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. The accurate knowledge of sea ice parameters, including sea ice thickness andsnow depth over the sea ice cover, is key to both climate studies and dataassimilation in operational forecasts. Large-scale active and passive remotesensing is the basis for the estimation of these parameters. In traditionalaltimetry or the retrieval of snow depth with passive microwave remotesensing, although the sea ice thickness and the snow depth are closelyrelated, the retrieval of one parameter is usually carried out underassumptions over the other. For example, climatological snow depth data or asderived from reanalyses contain large or unconstrained uncertainty, whichresult in large uncertainty in the derived sea ice thickness and volume. Inthis study, we explore the potential of combined retrieval of both sea icethickness and snow depth using the concurrent active altimetry and passivemicrowave remote sensing of the sea ice cover. Specifically, laser altimetryand L-band passive remote sensing data are combined using two forward models:the L-band radiation model and the isostatic relationship based on buoyancymodel. Since the laser altimetry usually features much higher spatialresolution than L-band data from the Soil Moisture Ocean Salinity (SMOS)satellite, there is potentially covariability between the observed snowfreeboard by altimetry and the retrieval target of snow depth on the spatialscale of altimetry samples. Statistically significant correlation isdiscovered based on high-resolution observations from Operation IceBridge(OIB), and with a nonlinear fitting the covariability is incorporated in theretrieval algorithm. By using fitting parameters derived from large-scalesurveys, the retrievability is greatly improved compared with theretrieval that assumes flat snow cover (i.e., no covariability).Verifications with OIB data show good match between the observed and theretrieved parameters, including both sea ice thickness and snow depth. Withdetailed analysis, we show that the error of the retrieval mainly arises fromthe difference between the modeled and the observed (SMOS) L-band brightnesstemperature (TB). The narrow swath and the limited coverage of the sea icecover by altimetry is the potential source of error associated with themodeling of L-band TB and retrieval. The proposed retrieval methodology canbe applied to the basin-scale retrieval of sea ice thickness and snow depth,using concurrent passive remote sensing and active laser altimetry based onsatellites such as ICESat-2 and WCOM.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data