A Sea Ice Concentration Estimation Methodology Utilizing ICESat-2 Photon-Counting Laser Altimeter in the Arctic

• Published in: Remote Sensing
• Main Authors: Jun Liu, Huan Xie, Yalei Guo, Xiaohua Tong, Peinan Li
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: arctic; ICESat-2; sea ice concentration; polar oceans; lidars; Science; Q; Arctic; Laptev Sea; Kara Sea; laptev; Sea ice; Siberia
• Online Access: https://doi.org/10.3390/rs14051130; https://doaj.org/article/6154801aeb2c47a8a82773ea60074608

NASA’s Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission was launched in September 2018. The sole instrument onboard ICESat-2 is ATLAS, a highly precise laser that now provides routine, very-high-resolution, surface height measurements across the globe, including over the Arctic. To further improve the detection accuracy of the sea ice concentration (SIC), we demonstrate a new processing chain that can be used to convert the along-track sea ice freeboard products (ATL10) obtained by ICESat-2 into the SIC, with our initial efforts being focused on the Arctic. For this conversion, we primarily make use of the classification results from the type (sea ice or lead) and segment length data gathered from ATL10. The along-track SIC is the ratio of the area that is covered by sea ice segments to the area of all of the along-track segments. We generated a monthly gridded SIC product with a 25 km resolution and compared this to the NSIDC Climate Data Record (CDR) sea ice concentration. The highest correlation was determined to be 0.7690 in September at high latitudes and the lowest correlation was found to be 0.8595 in June at mid-latitudes. The regions with large standard deviations in summer and autumn are mainly distributed in the thin-ice areas at mid-latitudes. In the Laptev Sea and Kara Sea of east Siberia, the differences in the standard deviation were large; the maximum bias was −0.1566, in November, and the minimum bias was −0.0216, in June. ICESat-2 shows great potential for the accurate estimation of the SIC.