Statistical-dynamical retrieval and driving mechanism study of monsoon variation over East Asia in the last millennium
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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.
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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) M 1—3 海-陆 热带西太平洋海表温度 Tropical southwest Pacific SST(Oppo et al,2009) T1 2—10 热力差异 副热带太平洋海表温度 Hawaiian Gold Coral d15N(Sherwood et al,2014) T2 10 北半球高纬度陆地地表温度 Avam-Taimyr Tree ring in Arctic(Briffa et al,2008) G 1 太阳辐射 太阳辐射变化 Total solar irradiance reconstruction(Usoskin et al,2014) S 5 大气环流 ENSO事件 ENSO(Pacific Ocean)(Yan et al,2011) Es 1 北极冰盖温度 GISP2 Ice Core TR(Kobashi et al,2011) Ta 1 CO2浓度含量 Law Dome Ice Core CO2(Meure et al,2006) Co 1 温室气体 CH4浓度含量 Law Dome Ice Core CH4(Meure et al,2006) Ch 1 N2O浓度含量 Law Dome Ice Core N2O(Meure et al,2006) No 1 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) Q 5 气溶胶 硫酸盐气溶胶总浓度含
Volcanic sulfate ppbGISP2 Ice Core Volcanic markers(Zielinski et al,1997) Vs 1—3 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 a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 a16 a17 a18 a19 a20 a21 a22 a23 a24 a25 a26 a27 a28 a29 a30 a31 a32 a33 a34 a35 a36 a37 a38 a39 a40 a41 a42 a43 a44 a45 a46 a47 a48 a49 a50 a51 a52 a53 a54 a55 a56 a57 a58 a59 a60 a61 a62 a63 a64 a65 a66 a67 a68 a69 a70 a71 a72 a73 a74 a75 a76 a77 a78 a79 a80 a81 a82 a83 a84 a85 a86 a87 a88 a89 a90 系数反演值 -0.168240 -0.052083 0.013303 0.072474 0.000450 -0.027443 -0.071501 0.005254 0.013907 0.044412 0.020401 -0.028007 -0.030632 -0.011471 0.018430 0.010519 0.009802 0.013885 -0.343240 0.147751 -0.047993 -0.008708 -0.007818 -0.000958 -0.007228 0.005566 0.040318 -0.010240 -0.024487 0.045063 -0.148214 0.051176 -0.006859 0.004205 0.011013 -0.002125 0.016257 0.011349 -0.056759 -0.082094 -0.114950 0.164226 0.028275 0.023119 -0.024880 0.043567 -0.010908 0.025171 0.035928 -0.062691 0.061626 0.032078 -0.019599 -0.028344 -0.006626 0.057976 0.093086 -0.009194 -0.006497 0.006629 -0.017457 -0.003935 -0.008998 0.075101 -0.081349 0.005028 0.002648 -0.039132 0.008271 -0.167598 -0.013656 0.008088 0.049027 0.011329 -0.039898 0.227637 0.402471 -0.010898 0.055305 0.017923 -0.371050 0.062108 0.022451 -0.098467 -0.050493 -0.021308 0.039733 0.021509 0.004947 -0.044692 相对贡献率 0.183657 0.029471 0.001906 0.046722 0.000002 0.008824 0.006263 0.000052 0.000550 0.017062 0.003680 0.004199 0.011363 0.002813 0.007479 0.002131 0.002388 0.004459 0.083549 0.015827 0.003761 0.001327 0.001082 0.000060 0.000366 0.000192 0.007395 0.000552 0.003710 0.001752 0.021167 0.004029 0.000218 0.000115 0.000448 0.000036 0.002106 0.001115 0.028521 0.006399 0.016727 0.054253 0.006048 0.003604 0.002821 0.010057 0.001019 0.007974 0.001606 0.006285 0.009128 0.008211 0.002813 0.003611 0.000303 0.016587 0.007872 0.000134 0.000103 0.000333 0.001835 0.000053 0.000695 0.005961 0.011317 0.000067 0.000065 0.011983 0.000321 0.038992 0.000250 0.000134 0.015114 0.000947 0.008774 0.021689 0.086526 0.000132 0.004057 0.000167 0.082557 0.005222 0.000799 0.007509 0.006276 0.001088 0.001681 0.003969 0.000091 0.005493 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。 -
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