A new software and database for paleomagnitude estimation

Paleoseismic data provide critical constraints on earthquake recurrence where instrumental records are limited, but magnitude estimation fromgeological evidence requires careful treatment of measurement uncertainties. We develop a Bayesian method with application to the estimation of paleoearthquake magnitudes in the central Apennines, Italy, by jointly
analyzing rupture length (L), throw (S), and age (T) data from field investigations. Our framework incorporates empirical scaling relationships with their full uncertainty, time-dependent preservation probabilities, and physically informed priors.