some properties of “aftershocks” some properties of aftershocks dave jackson ucla oct 25, 2011

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Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011 UC BERKELEY

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Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011 UC BERKELEY. Conclusions. Aftershocks are not clearly defined Whether aftershocks have different magnitude dependence or triggering potential depends upon their definition - PowerPoint PPT Presentation

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Page 1: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Some Properties of “aftershocks”

Some properties of AftershocksDave Jackson

UCLA

Oct 25, 2011

UC BERKELEY

Page 2: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Conclusions

• Aftershocks are not clearly defined• Whether aftershocks have different

magnitude dependence or triggering potential depends upon their definition

• For most reasonable definition, there is suggestive but weak evidence that triggered earthquakes have different magnitude distributions and triggering potential.

Page 3: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

ETAS model of earthquake triggering, from Zhuang et al 2008

Page 4: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 5: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Stochastic Declustering

Page 6: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Definitions

• Mainshock: largest earthquake in a cluster• Foreshock : An earthquake in a cluster,

occuring before the mainshock• Aftershock: An earthquake in a cluster,

occuring after the mainshock• Triggered event: An earthquake with a low

value of the independence probablity f, independent of its own magnitude

• Spontaneous event: An earthquake with a high value of the independence probability

Page 7: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 8: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 9: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 10: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 11: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 12: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Empirical, So Cal, mt=4.2 plus = triggered, triangle = spontaneous

Page 13: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Synthetic data, same parameters as for empirical study

Page 14: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Synthetic data, triggering of mag 4.2+ by mag 3.7+

Page 15: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Magnitude distributions for spontaneous and triggered quakes, California m4.7+ after 1933

Page 16: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Magnitude distribution after randomizing the independence weightings

Page 17: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 18: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011
Page 19: Some Properties of “aftershocks” Some properties of Aftershocks Dave Jackson UCLA Oct 25, 2011

Conclusions

• Aftershocks are not clearly defined• Whether aftershocks have different magnitude

dependence or triggering potential depends upon their definition

• For most reasonable definition, there is suggestive but weak evidence that triggered earthquakes have different magnitude distributions and triggering potential. Conclusions depend on clustering model