Abstract
Abstract. Following the launch of ESA's Soil Moisture and Ocean Salinity (SMOS) mission, it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In the first demonstration study, sea ice thickness up to 50 cm has been derived using a semi-empirical algorithm with constant tie-points. Here, we introduce a novel iterative retrieval algorithm that is based on a thermodynamic sea ice model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within the SMOS spatial resolution are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS-based sea ice thickness data set from 2010 on. The data set is compared to and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study (Kaleschke et al., 2012).
Highlights
Satellite-based observation of ice thickness is still very challenging
The mean ice thicknesses derived from Soil Moisture and Ocean Salinity (SMOS) Algorithm II and Moderate Resolution Imaging Spectroradiometer (MODIS) are of similar magnitude – 44 cm and 42 cm, respectively, whereas SMOS Algorithm I shows 31 cm on average
If we restrict the comparison to the pixels with MODIS ice thicknesses less than 50 cm, the mean ice thickness from SMOS Algorithm II is about 13 cm higher than the MODIS mean value
Summary
Satellite-based observation of ice thickness is still very challenging. The first satellite-borne observations of ice thickness were conducted with satellite radar altimeters carried on European Remote Sensing satellites (ERS-1 and ERS2) (Laxon et al, 2003) and thermal imagery from the Advanced Very High Resolution Radiometer (AVHRR) (Yu and Rothrock, 1996; Drucker et al, 2003). Where dice is the ice thickness, T1 and T0 are two constant tie points, which were estimated from the observed SMOS brightness temperatures over open water and thick first year ice during the freezing period of 2010 in the Arctic, and γ is a constant attenuation factor, which was derived from a sea ice radiation model (Menashi et al, 1993) for a representative bulk ice temperature and salinity in the Arctic. Ice salinity can be estimated from the underlying sea surface salinity (SSS) with an empirical function (Ryvlin, 1974) With these two parameters, we can calculate brightness temperature with the sea ice radiation model (Menashi et al, 1993). The basis of the retrieval is the brightness temperature measured by the SMOS L-band radiometer This data set is described in Sect.
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