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| Titel |
PI forecast with or without de-clustering: an experiment for the Sichuan-Yunnan region |
| VerfasserIn |
C. S. Jiang, Z. L. Wu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 3 ; Nr. 11, no. 3 (2011-03-07), S.697-706 |
| Datensatznummer |
250009251
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| Publikation (Nr.) |
 copernicus.org/nhess-11-697-2011.pdf |
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| Zusammenfassung |
| 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. |
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