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Better Earthquake Forecasts

Date: 4/24/2019

Time: 2:15 PM to 5:30 PM

Room: Pike

Earthquake forecasts have a wide range of applications from short-term guidance during earthquake sequences and swarms to being an ingredient in long-term Probabilistic Seismic Hazards Assessments (PSHA). In this session, we will discuss what makes an earthquake forecast useful and how to improve them. For short-term forecasts of swarms and earthquake sequences, most current, official forecasts are based on statistical models of earthquake clustering such as the Reasenberg & Jones model or the ETAS (Epidemic Type Aftershock Sequences) model. Can we improve these by including physics-based models of stress transfer or results from numerical simulators of earthquake occurrence on fault networks? For long-term forecasts, PSHA often relies on seismicity rates obtained by smoothing declustered earthquake catalogs. Would other declustering methods improve the forecasts or should we abandon declustering altogether and include aftershocks in hazards assessments and building codes? Some PSHA now also includes deformation information from plate motions or geodetic monitoring. How do we best combine that information with the seismicity rates? For all forecasts, how do we include fault-based information and do we need better ways to address earthquake catalog incompleteness and uncertainty? A critical step is testing these forecasting methods and the forecasts themselves, for example using approaches from the Collaboratory for the Study of Earthquake Predictability (CSEP). As we develop tests we need to consider the role of local versus global tests, prospective versus retrospective tests and tests of forecast ingredients versus complete forecasts. Questions about testing are particularly timely as CSEP develops its second phase of operations. Finally, we need to communicate these forecasts with different users to help inform a variety of decisions. These communications methods range from hazard curves for engineers to simplified text or graphics for the people impacted by the earthquake, broadcast media, emergency managers and first responders. Working alongside our social science colleagues is an important step to understanding more about our users, the channels they prefer and what information they need most to inform their decisions. We seek contributions that address any of the questions posed above or other ideas on how to improve earthquake forecasts.

Conveners

Andrew J. Michael, U.S. Geological Survey (ajmichael@usgs.gov)
Camilla Cattania, Stanford University (camcat@stanford.edu)
David D. Jackson, University of California, Los Angeles (djackson@g.ucla.edu)
Sara K. McBride, U.S. Geological Survey (skmcbride@usgs.gov)
Warner Marzocchi, Istituto Nazionale di Geofisica e Vulcanologia (warner.marzocchi@ingv.it)
Maximilian J. Werner, University of Bristol (max.werner@bristol.ac.uk)

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