Cooperative Institute for Research in Environmental Sciences

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Chapter 5. Solid-Earth Sciences

Earthquake Prediction Research

Servicing a portable seismic station in eastern Nepal.

Much of the innovative research at CIRES on prediction of earthquakes was led by Max Wyss, who left CU in 1991 to take up a position at the University of Alaska, Fairbanks. Variations in numerous geophysical parameters were examined for precursory patterns using global and regional (Hawaii, California, Turkey, Alaska) observations. In particular, Wyss and R. E. "Ted" Habermann, (who became and remains a NOAA CIRES fellow) focused attention on seismicity rate decreases (quiescence) prior to large earthquakes. As a crucial part of these studies, they developed quantitative tools for recognizing and understanding apparent seismicity variations caused by changes in seismic networks and data processing procedures. They demonstrated that many seismicity rate variations proposed as precursors are artificial and can be explained by common network changes. Wyss also investigated crustal uplift and subsidence as revealed by tide-gauge data and systematic variations in b-value as plausible precursors.

Kisslinger and Engdahl also carried out prediction studies, mostly based on observations with the Central Aleutians Seismic Network. A number of phenomena that have been suggested as precursory to an imminent earthquake were investigated. These included systematic rotation of focal mechanisms of local events before a stronger event, the isolation of possible asperities on the subduction thrust surface on the basis of the distribution of background seismicity and stress drops, variations in attenuation based on measurements of coda-Q, investigations of localized changes in seismic body-wave velocities prior to a strong event, and seismic quiescence. Of these, quiescence as detected with the data from an adequate local network emerged as most promising, but no consistently successful precursor has been identified.

Recent work by Rundle and others in the areas of non-linear continuum mechanics, chaotic behavior and the physics of complex systems may lead to advances in prediction technology, or at least to a better understanding of approaches to overcoming the difficulties. Rundle is approaching earthquake forecasting through the analysis of neural networks. Projects by his group have emphasized the development of techniques for understanding the space-time patterns and correlations that appear in many high-dimensional complex non-linear systems, including patterns of seismicity. The patterns are quantified in terms of eigenvectors of defined autocorrelation operators.

Measurements of tilt in the Long Valley Caldera, California, and of creep on the Hayward fault in the San Francisco Bay region, both directed by Bilham, are now part of early warning systems in these active zones. Data from these CIRES monitoring arrays are updated every 10 minutes on the following web site: http://quake.wr.usgs.gov/research/deformation/monitoring/index.html

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