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Nearly 600 California earthquakes help validate models that forecast next-day seismic risk
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Nearly 600 California earthquakes help validate models that forecast next-day seismic risk Gaby Clark Scientific Editor Alexander Pol Deputy Editor The University of Bristol–led study, published in Nature Communications, could help millions of people living in earthquake-prone countries make better-informed decisions about seismic risk, particularly during ongoing periods of increased earthquake activity. Recent earthquakes in Colombia, Japan and Venezuela have offered stark reminders of the...
Nearly 600 California earthquakes help validate models that forecast next-day seismic risk
Gaby Clark
Scientific Editor
Alexander Pol
Deputy Editor
The University of Bristol–led study, published in Nature Communications, could help millions of people living in earthquake-prone countries make better-informed decisions about seismic risk, particularly during ongoing periods of increased earthquake activity.
Recent earthquakes in Colombia, Japan and Venezuela have offered stark reminders of the importance of being as well prepared as possible for potential earthquakes.
Testing more than 50,000 next-day forecasts
To find out how reliable current earthquake forecast models are, researchers evaluated 27 earthquake forecasting models that, over the course of more than a decade, automatically generated a unique database of more than 50,000 next-day forecasts for California. The forecasts were contrasted against almost 600 earthquakes of magnitude 3.95 or greater recorded over the testing period.
The results show that select models described the location, timing and magnitude of earthquake activity consistently, as measured against observations collected prospectively.
Lead author Dr. José A. Bayona, an early-career Leverhulme research fellow in the University of Bristol's School of Earth Sciences, said, "No scientific method can currently predict exactly when and where the next earthquake will occur. However, probabilistic forecasting can provide useful information about where, when and how large earthquakes are more likely over a defined period.
"Our study shows that the type of models currently used for operational earthquake forecasting in some countries can produce forecasts that remain consistent with observations over long periods of prospective testing. This provides strong evidence for their use in public operational forecasting systems."
California's extensive prospective testing record
The forecasts were generated automatically and fully prospectively by the Collaboratory for the Study of Earthquake Predictability (CSEP), a global community of scientists dedicated to advancing earthquake predictability research through prospective evaluation of probabilistic seismicity models.
While previous CSEP experiments have evaluated earthquake forecasts in regions such as Japan, New Zealand and Italy, the California experiment is distinctive because of its combination of the number of models tested, the length of the experiment and the quantity of prospective earthquake observations available for evaluation.
A model recipe for operational forecasting
The findings could have practical implications for government agencies, civil protection authorities and scientific organizations developing—or considering developing—operational earthquake forecasting systems.
Bayona added, "We've provided a model 'recipe' identifying elements that can be considered when developing forecasts consistent with the observed number, spatial locations and magnitude distribution of earthquakes. We've also provided an open-source software package containing the code, data and documentation needed to transparently replicate the study's analyses, figures and results."
Publication details
José A. Bayona et al., Select earthquake forecasting models demonstrate consistency with prospective decadal observations in California, Nature Communications (2026). DOI: 10.1038/s41467-026-76243-7
Journal information: Nature Communications
Key concepts
earthquake probabilitiesProvided by University of Bristol
California (LOCATION)
Gaby Clark Scientific (PERSON)
Alexander Pol (PERSON)
The University of Bristol (ORG)
Nature Communications (ORG)
Colombia (LOCATION)
Japan (LOCATION)
Venezuela (LOCATION)
José A. Bayona (PERSON)
the University of Bristol's (ORG)
School of Earth Sciences (ORG)
Collaboratory (ORG)
CSEP (ORG)
New Zealand (LOCATION)
Italy (LOCATION)