An Intercomparison of Satellite Derived Arctic Sea Ice Motion Products

Abstract

Arctic sea ice motion information provides an important scientific basis for revealing the changing mechanism of Arctic sea ice and assessing the navigational safety of Arctic waterways. For now, many satellite derived Arctic sea ice motion products have been released but few studies have conducted comparisons of these products. In this study, eleven satellite sea ice motion products from the Ocean and Sea Ice Satellite Application Facility (OSI SAF), the National Snow and Ice Data Center (NSIDC), and the French Research Institute for the Exploitation of the Seas (Ifremer) were systematically evaluated and compared based on buoys from the International Arctic Buoy Program (IABP) and the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) over 2018–2020. The results show that the mean absolute errors (MAEs) of ice speed for these products are 1.15–2.26 km/d and the MAEs of ice motion angle are 14.93–23.19°. Among all products, Ifremer_AMSR2 achieves the best accuracy in terms of speed error, NSIDC_Pathfinder shows the lowest angle error and OSI-405-c_Merged performs best in sea-ice drift trajectory reconstruction. Moreover, season, region, data source, ice drift tracking algorithm, and time interval all influence the accuracy of these products: (1) The sea ice motion bias in the freezing season (1.04–1.96 km/d and 11.93–22.41°) is smaller than that in the melting season (1.13–3.90 km/d and 14.41–27.41°) for most of the products. (2) Most products perform worst in East Greenland, where ice movements are fast and complex. (3) The accuracies of the products derived from AMSR-2 remotely sensed data are better than those from other data sources. (4) The continuous maximum cross-correlation (CMCC) algorithm outperforms the maximum cross-correlation (MCC) algorithm in sea ice drift retrieval. (5) The MAEs of sea ice motion with longer time interval are relatively smaller. Overall, the results indicate that the eleven remote sensing Arctic sea ice drift products are of practical use for data assimilation and model validation if uncertainties are appropriately considered. Furthermore, this study provides some improvement directions for sea ice drift retrieval from satellite data.