Natural Hazards

, Volume 76, Issue 3, pp 1807–1829 | Cite as

Spectral coherence between climate oscillations and the M ≥ 7 earthquake historical worldwide record

  • Nicola ScafettaEmail author
  • Adriano Mazzarella
Original Paper


We compare the NOAA Significant Earthquake Historical database versus typical climatic indices and the length of the day (LOD). The Pacific Decadal Oscillation (PDO) record is mainly adopted because most of the analyzed earthquakes occurred at the land boundaries of the Pacific Plate. The NOAA catalog contains information on destructive earthquakes. Using advanced spectral and magnitude squared coherence methodologies, we found that the magnitude \(M\ge 7\) earthquake annual frequency and the PDO record share common frequencies at about 9-, 20-, and 50- to 60-year periods, which are typically found in climate records and among the solar and lunar harmonics. The two records are negatively correlated at the 20- and 50- to 60-year timescales and positively correlated at the 9-year and lower timescales. We use a simple harmonic model to forecast the \(M\ge 7\) significant earthquake annual frequency for the next decades. The next 15 years should be characterized by a relatively high \(M\ge 7\) earthquake activity (on average 10–12 occurrences per year) with possible maxima in 2020 and 2030 and a minimum in the 2040s. On the 60-year scale, the LOD is found to be highly correlated with the earthquake record (\(r=0.51\) for 1900–1994, and \(r=0.95\) for 1910–1970). However, the LOD variations appear to be too small to be the primary earthquake trigger. Our results suggest that large earthquakes are triggered by crust deformations induced by, and/or linked to climatic and oceanic oscillations induced by astronomical forcings, which also regulate the LOD.


Pacific Decadal Oscillation Climatic Index Earthquake Record Pacific Decadal Oscillation Index Earthquake Frequency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the two anonymous referees and Giuliano F. Panza for useful suggestions.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Meteorological Observatory, Department of Earth Sciences, Environment and GeoresourcesUniversity of Naples Federico IINaplesItaly
  2. 2.Active Cavity Radiometer Irradiance Monitor (ACRIM) LabCoronadoUSA
  3. 3.Duke UniversityDurhamUSA

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