Detecting premonitory seismicity patterns based on critical point dynamics
We test the hypothesis that critical point dynamics precedes strong earthquakes in a region surrounding the future hypocenter. Therefore, we search systematically for regions obeying critical point dynamics in terms of a growing spatial correlation length (GCL). The question of whether or not t...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2001-01-01
|
Series: | Natural Hazards and Earth System Sciences |
Online Access: | http://www.nat-hazards-earth-syst-sci.net/1/93/2001/nhess-1-93-2001.pdf |
id |
doaj-4b222f434dad4314aecfcab2a714cf8a |
---|---|
record_format |
Article |
spelling |
doaj-4b222f434dad4314aecfcab2a714cf8a2020-11-25T00:56:26ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812001-01-0111/29398Detecting premonitory seismicity patterns based on critical point dynamicsG. ZöllerS. HainzlS. HainzlWe test the hypothesis that critical point dynamics precedes strong earthquakes in a region surrounding the future hypocenter. Therefore, we search systematically for regions obeying critical point dynamics in terms of a growing spatial correlation length (GCL). The question of whether or not these spatial patterns are correlated with future seismicity is crucial for the problem of predictability. The analysis is conducted for earthquakes with <i>M</i> <u>></u> 6.5 in California. As a result, we observe that GCL patterns are correlated with the distribution of future seismicity. In particular, there are clear correlations in some cases, e.g. the 1989 Loma Prieta earthquake and the 1999 Hector Mine earthquake. We claim that the critical point concept can improve the seismic hazard assessment.http://www.nat-hazards-earth-syst-sci.net/1/93/2001/nhess-1-93-2001.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Zöller S. Hainzl S. Hainzl |
spellingShingle |
G. Zöller S. Hainzl S. Hainzl Detecting premonitory seismicity patterns based on critical point dynamics Natural Hazards and Earth System Sciences |
author_facet |
G. Zöller S. Hainzl S. Hainzl |
author_sort |
G. Zöller |
title |
Detecting premonitory seismicity patterns based on critical point dynamics |
title_short |
Detecting premonitory seismicity patterns based on critical point dynamics |
title_full |
Detecting premonitory seismicity patterns based on critical point dynamics |
title_fullStr |
Detecting premonitory seismicity patterns based on critical point dynamics |
title_full_unstemmed |
Detecting premonitory seismicity patterns based on critical point dynamics |
title_sort |
detecting premonitory seismicity patterns based on critical point dynamics |
publisher |
Copernicus Publications |
series |
Natural Hazards and Earth System Sciences |
issn |
1561-8633 1684-9981 |
publishDate |
2001-01-01 |
description |
We test the hypothesis that critical point dynamics precedes strong earthquakes in a region surrounding the future hypocenter. Therefore, we search systematically for regions obeying critical point dynamics in terms of a growing spatial correlation length (GCL). The question of whether or not these spatial patterns are correlated with future seismicity is crucial for the problem of predictability. The analysis is conducted for earthquakes with <i>M</i> <u>></u> 6.5 in California. As a result, we observe that GCL patterns are correlated with the distribution of future seismicity. In particular, there are clear correlations in some cases, e.g. the 1989 Loma Prieta earthquake and the 1999 Hector Mine earthquake. We claim that the critical point concept can improve the seismic hazard assessment. |
url |
http://www.nat-hazards-earth-syst-sci.net/1/93/2001/nhess-1-93-2001.pdf |
work_keys_str_mv |
AT gzoller detectingpremonitoryseismicitypatternsbasedoncriticalpointdynamics AT shainzl detectingpremonitoryseismicitypatternsbasedoncriticalpointdynamics AT shainzl detectingpremonitoryseismicitypatternsbasedoncriticalpointdynamics |
_version_ |
1725227146263134208 |