Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information

Abstract

SUMMARY Global seismicity models provide scientific hypotheses about the rate, location and magnitude of future earthquakes to occur worldwide. Given the aleatory variability of earthquake activity and epistemic uncertainties in seismicity forecasting, the veracity of these hypotheses can only be confirmed or rejected after prospective forecast evaluation. In this study, we present the construction of and test results for two updated global earthquake models, aimed at providing mean estimates of shallow (d ≤ 70 km) seismicity for seismic hazard assessment. These approaches, referred to as the Tectonic Earthquake Activity Model (TEAM) and the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) model, use the Subduction Megathrust Earthquake Rate Forecast (SMERF2), an earthquake-rate model for subduction zones constrained by geodetic strain measurements and earthquake-catalogue information. Thus, these global ensemble seismicity models capture two independent components necessary for long-term earthquake forecasting, namely interseismic crustal strain accumulation and sudden lithospheric stress release. The calibration period for TEAM and WHEEL extends from 1977 January 1 to 2013 December 31. Accordingly, we use m ≥ 5.95 earthquakes recorded during the 2014–2019 period to pseudo-prospectively evaluate the forecasting skills of these earthquake models, and statistically compare their performances to that of the Global Earthquake Activity Rate (GEAR1) model. As a result, GEAR1 and WHEEL are the most informative global seismicity models during the pseudo-prospective test period, as both rank with the highest information scores among all participant earthquake-rate forecasts. Nonetheless, further prospective evaluations are required to more accurately assess the abilities of these global ensemble seismicity models to forecast long-term earthquake activity.