HR: 1340h
AN: S33C-1463    [Abstracts]
TI: Comparing two earthquake predictability evaluation approaches: Molchan error trajectory and likelihood
AU: * Zechar, J D
EM: zechar@usc.edu
AF: University of Southern California, Department of Earth Sciences, 3651 Trousdale Pkwy, Los Angeles, CA 90089, United States
AU: Jordan, T H
EM: tjordan@usc.edu
AF: University of Southern California, Department of Earth Sciences, 3651 Trousdale Pkwy, Los Angeles, CA 90089, United States
AU: Jordan, T H
EM: tjordan@usc.edu
AF: Southern California Earthquake Center, 3651 Trousdale Parkway, Suite 169, Los Angeles, CA 90089, United States
AU: Schorlemmer, D
EM: ds@usc.edu
AF: University of Southern California, Department of Earth Sciences, 3651 Trousdale Pkwy, Los Angeles, CA 90089, United States
AU: Schorlemmer, D
EM: ds@usc.edu
AF: Southern California Earthquake Center, 3651 Trousdale Parkway, Suite 169, Los Angeles, CA 90089, United States
AU: Liukis, M
EM: liukis@usc.edu
AF: Southern California Earthquake Center, 3651 Trousdale Parkway, Suite 169, Los Angeles, CA 90089, United States
AB: The Regional Earthquake Likelihood Models (RELM) working group began a collaborative earthquake predictability experiment involving a dozen five-year forecasts of earthquake occurrence in a California natural laboratory. The forecasts are probabilistic in the sense that they consist of expected number of earthquakes in space-time-magnitude bins. Statistical hypothesis testing of the forecasts is achieved via three scores based on likelihood. Earthquake forecasts that do not adhere to the RELM template cannot be accommodated by these likelihood scoring tests. In order for the Collaboratory for the Study of Earthquake Predictability (CSEP) to succeed, it is desirable to expand the scope of predictability experiments; in doing so, additional evaluation techniques must be considered. We explore a score based on the Molchan error diagram, which plots miss rate versus the fraction of space occupied by alarms, and is commonly used to assess the skill of earthquake prediction methods using a single alarm set (i.e., one point on the error diagram). We supplement the point wise approach with a cumulative performance measure based on the normalized area under an error trajectory. We call this the area skill score; a score of unity indicates perfect skill and a score of zero indicates perfect non-skill. Both the RELM and the Molchan error trajectory techniques can be applied to the five-year forecasts of California seismicity. We compare the two methods both conceptually and practically – that is, by examining the results of their application to a dozen five-year forecasts and observed seismicity.
UR: http://www.cseptesting.org
DE: 3245 Probabilistic forecasting (3238)
DE: 7223 Earthquake interaction, forecasting, and prediction (1217, 1242)
SC: Seismology [S]
MN: 2007 Fall Meeting