“All Models Are Wrong, but Some Are Useful”

Building a new model, especially one used for policy purposes, takes considerable time, effort, and resources. In justifying such expenditures, one inevitably spends a lot of time denigrating previous models. For example, in pitching the third Uniform California Earthquake Rupture Forecast (UCERF3) (http://www.WGCEP.org/UCERF3), criticisms of the previous model included fault‐segmentation assumptions and the lack of multifault ruptures. In the context of including spatiotemporal clustering for operational earthquake forecasting (e.g., Jordan et al., 2011), another criticism has been that previous candidate models not only ignore elastic rebound but also produce results that are antithetical to that theory. For instance, the short‐term earthquake probabilities model (Gerstenberger et al., 2005), which provided California aftershock hazard maps at the U.S. Geological Survey web site between 2005 and 2010, implies that the time of highest likelihood for any rupture will be the moment after it occurs, even for a big one on the San Andreas fault. Furthermore, Monte Carlo simulations imply that excluding elastic rebound in such models also produces unrealistic triggering statistics (Field, 2012).