On the representation of snow in large scale sea ice models
International audience An assessment of the performance of a state-of-the-art large-scale coupled sea ice -ocean model, including a new snow multi-layer thermodynamic scheme, in simulating the sea ice thickness and extent over the past three decades in both hemispheres, is performed. Four simulation...
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Format: | Conference Object |
Language: | English |
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HAL CCSD
2013
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Online Access: | https://hal.science/hal-00912620 |
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ftepunivpsaclay:oai:HAL:hal-00912620v1 |
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Open Polar |
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École Polytechnique, Université Paris-Saclay: HAL |
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ftepunivpsaclay |
language |
English |
topic |
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] |
spellingShingle |
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] Lecomte, Olivier Fichefet, Thierry Vancoppenolle, Martin Dominé, Florent Massonnet, François Mathiot, Pierre Morin, Samuel Barriat, Pierre-Yves On the representation of snow in large scale sea ice models |
topic_facet |
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] |
description |
International audience An assessment of the performance of a state-of-the-art large-scale coupled sea ice -ocean model, including a new snow multi-layer thermodynamic scheme, in simulating the sea ice thickness and extent over the past three decades in both hemispheres, is performed. Four simulations from the model are compared against each other and against submarine, airborne and satellite observations. Each simulation uses a separate formulation for snow apparent thermal conductivity and density. In the first experiment, the snow density profile is prescribed from observations and the thermal conductivity is constant and equal to 0.31 W m -1 K -1 , a typical value for such models. Formulations (2) and (3) are typical power-law relationships linking thermal conductivity directly to density (prescribed as in simulation (1)). Parameterization (4) is newly developed and consists of a set of two linear equations relating the snow thermal conductivity and density to the mean seasonal wind speed. We show that the first simulation leads to an overestimation of the sea ice thickness due to overestimated snow thermal conductivity, particularly in the Northern Hemisphere. Formulation (2) leads to a realistic simulation of the Arctic sea ice mean state while (3) provides the minimum deviations with respect to sea ice extent and thickness observations in the Southern Ocean. Parameterization (4), accounting for the snow packing process in a simple way, is the most promising formulation. In particular, this formulation improves the simulated large-scale snow depth probability density functions. The intercomparison of all simulations suggests that the sea ice model is more sensitive to the snow representation in the Arctic than it is in the Southern Ocean, where both the simulated sea ice mean state and variability seem to be dominantly driven by the ocean. |
author2 |
Institut d'Astronomie et de Géophysique Georges Lemaître (UCL-ASTR) Université Catholique de Louvain = Catholic University of Louvain (UCL) Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN) Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Observatoire des Sciences de l'Univers de Grenoble (OSUG) Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) Centre Georges Lemaître for Earth and Climate Research Louvain (TECLIM) Earth and Life Institute Louvain-La-Neuve (ELI) Université Catholique de Louvain = Catholic University of Louvain (UCL)-Université Catholique de Louvain = Catholic University of Louvain (UCL) |
format |
Conference Object |
author |
Lecomte, Olivier Fichefet, Thierry Vancoppenolle, Martin Dominé, Florent Massonnet, François Mathiot, Pierre Morin, Samuel Barriat, Pierre-Yves |
author_facet |
Lecomte, Olivier Fichefet, Thierry Vancoppenolle, Martin Dominé, Florent Massonnet, François Mathiot, Pierre Morin, Samuel Barriat, Pierre-Yves |
author_sort |
Lecomte, Olivier |
title |
On the representation of snow in large scale sea ice models |
title_short |
On the representation of snow in large scale sea ice models |
title_full |
On the representation of snow in large scale sea ice models |
title_fullStr |
On the representation of snow in large scale sea ice models |
title_full_unstemmed |
On the representation of snow in large scale sea ice models |
title_sort |
on the representation of snow in large scale sea ice models |
publisher |
HAL CCSD |
publishDate |
2013 |
url |
https://hal.science/hal-00912620 |
op_coverage |
Vienne, Austria |
genre |
Arctic Sea ice Southern Ocean |
genre_facet |
Arctic Sea ice Southern Ocean |
op_source |
EGU General Assembly 2013 https://hal.science/hal-00912620 EGU General Assembly 2013, Apr 2013, Vienne, Austria. pp.5029 |
op_relation |
hal-00912620 https://hal.science/hal-00912620 BIBCODE: 2013EGUGA.15.5029L |
_version_ |
1799475074857697280 |
spelling |
ftepunivpsaclay:oai:HAL:hal-00912620v1 2024-05-19T07:36:03+00:00 On the representation of snow in large scale sea ice models Lecomte, Olivier Fichefet, Thierry Vancoppenolle, Martin Dominé, Florent Massonnet, François Mathiot, Pierre Morin, Samuel Barriat, Pierre-Yves Institut d'Astronomie et de Géophysique Georges Lemaître (UCL-ASTR) Université Catholique de Louvain = Catholic University of Louvain (UCL) Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN) Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Laboratoire de glaciologie et géophysique de l'environnement (LGGE) Observatoire des Sciences de l'Univers de Grenoble (OSUG) Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS) Centre Georges Lemaître for Earth and Climate Research Louvain (TECLIM) Earth and Life Institute Louvain-La-Neuve (ELI) Université Catholique de Louvain = Catholic University of Louvain (UCL)-Université Catholique de Louvain = Catholic University of Louvain (UCL) Vienne, Austria 2013-04-07 https://hal.science/hal-00912620 en eng HAL CCSD hal-00912620 https://hal.science/hal-00912620 BIBCODE: 2013EGUGA.15.5029L EGU General Assembly 2013 https://hal.science/hal-00912620 EGU General Assembly 2013, Apr 2013, Vienne, Austria. pp.5029 [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] info:eu-repo/semantics/conferenceObject Conference papers 2013 ftepunivpsaclay 2024-04-25T00:26:25Z International audience An assessment of the performance of a state-of-the-art large-scale coupled sea ice -ocean model, including a new snow multi-layer thermodynamic scheme, in simulating the sea ice thickness and extent over the past three decades in both hemispheres, is performed. Four simulations from the model are compared against each other and against submarine, airborne and satellite observations. Each simulation uses a separate formulation for snow apparent thermal conductivity and density. In the first experiment, the snow density profile is prescribed from observations and the thermal conductivity is constant and equal to 0.31 W m -1 K -1 , a typical value for such models. Formulations (2) and (3) are typical power-law relationships linking thermal conductivity directly to density (prescribed as in simulation (1)). Parameterization (4) is newly developed and consists of a set of two linear equations relating the snow thermal conductivity and density to the mean seasonal wind speed. We show that the first simulation leads to an overestimation of the sea ice thickness due to overestimated snow thermal conductivity, particularly in the Northern Hemisphere. Formulation (2) leads to a realistic simulation of the Arctic sea ice mean state while (3) provides the minimum deviations with respect to sea ice extent and thickness observations in the Southern Ocean. Parameterization (4), accounting for the snow packing process in a simple way, is the most promising formulation. In particular, this formulation improves the simulated large-scale snow depth probability density functions. The intercomparison of all simulations suggests that the sea ice model is more sensitive to the snow representation in the Arctic than it is in the Southern Ocean, where both the simulated sea ice mean state and variability seem to be dominantly driven by the ocean. Conference Object Arctic Sea ice Southern Ocean École Polytechnique, Université Paris-Saclay: HAL |