Retrospective short-term forecasting experiment in Italy based on the occurrence of strong (fore) shocks

Abstract

Summary In a recent work we computed the relative frequencies with which strong shocks (4.0 ≤ Mw < 5.0), widely felt by the population were followed in the same area by potentially destructive main shocks (Mw ≥ 5.0) in Italy. Assuming the stationarity of the seismic release properties, such frequencies can be tentatively used to estimate the probabilities of potentially destructive shocks after the occurrence of future strong shocks. This allows us to set up an alarm-based forecasting hypothesis related to strong foreshocks occurrence. Such hypothesis is tested retrospectively on the data of a homogenized seismic catalogue of the Italian area against a purely random hypothesis that simply forecasts the target main shocks proportionally to the space-time fraction occupied by the alarms. We compute the latter fraction in two ways a) as the ratio between the average time covered by the alarms in each area and the total duration of the forecasting experiment (60 years) and b) as the same ratio but weighted by the past frequency of occurrence of earthquakes in each area. In both cases the overall retrospective performance of our forecasting algorithm is definitely better than the random case. Considering an alarm duration of three months, the algorithm retrospectively forecasts more than 70 per cent of all shocks with Mw ≥ 5.5 occurred in Italy from 1960 to 2019 with a total space-time fraction covered by the alarms of the order of 2 per cent. Considering the same space-time coverage, the algorithm is also able to retrospectively forecasts more than 40 per cent of the first main shocks with Mw ≥ 5.5 of the seismic sequences occurred in the same time interval. Given the good reliability of our results, the forecasting algorithm is set and ready to be tested also prospectively, in parallel to other ongoing procedures operating on the Italian territory.

Comparison between alarm-based and probability-based earthquake forecasting methods

“…2 ) occurs in a given circle of radius R = 30 km . The results obtained retrospecti vel y b y Gasperini et al ( 2021 ) show that approximately 60 and 70 per cent of earthquakes with magnitude M ≥ 5.0 that occurred between 1960 and 2020 were anticipated by foreshocks in the three months and one year respecti vel y preceding them with space-time coverages of alarms less than 1 per cent. Such percentages increase by extending the alarm windo w, highlighting ho w the occurrence of strong shocks can contribute to improving stronger earthquake prediction.…”

“…For more details see also Gasperini et al ( 2021 ). The experiment is then repeated by varying the alarm time duration t from a few second to the total duration of the experiment (10 yr).…”

“…Following Shebalin et al ( 2011 ), we calculated the fraction of the space-time occupied also by weighting each alarm with the longter m ear thquake rate within each cell. We compute such rates using the historical earthquakes occurred in the time period 1620-1959 according to the CPTI15 V4.0 catalogue (Rovida et al 2020(Rovida et al , 2022 following the procedure described in Gasperini et al ( 2021 ). Hence for each t of the considered forecasting models, we compute both weighted τ w and unweighted τ u space-time fractions occupied by alarms.…”

“…In this work, the probabilistic forecasting models described in Biondini et al ( 2023 ) are compared with a deterministic forecasting method based on the occurrence of strong (fore) shocks (hereafter FORE method) described by Gasperini et al ( 2021 ). The latter sets an alarm of duration t every time an earthquake of magnitude 4 .…”

Implementation and verification of a real-time system for automatic aftershock forecasting in China

“…Approximately 5%-10% of strong earthquakes worldwide produce observable foreshocks (Reasenberg and Jones 1989), and the proportion increases with instrumental coverage improvement, as inferred by Trugman and Ross (2019). Although many researchers have attempted to capture foreshocks to generate short-term or imminent predictions of upcoming large earthquakes (Jones and Molnar 1979;McGuire et al 2005;Gasperini et al 2021), the identification of foreshocks remains uncertain due to the lack of understanding of the physical mechanism of foreshock activity. Moreover, the statistical characteristics of foreshocks are not considered in this system, and a small number of large earthquakes may be missed as a consequence.…”