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Hao Guanghua, Zhao Jiechen, Li Chunhua, Yang Qinghua, Wang Jiangpeng, Sun Xiaoyu, Zhang Lin. The sea ice observations and assessment of satellite sea-ice concentration along the Central Arctic Passage in summer 2017[J]. Haiyang Xuebao, 2018, 40(11): 54-63. doi: 10.3969/j.issn.0253-4193.2018.11.006
Citation: Hao Guanghua, Zhao Jiechen, Li Chunhua, Yang Qinghua, Wang Jiangpeng, Sun Xiaoyu, Zhang Lin. The sea ice observations and assessment of satellite sea-ice concentration along the Central Arctic Passage in summer 2017[J]. Haiyang Xuebao, 2018, 40(11): 54-63. doi: 10.3969/j.issn.0253-4193.2018.11.006

The sea ice observations and assessment of satellite sea-ice concentration along the Central Arctic Passage in summer 2017

doi: 10.3969/j.issn.0253-4193.2018.11.006
  • Received Date: 2018-01-19
  • Rev Recd Date: 2018-04-28
  • In summer 2017, for the first time, the Chinese R/V Xuelong successfully passed through the Central Arctic Passage (CAP) during the Chinese National Arctic Research Expedition (CHINARE 2017), the ship-based sea ice observations were carried out during this cruise. The results showed that the CAP was mainly occupied by thick first-year ice, the average sea ice concentration (SIC) and thickness along the CAP were 0.64 and 1.5 m, respectively; the ice floes in the central Arctic Ocean are significantly larger than the sea ice edge area. The 5 commonly used passive microwave satellite retrieved SIC datasets with a spatial resolution higher than 10 km were inter-compared and assessed using the ship-based SIC. The point to point comparison showed the AMSR2 SIC datasets (Bootstrap algorithm) released by University of Bremen had the largest bias and rms (root mean square) values with 0.19 and 0.28, while the AMSR2 SIC datasets (OSHD and TUD algorithm, respectively) released by Ocean and Sea Ice Satellite Application Facility (OSI SAF) were with the smallest bias of -0.02 and 0.01, and the rms values were both 0.20. The daily mean comparison showed that the AMSR2 SIC dataset (Bootstrap algorithm) released by University of Bremen and the AMSR2/OSI SAF (TUD) dataset had the largest (0.15 and 0.20) and smallest (0.0 and 0.11) mean bias and rms values, respectively.
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