印度各地日平均温度和露点之间的自组织临界性、因果关系和复发概率的相关性

Rajdeep Ray, Payel Majumder, M. H. Khondekar, K. Ghosh, A. Bhattacharjee
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引用次数: 1

摘要

在自组织临界状态下,对位于印度的7个气象站的温度和露点记录进行了审查。数据模型在t/fα噪声类型下具有几乎理想的标度行为;与α≈1。这种缩放行为强烈表明,这两个信号背后都存在自组织临界性(SOC)。为了进一步深入了解这一现象的具体动态并加强对这一现象的解释,本文利用奇异谱分析(SSA)、多元奇异谱分析(MSSA)和基于递归图的复现概率相关(CPR)对所有台站两个信号之间的因果关系进行了研究。结果表明,这些临界动力系统具有充分的因果关系和高度的重现概率相关性,为其提供了强有力的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-organized criticality, causality and correlation of probability of recurrence between daily mean temperature and dew point across India
The temperature and dew point records of seven weather stations, located in India have been scrutinized under the self-organized criticality regime. The data models an almost ideal scaling behaviour as of the type of t/fα noise; with α≈1. This scaling behaviour strongly suggests the presence of self-organized criticality (SOC) behind both the signals. To draw more insight into the detailed dynamics and to strengthen the explanation of such behaviour, causal relationship exploiting singularity spectrum analysis (SSA), multivariate singularity spectrum analysis (MSSA) and Correlation of Probability of Recurrence (CPR) based on recurrence plot have been studied in between the two signals for all the stations. The results reveal sufficient causal relationship and high correlation of probability of recurrence for strong support behind such critical dynamical systems.
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