Short term prediction of ice conditions: an integration of SAR Imagery and model derived sea ice drift data

The poster details the methodology and preliminary findings of an accuracy assessment for sea ice condition predictions. This assessment utilizes Synthetic Aperture Radar (SAR) imagery alongside sea ice drift data modeled by Barents 2.5 v2, and a warping algorithm developed by Anton Korosov and Anna Telegina, available at [https://github.com/nansencenter/sar_image_warping]. It presents an analysis of drift and distortion errors, supplementing these findings with case studies on the predictive behavior of sea ice in marginal ice zones and deformation zones, where more "ductile" types of sea ice are predominant.