An inverse scattering algorithm is presented that reconstructs ice growth under thermal cycling conditions by using time-series active microwave measurements. The algorithm uses a direct scattering model consisting of a physically based electromagnetic model that accounts for thermal and electromagnetic properties of ice and combined volume and surface scattering effects as well as a one-dimensional (1D) thermodynamic model of saline ice growth that includes thermal interactions with the atmosphere. The combined thermodynamic-electromagnetic scattering model is applied to interpret the United States Army Cold Regions Research and Engineering Laboratory, Hanover, NH, 1994 experimental observations (CRRELEX'94) on both the ice growth and the diurnal cycles in C-band polarimetric backscatter. The crucial part of the inversion algorithm is the use of sequentially measured radar data together with the direct scattering model to retrieve the sea ice parameters. The algorithm was applied to CRRELEX'94 data and successfully reconstructed the evolution of ice growth under a thermal cycling environment. This work shows that the inversion algorithm using time-series data offers a distinct advantage over algorithms using individual microwave data set.
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