Abstract

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.

Highlights

  • The Soil Moisture and Ocean Salinity (SMOS) mission carries the first satellite-based passive microwave radiometer that measures radiation emitted from the earth at a frequency of 1.4 GHz in the L-band

  • The presence of a snow layer modifies the radiation observed above sea ice, because the reflectivities between the air–snow and the snow–ice boundaries are lower than the reflectivity at the air–ice boundary

  • At vertical polarisation, the brightness temperature increase due to the presence of a snow cover decreases with increasing incidence angle

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Summary

Introduction

The Soil Moisture and Ocean Salinity (SMOS) mission carries the first satellite-based passive microwave radiometer that measures radiation emitted from the earth at a frequency of 1.4 GHz in the L-band. Designed to provide global estimates of soil moisture and ocean salinity, L-band brightness temperatures measured by SMOS can be used to retrieve thin sea ice thickness (Kaleschke et al, 2010, 2012). A snow layer on the ice has an impact on the effective emissivity and on the brightness temperature of sea ice. snow has a thermal insulation effect on ice, causing the bulk ice temperature of snow-covered sea ice generally to be higher than the bulk ice temperature of bare sea ice. Because the ice temperature determines the dielectric properties of sea ice, snow has an indirect effect on the brightness temperature of sea ice. Here, we use a multiple-layer model based on the radiation model presented in Burke et al (1979) to examine the impact of a snow cover on brightness temperatures above sea ice and the implications for the ice thickness retrieval of snow-covered sea ice. In order to test the validity of our theoretical investigations, we simulate brightness temperatures for ice and snow thicknesses measured during the National Aeronautics and Space Administration (NASA) Operation IceBridge flight campaign in spring 2012 in the Arctic. We evaluate whether SMOS has the potential for retrieving ice thickness over thin ice, and the potential for estimating snow thickness over thick sea ice in the Arctic

Data and methods
Emission model
SMOS data
The IceBridge flight campaign
Model simulations and sensitivities
Thermal insulation and dielectric properties of snow
Snow thickness
Comparison of brightness temperature simulations and SMOS observations
Results for all ice concentrations and all ice surface temperatures
Results for the closed ice cover cases and a fixed surface temperature
Potential for retrieval of snow thickness
Brightness temperatures for different snow thicknesses
Comparison of retrieved and measured snow thicknesses
Findings
Summary and discussion
Conclusions
Full Text
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