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Methods for the Evaluation of the Stochastic Properties of the Ionosphere for Earthquake Prediction—Random Matrix Theory

机译:预测电离层随机性的方法-随机矩阵理论

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Seismo-ionospheric coupling is a field of great interest and is currently subject to rigorous study; using both ground and satellite data and many phenomenological features, the ionospheric precursors of earthquakes were identified. In this work, we present methods to study the stochastic properties of the lower ionosphere, derived from the data obtained with very low frequency (VLF) receivers at frequencies in the range of 19.6 to 37.5 kHz. Two main approaches are described: auto-correlation and random matrix theory treatments of amplitude time series data. It is shown that before shallow earthquakes with magnitudes greater than four, there are measurable changes that can be used in earthquake prediction. Although the exact form of the causal chain that leads to these changes are currently subject to diligent study, we believe that the investigations described herein are worth adding to the repertoire of ionospheric precursors.
机译:地震-电离层耦合是一个令人关注的领域,目前正受到严格​​研究。利用地面和卫星数据以及许多现象学特征,确定了电离层地震的前兆。在这项工作中,我们提出了研究下电离层随机特性的方法,这些方法是从在19.6至37.5 kHz范围内的甚低频(VLF)接收器获得的数据得出的。描述了两种主要方法:幅度时间序列数据的自相关和随机矩阵理论处理。结果表明,在大于四级的浅层地震发生之前,存在可测量的变化可用于地震预测。尽管导致这些变化的因果链的确切形式目前正在认真研究中,但我们认为,本文所述的研究值得增加电离层前兆的组成部分。

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