Arctic sea ice drift - A comparison of modeled and remote sensing data

Abstract: The Arctic climate and the sea ice drift are important to study both for the improvement in short-term forecasts and to get a better understanding of the climate change. Short-term forecasts are needed to improve the shipping and offshore industries in the Arctic Ocean. Changes in the ice thickness and concentration can have massive consequences for people and the environment. In the present work, modeled sea-ice drift from a coupled ocean-ice model was compared with observational sea ice drift from remote sensing data with the aim to se if they correspond to each other. Hybrid Coordinate Ocean Model (HYCOM) was used as an ocean model and Los Alamos Sea ice Model (CICE) was the used sea ice model. The data sets were analyzed with Matlab with reason to create plots and easily readable information. The data sets were from year 2015 and showed that sea-ice maximum occurs in late winter and sea-ice minimum appears in late summer.