org:tc15148 2023-05-15T18:17:27+02:00 A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model Karvonen, J. Cheng, B. Vihma, T. Arkett, M. Carrieres, T. 2018-09-27 application/pdf https://doi.org/10.5194/tc-6-1507-2012 https://tc.copernicus.org/articles/6/1507/2012/ eng eng doi:10.5194/tc-6-1507-2012 https://tc.copernicus.org/articles/6/1507/2012/ eISSN: 1994-0424 Text 2018 ftcopernicus https://doi.org/10.5194/tc-6-1507-2012 2020-07-20T16:25:37Z An analysis of ice thickness distribution is a challenge, particularly in a seasonal sea ice zone with a strongly dynamic ice motion field, such as the Gulf of St. Lawrence off Canada. We present a novel automated method for ice concentration and thickness analysis combining modeling of sea ice thermodynamics and detection of ice motion on the basis of space-borne Synthetic Aperture Radar (SAR) data. Thermodynamic evolution of sea ice thickness in the Gulf of St. Lawrence was simulated for two winters, 2002–2003 and 2008–2009. The basin-scale ice thickness was controlled by atmospheric forcing, but the spatial distribution of ice thickness and concentration could not be explained by thermodynamics only. SAR data were applied to detect ice motion and ice surface structure during these two winters. The SAR analysis is based on estimation of ice motion between SAR image pairs and analysis of the local SAR texture statistics. Including SAR data analysis brought a significant added value to the results based on thermodynamics only. Our novel method combining the thermodynamic modeling and SAR yielded results that well match with the distribution of observations based on airborne Electromagnetic Induction (EM) method. Compared to the present operational method of producing ice charts for the Gulf of St. Lawrence, which is based on visual interpretation of SAR data, the new method reveals much more detailed and physically based information on spatial distribution of ice thickness. The algorithms can be run automatically, and the final products can then be used by ice analysts for operational ice service. The method is globally applicable to all seas where SAR data are available. Text Sea ice Copernicus Publications: E-Journals Canada The Cryosphere 6 6 1507 1526
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description An analysis of ice thickness distribution is a challenge, particularly in a seasonal sea ice zone with a strongly dynamic ice motion field, such as the Gulf of St. Lawrence off Canada. We present a novel automated method for ice concentration and thickness analysis combining modeling of sea ice thermodynamics and detection of ice motion on the basis of space-borne Synthetic Aperture Radar (SAR) data. Thermodynamic evolution of sea ice thickness in the Gulf of St. Lawrence was simulated for two winters, 2002–2003 and 2008–2009. The basin-scale ice thickness was controlled by atmospheric forcing, but the spatial distribution of ice thickness and concentration could not be explained by thermodynamics only. SAR data were applied to detect ice motion and ice surface structure during these two winters. The SAR analysis is based on estimation of ice motion between SAR image pairs and analysis of the local SAR texture statistics. Including SAR data analysis brought a significant added value to the results based on thermodynamics only. Our novel method combining the thermodynamic modeling and SAR yielded results that well match with the distribution of observations based on airborne Electromagnetic Induction (EM) method. Compared to the present operational method of producing ice charts for the Gulf of St. Lawrence, which is based on visual interpretation of SAR data, the new method reveals much more detailed and physically based information on spatial distribution of ice thickness. The algorithms can be run automatically, and the final products can then be used by ice analysts for operational ice service. The method is globally applicable to all seas where SAR data are available.
format Text
author Karvonen, J.
Cheng, B.
Vihma, T.
Arkett, M.
Carrieres, T.
spellingShingle Karvonen, J.
Cheng, B.
Vihma, T.
Arkett, M.
Carrieres, T.
A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
author_facet Karvonen, J.
Cheng, B.
Vihma, T.
Arkett, M.
Carrieres, T.
author_sort Karvonen, J.
title A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
title_short A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
title_full A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
title_fullStr A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
title_full_unstemmed A method for sea ice thickness and concentration analysis based on SAR data and a thermodynamic model
title_sort method for sea ice thickness and concentration analysis based on sar data and a thermodynamic model
publishDate 2018
url https://doi.org/10.5194/tc-6-1507-2012
https://tc.copernicus.org/articles/6/1507/2012/
geographic Canada
geographic_facet Canada
genre Sea ice
genre_facet Sea ice
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-6-1507-2012
https://tc.copernicus.org/articles/6/1507/2012/
op_doi https://doi.org/10.5194/tc-6-1507-2012
container_title The Cryosphere
container_volume 6
container_issue 6
container_start_page 1507
op_container_end_page 1526
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