In this study, the classification potential of polarimetric parameters derived after Cloude–Pottier decomposition, Touzi decomposition, Freeman–Durden decomposition, normalized radar cross section measurements, phase differences, and statistical synthetic aperture radar correlation measures is evaluated by relating them to three pre-identified sea ice types and wind-roughened open water. A combined approach that constitutes a visual inspection of estimated probability densities of the polarimetric parameters and quantitative analysis using supervised classifications (k means and maximum likelihood) is adopted. Polarimetric parameters are iteratively combined in pairs and triplets to test for their ice type discrimination potential. Sensitivity of polarimetric parameters to radar incidence angle is also examined. Our results demonstrated strong but variable sensitivity of polarimetric parameters to different ice types, which was dependent on radar incidence angle. Results of parameter evaluation demonstrated that no single parameter discriminates significantly (>60%) between all the ice types considered in the study. Combining two low correlated parameters increased the classification accuracy by 10%–22%. Combining the third polarimetric parameter did not necessarily improve the classification results. However, the best classification results were achieved using a combination of three parameters.