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Zhao Jiechen, Yang Qinghua, Li Ming, Li Qun, Li Chunhua, Tian Zhongxiang, Zhang Lin. Improving Arctic sea ice concentration forecasts witha Nudging data assimilation method[J]. Haiyang Xuebao, 2016, 38(5): 70-82. doi: 10.3969/j.issn.0253-4193.2016.05.007
Citation: Zhao Jiechen, Yang Qinghua, Li Ming, Li Qun, Li Chunhua, Tian Zhongxiang, Zhang Lin. Improving Arctic sea ice concentration forecasts witha Nudging data assimilation method[J]. Haiyang Xuebao, 2016, 38(5): 70-82. doi: 10.3969/j.issn.0253-4193.2016.05.007

Improving Arctic sea ice concentration forecasts witha Nudging data assimilation method

doi: 10.3969/j.issn.0253-4193.2016.05.007
  • Received Date: 2015-07-14
  • The rapid decrease of Arctic sea ice in summer makes shipping in the Arctic possible. The accurate sea ice forecasts are urgently required to well service the Arctic shipping activities. A numerical Arctic forecasting system was built based on MIT general circulation model (MITgcm) ice-ocean coupled model and the Nudging data assimilation method was applied into this model and assimilate the Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration data. Three different kinds of Nudging assimilation schemes were firstly accessed and the results showed that all three nudging schemes can largely improve the initial sea ice concentration fields. For comparison, two forecasting experiments with and without Nudging assimilation but with the same forcing were designed to evaluate the role of nudging data assimilation. By comparing with the assimilated satellite-derived data and the ship-based in situ sea ice concentration observations, it was shown that the nudging assimilation significantly improved the 24-120 h sea ice concentration forecasts. The results showed that improvements occurred not only in the whole Arctic sea ice concentration forecasts, but also in the single point forecasts. The persistence forecasts performed better in 24-120 h forecast than Nudging experiments when sea ice chance little in August.
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