Sea Ice Extent Retrieval Using CSCAT 12.5 km Sampling Data

Abstract

Polar sea ice extent exhibits a highly dynamic nature. This paper investigates the sea ice extent retrieval on a fine (6.25 km) grid based on the 12.5 km sampling data from the China France Ocean Satellite Scatterometer (CSCAT), which is generated by an adapted Bayesian sea ice detection algorithm. The CSCAT 12.5 km sampling data are analyzed, a corresponding sea ice GMF model is established, and the important calculation procedures and parameter settings of the adapted Bayesian algorithm for CSCAT 12.5 km sampling data are elaborated on. The evolution of the sea ice edge and extent based on CSCAT 12.5 km sampling data from 2020 to 2022 is introduced and quantitatively compared with sea ice extent products of Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Advanced Scatterometer onboard MetOp-C (ASCAT-C). The results suggest the sea ice extent of CSCAT 12.5 km sampling data has good consistency with AMSR2 at 15% sea ice concentration. The sea ice edge accuracy between them is about 7 km and 10 km for the Arctic and Antarctic regions, and their sea ice extent difference is 0.25 million km2 in 2020 and 0.5 million km2 in 2021 and 2022. Compared to ASCAT-C 12.5 km sampling data, the sea ice edge Euclidean distance (ED) of CSCAT 12.5 km data is 14 km (2020 and 2021) and 12.5 km (2022) for the Arctic region and 14 km for the Antarctic region. The sea ice extent difference between them is small except for January to May 2020 and 2021 for the Arctic region. There are significant deviations in the sea ice extents of CSCAT 12.5 km and 25 km sampling data, and their sea ice extent difference is 0.3–1.0 million km2.