The epidemic‐type aftershock sequence (ETAS) model has been shown to describe successfully the statistical seismicity properties, if earthquake triggering is related to tectonic forcing and earthquake‐induced stress changes. However, seismicity is locally often dominated by stress changes related to transient aseismic processes. To avoid erroneous parameter estimations leading to biased forecasts, it is important to account for those transients. We apply a recently developed iterative algorithm based on the ETAS model to identify the time‐dependent background and ETAS parameters simultaneously. We find that this procedure works well for synthetic data sets if catalog errors are appropriately considered. However, ignoring the time dependence leads to significantly biased parameter estimations. In particular, the α‐value describing the magnitude dependence of the triggering kernel can be strongly underestimated if transients are ignored. Low α‐values have been previously found for swarm activity, for which transient aseismic processes are expected to play a major role. These observed anomalously low α‐values might thus indicate the importance of transient forcing, rather than being due to differences in the earthquake–earthquake trigger mechanism. To explore this, we apply the procedure systematically to earthquake clusters detected in southern California and to earthquake swarm activity in Vogtland/Western Bohemia. While low α‐values are mostly shown to be a consequence of catalog errors and time‐dependent forcing but not related to different earthquake–earthquake interaction mechanisms, some significant low values are observed in high heat‐flow areas in California, confirming the existence of thermal control on earthquake triggering.

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