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大气科学  2012 

BCC_CSM1.1对10年尺度全球及区域温度的预测研究

DOI: 10.3878/j.issn.1006-9895.2012.11243

Keywords: 模拟,气候系统模式,年代际预测,BCC_CSM,CMIP5

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Abstract:

近期10~30年时间尺度的年代际预测是第五次耦合模式国际比较计划(CMIP5)重要内容之一。按照CMIP5试验要求,国家气候中心利用气候系统模式BCC_CSM1.1完成并提交了年代际试验结果。本文评估了该模式年代际试验对10年尺度全球及区域地表温度的预测能力,并通过与20世纪历史气候模拟试验的对比分析,研究模式模拟对海洋初始观测状态的依赖程度。分析结果表明:(1)在有、无海洋初始化条件下,模式均能模拟出1960~2005年间全球10年平均实测地表温度的变暖趋势,但在有海洋初始化条件下,可以明显减小BCC_CSM1.1模式模拟的全球升温趋势,使得年代际试验比历史试验的结果更接近观测值。这一特点在观测资料相对丰富的南北纬50°以内地区更为显著。(2)在年代际试验预测前期,通过Nudging方法,利用SODA再分析海洋温度资料对模式进行初始化,经过前期8~12月的协调后,模式预测的第1年南北纬50°范围海洋、陆面的平均地表气温接近于观测值(CRUTEM3,HadSST2)。由于模式初值SODA再分析SST资料与HadSST2观测值存在明显的全球大洋系统暖偏差以及模式本身系统偏差的影响,年代际试验模拟的地表气温在2~7年之内,从观测SST状态逐渐恢复到模式系统本身状态。在同组Decadal试验中,陆面和海洋恢复调整的时间长度几乎一致。(3)从10年平均气候异常在区域尺度上的预报技巧来看,有、无海洋初始同化对预测结果影响不大,高预测技巧区主要分布在南半球印度洋中高纬度、热带西太平洋以及热带大西洋区域。(4)SST变化与下垫面热通量密切相关,在热带和副热带海洋区域,长波辐射和感热通量是影响10年时间尺度SST变化较大的物理量,在中高纬度海洋,洋面温度变化主要受潜热通量的影响相对较大。

References

[1]  Branstator G, Teng H Y. 2010. Two limits of initial-value decadal predictability in a CGCM [J]. J. Climate, 23 (23): 6292-6311.
[2]  Brohan P, Kennedy J J, Harris I, et al. 2006. Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850 [J]. J. Geophys. Res., 111: D12106.
[3]  Carton J A, Giese B S, Grodsky S A. 2005. Sea level rise and the warming of the oceans in the Simple Ocean Data Assimilation (SODA) ocean reanalysis [J]. J. Geophys. Res., 110: C09006.
[4]  Carton J A, Giese B S. 2008. A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA) [J]. Mon. Wea. Rev., 136 (8): 2999-3017
[5]  Chen H M, Yu R C, Li J, et al. 2011. The coherent interdecadal changes of East Asia climate in mid-summer simulated by BCC_AGCM 2.0.1[J]. Climate Dyn., doi: 10.1007/s00382-011-1154-6 (published online first).
[6]  董敏, 吴统文, 王在志, 等. 2009. 北京气候中心大气环流模式对季节内振荡的模拟 [J]. 气象学报, 67 (6): 912-922. Dong Min, Wu Tongwen, Wang Zaizhi, et al. 2009. Simulations of the tropical intraseasonal oscillation by the atmospheric general circulation model of the Beijing Climate Center [J]. Acta Meteorologica Sinica (in Chinese), 67 (6): 912-922.
[7]  郭准, 吴春强, 周天军, 等. 2011. LASG/IAP和BCC大气环流模式模拟的云辐射强迫之比较 [J]. 大气科学, 35 (4): 739-752. Guo Zhun, Wu Chunqiang, Zhou Tianjun, et al. 2011. A comparison of cloud radiative forcings simulated by LASG/IAP and BCC atmospheric general circulation models [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 35 (4): 739-752.
[8]  IPCC. 2007. Climate Change 2007: The Physical Science Basis [M]. Cambridge: Cambridge University Press.
[9]  Ji J J. 1995. A climate-vegetation interaction model: Simulating physical and biological processes at the surface [J]. Journal of Biogeography, 22 (2-3): 445-451.
[10]  Ji J J, Huang M, Li K R. 2008. Prediction of carbon exchanges between China terrestrial ecosystem and atmosphere in 21st century [J]. Science in China (Series D: Earth Sciences), 51 (6): 885-898.
[11]  颉卫华, 吴统文. 2010. 全球大气环流模式BCC_AGCM2.0.1对1998年夏季江淮流域强降水过程的回报试验研究 [J]. 大气科学, 34 (5): 962-978. Jie Weihua, Wu Tongwen. 2010. Hindcast for the 1998 summer heavy precipitation in the Yangtze and Huaihe River valley using BCC_AGCM2.0.1 model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 34 (5): 962-978.
[12]  Keenlyside N S, Latif M, Jungclaus J, et al. 2008. Advancing decadal-scale climate prediction in the North Atlantic sector[J]. Nature, 453 (7191): 84-88.
[13]  Latif M, Collins M, Pohlmann H, et al. 2006. A review of predictability studies of Atlantic sector climate on decadal time scales [J]. J. Climate, 19 (23): 5971-5987.
[14]  Pohlmann H, Jungclaus J H, K?hl A, et al. 2009. Initializing decadal climate predictions with the GECCO oceanic synthesis: Effects on the North Atlantic [J]. J. Climate, 22 (14): 3926-3938.
[15]  Rayner N A, Brohan P, Parker D E, et al. 2006. Improved analyses of changes and uncertainties in sea surface temperature measured in situ since the mid-nineteenth century: The HadSST2 dataset [J]. J. Climate, 19: 446-469.
[16]  Smith D M, Cusack S, Colman A W, et al. 2007. Improved surface temperature prediction for the coming decade from a global climate model [J]. Science, 317 (5839): 796-799.
[17]  Smith D M, Eade R, Dunstone N J, et al. 2010. Skilful multi-year predictions of Atlantic hurricane frequency [J]. Nature Geoscience, 3 (12): 846-849.
[18]  Taylor K E, Stouffer R J, Meehl G A. 2012. An overview of CMIP5 and the experiment design [J]. Bull. Amer. Meteor. Soc., 93 (4): 485-498.
[19]  Troccoli A, Palmer T N. 2007. Ensemble decadal predictions from analysed initial conditions [J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365 (1857): 2179- 2191.
[20]  王璐, 周天军, 吴统文, 等. 2009. BCC大气环流模式对亚澳季风年际变率主导模态的模拟[J]. 气象学报, 67(6): 973-982. Wang Lu, Zhou Tianjun, Wu Tongwen, et al. 2009. Simulation of the leading mode of Asian-Australian monsoon interannual cariability with the Beijing Climate Center atmospheric general circulation model [J]. Acta Meteorologica Sinica (in Chinese), 67 (6): 973-982.
[21]  Wu T W, Yu R C, Zhang F. 2008. A modified dynamic framework for the atmospheric spectral model and its application [J]. J. Atmos. Sci., 65 (7): 2235-2253.
[22]  Wu T W, Yu R C, Zhang F, et al. 2010. The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate [J]. Climate Dyn., 34 (1): 123-147.
[23]  Wu T W. 2012. A mass-flux cumulus parameterization scheme for large-scale models: Description and test with observations [J]. Climate Dyn., 38 (3-4): 725-744.
[24]  Zhou T J, Yu R C. 2006. Twentieth-century surface air temperature over China and the globe simulated by coupled climate models [J]. J. Climate, 19 (22): 5843-5858.

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