Magnitude correlation exposes hidden short-term earthquake catalog incompleteness

Current models used for earthquake forecasting assume that the magnitude of an earthquake is independent of past earthquakes, i.e., the earthquake magnitudes are uncorrelated. Nevertheless, several studies have challenged this assumption by revealing correlations between the magnitude of subsequent earthquakes in a sequence. These findings could significantly improve earthquake forecasting and help in understanding the physics of the nucleation process.

We investigate this phenomenon for the foreshock sequence of the first 2019 Ridgecrest event (M_w6.4) using a high-resolution catalog; choosing this foreshock sequence has been guided by a low b-value (~0.68 ± 0.06 after converting local magnitudes to moment magnitudes) and a significant magnitude correlation, even when considering only earthquakes above the completeness level estimated with different methods. To disregard incomplete events in the b-value estimation, we apply the b-positive approach (van der Elst 2021), i.e., using only positive magnitude differences; those magnitude differences are uncorrelated and we obtain a markedly higher b-value (~0.9 ± 0.1). Apparently, the foreshock sequence contained substantial short-term aftershock incompleteness due to a M_w4.0 event.

We observe a similar behaviour for whole Southern California after stacking earthquake sequences. Finally, we generate synthetic catalogs and apply short-term incompleteness to demonstrate that common methods for estimating the completeness level still result in magnitude correlation, indicating hidden incompleteness.

Our findings highlight that (i) existing methods for estimating the completeness level have limited statistical power and the remaining incompleteness can significantly bias the b-value estimation; (ii) the magnitude correlation is the most powerful property to detect incompleteness, so it should supplement statistical analyses of earthquake catalogs.