Abstract
Abstract. Pattern Informatics (PI) algorithm uses earthquake catalogues for estimating the increase of the probability of strong earthquakes. The main measure in the algorithm is the number of earthquakes above a threshold magnitude. Since aftershocks occupy a significant proportion of the total number of earthquakes, whether de-clustering affects the performance of the forecast is one of the concerns in the application of this algorithm. This problem is of special interest after a great earthquake, when aftershocks become predominant in regional seismic activity. To investigate this problem, the PI forecasts are systematically analyzed for the Sichuan-Yunnan region of southwest China. In this region there have occurred some earthquakes larger than MS 7.0, including the 2008 Wenchuan earthquake. In the analysis, the epidemic-type aftershock sequences (ETAS) model was used for de-clustering. The PI algorithm was revised to consider de-clustering, by replacing the number of earthquakes by the sum of the ETAS-assessed probability for an event to be a "background event" or a "clustering event". Case studies indicate that when an intense aftershock sequence is included in the "sliding time window", the hotspot picture may vary, and the variation lasts for about one year. PI forecasts seem to be affected by the aftershock sequence included in the "anomaly identifying window", and the PI forecast using "background events" seems to have a better performance.
Highlights
The Pattern Informatics (PI) algorithm, which has been developed in recent years and has been successfully applied to California (Rundle et al, 2000, 2003; Tiampo et al, 2002), central Japan (Nanjo et al, 2006), Taiwan (Chen et al, 2005), south-west China (Jiang and Wu, 2008) and other regions, uses earthquakes catalogues to identify the increase of probability of strong earthquakes
Calculation of the probabilities is through the “epidemic-type aftershock sequences (ETAS)” model, based on the consideration of a stochastic point process, in which each earthquake has some magnitude-dependent capability to trigger its own Omori-law type aftershocks (Ogata, 1988; Helmstetter and Sornette, 2002)
In the PI algorithm, the whole region under study is binned into boxes or “pixels” with size D ×D centered at a point xi
Summary
One of the scientific problems related is: whether declustering, or the removal of aftershocks, affects the result of the PI forecast This problem becomes more important after a great earthquake, such like the 12 May 2008, Wenchuan MS 8.0 earthquake, since after this large earthquake, aftershocks became predominant in regional seismic activity. To investigate this problem, this study considers Sichuan-Yunnan and the surrounding regions of southwest China (hereafter referred to as Sichuan-Yunnan region). Related to de-clustering, Jiang and Zhuang (2010) estimated the background seismicity and potential source zones of strong earthquakes in the SichuanYunan region by using the space-time ETAS model
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