Earthquake Counting Method for Spatially Localized Probabilities: Challenges in Real-Time Information Delivery
James R Holliday, William R Graves, John B Rundle, and Donald L, Turcotte

TL;DR
This paper introduces a novel global earthquake forecasting method based on small event counts as natural time markers, enabling real-time, region-agnostic probability estimates for large earthquakes.
Contribution
The paper develops a new natural time Weibull forecasting approach that operates on arbitrary regions without fixed boundaries, improving real-time earthquake risk assessment.
Findings
Japan region identified at high risk for M>8 earthquake within 1-2 years
Method leverages small earthquake counts as indicators of imminent large events
Forecasts are consistent with Gutenberg-Richter relation completeness
Abstract
We develop and implement a new type of global earthquake forecast. Our forecast is a perturbation on a smoothed seismicity (Relative Intensity) spatial forecast combined with a temporal time-averaged (Poisson) forecast. A variety of statistical and fault-system models have been discussed for use in computing forecast probabilities. Our paper takes a new approach. The idea is based on the observation that GR statistics characterize seismicity for all space and time. Small magnitude event counts (quake counts) are used as markers for the approach of large events. More specifically, if the GR b-value = 1, then for every 1000 M>3 earthquakes, one expects 1 M>6 earthquake. So if ~1000 M>3 events have occurred in a spatial region since the last M>6 earthquake, another M>6 earthquake should be expected soon. In physics, event count models have been called natural time models, since counts of…
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Taxonomy
Topicsearthquake and tectonic studies · Earthquake Detection and Analysis · Seismology and Earthquake Studies
