Evaluation of the AMSR2 Ice Extent at the Arctic Sea Ice Edge Using an SAR-Based Ice Extent Product

Passive microwave (PM) and synthetic aperture radar (SAR) observations are essential tools for providing long time series of sea-ice cover information, including sea-ice concentration (SIC) and sea-ice extent (SIE). Large uncertainties have been revealed in PM SIC/SIE products in the marginal ice zone (MIZ) and during the melting season, where fusion with SAR data could be effective for improving accuracy due to its high spatial resolution and ability to preserve detailed ice distributions. A comprehensive comparison of PM and SAR ice cover products is needed for better data fusion. This study evaluates one of the PM SIE products, the advanced microwave scanning radiometer 2 (AMSR2) SIE product retrieved with the arctic radiation and turbulence interaction study (ARTIST) sea ice (ASI) algorithm, using a neural-network-based SAR SIE product throughout the year 2019. First, we present key results of three assessment parameters, including the overall accuracy (OA), error-of-ice (EI), and ice edge location distance (LD), and then estimate the optimal SIC segmentation threshold for AMSR2 ASI SIE. Based on OA and EI, the annual average SIC threshold of 12.24%, winter average of 9.25%, and summer average of 16.43% are obtained and regarded as optimal by excluding cases with large uncertainties. Second, the AMSR2 ASI SIE product is found to perform better in identifying thin ice and melt ponds, while the SAR NN SIE product has better detection of brash ice and frazil ice. We introduce a parameter of sea-ice fragmentation fraction (IFF) to analyze the primary impact factors behind the different performances. It is found that the ratio of LD to IFF could distinguish the aforementioned different ice conditions, thus providing hints for combining the complementary advantages of the two SIE products during data fusion.