【摘要】 过去1000年的气候变化是最近数十年人类活动影响加强情况下全球气候变化的自然背景,其变化规律和驱动机制的研究对预测未来气候变化有着重要意义。非线性统计-动力反演方法结合了统计模型和动力模型的优点,能充分利用观测数据反演系统各因子之间的相互关系。本文尝试应用非线性统计-动力反演方法建立印度夏季风的动力方程,为研究印度夏季风的驱动机制提供量化参考。经研究发现:近千年印度夏季风系统是复杂非线性动力系统;工业革命前印度夏季风变化的主要驱动力是北大西洋海表温,其次是温室气体（N₂O和CO₂）浓度与阿拉伯海海表温、ENSO及太阳辐照度等的相互作用;在工业革命后期,温室气体（CH₄、N₂O和CO₂）浓度及其与北大西洋海表温、太阳辐照度、ENSO及北极温度等的相互作用成为印度夏季风的主要驱动力;单因子甲烷和N₂O是印度夏季风的驱动力,而它们的非线性相互作用（两个因子的交叉项）却是稳定作用力。总体来说,工业革命前,北大西洋海表温度是印度夏季风的主要驱动因子;工业革命后,温室气体则成为主要的驱动因子。更多还原

【Abstract】 Researches on paleoclimate driving mechanism during the last millennium allow us to place the warming of the20 th century within a historical context.The mechanism also plays a significant role in understanding the evolution law of the climate system and predicting the future climate variability.Indian Summer Monsoon（ISM） is the most prominent part of the world’s monsoon systems,which primarily affects India and its surrounding water bodies.Solar radiation and volcanic impact are acknowledged external forcing of ISM.Many researches have shown that there are close relevance between ISM,El Nino Southern Oscillation（ENSO）,Pacific Decadal Oscillation（PDO）,North Atlantic Sea Surface Temperature（SST） and so on.Someone proposed that the mechanical and thermodynamic force of Qinghai-Tibet Plateau may be incentives of the Asian summer monsoon outburst.In addition,volcanic eruption may also be an nonnegligible factor of ISM.However,our understanding of the ISM variability on centennial time scales remains insufficient.Cave stalagmites S X) is one of the most important high-resolution proxies of paleo-monsoon.Jhumar Cave is located near the town of Jagdalpur in central India（18°52’N,81°52’E;600m a.s.l.）,where annual precipitation variability is dominated（70%⁸0%） by monsoon precipitation from July to September.As the annual precipitation of Jhumar Cave is highly related to regional monsoon precipitation,stalagmites from this cave can be used to indicate the ISM variability.In this study,a nonlinear statisticaldynamical inversion model was used to quantitatively analyze the driving mechanism of ISM based on the stalagmite data of Jhumar Cave.Traditionally,the statistical models work best in data processing,especially in the aspects of regression,fitting and correlation analysis.However,they cannot reveal the internal dynamic mechanism of data as the mechanism models do.Our nonlinear statistical-dynamical inversion model,which combines both the advantages of the traditional statistical models and dynamical models,can quantitatively analyze the driving mechanism of the paleoclimate system by making full use of the observation data.Based on this model,the following results are obtained;（1） The ISM system is a complex nonlinear dynamical system.（2） Before the Industrial Revolution,ISM is mainly driven by the North Atlantic SST,then the interaction among the greenhouse gas（N₂O and CO₂）concentration,the Arabian Sea surface temperature,ENSO and the total solar irradiance and so on.After the Industrial Revolution,the interaction among the greenhouse gas（CH₄,N₂O and CO₂） concentration,the North Atlantic Sea surface temperature,the total solar irradiance,ENSO and North polar temperature and so on become the main driving factors of ISM.（3） The linear term of CH₄ and N₂O are two driving factors of ISM after1800 A.D.,but the nonlinear interaction between the two factors is stabilizing factor.In general,the North Atlantic play an important role in affecting the ISM variability before 1800 A.D.and the greenhouse gases play an important role after 1800 A.D.更多还原