Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion

We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in the sea surface wind and sea ice cohesion. The ice mechanics in neXtSIM is based on a brittle-like rheological framework. The study considers short-term ensemble forecasts of the Arctic sea ice from January to April...

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Main Authors: Cheng, Sukun, Aydoğdu, Ali, Rampal, Pierre, Carrassi, Alberto, Bertino, Laurent
Format: Article in Journal/Newspaper
Language:unknown
Published: arXiv 2020
Subjects:
Online Access:https://dx.doi.org/10.48550/arxiv.2009.04881
https://arxiv.org/abs/2009.04881
id ftdatacite:10.48550/arxiv.2009.04881
record_format openpolar
spelling ftdatacite:10.48550/arxiv.2009.04881 2023-05-15T14:53:39+02:00 Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion Cheng, Sukun Aydoğdu, Ali Rampal, Pierre Carrassi, Alberto Bertino, Laurent 2020 https://dx.doi.org/10.48550/arxiv.2009.04881 https://arxiv.org/abs/2009.04881 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Atmospheric and Oceanic Physics physics.ao-ph FOS Physical sciences Article CreativeWork article Preprint 2020 ftdatacite https://doi.org/10.48550/arxiv.2009.04881 2022-03-10T15:18:57Z We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in the sea surface wind and sea ice cohesion. The ice mechanics in neXtSIM is based on a brittle-like rheological framework. The study considers short-term ensemble forecasts of the Arctic sea ice from January to April 2008. Ensembles are generated by perturbing the wind inputs and ice cohesion field both separately and jointly. The resulting uncertainty in the probabilistic forecasts is evaluated statistically based on the analysis of Lagrangian sea ice trajectories as sampled by virtual drifters seeded in the model to cover the Arctic Ocean and using metrics borrowed from the search-and-rescue literature. The comparison among the different ensembles indicates that wind perturbations dominate the forecast uncertainty i.e. the absolute spread of the ensemble, while the inhomogeneities in the ice cohesion field significantly increase the degree of anisotropy in the spread i.e. trajectories drift differently in different directions. We suggest that in order to get a full flavor of uncertainties in a sea ice model with brittle-like rheologies, to predict sea ice drift and trajectories, one should consider using ensemble-based simulations where both wind forcing and sea ice cohesion are perturbed. : 18 pages, 10 figures Article in Journal/Newspaper Arctic Arctic Ocean Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Atmospheric and Oceanic Physics physics.ao-ph
FOS Physical sciences
spellingShingle Atmospheric and Oceanic Physics physics.ao-ph
FOS Physical sciences
Cheng, Sukun
Aydoğdu, Ali
Rampal, Pierre
Carrassi, Alberto
Bertino, Laurent
Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
topic_facet Atmospheric and Oceanic Physics physics.ao-ph
FOS Physical sciences
description We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in the sea surface wind and sea ice cohesion. The ice mechanics in neXtSIM is based on a brittle-like rheological framework. The study considers short-term ensemble forecasts of the Arctic sea ice from January to April 2008. Ensembles are generated by perturbing the wind inputs and ice cohesion field both separately and jointly. The resulting uncertainty in the probabilistic forecasts is evaluated statistically based on the analysis of Lagrangian sea ice trajectories as sampled by virtual drifters seeded in the model to cover the Arctic Ocean and using metrics borrowed from the search-and-rescue literature. The comparison among the different ensembles indicates that wind perturbations dominate the forecast uncertainty i.e. the absolute spread of the ensemble, while the inhomogeneities in the ice cohesion field significantly increase the degree of anisotropy in the spread i.e. trajectories drift differently in different directions. We suggest that in order to get a full flavor of uncertainties in a sea ice model with brittle-like rheologies, to predict sea ice drift and trajectories, one should consider using ensemble-based simulations where both wind forcing and sea ice cohesion are perturbed. : 18 pages, 10 figures
format Article in Journal/Newspaper
author Cheng, Sukun
Aydoğdu, Ali
Rampal, Pierre
Carrassi, Alberto
Bertino, Laurent
author_facet Cheng, Sukun
Aydoğdu, Ali
Rampal, Pierre
Carrassi, Alberto
Bertino, Laurent
author_sort Cheng, Sukun
title Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
title_short Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
title_full Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
title_fullStr Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
title_full_unstemmed Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
title_sort probabilistic forecasts of sea ice trajectories in the arctic: impact of uncertainties in surface wind and ice cohesion
publisher arXiv
publishDate 2020
url https://dx.doi.org/10.48550/arxiv.2009.04881
https://arxiv.org/abs/2009.04881
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
genre Arctic
Arctic Ocean
Sea ice
genre_facet Arctic
Arctic Ocean
Sea ice
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.2009.04881
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