Abstract

Accurate knowledge of the sea ice parameters, including the thickness and the snow depth over sea ice, are key to both climate change studies and operational forecast in polar regions. The estimation of these parameters mainly relies on satellite based remote sensing, and current retrieval algorithms usually focus on the retrieval of a single parameter under simple assumptions over the other. In this article, we explore the potential of combined retrieval of both sea ice thickness and snow depth through the data synergy two types of concurrent observations of the sea ice cover: the active altimetry and the L-band passive remote sensing. The data synergy is based on two physical constrains: (1) L-band (1.4 GHz) radiation model for the sea ice cover, and (2) the hydrostatic equilibrium as used in satellite altimetry. Two schemes of data synergy are proposed: (1) the synergy between L-band brightness temperature ( T B ) from passive microwave remote sensing and sea ice freeboard ( F B i c e ) as measured by radar altimetry, and (2) the synergy between L-band T B and snow freeboard ( F B s n o w ) as measured by laser altimetry. Based on retrievability studies, we show that both parameters can be retrieved using the two sets of data. Specifically, we show that there is potential problem of ill-posedness for the synergy between L-band T B and F B s n o w , with two possible retrieval solutions for a small portion of the solution space. On the other hand, the synergy between L-band T B and F B i c e is always well-posed. In terms of sensitivity, lower uncertainty is witnessed for thin ice for the retrieval with F B i c e , while the retrieval with F B s n o w shows advantage for thick ice. Besides the input parameters of T B , F B i c e and F B s n o w , the uncertainty associated with certain model parameters such as snow and ice densities is not negligible for the uncertainty estimation of the retrieved parameters. Verification is carried out with observational data from Operation IceBridge (OIB) campaigns and SMOS satellite, showing that both sea ice thickness and snow depth can be attained by the proposed retrieval algorithms. These algorithms serve as the basis for large-scale retrieval with satellite remote sensing data, including concurrent observation of the Arctic Ocean by independent satellite campaigns such as SMOS, CryoSat-2 and ICESat.

Highlights

  • The sea ice forms as the result of the cooling and the phase change of the sea surface [1]

  • In this study we propose the data synergy between active altimetry and L-band passive microwave remote sensing of the sea ice cover, for the retrieval of both sea ice thickness and snow depth

  • The synergy is based on two physical models: (1) the hydrostatic equilibrium relationship which is widely adopted in satellite altimetry, and (2) the L-band radiation model [32]

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Summary

Introduction

The sea ice forms as the result of the cooling and the phase change of the sea surface [1]. Sea ice thickness can be retrieved through passive microwave satellite remote sensing. In Kaleschke et al [20] and related works, the retrieval of thin ice thickness with L-band (1.4 GHz) TB measurements from Soil Moisture and Ocean Salinity (SMOS) satellite is carried out, based on a forward sea ice radiation model. We carry out theoretical study over the simultaneous retrieval of both sea ice thickness and snow depth, by data synergy of concurrent active and passive remote sensing of the Remote Sens. The proposed data synergy serves as a theoretical basis for the basin-scale retrieval of sea ice parameters using concurrent active and passive satellite remote sensing data, including SMOS and CryoSat-2 or ICESat-2

Retrievability Studies
Forward Models
Retrievability Analysis
Retrieval Algorithms
II III IV
Sensitivity Studies
Effect of Input Parameters for the Synergy between TB and FBice
Effect of Input Parameters for the Synergy between TB and FBsnow
Uncertainty Analysis from Model Parameters
Verification with OIB and SMOS Data
Results and Discussion
Summary and Future Work

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