This paper utilizes an electromagnetic inverse-scattering algorithm to quantitatively reconstruct the vertical temperature and salinity profiles of snow-covered sea ice from time-series monostatic polarimetric normalized radar cross-section (NRCS) data. The reconstructed profile at a given time step is utilized to provide a priori information for the profile reconstruction at the subsequent time step. This successive use of a priori information in the inversion algorithm results in achieving high reconstruction accuracy over the time period of interest. This inversion scheme is evaluated against the experimental data collected from snow-covered sea ice grown in an Arctic ocean mesocosm facility. It will be shown that the time evolution of the temperature, salinity, and density profiles of an artificially grown snow-covered sea ice can be quantitatively reconstructed using single-frequency time-series radar cross-section data assuming that these profiles are initially known with sufficient accuracy.
- Electromagnetic inverse scattering
- polarimetric time-series radar signatures
- salinity and temperature profiles
- snow-covered surfaces