Benefits from representing snow properties and related processes in coupled ocean–sea ice models
•The influence snow physics in asea ice model is analyzed.•Perennial ice seems more sensitive to changes in snow physics than seasonal ice.•Representing snow in sea ice models is important for simulations of Arctic sea ice.•Antarctic sea ice in model simulations is mostly driven by the ocean and atm...
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| Published in | Ocean modelling (Oxford) Vol. 87; pp. 81 - 85 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.03.2015
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1463-5003 1463-5011 |
| DOI | 10.1016/j.ocemod.2014.11.005 |
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| Abstract | •The influence snow physics in asea ice model is analyzed.•Perennial ice seems more sensitive to changes in snow physics than seasonal ice.•Representing snow in sea ice models is important for simulations of Arctic sea ice.•Antarctic sea ice in model simulations is mostly driven by the ocean and atmosphere.
Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselves. |
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| AbstractList | Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselve Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean-sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselves. •The influence snow physics in asea ice model is analyzed.•Perennial ice seems more sensitive to changes in snow physics than seasonal ice.•Representing snow in sea ice models is important for simulations of Arctic sea ice.•Antarctic sea ice in model simulations is mostly driven by the ocean and atmosphere. Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselves. |
| Author | Fichefet, Thierry Massonnet, François Vancoppenolle, Martin Lecomte, Olivier |
| Author_xml | – sequence: 1 givenname: Olivier surname: Lecomte fullname: Lecomte, Olivier email: olivier.lecomte@uclouvain.be organization: Georges Lemaître Center for Earth and Climate Research, Earth and Life Insitute, Université Catholique de Louvain, Place Louis Pasteur 3 – Boîte L4.03.08, 1348 Louvain-la-Neuve, Belgium – sequence: 2 givenname: Thierry surname: Fichefet fullname: Fichefet, Thierry organization: Georges Lemaître Center for Earth and Climate Research, Earth and Life Insitute, Université Catholique de Louvain, Place Louis Pasteur 3 – Boîte L4.03.08, 1348 Louvain-la-Neuve, Belgium – sequence: 3 givenname: François surname: Massonnet fullname: Massonnet, François organization: Georges Lemaître Center for Earth and Climate Research, Earth and Life Insitute, Université Catholique de Louvain, Place Louis Pasteur 3 – Boîte L4.03.08, 1348 Louvain-la-Neuve, Belgium – sequence: 4 givenname: Martin surname: Vancoppenolle fullname: Vancoppenolle, Martin organization: Laboratoire d’Océanographie et du Climat (LOCEAN-IPSL), Centre National de la Recherche Scientifique (CNRS), Sorbonne Universités (UPMC, Univ Paris 06), 4 Place Jussieu, F-75005 Paris, France |
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| Snippet | •The influence snow physics in asea ice model is analyzed.•Perennial ice seems more sensitive to changes in snow physics than seasonal ice.•Representing snow... Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean-sea ice model under the same experimental setup but... Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but... |
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| SubjectTerms | Antarctic Arctic Arctic regions Atmospheric models Computer simulation Geophysics Joining Marine Mathematical models Ocean models Physics Sea ice Snow |
| Title | Benefits from representing snow properties and related processes in coupled ocean–sea ice models |
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