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杨清华, 刘骥平, 张占海, 等. 北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验[J]. 大气科学, 2011, 35(3): 473-482. DOI: 10.3878/j.issn.1006-9895.2011.03.08
引用本文: 杨清华, 刘骥平, 张占海, 等. 北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验[J]. 大气科学, 2011, 35(3): 473-482. DOI: 10.3878/j.issn.1006-9895.2011.03.08
Yang Qinghua, Liu Jiping, Zhang Zhanhai, et al. A Preliminary Study of the Arctic Sea Ice Numerical Forecasting: Coupled Sea Ice-Ocean Modelling Experiments Based on MITgcm[J]. Chinese Journal of Atmospheric Sciences, 2011, 35(3): 473-482. DOI: 10.3878/j.issn.1006-9895.2011.03.08
Citation: Yang Qinghua, Liu Jiping, Zhang Zhanhai, et al. A Preliminary Study of the Arctic Sea Ice Numerical Forecasting: Coupled Sea Ice-Ocean Modelling Experiments Based on MITgcm[J]. Chinese Journal of Atmospheric Sciences, 2011, 35(3): 473-482. DOI: 10.3878/j.issn.1006-9895.2011.03.08

北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验

A Preliminary Study of the Arctic Sea Ice Numerical Forecasting: Coupled Sea Ice-Ocean Modelling Experiments Based on MITgcm

  • 摘要: 利用最近发展的MITgcm (麻省理工学院通用环流模式) 海冰—海洋耦合模式, 以NCEP (美国国家环境预测中心) 再分析资料为大气强迫场进行了1992年1月至2009年12月北极海冰数值模拟。结果表明, 此模式能很好地模拟卫星观测的北极海冰季节和年际变化, 具备很好的北极海冰数值模拟能力。以此为基础, 对2009年7月和10月北极海冰消融和增长两个例分别进行了4组后报试验研究。试验分别以NCEP再分析气候场、 NCEP GFS (全球预报系统) 预报资料为大气强迫场, 并采用了两种不同的融合SSM/I (专用微波成像仪) 海冰密集度的初始化方案。预报结果与SSM/I的对比, 以及预报技能分析表明, 此模式具备对北极海冰的短时预报能力。大气强迫场的不同对海冰预报的改善不显著, 而初始化考虑SSM/I海冰密集度以减少初始误差的预报能更好地模拟出海冰的消融和增长。此外, 模式模拟的海冰密集度略为偏高, 对海冰冻结过程的模拟能力要优于消融过程。

     

    Abstract: Based on the forcing from the NCEP (National Centers for Environmental Prediction) reanalysis data for the period 1992-2009, the newly developed MITgcm (MIT general circulation model) coupled ice-ocean model shows that the simulated variabilities of the Arctic sea ice extent/area are in good agreement with the observations derived from the SSM/I (Special Sensor Microwave Imager). On the basis of this, the ability of the MITgcm coupled ice-ocean model in forecasting the Arctic sea ice is investigated. Two cases are selected, one is during the melting period and the other is during the freezing period in 2009. Four forecasting experiments are conducted using atmospheric forcing from the NCEP reanalysis data and GFS (Global Forecast System), which use partly and entirely initialized SSM/I sea ice concentrations..The preliminary results show that the model does have the Arctic sea ice forecast capability. It demonstrates that the sea ice forecast is not very sensitive to different atmospheric forcings, whereas initialization using SSM/I sea ice concentrations can much improve the sea ice forecast. 

     

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