大气与环境光学学报 ›› 2025, Vol. 20 ›› Issue (4): 436-448.doi: 10.3969/j.issn.1673-6141.2025.04.002

• 大气光学 • 上一篇    下一篇

霾过程大气消光系数时间序列确定性与非线性检验

王思媛 1,2, 倪长健 1,2*, 孟子圣 1,2, 石荞语 3, 蒋梦姣 1,2, 张莹 1,2   

  1. 1 成都信息工程大学大气科学学院, 四川 成都 610225; 2 成都平原城市气象与环境四川省野外科学观测研究站, 四川 成都 610225; 3 中国气象局成都高原气象研究所, 四川 成都 610072
  • 收稿日期:2023-04-06 修回日期:2023-05-21 出版日期:2025-07-28 发布日期:2025-07-25
  • 通讯作者: E-mail: ncj1970@163.com E-mail:ncj1970@163.com
  • 作者简介:王思媛 (2000- ), 女, 四川内江人, 硕士研究生, 主要从事大气物理学与大气环境方面的研究。E-mail: wsiyuan00@163.com
  • 基金资助:
    四川省科技厅应用基础研发项目 (2021YJ0314), 国家重点研发计划项目 (2018YFC0214004, 2018YFC1506006)

Deterministic and nonlinear tests of time series of atmospheric extinction coefficient in haze events

WANG Siyuan 1,2, NI Changjian 1,2*, MENG Zisheng 1,2, SHI Qiaoyu 3, JIANG Mengjiao 1,2, ZHANG Ying 1,2   

  1. 1 College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, China; 2 Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu 610225, China; 3 Institute of Plateau Meteorology, China Meteorological Administration, Chengdu 610072, China
  • Received:2023-04-06 Revised:2023-05-21 Online:2025-07-28 Published:2025-07-25

摘要: 霾的形成是气溶胶与特定多尺度过程 (大气边界层变化、天气和气候过程以及大气化学过程) 复杂相互作用的 结果。本工作利用成都市2014―2017 年PM2.5、地面能见度和相对湿度的逐时观测数据, 首先通过Koschmieder's 公式 反演了研究时段内6 次霾过程大气消光系数时间序列。随后, 基于相空间重构理论计算了对应序列的最佳延迟时间τ 和最佳嵌入维数m, 并借助递归图方法证实了霾过程大气消光系数时间序列源于确定性系统的演化。最后, 对霾过程 大气消光系数时间序列非线性进行了检验。其中, 非线性特征量 (饱和关联维数、最大Lyapunov 指数、Kolmogorov 熵) 的分析表明, 大气消光系数时间序列具有弱混沌特性; Cao 方法的应用排除了该时间序列为随机序列的可能性; 而替 代数据法的进一步诊断, 最终确定了霾过程消光系数时间序列为非线性时间序列。本研究揭示了霾过程大气消光系 数时间序列的复杂性, 并为霾系统演化行为的深入认知奠定了基础。

关键词: 霾过程, 大气消光系数, 时间序列, 确定性, 非线性

Abstract: The occurrence of haze events is the consequence of complex interactions between aerosols and specific multi-scale processes, including atmospheric boundary layer variations, weather and climate processes, and atmospheric chemical processes. Utilizing the hourly observation data of PM2.5, surface visibility and relative humidity in Chengdu, China, from 2014 to 2017, the atmospheric extinction coefficient time series of six haze events during the observation period were retrieved firstly by Koschmieder's formula. Then based on the phase space reconstruction theory, the optimal delay time τ and the optimal embedding dimension m of the corresponding series were calculated, and the recurrence plot method was used to verify that the atmospheric extinction coefficient time series of the haze events originated from the evolution of the deterministic systems. Finally, the time series nonlinearity of atmospheric extinction coefficient in haze events was tested. The analysis of nonlinear characteristic variables (saturation correlation dimension, maximum Lyapunov exponent and Kolmogorov entropy) showed that the time series of atmospheric extinction coefficient had weak chaotic characteristics, the application of Cao method excluded the possibility that the time series was random, and the further diagnosis of surrogate data method finally determined that the extinction coefficient time series of the haze events were nonlinear. Our findings reveal the complexity of the atmosphere extinction coefficient time series of the haze events and lay the foundation for a deeper understanding of the evolutionary behavior of haze systems.

Key words: haze event, atmospheric extinction coefficient, time series, determinacy, nonlinearity

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