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| Titel |
On the representation of snow in large scale sea ice models |
| VerfasserIn |
Olivier Lecomte, Thierry Fichefet, Martin Vancoppenolle, Florent Dominé, François Massonnet, Pierre Mathiot, Samuel Morin, Pierre-Yves Barriat |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250076314
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| Zusammenfassung |
| 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. |
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