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对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估
引用本文:舒启,乔方利,鲍颖,尹训强.对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估[J].海洋学报,2015,37(11):33-40.
作者姓名:舒启  乔方利  鲍颖  尹训强
作者单位:国家海洋局 第一海洋研究所, 山东 青岛 266061;海洋环境科学和数值模拟国家海洋局重点实验室, 山东 青岛 266061
基金项目:极地对全球和我国气候变化影响的综合评价(CHINARE2015-04-04);国家自然科学基金项目(41406027);国家海洋局第一海洋研究所基本科研业务费资助项目(2015P01,2015P03)。
摘    要:本文评估了地球系统模式FIO-ESM(First Institute of Oceanography-Earth System Model)基于集合调整Kalman滤波同化实验对1992-2013年北极海冰的模拟能力。结果显示:尽管同化资料只包括了全球海表温度和全球海面高度异常两类数据,而并没有对海冰进行同化,但实验结果能很好地模拟出与观测相符的北极海冰基本态和长期变化趋势,卫星观测和FIO-ESM同化实验所得的北极海冰覆盖范围在1992-2013年间的线性变化趋势分别为-7.06×105和-6.44×105 km2/(10a),同化所得的逐月海冰覆盖范围异常和卫星观测之间的相关系数为0.78。与FIO-ESM参加CMIP5(Coupled Model Intercomparison Project Phase 5)实验结果相比,该同化结果所模拟的北极海冰覆盖范围的长期变化趋势和海冰密集度的空间变化趋势均与卫星观测更加吻合,这说明该同化可为利用FIO-ESM开展北极短期气候预测提供较好的预测初始场。

关 键 词:数据同化    FIO-ESM    气候变化    北极海冰
收稿时间:2015/4/20 0:00:00

Assessment of Arctic sea ice simulation by FIO-ESM based on data assimilation experiment
Shu Qi,Qiao Fangli,Bao Ying and Yin Xunqiang.Assessment of Arctic sea ice simulation by FIO-ESM based on data assimilation experiment[J].Acta Oceanologica Sinica (in Chinese),2015,37(11):33-40.
Authors:Shu Qi  Qiao Fangli  Bao Ying and Yin Xunqiang
Institution:First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Key Lab of Marine Science and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China
Abstract:In this study, Arctic sea ice during 1992-2013 simulated by FIO-ESM (First Institute of Oceanography-Earth System Model) based on ensemble adjustment Kalman filter data assimilation experiment is assessed. Although only global sea surface temperature and global sea level anomaly are assimilated to FIO-ESM and there is no sea ice assimilation, our study shows that the climatology and long-term trend of Arctic sea ice can also be well reproduced with this kind of data assimilation. The linear trends of Arctic sea ice extent during 1992-2013 from satellite observations and FIO-ESM simulations are -7.06×105 and -6.44×105 km2/(10 a), respectively. The correlation coefficient between modeled and observed Arctic sea ice extent anomalies is 0.78. Compared with the results from FIO-ESM in CMIP5 (Coupled Model Intercomparison Project Phase 5) experiment, the long-term trends of Arctic sea ice extent and sea ice concentration from data assimilation experiment fit the observations much better, so these results from FIO-ESM data assimilation experiment can be used as initial condition for Arctic climate projection.
Keywords:data assimilation  FIO-ESM  climate change  Arctic sea ice
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