近千年东亚季风变化统计动力反演与驱动机制研究

侯立春, 林振山, 何亮, 罗虎明

侯立春, 林振山, 何亮, 罗虎明. 2017: 近千年东亚季风变化统计动力反演与驱动机制研究. 气象学报, 75(1): 67-79. DOI: 10.11676/qxxb2017.005
引用本文: 侯立春, 林振山, 何亮, 罗虎明. 2017: 近千年东亚季风变化统计动力反演与驱动机制研究. 气象学报, 75(1): 67-79. DOI: 10.11676/qxxb2017.005
Lichun HOU, Zhenshan LIN, Liang HE, Huming LUO. 2017: Statistical-dynamical retrieval and driving mechanism study of monsoon variation over East Asia in the last millennium. Acta Meteorologica Sinica, 75(1): 67-79. DOI: 10.11676/qxxb2017.005
Citation: Lichun HOU, Zhenshan LIN, Liang HE, Huming LUO. 2017: Statistical-dynamical retrieval and driving mechanism study of monsoon variation over East Asia in the last millennium. Acta Meteorologica Sinica, 75(1): 67-79. DOI: 10.11676/qxxb2017.005

近千年东亚季风变化统计动力反演与驱动机制研究

基金项目: 

国家自然科学基金项目 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项目 

详细信息
    作者简介:

    侯立春,主要从事气象与气候变化模拟及机制方向研究。E-mail:houlchjs@163.com

    通讯作者:

    林振山,主要从事气象与气候变化模拟及机制方向研究。E-mail:linzhenshan@njnu.edu.cn

  • 中图分类号: P462

Statistical-dynamical retrieval and driving mechanism study of monsoon variation over East Asia in the last millennium

  • 摘要: 利用观测数据和非线性统计-动力学方法,构建了东亚季风变化的动力方程。量化了单因子强迫及各因子间相互作用在东亚季风演化中的相对贡献率,为东亚季风驱动机制研究提供了量化参考。研究发现:(1)过去千年东亚季风是多种因子共同作用下的复杂非线性动力系统。有些因子以起驱动作用为主,则有些以反馈调节作用为主,因子间交互作用与东亚季风演化存在耦合效应机制。(2)季风的驱动力主要来源于副热带太平洋海表温度、青藏高原动力热力强迫、CO2和N2O交叉项、太阳辐射和N2O交叉项、CO2与CH4交叉项等的耦合作用机制;调节作用主要是石笋δ18O指代的地理位置、单因子CO2浓度、太阳辐射变化、CH4与N2O交叉项、太阳辐射与ENSO交叉项等的耦合作用机制。温室气体(CO2、CH4与N2O)浓度对东亚季风演化的驱动与调节作用贡献较大。(3)通过动力反演机制推论副热带太平洋和热带西太平洋对东亚季风均有驱动作用,但主要驱动力来自副热带太平洋,即驱动东亚季风变化的主源地在副热带太平洋海区,次源地在热带西太平洋海区。(4)由海-陆温差对季风演变贡献大小推测石笋δ18O指代的也主要是夏季风信息。
    Abstract: A nonlinear statistical-dynamical model of the East Asian monsoon is established using observed data. The model is applied to quantify individual contributions of different factors, which provide a quantitative reference for the study of the driving mechanism of East Asian monsoon. Results show that:(1) The East Asian monsoon is a complex nonlinear dynamic system influenced by many factors over the past thousand years. Some factors are driving forces and others are feedback regulations. Interactions among these factors are coupled with the East Asian monsoon; (2) The monsoon driving forces mainly come from sea surface temperature over the subtropical Pacific, the Tibetan Plateau thermal forcing, the coupling interaction mechanism of CO2 and N2O, solar radiation and N2O cross-terms, CO2 and CH4 cross-term. Regulation effect is mainly from the location of continent by stalagmite δ18O, CO2 concentration, changes in solar radiation, the coupling interaction mechanism of CH4 and N2O, solar radiation and ENSO cross-term, stalagmite and CH4 cross-term. The concentrations of greenhouse gases (CO2, CH4 and N2O) have a great contribution to the driving force and regulating effects of the East Asian monsoon; (3) It is inferred from the dynamic retrieval mechanism that the subtropical Pacific and the tropical western Pacific have driving effects on the East Asian monsoon. The main driving force comes from subtropical Pacific, which indicates that the main driving source of East Asian monsoon changes is in the subtropical Pacific Ocean, and the secondary source is in the tropical western Pacific Ocean; (4) Stalagmite δ18O mainly refers to the features of summer monsoon contributed by sea-land temperature to monsoon evolution.
  • 图  1   基于模型式(6)系数计算的中国湖北和尚洞石笋δ18O的反演值(红色)与实际值(蓝色)

    Figure  1.   Comparison between retrieved values(red)and real values(blue) of the stalagmite δ18O in Heshang Cave of Hubei, China after the coefficients were obtained according to the retrieval model(6)

    图  2   各驱动单因子分别参与湖北和尚洞石笋δ18О反演得到的模拟值与实际值对比

    Figure  2.   Simulated values of the δ18O of stalagmite in Heshang Cave of Hubei after the coefficients were obtained based on the single factor inversing equation

    图  3   影响因子线性项与平方项的和在其阈值范围内的单调性

    Figure  3.   The monotonicity of the sum of the influential factor’s linear term and quadratic term within threshold

    图  4   模型(7)反演得到系数后,中国湖北和尚洞石笋δ18О的反演值(红色)与实际值(蓝色)

    Figure  4.   Comparison between retrieved values(red)and real values(blue) of the stalagmite δ18O in Heshang Cave of Hubei, China after the coefficients were obtained from the retrieval equation(7)

    表  1   东亚季风驱动因子及其代用指标

    Table  1   Proxy indexes of the East-Asian monsoon driving factors

    驱动类型驱动因子代用数据代码分辨率(a)
    石笋δ18О和尚洞石笋δ18О(Hu et al,2008)M1—3
    海-陆热带西太平洋海表温度Tropical southwest Pacific SST(Oppo et al,2009)T12—10
    热力差异副热带太平洋海表温度Hawaiian Gold Coral d15N(Sherwood et al,2014)T210
    北半球高纬度陆地地表温度Avam-Taimyr Tree ring in Arctic(Briffa et al,2008)G1
    太阳辐射太阳辐射变化Total solar irradiance reconstruction(Usoskin et al,2014)S5
    大气环流ENSO事件ENSO(Pacific Ocean)(Yan et al,2011)Es1
    北极冰盖温度GISP2 Ice Core TR(Kobashi et al,2011)Ta1
    CO2浓度含量Law Dome Ice Core CO2(Meure et al,2006)Co1
    温室气体CH4浓度含量Law Dome Ice Core CH4(Meure et al,2006)Ch1
    N2O浓度含量Law Dome Ice Core N2O(Meure et al,2006)No1
    青藏高原青藏高原动力热力青藏高原普若岗日冰芯δ18О(Thompson et al,2006)Q5
    气溶胶硫酸盐气溶胶总浓度含
    Volcanic sulfate ppb
    GISP2 Ice Core Volcanic markers(Zielinski et al,1997)Vs1—3
    下载: 导出CSV

    表  2   统计动力反演模型式(6)的反演结果

    Table  2   Retrieval results of the statistical-dynamical model(6)

    系数a1a2a3a4a5a6a7a8a9a10a11a12a13a14a15a16a17a18a19a20a21a22a23a24a25a26a27a28a29a30a31a32a33a34a35a36a37a38a39a40a41a42a43a44a45a46a47a48a49a50a51a52a53a54a55a56a57a58a59a60a61a62a63a64a65a66a67a68a69a70a71a72a73a74a75a76a77a78a79a80a81a82a83a84a85a86a87a88a89a90
    系数反演值-0.168240-0.0520830.0133030.0724740.000450-0.027443-0.0715010.0052540.0139070.0444120.020401-0.028007-0.030632-0.0114710.0184300.0105190.0098020.013885-0.3432400.147751-0.047993-0.008708-0.007818-0.000958-0.0072280.0055660.040318-0.010240-0.0244870.045063-0.1482140.051176-0.0068590.0042050.011013-0.0021250.0162570.011349-0.056759-0.082094-0.1149500.1642260.0282750.023119-0.0248800.043567-0.0109080.0251710.035928-0.0626910.0616260.032078-0.019599-0.028344-0.0066260.0579760.093086-0.009194-0.0064970.006629-0.017457-0.003935-0.0089980.075101-0.0813490.0050280.002648-0.0391320.008271-0.167598-0.0136560.0080880.0490270.011329-0.0398980.2276370.402471-0.0108980.0553050.017923-0.3710500.0621080.022451-0.098467-0.050493-0.0213080.0397330.0215090.004947-0.044692
    相对贡献率0.1836570.0294710.0019060.0467220.0000020.0088240.0062630.0000520.0005500.0170620.0036800.0041990.0113630.0028130.0074790.0021310.0023880.0044590.0835490.0158270.0037610.0013270.0010820.0000600.0003660.0001920.0073950.0005520.0037100.0017520.0211670.0040290.0002180.0001150.0004480.0000360.0021060.0011150.0285210.0063990.0167270.0542530.0060480.0036040.0028210.0100570.0010190.0079740.0016060.0062850.0091280.0082110.0028130.0036110.0003030.0165870.0078720.0001340.0001030.0003330.0018350.0000530.0006950.0059610.0113170.0000670.0000650.0119830.0003210.0389920.0002500.0001340.0151140.0009470.0087740.0216890.0865260.0001320.0040570.0001670.0825570.0052220.0007990.0075090.0062760.0010880.0016810.0039690.0000910.005493
    注:相对贡献率量级小于0.001作为剔除条件,即根据式(5)W=0.001作为多项式筛选条件,表中黑体字为保留项。
    下载: 导出CSV
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  • 收稿日期:  2016-04-18
  • 修回日期:  2016-10-04
  • 发布日期:  2017-01-31

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