The influence of random magnitude errors on the results of intermediate-term earthquake predictions is analyzed in this study. The particular case of predictions performed using the algorithm CN in central Italy is considered. The magnitudes of all events reported in the original catalog (OC) are randomly perturbed within the range of the expected errors, thus generating a set of randomized catalogs. The results of predictions for the original and the randomized catalogs, performed following the standard CN rules, are then compared. The average prediction quality of the algorithm CN appear stable with respect to magnitude errors up to ±0.3 units. Such a stable prediction is assured if the threshold setting period corresponds to a time interval sufficiently long and representative of the seismic activity within the region, while if the threshold setting period is too short, the average quality of CN decreases linearly for increasing maximum error in magnitude.

Stability of intermediate-term earthquake predictions with respect to random errors in magnitude: the case of Central Italy

Peresan A.;
2002

Abstract

The influence of random magnitude errors on the results of intermediate-term earthquake predictions is analyzed in this study. The particular case of predictions performed using the algorithm CN in central Italy is considered. The magnitudes of all events reported in the original catalog (OC) are randomly perturbed within the range of the expected errors, thus generating a set of randomized catalogs. The results of predictions for the original and the randomized catalogs, performed following the standard CN rules, are then compared. The average prediction quality of the algorithm CN appear stable with respect to magnitude errors up to ±0.3 units. Such a stable prediction is assured if the threshold setting period corresponds to a time interval sufficiently long and representative of the seismic activity within the region, while if the threshold setting period is too short, the average quality of CN decreases linearly for increasing maximum error in magnitude.
Earthquake prediction; Algorithm CN; Magnitude error; Randomization; Italy
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.14083/3371
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