The variations in the Arctic sea ice thickness (SIT) due to climate change have both positive and negative effects on commercial human activities, the ecosystem, and the Earth’s environment. Satellite microwave remote sensing based on microwave reflection signals reflected by the sea ice surface has been playing an essential role in monitoring and analyzing the Arctic SIT and sea ice concentration (SIC) during the past decades. Recently, passive microwave satellites incorporating an L-band radiometer, such as soil moisture and ocean salinity (SMOS) and soil moisture active passive (SMAP), have been used for analyzing sea ice characteristics, in addition to land and ocean research. In this study, we present a novel method to estimate thin SIT and sea ice roughness (SIR) using a conversion relationship between them, from the SMAP and SMOS data. Methodologically, the SMAP SIR is retrieved. The SMAP thin SIT and SMOS SIR are estimated using a conversion relationship between thin SIT data from SMOS data and SMAP-derived SIR, which is obtained from the spatial and temporal collocation of the SMOS thin SIT and the SIR retrieved from SMAP. Our results for the Arctic sea ice during December for four consecutive years from 2015 to 2018, show high accuracy (bias = −2.268 cm, root mean square error (RMSE) = 15.919 cm, and correlation coefficient (CC) = 0.414) between the SMOS-provided thin SIT and SMAP-derived SIT, and good agreement (bias = 0.03 cm, RMSE = 0.228 cm, and CC = 0.496) between the SMOS-estimated SIR and SMAP-retrieved SIR. Consequently, our study could be effectively used for monitoring and analyzing the variation in the Arctic sea ice.
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