New Methods for Analyzing the Nature of Seismic Regime Non-Stationarity

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Abstract

Three new methods in geophysics for analyzing the non-stationarity of data series are used to analyze earthquake catalogs of the Kuril-Kamchatka and Mid-Atlantic Ridge regions. The possibility of identifying the non-stationary component of the seismic regime and the nature of non-stationarity are discussed. The use of new methods confirmed a number of known (expected) patterns and indicated a number of non-trivial points. Among these, the following were identified: a tendency of increasing non-stationarity with increasing characteristic time, which may conform to the correspondence of seismic activity spectrum to the flicker noise; 2) a difference in the nature of the magnitude distribution, possibly corresponding to a decrease in b-values, for clustering main events; 3) detection of two tendencies in the seismicity regime over time — clustering at smaller relative distances and repulsion at larger ones; these tendencies may correspond to the epochs of seismic activity growth and subsequent attenuation, during the accumulation of tectonic stresses. The results indicate the prospects of using these new analysis methods in seismology, providing clarification of the non-stationary nature of the seismic process.

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About the authors

А. А. Kislitsyn

Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences; Institute of Earthquake Prediction Theory and Mathematical Geophysics of the Russian Academy of Sciences

Email: rodkin@mitp.ru
Russian Federation, Moscow; Moscow

Yu. N. Orlov

Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences

Email: rodkin@mitp.ru
Russian Federation, Moscow

М. V. Rodkin

Institute of Earthquake Prediction Theory and Mathematical Geophysics of the Russian Academy of Sciences; Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences

Author for correspondence.
Email: rodkin@mitp.ru
Russian Federation, Moscow; Moscow

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Supplementary files

Supplementary Files
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2. Fig. 1. Magnitude distributions in 10 classes of Table 2 for different time intervals (t = 1-10) between the events (explanations in the text, CC catalogue without aftershocks).

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3. Fig. 2. Non-stationarity indices J (N) of event occurrence times.

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4. Fig. 3. Flow parameter for the KK region estimated from a sample length of 1000 days in 1-day increments.

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5. Fig. 4. Flow parameter for the AH region estimated using a sample length of 300 days in 1-day increments.

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6. Fig. 5. Mean annual flux parameter for the CC region (1) and AH (2).

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7. Fig. 6. Graphs of first (a) and first + second "neighbours" (b) for 100 vertices for consecutive time intervals of the first 4950 events of the QC catalogue, considered as random values.

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