Towards improving short-term sea ice predictability using deformation observations

International audience Short-term sea ice predictability is challenging due to the lack of constraints on ice deformation features (open leads and ridges) at kilometre scale. Deformation observations capture these small-scale features and have the potential to improve the predictability. A new metho...

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Published in:The Cryosphere
Main Authors: Korosov, Anton, Rampal, Pierre, Ying, Yue, Ólason, Einar, Williams, Timothy
Other Authors: Nansen Environmental and Remote Sensing Center Bergen (NERSC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2023
Subjects:
Online Access:https://hal.science/hal-03796640
https://hal.science/hal-03796640v2/document
https://hal.science/hal-03796640v2/file/Korosov2023The_Cryosphere.pdf
https://doi.org/10.5194/tc-17-4223-2023
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spelling ftccsdartic:oai:HAL:hal-03796640v2 2023-12-17T10:49:45+01:00 Towards improving short-term sea ice predictability using deformation observations Korosov, Anton Rampal, Pierre Ying, Yue Ólason, Einar Williams, Timothy Nansen Environmental and Remote Sensing Center Bergen (NERSC) Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Université Grenoble Alpes (UGA) 2023-10-05 https://hal.science/hal-03796640 https://hal.science/hal-03796640v2/document https://hal.science/hal-03796640v2/file/Korosov2023The_Cryosphere.pdf https://doi.org/10.5194/tc-17-4223-2023 en eng HAL CCSD Copernicus info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-4223-2023 hal-03796640 https://hal.science/hal-03796640 https://hal.science/hal-03796640v2/document https://hal.science/hal-03796640v2/file/Korosov2023The_Cryosphere.pdf doi:10.5194/tc-17-4223-2023 info:eu-repo/semantics/OpenAccess ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-03796640 The Cryosphere, 2023, 17 (10), pp.4223-4240. ⟨10.5194/tc-17-4223-2023⟩ [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology info:eu-repo/semantics/article Journal articles 2023 ftccsdartic https://doi.org/10.5194/tc-17-4223-2023 2023-11-18T23:40:57Z International audience Short-term sea ice predictability is challenging due to the lack of constraints on ice deformation features (open leads and ridges) at kilometre scale. Deformation observations capture these small-scale features and have the potential to improve the predictability. A new method for assimilation of satellite-derived sea ice deformation into the neXt generation Sea Ice Model (neXtSIM) is presented. Ice deformation provided by the Copernicus Marine Environmental Monitoring Service is computed from sea ice drift derived from Synthetic Aperture Radar at a spatio-temporal resolution of 10 km and 24 hours. We show that high values of ice deformation can be interpreted as reduced ice concentration and increased ice damage-scalar variables of neXtSIM. The proof-of-concept assimilation scheme uses a data nudging approach and deterministic forecasting with one member. Assimilation and forecasting experiments are run on example observations from January 2021 and show improvement of neXtSIM skills to predict sea ice deformation in 3-5 days horizon. It is demonstrated that neXtSIM is also capable of extrapolating the assimilated information in space-gaps in spatially discontinuous satellite observations of deformation are filled with a realistic pattern of ice cracks, confirmed by later satellite observations. The experiments also indicate that reduction in sea ice concentration plays a bigger role in improving ice deformation forecast on synoptic scales. Limitations and usefulness of the proposed assimilation approach are discussed in a context of ensemble forecasts. Pathways to estimate intrinsic predictability of sea ice deformation are proposed. Article in Journal/Newspaper Sea ice The Cryosphere Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) The Cryosphere 17 10 4223 4240
institution Open Polar
collection Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
op_collection_id ftccsdartic
language English
topic [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
spellingShingle [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
Korosov, Anton
Rampal, Pierre
Ying, Yue
Ólason, Einar
Williams, Timothy
Towards improving short-term sea ice predictability using deformation observations
topic_facet [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
description International audience Short-term sea ice predictability is challenging due to the lack of constraints on ice deformation features (open leads and ridges) at kilometre scale. Deformation observations capture these small-scale features and have the potential to improve the predictability. A new method for assimilation of satellite-derived sea ice deformation into the neXt generation Sea Ice Model (neXtSIM) is presented. Ice deformation provided by the Copernicus Marine Environmental Monitoring Service is computed from sea ice drift derived from Synthetic Aperture Radar at a spatio-temporal resolution of 10 km and 24 hours. We show that high values of ice deformation can be interpreted as reduced ice concentration and increased ice damage-scalar variables of neXtSIM. The proof-of-concept assimilation scheme uses a data nudging approach and deterministic forecasting with one member. Assimilation and forecasting experiments are run on example observations from January 2021 and show improvement of neXtSIM skills to predict sea ice deformation in 3-5 days horizon. It is demonstrated that neXtSIM is also capable of extrapolating the assimilated information in space-gaps in spatially discontinuous satellite observations of deformation are filled with a realistic pattern of ice cracks, confirmed by later satellite observations. The experiments also indicate that reduction in sea ice concentration plays a bigger role in improving ice deformation forecast on synoptic scales. Limitations and usefulness of the proposed assimilation approach are discussed in a context of ensemble forecasts. Pathways to estimate intrinsic predictability of sea ice deformation are proposed.
author2 Nansen Environmental and Remote Sensing Center Bergen (NERSC)
Institut des Géosciences de l’Environnement (IGE)
Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Université Grenoble Alpes (UGA)
format Article in Journal/Newspaper
author Korosov, Anton
Rampal, Pierre
Ying, Yue
Ólason, Einar
Williams, Timothy
author_facet Korosov, Anton
Rampal, Pierre
Ying, Yue
Ólason, Einar
Williams, Timothy
author_sort Korosov, Anton
title Towards improving short-term sea ice predictability using deformation observations
title_short Towards improving short-term sea ice predictability using deformation observations
title_full Towards improving short-term sea ice predictability using deformation observations
title_fullStr Towards improving short-term sea ice predictability using deformation observations
title_full_unstemmed Towards improving short-term sea ice predictability using deformation observations
title_sort towards improving short-term sea ice predictability using deformation observations
publisher HAL CCSD
publishDate 2023
url https://hal.science/hal-03796640
https://hal.science/hal-03796640v2/document
https://hal.science/hal-03796640v2/file/Korosov2023The_Cryosphere.pdf
https://doi.org/10.5194/tc-17-4223-2023
genre Sea ice
The Cryosphere
genre_facet Sea ice
The Cryosphere
op_source ISSN: 1994-0424
EISSN: 1994-0416
The Cryosphere
https://hal.science/hal-03796640
The Cryosphere, 2023, 17 (10), pp.4223-4240. ⟨10.5194/tc-17-4223-2023⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-4223-2023
hal-03796640
https://hal.science/hal-03796640
https://hal.science/hal-03796640v2/document
https://hal.science/hal-03796640v2/file/Korosov2023The_Cryosphere.pdf
doi:10.5194/tc-17-4223-2023
op_rights info:eu-repo/semantics/OpenAccess
op_doi https://doi.org/10.5194/tc-17-4223-2023
container_title The Cryosphere
container_volume 17
container_issue 10
container_start_page 4223
op_container_end_page 4240
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