DO GLOBAL CLIMATE AND EARTHQUAKE INDICATORS EXPLAIN YEAR-TO-YEAR VARIATION IN GREAT-EARTHQUAKE ACTIVITY? A STATISTICAL ASSESSMENT OF WORLDWIDE M ≥ 7.0 EARTHQUAKES, 1984–2020

Surface loading by water, ice and the atmosphere can perturb crustal stress, and regional studies report that seismicity responds to such loading. Whether global climate indicators are statistically related to the annual occurrence of great earthquakes remains unresolved. We compiled annual counts and annual maximum magnitudes of worldwide earthquakes of magnitude ≥ 7.0 from the USGS catalogue. We related these to annual atmospheric pressure anomalies, air temperature, and sea surface temperature (SST) anomalies for 1984–2020 (n = 37 years). Five geomagnetic and solar indices were examined. We used Pearson and Spearman correlations, ordinary least squares and Poisson regression, and tested for robustness by extending the window, excluding influential years, adjusting for a linear trend and differencing the series. The three climate indicators jointly accounted for 28% of the variance in annual maximum magnitude (adjusted R2 = 0.21; F3,33 = 4.27, p = 0.012), with a positive SST coefficient and a negative pressure coefficient, but not for annual earthquake count (R2 = 0.12, p = 0.22; Poisson likelihood-ratio p = 0.24). The SST association vanished once a linear time trend was included (p = 0.84) and in first-differenced data; the pressure association survived detrending but not differencing. None of the 16 bivariate correlations remained significant after multiple-comparison correction. The data show co-varying long-term tendencies but no robust year-to-year relationship between global climate indicators and great-earthquake activity. The apparent association with SST is most parsimoniously explained by shared trends in short series, and the analysis cannot support causal inference. Spatially resolved, physically motivated designs are needed to test climate–seismicity coupling