温室气体强迫与东亚亚热带季风演变耦合效应及动力机制研究

doi:10.13249/j.cnki.sgs.2018.01.0017

地理科学 ›› 2018, Vol. 38 ›› Issue (1): 151-160.doi: 10.13249/j.cnki.sgs.2018.01.0017

• • 上一篇

温室气体强迫与东亚亚热带季风演变耦合效应及动力机制研究

侯立春^1,^2,^3,^4,⁵(), 林振山^1,^3,^4,⁵(), 何亮⁶

1.南京师范大学地理科学学院环境与生态建模研究室,江苏南京210023
2.江西上饶师范学院历史地理与旅游学院,江西上饶 334001
3.南京师范大学虚拟地理环境教育部重点实验室,江苏南京210023
4.江苏省地理环境演化国家重点实验室培育建设点,江苏南京210023
5.江苏省地理信息资源开发与利用协同创新中心,江苏南京210023
6.国家气象中心, 北京100081

收稿日期:2017-01-04 修回日期:2017-04-02 出版日期:2018-01-10 发布日期:2018-01-10
作者简介:
作者简介：侯立春（1965-）,男,江苏新沂人,副教授,博士研究生,主要从事地学建模与气候变化模拟及机制方向研究。 E-mail：houlchjs@163.com
基金资助:
国家自然科学基金项目（41173093,31470519）、江苏省自然科学基金项目（BK20131399)、江苏省高校优势学科建设工程资助项目资助

Coupling Effect and Dynamic Mechanism of Greenhouse Gas Forcing and East Asian Subtropical Monsoon Evolution

Lichun Hou^1,^2,^3,^4,⁵(), Zhenshan Lin^1,^3,^4,⁵(), Liang He⁶

1.College of Geographical Science, Nanjing Normal University, Nanjing 210023, Jiangsu, China
2.School of History Geography and Tourism, Shangrao Normal Universityt, Shangrao 334000, Jiangxi,China
3.Key Laboratory of Virtual Geographic Environment Ministry of Education, Nanjing Normal University, Nanjing 210023, Jiangsu, China
4.State Key Laboratory Cultivation Base of Geographical Environment Evolution Jiangsu Province, Nanjing 210023, Jiangsu, China
5.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, Jiangsu, China
6.National Meteorological Center, Beijing 100081, China

Received:2017-01-04 Revised:2017-04-02 Online:2018-01-10 Published:2018-01-10
Supported by:
National Natural Science Foundation of China (41173093,31470519), Natural Science Foundation of Jiangsu Province (BK20131399), the Priority Academic Program of Jiangsu Higher Education Institutions

摘要/Abstract

摘要：

基于主要温室气体（CO₂、CH₄和N₂O）强迫因子和石笋δ¹⁸О观测资料（1~2002 年）,分别利用关联性耦合模型和非线性统计-动力学方法,分析温室气体强迫与东亚亚热带季风演变耦合度的时序规律和定量反演模拟温室气体强迫对近2 000 a东亚亚热带季风演变影响的非线性趋势和相对贡献。研究发现：① 温室气体与季风演变耦合度的高低对应季风的强弱变化,即两者耦合作用越强,东亚亚热带季风越强;反之,两者耦合强度越小,东亚亚热带季风越弱;耦合度峰谷值对应季风极强降水和极端干旱时段。② 时序演变规律为：N₂O和CO₂相互作用与季风演变间耦合效应最强,成为东亚亚热带季风演变的主要驱动力。其次,N₂O一次项和CO₂非线性项对季风演变起主要的负反馈调节机制。③ 时序演变阶段上有所不同：1~180年,CH₄因子对季风演变主要起负反馈调节机制;180~1760年和1760~2002年,对季风演变起主要的驱动和调节机制分别为CO₂因子和N₂O因子;但1900年后N₂O和CO₂相互作用与季风演变的耦合驱动效应近百年来明显增强,耦合度在中等-较强（或极强）之间来回波动转换,耦合作用明显增强,在耦合度由较强（或极强）转弱至中等时,东亚亚热带季风也随之减弱。

关键词: 温室气体, 东亚亚热带季风演变, 统计动力反演

Abstract:

Based on the observed data of the main greenhouse gases (CO₂, CH₄ and N₂O) and stalagmites δ¹⁸О (1-2002), the correlation coupling model was used to analyze the coupling degree temporal variation rule of greenhouse gas forcing and the East Asian monsoon,and the nonlinear statistical-dynamics method was used to simulate the nonlinear trend and relative contribution of greenhouse gas forcing to the East Asian subtropical monsoon evolution over the last two millenniums, which provide the new scientific insights for the assessment of East Asian monsoon evolution. The results show that: 1) The coupling degree of the greenhouse gas and the East Asian monsoon is corresponding to the intensity of the East Asian monsoon, i.e. the stronger the coupling effect is, the stronger the East Asian monsoon is; on the contrary, the weaker coupling strength is, the weaker East Asian monsoon is; the peak-valley value of coupling degree is correlated with extreme strong monsoon precipitation and extreme drought period. 2) The coupling effect betweenthe interaction of N₂O and CO₂ and the evolution of East Asian monsoon is the strongest, which is the main driving force of East Asian subtropical monsoon evolution. Additionally, N₂O and nonlinear term of CO₂plays the main negative feedback regulation mechanism for the monsoon evolution. 3) The temporal evolution phases are different: the CH₄ has a negative feedback regulation mechanism on the East Asian monsoon in 1-180. The CO₂ and N₂O play the main driving and regulating mechanism role in the monsoon evolution in 180-1760 and 1760-2002, respectively. But the coupled driving effect of N₂O and CO₂ interaction and monsoon evolution is evidently enhanced after 1900. The coupling degree fluctuates back and forth between medium and strong (or very strong), and the coupling effect is obviously enhanced. The East Asian monsoon also weakened when the coupling degree weakened from strong (or stronger) to moderate period.

Key words: greenhouse gases, East Asian subtropical monsoon evolution, statistical dynamic inversion

中图分类号:

P462

侯立春, 林振山, 何亮. 温室气体强迫与东亚亚热带季风演变耦合效应及动力机制研究[J]. 地理科学, 2018, 38(1): 151-160.

Lichun Hou, Zhenshan Lin, Liang He. Coupling Effect and Dynamic Mechanism of Greenhouse Gas Forcing and East Asian Subtropical Monsoon Evolution[J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(1): 151-160.

图/表 8

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参考文献 22

[1]	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.Cambridge and New York: Cambridge University Press,2013.
[2]	张华,张若玉,何金海,等. CH4和N2O的辐射强迫与全球增温潜能[J].大气科学,2013,37(3):745-754, doi:10.3878/j.issn.1006- doi: 10.3878/j.issn.1006-9895.2012.12013
	9895.2012.12013. doi: 10.3878/j.issn.1006-9895.2012.12013
	[Zhang Hua, Zhang Ruoyu,He Jinhaiet al.Radiative forcing and global warming potentials of CH4 and N2O. Chinese Journal of Atmospheric Sciences (in Chinese),2013, 37(3): 745-754.] doi: 10.3878/j.issn.1006-9895.2012.12013
[3]	高学杰,赵宗慈,丁一汇,等.温室效应引起的中国区域气候变化的数值模II:中国区域气候的可能变化[J]. 气象学报,2003,61(1):29-37. doi: 10.11676/qxxb2003.004
	[Gao Xuejie, Zhao Zongci,Ding Yihuiet al.Climate change due to greenhouse effects in China as simulated by a regional climate Model Part II : Climate Change.Acta Meteorologica Sinica,2003,61(1):29-37.] doi: 10.11676/qxxb2003.004
[4]	Feng L, Zhou T J,Wu Bet al.Projection of future precipitation change over China with a high-resolution global atmospheric model[J].Adv Atmos Sci,2010,28: 464-476. doi: 10.1007/s00376-010-0016-1
[5]	江志红, 陈威霖, 宋洁, 等. 7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估[J].大气科学,2009, 33(1): 109-120. doi: 10.3878/j.issn.1006-9895.2009.01.10
	[Jiang Zhihong,ChenWeilin,Song Jieet al.Projection and evaluation of the precipitation extremes indices over China based on Seven IPCC AR4 coupled climate models. Chinese Journal of Atmospheric Sciences,2009, 33(1): 109-120.] doi: 10.3878/j.issn.1006-9895.2009.01.10
[6]	Kikttev D,Caesar J,Alexander L Vet al. Comparison of observed and multi-modeled trends in annual extremes of temperature and precipitation[J]. Geophys Res Lett,2007,34, L10702, doi:10.1029/2007GL029539. doi: 10.1029/2007GL029539
[7]	赵天保, 李春香, 左志燕. 基于CMIP5 多模式评估人为和自然因素外强迫在中国区域气候变化中的相对贡献[J]. 中国科学: 地球科学,2016, 46(2): 237-252.
	[Zhao Tianbao, Li Chunxiang, Zuo Zhiyan.Contributions of anthropogenic and external natural forcings to climate changes over China based on CMIP5 model simulations. Sci China: Earth Sci,2016,46(2):237-252.]
[8]	《全球变化及其区域响应》科学指导与评估专家组. 深入探索全球变化机制——国家自然科学基金委重大研究计划的战略研究[J]. 中国科学: 地球科学,2012, 42(6): 795-804.
	[Scientific steering group of the major project “Global Change and Regional Response”. Exploring the mechanism of global change—Research strategy of major projects of the National Natural Science Foundation of China (in Chinese). Sci China:Earth Sci,2012,42(6): 795-804.]
[9]	汪永进,刘殿兵.亚洲古季风变率和机制的洞穴石笋档案[J].科学通报,2016, 61(9): 938-951.
	[Wang Yongjin, Liu Dianbing.Speleothem records of Asian paleomonsoon variability and mechanisms (in Chinese). Chin Sci Bull,2016,61(9): 938-951.]
[10]	Wang Y J, Cheng H,Edwards R Let al. A high-resolution absolute-dated Late Pleistocene monsoon record from Hulu cave, China[J].Science,2001,294:2345-2348. doi: 10.1126/science.1064618 pmid: 11743199
[11]	Wang Y J, Cheng H,Edwards R Let al. Millennial and orbital scale changes in the East Asian monsoon over the past 224000 years[J]. Nature,2008, 451:1090-1093. doi: 10.1038/nature06692 pmid: 18305541
[12]	Fleitmann D, Burns S J,Mudelsee Met al. Holocene Forcing of the Indian Monsoon Recorded in a Stalagmite from Southern Oman[J].Science,2003, 300(5626): 1737-1739. doi: 10.1126/science.1083130 pmid: 12805545
[13]	Hu C, Henderson G M,Huang Jet al. Quantification of Holocene Asian monsoon rainfall from spatially separated cave records[J]. Earth and Planetary Science Letters,2008, 266:221-232. doi: 10.1016/j.epsl.2007.10.015
[14]	MacFarlingMeure C, Etheridge D, Trudinger Cet al. The law dome CO2, CH4 and N2O ice core records extended to 2000 years BP[J]. Geophysical Research Letters,2006, 33(14), 70-84. doi: 10.1029/2006GL026152
[15]	邓聚龙.灰色系统基本方法[M].武汉:华中理工大学出版社,1987: 34-41.
	[Deng Julong.The basic methods of grey system theory. Wuhan:Huazhong University of Science and Technology Press, 1987: 34-41.]
[16]	刘耀彬,李仁东,宋学锋.中国区域城市化与生态环境耦合的关联分析[J]. 地理学报,2005,60(2):237-247.
	[Liu Yaobin, Li Rendong, Song Xuefeng.Grey associative analysis of regional urbanization and eco-environment coupling in China. Acta GeographicaSinica,2005, 60(2): 237-247.]
[17]	黄建平,衣育红.利用观测资料反演非线性动力模型[J].中国科学(B辑), 1991(3): 331-336.
	[Huang Jianping, Yi Yuhong.Nonlinear dynamic model inversion based on observation data. Science in China(Series B), 1991(3):331-336.]
[18]	林振山,史芳斌.天津局地气候的反演建模及其研究[J].气象学报,1995, 53(1):115-121. doi: 10.11676/qxxb1995.013
	[Lin Zhenshan, Shi Fangbin.The retrieved model of Tianjin local climate. Acta Meteorologica Sinica,1995, 53(1):115-121.] doi: 10.11676/qxxb1995.013
[19]	侯立春, 林振山, 何亮, 等.近千年东亚季风变化统计动力反演与驱动机制研究[J].气象学报,2017, 75(1):67-79.
	[Hou Lichun, Lin Zhenshan, He Liang et al.Statistical-dynamical retrieval and driving mechanism study of monsoon variation over East Asia in the last millennium.Acta Meteorologica Sinica,2017, 75(1): 67-79.]
[20]	李荣华, 冯果忱.微分方程的数值解法[M].北京:高等教育出版社, 1996: 54-62.
	[Li Ronghua, Feng Guochen.Numerical analysis of differential equations. Beijing: Higher Education Press, 1996: 54-62.]
[21]	Chappellaz J, Barnola J M,Raynaud Det al. Atmospheric CH4 record over the last climatic cycle revealed by the Vostok ice core[J]. Nature,1990, 345(6271) :127-131. doi: 10.1038/345127a0
[22]	陈碧辉. 温室气体源汇及其对气候影响的研究现状[J].气象科学,2006, 26(5): 586-589.
	[Chen Bihui.The present situation of research on greenhouse gases. Scientia Meteorologica Sinica,2006, 26(5): 586-589.]

驱动类型	驱动因子	代用数据	代码	分辨率（a）
季风演变背景	石笋δ¹⁸О	和尚洞石笋δ¹⁸О^[13]	M	1~3
温室气体	CO₂浓度含量	Law Dome Ice Core CO₂^[14]	C_O	1
	CH₄浓度含量	Law Dome Ice Core CH₄^[14]	C_H	1
	N₂O浓度含量	Law Dome Ice Core N₂O^[14]	No	1

系数	a₁	a₂	a₃	a₄	a₅
系数反演值	0.004990	0.020793	0.004544	-0.135315	-0.016101
相对贡献率	3.04E-07	0.006095	0.001756	0.234288	0.000218
系数	a₆	a₇	a₈	a₉	a₁₀
系数反演值	-0.000413	5.31E-07	-5.84E-05	-0.000197	-0.000153
相对贡献率	0.190956	1.38E-05	0.003134	3.74E-05	0.000135
系数	a₁₁	a₁₂	a₁₃	a₁₄	a₁₅
系数反演值	-0.000569	2.86E-05	0.000707	-5.43E-05	13.7113
相对贡献率	0.000283	0.005654	0.505561	0.018298	0.03357

系数	a₁	a₂	a₃	a₄	a₅
系数反演值	-4.29158	10.2974	-48.8316	-73.2095	0.203813
相对贡献率	7.85E-07	0.004716	0.553539	0.216387	1.32E-07
系数	a₆	a₇	a₈	a₉	a₁₀
系数反演值	-0.23743	0.005652	0.061639	0.033863	0.003416
相对贡献率	0.194077	0.002997	0.010781	3.78E-06	2.01E-07
系数	a₁₁	a₁₂	a₁₃	a₁₄	a₁₅
系数反演值	0.001089	0.007094	-0.07185	-0.002632	777.2398
相对贡献率	3.56E-09	0.000904	0.016134	0.000113	0.000347

系数	a₁	a₂	a₃	a₄	a₅
系数反演值	-0.591287	0.228742	-0.0003	0.008404	-0.02055
相对贡献率	0.002980	0.519552	4.96E-06	0.000638	0.000243
系数	a₆	a₇	a₈	a₉	a₁₀
系数反演值	-0.00047	4.29E-06	0.000148	0.002966	-0.00015
相对贡献率	0.170664	0.000448	0.014092	0.005857	8.50E-05
系数	a₁₁	a₁₂	a₁₃	a₁₄	a₁₅
系数反演值	-0.00196	0.000107	-5.38E-05	-0.000136	-35.3044
相对贡献率	0.00232	0.049604	0.002045	0.072947	0.158519

系数	a₁	a₂	a₃	a₄	a₅
系数反演值	2.537038	0.583865	-0.14414	2.00576	0.186296
相对贡献率	0.000695	0.044244	0.02698	0.465308	0.000275
系数	a₆	a₇	a₈	a₉	a₁₀
系数反演值	0.001049	-1.29E-05	-0.001547	-0.021196	0.000286
相对贡献率	0.012741	0.000269	0.021725	0.004215	7.47E-06
系数	a₁₁	a₁₂	a₁₃	a₁₄	a₁₅
系数反演值	0.023325	1.74E-05	-0.005	0.000590	-291.312
相对贡献率	0.004567	3.74E-05	0.256224	0.036959	0.125753

温室气体强迫与东亚亚热带季风演变耦合效应及动力机制研究

Coupling Effect and Dynamic Mechanism of Greenhouse Gas Forcing and East Asian Subtropical Monsoon Evolution

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系数	a₁	a₂	a₃	a₄	a₅
系数反演值	31.390979	-3.72695	-0.07291	5.828805	0.054268
相对贡献率	0.001828	0.037125	0.000201	0.076478	3.84E-07
系数	a₆	a₇	a₈	a₉	a₁₀
系数反演值	-0.01701	-2.30E-05	-0.038469	0.016480	0.003997
相对贡献率	0.078672	3.44E-05	0.282875	5.02E-05	4.09E-05
系数	a₁₁	a₁₂	a₁₃	a₁₄	a₁₅
系数反演值	-0.13915	0.000405	0.047722	0.000113	-119.046
相对贡献率	0.003024	0.000657	0.518595	4.17E-05	0.000377

[1]	盛浩, 李旭, 杨智杰, 谢锦升, 陈光水, 杨玉盛. 中亚热带山区土地利用变化对土壤CO₂排放的影响[J]. 地理科学, 2010, 30(3): 446-451.
[2]	宋长春, 王毅勇, 王跃思, 赵志春. 人类活动影响下淡水沼泽湿地温室气体排放变化[J]. 地理科学, 2006, 26(1): 82-86.
[3]	齐玉春, 董云社. 中国能源领域温室气体排放现状及减排对策研究[J]. 地理科学, 2004, 24(5): 528-534.
[4]	刘子刚. 湿地生态系统碳储存和温室气体排放研究[J]. 地理科学, 2004, 24(5): 634-639.
[5]	张金屯. 全球气候变化对自然土壤碳、氮循环的影响[J]. 地理科学, 1998, 18(5): 463-471.