Please wait a minute...
img img
地球科学进展  2017, Vol. 32 Issue (4): 331-341    DOI: 10.11867/j.issn.1001-8166.2017.04.0331
周天军1, 2, 吴波1
1.中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京 100029;
2.中国科学院大学,北京 100049
Decadal Climate Prediction: Scientific Frontier and Challenge
Zhou Tianjun1, 2, Wu Bo1
1. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China
 全文: PDF(945 KB)   HTML


关键词: 初始化年代际外强迫耦合模式    

The prediction of climate change in the future 10~30 year is a hot research area of the international community of the climate science, which has been listed as a core content of the Coupled Model Intercomparison Project (CMIP) and some other important international scientific projects. The forecast object of the decadal climate prediction has been extended from averaged state over the future 10~30 years to temporal evolutions in future 1~10 or 30 years. Recently, the World Meteorological Organization (WMO) has been preparing to issue climate states in the near future based on decadal climate prediction systems. Focusing on the cut-edging and challenging scientific questions of the decadal climate prediction, we reviewed the theoretic basis of the predictability of the decadal climate and recent progresses of the practical decadal prediction experiments by international modelling centers in the paper. Finally, we summarized the core scientific questions to be solved in the area and discuss ed possible pathways to improve the skills of the decadal climate prediction.

Key words: Decadal variability    External forcing    Coupled model.    Initialization
收稿日期: 2016-11-22 出版日期: 2017-04-20
ZTFLH:  P467  

公益性行业(气象)科研专项项目“基于FGOALS-s、CMA和CESM气候系统模式的年代际集合预测系统的建设与研究”(编号:GYHY201506012); 国家自然科学基金项目“20世纪全球季风变化模拟和未来变化预估”(编号:41330423)资助

作者简介: 周天军(1969-),男,山东龙口人,研究员,主要从事气候模拟、海气相互作用和东亚气候研究
E-mail Alert


周天军, 吴波. 年代际气候预测问题:科学前沿与挑战[J]. 地球科学进展, 2017, 32(4): 331-341.

Zhou Tianjun, Wu Bo. Decadal Climate Prediction: Scientific Frontier and Challenge. Advances in Earth Science, 2017, 32(4): 331-341.


[1] Meehl G A, Goddard L, Murphy J, et al . Decadal prediction: Can it be skilful?[J]. Bulletin of the American Meteorological Society ,2009,90:(10)1 467-1 485,doi:10.1175/2009BAMS2778.1.
[2] Hurrell J, Meehl G A, Bader D, et al . A unified modeling approach to climate system prediction[J]. Bulletin of the American Meteorological Society , 2009, 90(12):1 819-1 832.
[3] Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society , 2011, 93(4):485-498.
[4] Boer G J, Smith D M, Cassou C, et al . The Decadal Climate Prediction Project (DCPP) contribution to CMIP6[J]. Geoscientific Model Development ,2016,9(10): 3 751-3 777, doi:10.5194/gmd-9-3751-2016.
[5] Bellucci A, Haarsma R, Gualdi S, et al . An assessment of a multi-model ensemble of decadal climate predictions[J]. Climate Dynamics , 2014, 44(9/10):1-20.
[6] Lee T C K, Zwiers F W, Zhang X, et al . Evidence of decadal climate prediction skill resulting from changes in anthropogenic forcing[J]. Journal of Climate , 2010, 19(20):5 305-5 318.
[7] Meehl G A, Washington W M, Collins W D, et al . How much more global warming and sea level rise?[J]. Science , 2005, 307(5 716):1 769-1 772.
[8] Meehl G A, Stocker T F, Collins W D. Contribution of working group I to the fourth assessment report[C]∥Climate Change 2007: of the Intergovernmental Panel on Climate Change.2013.
[9] Smith D, Eade R, Pohlmann H. A comparison of full-field and anomaly initialization for seasonal to decadal climate prediction[J]. Climate Dynamics , 2013, 41(11/12):3 325-3 338.
[10] Bellucci A, Haarsma R, Bellouin N, et al . Advancements in decadal climate predictability: The role of nonoceanic drivers[J]. Reviews of Geophysics , 2015, 53(2):165-202.
[11] Khodayar S, Sehlinger A, Feldmann H, et al . Sensitivity of soil moisture initialization for decadal predictions under different regional climatic conditions in Europe[J]. International Journal of Climatology , 2015, 35(8):1 899-1 915.
[12] Corti S, Palmer T, Balmaseda M, et al . Impact of initial conditions versus external forcing in decadal climate predictions: A sensitivity experiment[J]. Journal of Climate , 2015, 28(11):63-65.
[13] Smith D M, Cusack S, Colman A W, et al . Improved surface temperature prediction for the coming decade from a global climate model[J]. Science , 2007, 317(5 839):796-799.
[14] Keenlyside N, Latif M, Jungclaus J, et al . Advancing decadal-scale climate prediction in the North Atlantic sector[J]. Nature , 2008, 453(7 191):84-88.
[15] Sugiura N, Awaji T, Masuda S, et al . Potential for decadal predictability in the North Pacific region[J]. Geophysical Research Letters ,2009,36(20),doi:10.1029/2009GL039787.
[16] Mochizuki T, Wallace J M. Pacific decadal oscillation hindcasts relevant to near-term climate prediction[J]. Proceedings of the National Academy of Sciences of the United States of America , 2010, 107(5):1 833-1 837.
[17] Wang B, Liu M, Yu Y, et al . Preliminary evaluations of FGOALS-g2 for decadal predictions[J]. Advances in Atmospheric Sciences , 2013, 30(3):674-683.
[18] Wu B, Chen X, Song F, et al . Decadal predictions by a coupled global climate model FGOALS-s2[J]. Advances in Meteorology , 2015, (6):1-12, doi:10.1155/2015/904826.
[19] Gao Feng, Xin Xiaoge, Wu Tongwen. A study of the prediction of regional and global temperature on decadal time scale with BCC_CSM1.1 Model[J]. Chinese Jouranl of Atmospheric Sciences , 2012, 36(6):1 165-1 179.[高峰,辛晓歌,吴统文. BCC_CSM1.1对10年尺度全球及区域温度的预测研究[J]. 大气科学, 2012, 36(6):1 165-1 179.]
[20] Wei Linxiao, Xin Xiaoge, Cheng Bingyan, et al . Hindcast of china climate with decadal experiment by BCC_CSM1.1 climate model[J]. Advances in Climate Change Research , 2016, 12(4): 294-302.
. 气候变化研究进展, 2016, 12(4): 294-302.]
[21] Meehl G A, Goddard L, Boer G, et al . Decadal climate prediction: An update from the trenches[J]. Bulletin of the American Meteorological Society , 2014, 95(2):243-267.
[22] Doblas-Reyes F J, Andreuburillo I, Chikamoto Y, et al . Initialized near-term regional climate change prediction[J]. Nature Communications , 2013, 4(7):1 078-1 090.
[23] García-Serrano J, Guemas V,Doblas-Reyes F J. Added-value from initialization in predictions of Atlantic multi-decadal variability[J]. Climate Dynamics , 2015, 44(9/10):2 539-2 555.
[24] Guemas V, Corti S, García-Serrano J, et al . The Indian Ocean: The region of highest skill worldwide in decadal climate prediction[J]. Journal of Climate ,2013, 26(3):726-739.
[25] Dong L, Zhou T. The Indian Ocean sea surface temperature warming simulated by CMIP5 Models during the 20th Century: Competing forcing roles of GHGs and anthropogenic aerosols[J]. Journal of Climate , 2014, 27(9):3 348-3 362,doi:10.1175/JCLI-D-13-00396.1.
[26] Dong Lu, Zhou Tianjun,Wu Bo. Indian Ocean warming during 1958-2004 simulated by a climate system model and its mechanism[J]. Climate Dynamics ,2014, 42(1/2): 203-217, doi:10.1007/s00382-013-1722-z.
[27] Dong L, Zhou T, Dai A, et al . The footprint of the inter-decadal Pacific oscillation in Indian Ocean sea surface temperatures[J]. Scientific Reports , 2016, 6, doi:10.1038/srep21251.
[28] Zhou T, Yu R, Li H, et al . Ocean forcing to changes in global monsoon precipitation over the recent half-century[J]. Journal of Climate , 2008, 21(15):3 833-3 852.
[29] Li H, Dai A, Zhou T, et al . Responses of East Asian summer monsoon to historical SST and atmospheric forcing during 1950-2000[J]. Climate Dynamics , 2010, 34(4):501-514.
[30] Zhou T, Song F, Lin R, et al . The 2012 North China floods: Explaining an extreme rainfall event in the context of a long-term drying tendency[J]. Bulletin of the American Meteorological Society , 2013, 94(9):S49-S50.
[31] Qian C, Zhou T. Multidecadal variability of North China aridity and its relationship to PDO during 1900-2010[J]. Journal of Climate , 2014, 27(3):1 210-1 222.
[32] Wu B, Zhou T, Li T. Impacts of the Pacific-Japan and circumglobal teleconnection patterns on the interdecadal variability of the East Asian summer monsoon[J]. Journal of Climate , 2016, 2(9):3 253-3 271.
[33] Lienert F, Doblas-Reyes F J. Decadal prediction of interannual tropical and North Pacific sea surface temperature[J]. Journal of Geophysical Research Atmospheres , 2013, 118(12):5 913-5 922.
[34] Kim H M, Ham Y G, Scaife A A. Improvement of initialized decadal predictions over the north pacific ocean by systematic anomaly pattern correction[J]. Journal of Climate , 2014, 27(13):5 148-5 162.
[35] Gaetani M, Mohino E. Decadal prediction of the sahelian precipitation in CMIP5 simulations[J]. Journal of Climate , 2013, 26(19):7 708-7 719.
[36] Zhang Lixia, Zhang Wenxia, Zhou Tianjun, et al . Assessment of the decadal prediction skill on global land summer monsoon precipitation in the coupled models of ENSEMBLES[J]. Advances in Earth Science , 2017,32(4):409-419.
. 地球科学进展,2017,32(4):409-419.]
[37] Choi J, Son S, Seo K, et al . Potential for long-lead prediction of the western North Pacific monsoon circulation beyond seasonal time scales[J]. Geophysical Research Letters , 2016, 43(4),doi:10.1002/2016GL067902.
[38] Vecchi G A, Msadek R, Anderson W, et al . Multiyear predictions of north Atlantic hurricane frequency: Promise and limitations[J]. Journal of Climate , 2013, 26(15):5 337-5 357.
[39] Caron L P, Jones C G, Doblas-Reyes F. Multi-year prediction skill of Atlantic hurricane activity in CMIP5 decadal hindcasts[J]. Climate Dynamics , 2013, 42(9/10):2 675-2 690.
[40] Knight J R, Andrews M B, Smith D M, et al . Predictions of climate several years ahead using an improved decadal prediction system[J]. Journal of Climate , 2014, 27(20):7 550-7 567.
[41] Wu Bo, Zhou Tianjun, Sun Qian. Impacts of initialization schemes of oceanic states on the predictive skills of the IAP neat-term climate prediction system[J]. Advances in Earth Science , 2017, 32(4):342-352.
. 地球科学进展, 2017, 32(4):342-352.]
[42] Karspeck A, Yeager S, Danabasoglu G, et al . An evaluation of experimental decadal predictions using CCSM4[J]. Climate Dynamics , 2014, 44(3/4):907-923.
[43] Robson J, Sutton R, Smith D. Decadal predictions of the cooling and freshening of the North Atlantic in the 1960s and the role of ocean circulation[J]. Climate Dynamics , 2014, 42(9/10):1-13.
[44] Guemas V, Doblas F J. Retrospective prediction of the global warming slowdown in the past decade[J]. Nature Climate Change , 2013, 3(7):649-653.
[45] Wu Bo, Zhou Tianjun. Decadal evolution of the sea surface temperature predicted by IAP/LASG climate system model FGOALS-gl[J]. Chinese Science Bulletin , 2012, 57(13):1 168-1 175.
. 科学通报, 2012, 57(13):1 168-1 175.]
[46] Yang X, Rosati A, Zhang S, et al . A predictable AMO-like pattern in the GFDL fully coupled ensemble initialization and decadal forecasting system[J]. Journal of Climate , 2013, 26(2):650-661.
[47] Counillon F, Bethke I, Keenlyside N, et al . Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: A twin experiment[J]. Tellus , 2014, 66(1):159-163.
[48] Man W, Zhou T, Jungclaus J H. Effects of large volcanic eruptions on global summer climate and east asian monsoon changes during the last millennium: Analysis of MPI-ESM simulations[J]. Journal of Climate , 2014, 27: 7 394-7 409.
[49] Man W M, Zhou T J. Regional-scale surface air temperature and East Asian summer monsoon changes during the last millennium simulated by the FGOALS-gl climate system model[J]. Advances in Atmospheric Sciences , 2014, 31(4): 765-778.
[50] Man Wenmin, Zhou Tianjun,Jungclaus J H. Simulation of the East Asian Summer Monsoon during the Last Millennium with the MPI Earth System Model[J]. Journal of Climate , 2012,25(22): 7 852-7 866.
[51] Meehl G A, Hu A X, Tebaldi C. Decadal prediction in the Pacific region[J]. Journal of Climate , 2010, 23(11):2 959-2 973.
[52] Fu C B, Qian C, Wu Z H. Projection of global mean surface air temperature changes in next 40 years: Uncertainties of climate models and an alternative approach[J]. Science in China ( Series D ), 2011, 54: 1 400-1 406.
[53] Qi Yajie, Qian Cheng, Yan Zhongwei. An alternative multi-model ensemble mean approach for near-term projection[J]. International Journal of Climatology , 2016, doi:10.1002/joc.4690.
[54] Wei Meng, Qiao Fangli, Deng Jia. A quantitative definition of global warming Hiatus and 50-year prediction of global-mean surface temperature[J]. Journal of the Atmospheric Sciences , 2015, 72(8):3 281-3 289.
[55] Wu Kaijun, Qian Weihong. Secular non-linear trends and multi-timescale oscillations of regional surface air temperature in Eastern China[J]. Climate Research , 2015, 63(1):19-30.
[56] Li Hongmei, Ilyina T, Müller W A, et al . Decadal predictions of the North Atlantic CO 2 uptake[J]. Nature Communication , 2016, doi:10.1038/ncomms11076.
[57] Han Zhenyu, Wu Bo, Xin Xiaoge. Decadal prediction skill of the global sea surface temperature in the BCC_CSM1.1 climate model[J]. Advances in Earth Science ,2017, 32(4):394-405.
. 地球科学进展, 2017,32(4): 394-405.]
[58] Man Wenmin,Zhou Tianjun. The impact of volcanic eruption on decadal-scale climate prediction skill of Paciflc Sea surface temperatures in the IAP decadal climate prediction system[J]. Advances in Earth Science ,2017, 32(4):352-360.
. 地球科学进展, 2017,32(4): 352-360.]
[59] Chen Xiaolong, Wu Bo, Zhou Tianjun. Interdecadal change of telation between East Asian summer monsoon and ENSO in previous winter in an ocean assimilation dystem based on FGOALS-s2[J]. Advances in Earth Science ,2017, 32(4):362-372.
.地球科学进展,2017, 32(4):362-372.]
[60] Guo Zhun, Zhou Tianjun. The simulation of stratocumulus and its impacts on SST: Based on the IAP near-term climate prediction system[J]. Advances in Earth Science ,2017, 32(4):373-381.
.地球科学进展,2017, 32(4): 373-381.]
[61] Kirtman B, Power S B. Near-term climate change: Projections and predictability[M]∥Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate.Cambridge, UK:Cambridge University Press, 2013.

[1] 安俊岭, 陈勇, 屈玉, 陈琦, 庄炳亮, 张平文, 吴其重, 徐勤武, 曹乐, 姜海梅, 陈学舜, 郑捷. 全耦合空气质量预报模式系统[J]. 地球科学进展, 2018, 33(5): 445-454.
[2] 张丽霞, 张文霞, 周天军, 吴波. ENSEMBLES耦合模式对全球陆地季风区夏季降水的年代际预测能力评估[J]. 地球科学进展, 2017, 32(4): 409-419.
[3] 郭准, 周天军. IAP近期际气候预测系统海洋初始化试验中海表温度和层积云的关系[J]. 地球科学进展, 2017, 32(4): 373-381.
[4] 吴波, 周天军, 孙倩. 海洋模式初始化同化方案对IAP近期气候预测系统回报试验技巧的影响[J]. 地球科学进展, 2017, 32(4): 342-352.
[5] 韩振宇, 吴波, 辛晓歌. BCC_CSM1.1气候模式对全球海表温度年代际变化的回报能力评估[J]. 地球科学进展, 2017, 32(4): 396-408.
[6] 容新尧, 刘征宇, 段晚锁. 耦合模式中北太平洋和北大西洋海表面温度年代际可预报性和预报技巧的季节依赖性[J]. 地球科学进展, 2017, 32(4): 382-395.
[7] 陈晓龙, 吴波, 周天军. FGOALS-s2海洋同化系统中东亚夏季风和前冬厄尔尼诺—南方涛动关系的年代际变化[J]. 地球科学进展, 2017, 32(4): 362-372.
[8] 满文敏, 周天军. IAP年代际预测试验中火山活动对太平洋海温预测技巧的影响[J]. 地球科学进展, 2017, 32(4): 353-361.
[9] 叶晓燕, 陈崇成, 罗明. 东亚夏季降水与全球海温异常的年代际变化关系[J]. 地球科学进展, 2016, 31(9): 984-994.
[10] 林霄沛, 许丽晓, 李建平, 罗德海, 刘海龙. 全球变暖“停滞”现象辨识与机理研究[J]. 地球科学进展, 2016, 31(10): 995-1000.
[11] 孙炜毅, 刘健, 王志远. 过去2000年东亚夏季风降水百年际变化特征及成因的模拟研究[J]. 地球科学进展, 2015, 30(7): 780-790.
[12] 陈幸荣, 蔡怡, 谭晶, 黄勇勇, 汪雷. 全球变暖hiatus现象的研究进展[J]. 地球科学进展, 2014, 29(8): 947-955.
[13] 邹立维,周天军. 区域海气耦合模式研究进展[J]. 地球科学进展, 2012, 27(8): 857-865.
[14] 王万里, 王颢樾, 谢应齐, 王卫国,王祖武, 王凯,杜良敏,邓南圣,蔡述明,刘耀林. 夏季东亚大槽和副热带高压年代际变化的分析[J]. 地球科学进展, 2012, 27(3): 304-320.
[15] 林祥,钱维宏. 全球季风和季风边缘研究[J]. 地球科学进展, 2012, 27(1): 26-34.