Empirical Calibration of Local Magnitude Data Sets Versus Moment Magnitude in Italy

Abstract

Using general orthogonal regressions (GORs), we calibrated local magnitudes, estimated in Italy using various methods in different periods of time from 1981 to 2010, with a set of homogeneous moment magnitudes ( M w). Magnitude uncertainties, necessary for the application of GOR methods, are inferred by a trial‐and‐error procedure based on a priori information and empirical regression results. We found that local magnitudes determined using real or synthesized Wood–Anderson waveforms ( M L) scale 1:1 with M w in most cases but in general underestimate M w by about 0.1–0.2 magnitude units. The only significant deviation from the 1:1 scaling concerns the most recent data provided by the online ISIDE bulletin of the Istituto Nazionale di Geofisica e Vulcanologia and is probably due to the use of a distance correction table (−log A ) not fully appropriate for the Italian area. Magnitudes computed from the duration of the seismogram coda ( M D) do not generally scale 1:1 with M w and are also underestimated. The relevant regression coefficients vary significantly from one data set to another depending on the empirical formulas used by different catalogs and bulletins. The derived regression coefficients are used to build a homogenized catalog in terms of M w that also includes a consistent estimate of uncertainty for all reported magnitudes. The analysis of the frequency–magnitude distribution of the resulting catalog, covering 30 years of data, shows a b ‐value slightly lower than 1, which is reasonably uniform over the different time intervals and data sets. It also shows a progressive decay of the earthquake rates below the best‐fit straight line for M w>4.5 that might reflect a magnitude distribution truncated or tapered to relatively small maximum magnitudes for some Italian seismic zones with low activity. This behavior also seems to exclude a characteristic earthquake recurrence mechanism for Italy. Online Material: Description of data sets and details of regression and frequency–magnitude distribution analyses.