Reducing the Impact of Thin Clouds on Arctic Ocean Sea Ice Concentration From FengYun-3 MERSI Data Single Cavity

• Published in: IEEE Access
• Main Authors: Xing-DONG Wang, Zhan-Kai Wu, Cheng Wang, Xin-Wu Li, Xin-Guang Li, Yu-Bao Qiu
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2017
• Subjects: Sea ice concentration; FengYun-3 satellite; thin clouds; atmospheric precipitation; influential factor iteration method; Electrical engineering. Electronics. Nuclear engineering; TK1-9971; Arctic; Arctic Ocean; Baffin Bay; Baffin; Davis Strait; National Snow and Ice Data Center; Sea ice
• Online Access: https://doi.org/10.1109/ACCESS.2017.2737326; https://doaj.org/article/8e2782167525404891f3487febb708fb

Arctic sea ice concentration information can provide technical support for the safety of Arctic shipping routes using visible and near-infrared satellite imagery, but clouds reduce detection accuracy. According to the reflectance changes of ice, clouds, and water, and because the near-infrared reflectances of clouds are much higher than that of ice and water, we propose a new method for identifying clouds. On this basis, thin clouds are extracted using atmospheric precipitation. The Arctic Ocean sea ice distribution under thin cloud cover over can be obtained based on the proposed influential factor iteration method. Finally, we obtain the sea ice concentration in the critical region of Baffin Bay and Davis Strait on June 15, 2014 from the Medium Resolution Imaging Spectrometer (MERSI) data. MERSI is one of the major payloads of the Chinese second-generation polar-orbiting meteorological satellite, FengYun-3, and is similar to the Moderate-resolution Imaging Spectroradiometer. The proposed method is shown to accurately detect sea ice concentration under thin clouds by comparison with the sea ice results from the National Snow and Ice Data Center.