Assessing annual global M6+ seismicity forecasts

We consider a seismicity forecast experiment conducted during the last 4 yr. At the beginning of each year, three models make a 1-yr forecast of the distribution of large earthquakes everywhere on the Earth. The forecasts are generated and the observations are collected in the Collaboratory for the Study of Earthquake Predictability (CSEP). We apply CSEP likelihood measures of consistency and comparison to see how well the forecasts match the observations, and we compare results from some intuitive reference models. These results illustrate some undesirable properties of the consistency tests: the tests can be extremely sensitive to only a few earthquakes, and yet insensitive to seemingly obvious flaws—a naïve hypothesis that large earthquakes are equally likely everywhere is not always rejected. The results also suggest that one should check the assumptions of the so-called T and W comparison tests, and we illustrate some methods to do so. As an extension of model assessment, we explore strategies to combine forecasts, and we discuss the implications for operational earthquake forecasting. Finally, we make suggestions for the next generation of global seismicity forecast experiment

On the Testing of Seismicity Models

Recently a likelihood-based methodology has been developed by the Collaboratory for the Study of Earthquake Predictability (CSEP) with a view to testing and ranking seismicity models. We analyze this approach from the standpoint of possible applications to hazard analysis. We arrive at the conclusion that model testing can be made more efficient by focusing on some integral characteristics of the seismicity distribution. This is achieved either in the likelihood framework but with economical and physically reasonable coarsening of the phase space or by choosing a suitable measure of closeness between empirical and model seismicity rate in this space.Comment: To appear at Acta Geophysic