Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ...
The poster details the methodology and preliminary findings of an accuracy assessment for sea ice condition predictions. This assessment utilizes Synthetic Aperture Radar (SAR) imagery alongside sea ice drift data modeled by Barents 2.5 v2, and a warping algorithm developed by Anton Korosov and Anna...
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Online Access: | https://dx.doi.org/10.5281/zenodo.10623657 https://zenodo.org/doi/10.5281/zenodo.10623657 |
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ftdatacite:10.5281/zenodo.10623657 2024-03-31T07:55:15+00:00 Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... Telegina, Anna Dierking, Wolfgang Doulgeris, Anthony P. Korosov, Anton Demchev, Denis 2024 https://dx.doi.org/10.5281/zenodo.10623657 https://zenodo.org/doi/10.5281/zenodo.10623657 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10623658 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Poster article-journal Text ScholarlyArticle 2024 ftdatacite https://doi.org/10.5281/zenodo.1062365710.5281/zenodo.10623658 2024-03-04T12:16:04Z The poster details the methodology and preliminary findings of an accuracy assessment for sea ice condition predictions. This assessment utilizes Synthetic Aperture Radar (SAR) imagery alongside sea ice drift data modeled by Barents 2.5 v2, and a warping algorithm developed by Anton Korosov and Anna Telegina, available at [https://github.com/nansencenter/sar_image_warping]. It presents an analysis of drift and distortion errors, supplementing these findings with case studies on the predictive behavior of sea ice in marginal ice zones and deformation zones, where more "ductile" types of sea ice are predominant. ... Text Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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description |
The poster details the methodology and preliminary findings of an accuracy assessment for sea ice condition predictions. This assessment utilizes Synthetic Aperture Radar (SAR) imagery alongside sea ice drift data modeled by Barents 2.5 v2, and a warping algorithm developed by Anton Korosov and Anna Telegina, available at [https://github.com/nansencenter/sar_image_warping]. It presents an analysis of drift and distortion errors, supplementing these findings with case studies on the predictive behavior of sea ice in marginal ice zones and deformation zones, where more "ductile" types of sea ice are predominant. ... |
format |
Text |
author |
Telegina, Anna Dierking, Wolfgang Doulgeris, Anthony P. Korosov, Anton Demchev, Denis |
spellingShingle |
Telegina, Anna Dierking, Wolfgang Doulgeris, Anthony P. Korosov, Anton Demchev, Denis Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
author_facet |
Telegina, Anna Dierking, Wolfgang Doulgeris, Anthony P. Korosov, Anton Demchev, Denis |
author_sort |
Telegina, Anna |
title |
Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
title_short |
Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
title_full |
Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
title_fullStr |
Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
title_full_unstemmed |
Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data ... |
title_sort |
short term prediction of ice conditions: an integration of sar imagery and model derived sea ice drift data ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10623657 https://zenodo.org/doi/10.5281/zenodo.10623657 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://dx.doi.org/10.5281/zenodo.10623658 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1062365710.5281/zenodo.10623658 |
_version_ |
1795036886883893248 |