Published July 21, 2020 | Version v1
Journal article Open

Pseudoprospective Evaluation of UCERF3‐ETAS Forecasts during the 2019 Ridgecrest Sequence

  • 1. Southern California Earthquake Center
  • 2. University of Bristol
  • 3. Università degli Studi di Napoli Federico II
  • 4. GNS Science
  • 5. UCLA
  • 6. US Geological Survey

Description

The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic‐type aftershock sequences (UCERF3‐ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3‐NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3‐ETAS and UCERF3‐NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude‐number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3‐ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.

Notes

Maximilian J. Werner and Warner Marzocchi received funding from the European Union's Horizon 2020 research and innovation program (Number 821115, RISE: Real‐Time Earthquake Risk Reduction for a Resilient Europe). This research was supported by the Southern California Earthquake Center (SCEC; Contribution Number 10082). SCEC is funded by National Science Foundation (NSF) Cooperative Agreement EAR‐1600087 and the U.S. Geological Survey (USGS) Cooperative Agreement G17AC00047.

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