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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 6
The Cryosphere, 7, 1971-1989, 2013
https://doi.org/10.5194/tc-7-1971-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Earth observation of the Cryosphere

The Cryosphere, 7, 1971-1989, 2013
https://doi.org/10.5194/tc-7-1971-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 Dec 2013

Research article | 20 Dec 2013

Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

N. Maaß1, L. Kaleschke1, X. Tian-Kunze1, and M. Drusch2 N. Maaß et al.
  • 1Institute of Oceanography, University of Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
  • 2European Space Agency, ESA-ESTEC, 2200 AG Noordwijk, the Netherlands

Abstract. The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data.

We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

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