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Abstract <p>This work focuses on examining the precursory signatures through the study of anomalous changes in solid earth tides (SET), relative humidity (RH), and outgoing longwave radiation flux (OLR). Retrospective time series analysis was carried out to identify significant anomalies that occur on these precursors, and it was found that appreciable abnormal changes were observed not more than 2-3 lunar months before the earthquakes. Hence, the analysis covered six months preceding the seismic events. To normalize the range of data to a standard scale and pinpoint any anomalous activity for further investigation, the method of z-score normalization was used independently for each dataset. The study focuses on analyzing earthquakes with magnitudes greater than 6.0 Mw that occurred within a 75 km radius of Sumatra, Indonesia, concerning the epicenter of the 26 December 2004 earthquake. The analysis investigates the characteristics of these precursory signatures and any associated anomalies before an earthquake. This work aims to provide new insights into the association of these precursory signatures in the seismically active region. The results suggest that the anomalous variations of the monthly cumulative value of precursors cross the threshold limit of 29.4 when all precursors occur in a sequence, with SET followed by atmospheric parameters like relative humidity and OLR within a lunar month.</p> Research highlights <p><UnorderedList Mark="Bullet"> <ItemContent> <p>Established a multi-parameter cumulative index framework by integrating Solid Earth Tides, Relative Humidity, and OLR anomalies for pre-seismic precursors.</p> </ItemContent> <ItemContent> <p>Derived an objective threshold from the 95th-percentile background distribution to distinguish anomalous months from non-precursory variability.</p> </ItemContent> <ItemContent> <p>Demonstrated that precursor lead times vary with fault heterogeneity, depth, and stress state, revealing complex lithosphere–atmosphere coupling behaviour.</p> </ItemContent> </UnorderedList></p>

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Threshold based precursory sequence before Sumatra-Indonesia region (M≥6.0) earthquakes

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Ramya Jeyaraman,
  • Venkatanathan Natarajan,
  • M Saravanan

摘要

Abstract

This work focuses on examining the precursory signatures through the study of anomalous changes in solid earth tides (SET), relative humidity (RH), and outgoing longwave radiation flux (OLR). Retrospective time series analysis was carried out to identify significant anomalies that occur on these precursors, and it was found that appreciable abnormal changes were observed not more than 2-3 lunar months before the earthquakes. Hence, the analysis covered six months preceding the seismic events. To normalize the range of data to a standard scale and pinpoint any anomalous activity for further investigation, the method of z-score normalization was used independently for each dataset. The study focuses on analyzing earthquakes with magnitudes greater than 6.0 Mw that occurred within a 75 km radius of Sumatra, Indonesia, concerning the epicenter of the 26 December 2004 earthquake. The analysis investigates the characteristics of these precursory signatures and any associated anomalies before an earthquake. This work aims to provide new insights into the association of these precursory signatures in the seismically active region. The results suggest that the anomalous variations of the monthly cumulative value of precursors cross the threshold limit of 29.4 when all precursors occur in a sequence, with SET followed by atmospheric parameters like relative humidity and OLR within a lunar month.

Research highlights

Established a multi-parameter cumulative index framework by integrating Solid Earth Tides, Relative Humidity, and OLR anomalies for pre-seismic precursors.

Derived an objective threshold from the 95th-percentile background distribution to distinguish anomalous months from non-precursory variability.

Demonstrated that precursor lead times vary with fault heterogeneity, depth, and stress state, revealing complex lithosphere–atmosphere coupling behaviour.