留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估

舒启 乔方利 鲍颖 尹训强

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. doi: 10.3969/j.issn.0253-4193.2015.11.004
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. doi: 10.3969/j.issn.0253-4193.2015.11.004
Shu Qi, Qiao Fangli, Bao Ying, Yin Xunqiang. Assessment of Arctic sea ice simulation by FIO-ESM based on data assimilation experiment[J]. Haiyang Xuebao, 2015, 37(11): 33-40. doi: 10.3969/j.issn.0253-4193.2015.11.004
Citation: Shu Qi, Qiao Fangli, Bao Ying, Yin Xunqiang. Assessment of Arctic sea ice simulation by FIO-ESM based on data assimilation experiment[J]. Haiyang Xuebao, 2015, 37(11): 33-40. doi: 10.3969/j.issn.0253-4193.2015.11.004

对地球系统模式FIO-ESM同化实验中北极海冰模拟的评估

doi: 10.3969/j.issn.0253-4193.2015.11.004
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)。

Assessment of Arctic sea ice simulation by FIO-ESM based on data assimilation experiment

  • 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/(10 a),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。
  • Zhang S, Harrison M J, Rosati A, et al. System design and evaluation of coupled ensemble data assimilation for global oceanic climate studies[J]. Monthly Weather Review, 2007, 135(10): 3541-3564.
    Massonnet F, Fichefet T, Goosse H. Prospects for improved seasonal Arctic sea ice predictions from multivariate data assimilation[J]. Ocean Modelling, 2015, 88: 16-25.
    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的模拟实验[J]. 大气科学, 2011, 35(3): 473-482. Yang Qinghua, Liu Jiping, Zhang Zhanhai, et al. A preliminary study of the Arctic sea ice numerical forecasting: coupled sea ice-ocean modeling experiments based on MITgcm[J]. Chinese Journal of Atmosphere Science, 2011, 35(3): 473-482.
    凌铁军, 王彰贵, 王斌, 等. 基于CCSM3气候模式的同化模拟实验[J]. 海洋学报, 2009, 31(6): 9-21. Ling Tiejun, Wang Zhanggui, Wang Bin, et al. Assimilation modeling by using CCSM3 model[J]. Haiyang Xuebao, 2009, 31(6): 9-21.
    Qiao F, Song Z, Bao Y, et al. Development and evaluation of a Earth System Model with surface gravity waves[J]. Journal of Geophysical Research: Oceans, 2013, 118: 4514-4524.
    陈辉, 尹训强, 宋振亚, 等.气候模式中海洋数据同化对热带降水偏差的影响[J].海洋学报, 2015, 37(7):41-53. Chen Hui, Yin Xunqiang, Song Zhenya, et al. The impacts of ocean data assimilation on tropical precipitation bias in a climate model[J]. Haiyang Xuebao, 2015, 37(7):41-53.
    尹训强. 集合调整Kalman滤波同化模块的建立及其在海洋和气候模式中的应用[D]. 青岛: 中国海洋大学, 2015. Yin Xunqiang. Development of assimilation module for ensemble adjustment Kalman filter and its application in ocean and climate models[D]. Qingdao: Ocean University of China, 2015.
    Collins W D, Rasch P J, Boville B A, et al. Description of the NCAR Community Atmosphere Model (CAM 3.0)[M]. Colorado: National Center for Atmospheric Research, 2004.
    Yang Y, Qiao F, Zhao W, et al. MASNUM ocean wave model in spherical coordinate and its application[J]. Acta Oceanologica Sinica, 2005, 27(3): 1-7.
    Smith R, Jones P, Briegleb B, et al. The parallel ocean program (POP) reference manual[M]. Los Alamos National Laboratory, LAUR-10-01853, 2010.
    Elizabeth C H, William H L. CICE: the Los Alamos sea ice model documentation and software user's manual version 4.0[M]. Los Alamos National Laboratory, LA-CC-06-012, 2008.
    Oleson K W, Niu G Y, Yang Z L, et al. Improvements to the Community Land Model and their impact on the hydrological cycle[J]. Journal of Geophysical Research, 2008, 113: G01021.
    宋振亚. 波致混合对气候模式中赤道SST的影响机制研究[D]. 青岛: 中国海洋大学, 2011. Song Zhenya. The mechanism of the wave induced mixing effect on the equatorial SST in the climate system model[D]. Qingdao: Ocean University of China, 2011.
    Song Y, Qiao F, Song Z, et al. Water vapor transport and cross-equatorial flow over the Asian-Australia monsoon region simulated by CMIP5 climate models[J]. Advances in Atmospheric Sciences, 2013, 30: 726-738.
    舒启, 乔方利, 宋振亚. 地球系统模式FIO-ESM 对北极海冰的模拟和预估[J]. 海洋学报, 2013, 35(5): 37-45. Shu Qi, Qiao Fangli, Song Zhenya. The hindcast and forecast of Arctic sea ice from FIO-ESM[J]. Haiyang Xuebao, 2013, 35(5): 37-45.
    Reynolds R W, Smith T M, Liu C, et al. Daily high-resolution blended analyses for sea surface temperature[J]. J Climate, 2007, 20: 5473-5496.
    Cavalieri D, Parkinson C, Gloersen P, et al. Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data, 1979-2007[M]. USA: National Snow and Ice Data Center, Digital Media, Boulder (updated 2013), 1996.
    Wendler G, Chen L, Moore B. Recent sea ice increase and temperature decrease in the Bering Sea area, Alaska[J]. Theor Appl Climatol, 2013, 117(3/4):235-242.
    Massonnet F, Fichefet T, Goosse H, et al. Constraining projections of summer Arctic sea ice[J]. The Cryosphere, 2012, 6: 1383-1394.
    Wang M, Overland J E. A sea ice free summer Arctic within 30 years?[J]. Geophysical Reseatch Letters, 2009, 36: L07502.
    Wang M, Overland J E. A sea ice free summer Arctic within 30 years: An update from CMIP5 models[J]. Geophys Res Lett, 2012, 39: L18501.
  • 加载中
计量
  • 文章访问数:  1758
  • HTML全文浏览量:  11
  • PDF下载量:  1199
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-04-20

目录

    /

    返回文章
    返回