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海洋气候变化预估及研究方法综述
作者:何越1 2  蔡怡2 3  陈幸荣2  王海燕2 
单位:1. 厦门大学海洋与地球学院, 福建 厦门 361005;
2. 国家海洋环境预报中心, 北京 100081;
3. 国家海洋局海洋灾害预报技术研究重点实验室, 北京 100081
关键词:海洋气候变化预估 气候模式 多模式集合 动力降尺度 
分类号:P732.5
出版年·卷·期(页码):2017··第六期(89-98)
摘要:
概述了目前预估的未来海洋气候变化状态,总结了在气候变化预估中常用的气候模式,包括简单概念性气候模式、中等复杂程度气候模式、气候系统模式和地球系统模式,介绍了海洋气候变化预估的多模式集合法和动力降尺度法。指出当前对一些对气候变化影响较大的区域海洋和气候系统自然变率的模拟预估研究还存在很多不足之处。高分辨率气候系统模式和基于多模式集合的概率预估可以在一定程度上减少海洋气候变化预估的不确定性,高分辨率气候模式的研发和概率预估的应用是当前的两个主要发展趋势。
The projection of the main ocean climate changes in the future are generalized. The major climate models used to simulate the ocean climate are summarized, including Simple Conceptual Climate Models (SCMs), Earth System Models of Intermediate Complexity(EMICs), General Circulation Models(GCMs) and Earth System Models(ESMs). The methods of multi-model ensemble and dynamical down-scaling in the ocean climate change projection are introduced. The paper points out some proposals on the projection of ocean climate change research. The projection of some regional oceans and climate system natural variabilities which have great values to the climate change is still under a low level. High-resolution climate system models and probabilistic prediction can efficiently reduce the projection uncertainty. The research and development of high-resolution climate models and application of probabilistic prediction are the two main study direction.
参考文献:
[1] 陈宜瑜. 全球变化与社会可持续发展[J]. 地球科学进展, 2003, 18(1):1-3.
[2] 徐冠华, 葛全胜, 宫鹏, 等. 全球变化和人类可持续发展:挑战与对策[J]. 科学通报, 2013, 58(21):2100-2106.
[3] IPCC. Climate Change 2013:The physical science basis. contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change[M]. Cambridge:Cambridge University Press, 2013.
[4] Stewart R V V. Ocean and climate[J]. Impact of Science on Society, 1990, 166:47-53.
[5] Moss R H, Edmonds J A, Hibbard K A, et al. The next generation of scenarios for climate change research and assessment[J]. Nature, 2010, 463(7282):747-756.
[6] Pörtner H O, Karl D M, Boyd P W, et al. Climate change 2013:Ocean systems[M]//Intergovernmental Panel on Climate Change, Working Group I Contribution to the IPCC Fifth Assessment Report (AR5). New York:Cambridge University Press, 2013.
[7] Guldberg O H, Cai R, et al. Climate change 2013:the ocean[C]//Intergovernmental Panel on Climate Change. Working Group I Contribution to the IPCC Fifth Assessment Report (AR5). New York:Cambridge University Press, 2013.
[8] Burkett V, Suarez A G, Bindi M, et al. Climate change 2013:point of departure[C]//Intergovernmental Panel on Climate Change. Working Group I Contribution to the IPCC Fifth Assessment Report (AR5). New York:Cambridge University Press, 2013.
[9] Wong P P, Losada I J, et al. Climate change 2013:coastal systems and low-lying areas[C]//Intergovernmental Panel on Climate Change. Working Group I Contribution to the IPCC Fifth Assessment Report (AR5). New York:Cambridge University Press, 2013.
[10] Matear R J, Chamberlain M A, Sun C, et al. Climate change projection of the Tasman Sea from an eddy-resolving ocean model[J]. Journal of Geophysical Research:Oceans, 2013, 118(6):2961-2976.
[11] Yu X L, Wang F, Tang X H. Future projection of East China Sea temperature by dynamic downscaling of the IPCC_AR4 CCSM3 model result[J]. Chinese Journal of Oceanology and Limnology, 2012, 30(5):826-842.
[12] Liu Y Y, Lee S K, Enfield D B, et al. Potential impact of climate change on the Intra-Americas Sea:Part-1. A dynamic downscaling of the CMIP5 model projections[J]. Journal of Marine Systems, 2015, 148:56-69.
[13] Nurse L A, Charlery J L. Projected SST trends across the Caribbean Sea based on PRECIS downscaling of ECHAM4, under the SRES A2 and B2 scenarios[J]. Theoretical and Applied Climatology, 2016, 123(1-2):199-215.
[14] Sun C J, Feng M, Matear R J, et al. Marine downscaling of a future climate scenario for Australian boundary currents[J]. Journal of Climate, 2012, 25(8):2947-2962.
[15] Seo G H, Cho Y K, Choi B J, et al. Climate change projection in the Northwest Pacific marginal seas through dynamic downscaling[J]. Journal of Geophysical Research:Oceans, 2014, 119(6):3497-3516.
[16] 宋春阳, 张守文, 姜华, 等. CMIP5模式对中国近海海表温度的模拟及预估[J]. 海洋学报, 2016, 38(10):1-11.
[17] 黄传江, 乔方利, 宋亚娟, 等. CMIP5模式对南海SST的模拟和预估[J]. 海洋学报, 2014, 36(1):38-47.
[18] 王斌, 周天军, 俞永强, 等. 地球系统模式发展展望[J]. 气象学报, 2008, 66(6):857-869.
[19] 张冉, 李力, 郭庆春, 等. 古气候研究中气候模式的发展与应用[J]. 干旱区研究, 2007, 24(5):704-711.
[20] 王勇, 刘苏峡, 邵亚平, 等. 简单地球模型的研究进展[J]. 气象科技进展, 2014, 4(3):26-31.
[21] Gallée H, Van Ypersele J P, Fichefet T, et al. Simulation of the last glacial cycle by a coupled, sectorially averaged climate-ice sheet model:1. The climate model[J]. Journal of Geophysical Research, 1991, 96(D7):13139-13161.
[22] Ganopolski A, Petoukhov V, Rahmstorf S, et al. CLIMBER-2:a climate system model of intermediate complexity. Part I:model description and performance for present climate[J]. Climate Dynamics, 2000, 16:1-17.
[23] Fraedrich K, Jansen H, Kirk E, et al. The planet simulator:green planet and desert world[J]. Meteorologische Zeitschrift, 2005, 14(3):305-314.
[24] Fraedrich K, Jansen H, Kirk E, et al. The planet simulator:towards a user friendly model[J]. Meteorologische Zeitschrift, 2005, 14(3):299-304.
[25] IPCC. IPCC fourth assessment report (AR4). Climate change 2007:the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change[M]. Cambridge:Cambridge University Press, 2007.
[26] Haltiner G J, Williams R T. Numerical prediction and dynamic meteorology[M]. 2nd ed. New York:John Wiley & Sons, 1980.
[27] Hansen J, Russell G, Rind D, et al. Efficient three-dimensional global models for climate studies:models I and Ⅱ[J]. Monthly Weather Review, 1983, 111(4):609-662.
[28] 罗勇, 王绍武, 党鸿雁, 等. 近20年来气候模式的发展与模式比较计划[J]. 地球科学进展, 2002, 17(3):372-377.
[29] 周天军, 邹立维, 吴波, 等. 中国地球气候系统模式研究进展:CMIP计划实施近20年回顾[J]. 气象学报, 2014, 72(5):892-907.
[30] Wang Y Q, Leung L R, McGregor J L, et al. Regional climate modeling:progress, challenges, and prospects[J]. Journal of the Meteorological Society of Japan, 2004, 82(6):1599-1628.
[31] 陆其峰, 潘晓玲, 钟科, 等. 区域气候模式研究进展[J]. 南京气象学院学报, 2003, 26(4):557-565.
[32] 彭世球, 刘段灵, 孙照渤, 等. 区域海气耦合模式研究进展[J]. 中国科学:地球科学, 2012, 42(9):1301-1316.
[33] Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society, 2012, 93(4):485-498.
[34] Anav A, Friedlingstein P, Kidston M, et al. Evaluating the land and ocean components of the global carbon cycle in the CMIP5 earth system models[J]. Journal of Climate, 2013, 26(18):6801-6843.
[35] Tebaldi C, Knutti R. The use of the multi-model ensemble in probabilistic climate projections[J]. Philosophical Transactions of the Royal Society A, Mathematical, Physical and Engineering Sciences, 2007, 365(1857):2053-2075.
[36] Van Oldenborgh G J, Doblas-Reyes F J, Wouters B, et al. Decadal prediction skill in a multi-model ensemble[J]. Climate Dynamics, 2012, 38(7-8):1263-1280.
[37] Randall D, Khairoutdinov M, Arakawa A, et al. Breaking the cloud parameterization deadlock[J]. Bulletin of the American Meteorological Society, 2003, 84(11):1547-1564.
[38] Bony S, Dufresne J L. Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models[J]. Geophysical Research Letters, 2005, 32(20):L20806, doi:10.1029/2005gl023851.
[39] Min S K, Hense A. A Bayesian assessment of climate change using multimodel ensembles. Part Ⅱ:regional and seasonal mean surface temperatures[J]. Journal of Climate, 2007, 20(12):2769-2790.
[40] Duan Q Y, Ajami N K, Gao X G, et al. Multi-model ensemble hydrologic prediction using Bayesian model averaging[J]. Advances in Water Resources, 2007, 30(5):1371-1386.
[41] Palmer T N, Doblas-Reyes F J, Hagedorn R, et al. Probabilistic prediction of climate using multi-model ensembles:from basics to applications[J]. Philosophical Transactions of the Royal Society B:Biological Sciences, 2005, 360(1463):1991-1998.
[42] Arzhanov M M, Semenov V A, Mokhov I I, et al. Climate change projections in the Black Sea region based on CMIP5 model ensemble[J]. Research Activities in Atmospheric and Oceanic Modelling, 2013, 43(7):5-6.
[43] 赵宗慈, 罗勇, 黄建斌. 对地球系统模式评估方法的回顾[J]. 气候变化研究进展, 2013, 9(1):1-8.
[44] Robertson A. W, Lall U, Zebiak S E, et al. Improved combination of multiple atmospheric GCM ensembles for seasonal prediction[J]. Monthly Weather Review, 2004, 132(12):2732-2744.
[45] Semenov M A, Stratonovitch P. Use of multi-model ensembles from global climate models for assessment of climate change impacts[J]. Climate Research, 2010, 41(1):1-14.
[46] Räisänen J, Palmer T N. A probability and decision-model analysis of a multimodel ensemble of climate change simulations[J]. Journal of Climate, 2001, 14(15):3212-3226.
[47] Cohen S J. Bringing the global warming issue closer to home:the challenge of regional impact studies[J]. Bulletin of the American Meteorological Society, 1990, 71(4):520-526.
[48] Wilby R L, Charles S P, Zorita E, et al. Guidelines for use of climate scenarios developed from statistical downscaling methods[EB/OL]. IPCC Publications, 2004, http://www.ipccdata.org/guidelines/dgm_no2_v1_09_2004.pdf.
[49] Ådlandsvik B, Bentsen M. Downscaling a twentieth century global climate simulation to the North Sea[J]. Ocean Dynamics, 2007, 57(4-5):453-466.
[50] Ådlandsvik B. Marine downscaling of a future climate scenario for the North Sea[J]. Tellus A, 2008, 60(3):451-458.
[51] Meier H E M. Baltic Sea climate in the late twenty-first century:a dynamical downscaling approach using two global models and two emission scenarios[J]. Climate Dynamics, 2006, 27(1):39-68.
[52] Xue Y K, Janjic Z, Dudhia J, et al. A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability[J]. Atmospheric Research, 2014, 147-148:68-85, doi:10.1016/j. atmosres.2014.05.001.
[53] Meehl G A, Arblaster J M, Fasullo J T, et al. Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods[J]. Nature Climate Change, 2011, 1(7):360-364.
[54] 宇如聪. 高分辨率气候系统模式的研制与评估[J]. 中国基础科学·研究进展, 2015, (2):27-37, doi:10.3969/j.issn.1009-2412. 2015.02.005.
[55] 栾贻花, 俞永强, 郑伟鹏. 全球高分辨率气候系统模式研究进展[J]. 地球科学进展, 2016, 31(3):258-268.
[56] Bennartz R, Lauer A, Brenguier J L. Scale-aware integral constraints on autoconversion and accretion in regional and global climate models[J]. Geophysical Research Letters, 2011, 38(10):L10809, doi:10.1029/2011GL047618.
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