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Regional Travel-Time Uncertainty and Seismic Location Improvement Using a Three-Dimensional a priori Velocity Model

¹ Atmospheric, Earth, and Energy Department
Energy and Environment Directorate
Lawrence Livermore National Laboratory
P.O. Box 808, L-205
Livermore, California 94551
 (M.P.F., S.C.M.)
² Department of Earth and Atmospheric Sciences
Saint Louis University
3507 Laclede Avenue
St. Louis, Missouri 63103
 (K.D.K.)

We demonstrate our ability to improve regional travel-time prediction and seismic event location accuracy using an a priori 3D velocity model of Western Eurasia and North Africa (WENA1.0). Travel-time residuals are assessed relative to the iasp91 model for approximately 6000 Pg, Pn, and P arrivals, from seismic events having 2 epicenter accuracy between 1 km and 25 km (ground truth 1 [GT1] and GT25, respectively), recorded at 39 stations throughout the model region. Ray paths range in length between 0° and 40° (local, regional, and near teleseismic) providing depth sounding that spans the crust and upper mantle. The dataset also provides representative geographic sampling across Eurasia and North Africa including aseismic areas. The WENA1.0 model markedly improves travel-time predictions for most stations with an average variance reduction of 29% for all ray paths from the GT25 events; when we consider GT5 and better events alone, the variance reduction is 49%. For location tests we use 196 geographically distributed GT5 and better events. In 134 cases (68% of the events), locations are improved, and average mislocation is reduced from 24.9 km to 17.7 km. We develop a travel-time uncertainty model that is used to calculate location coverage ellipses. The coverage ellipses for WENA1.0 are validated to be representative of epicenter error and are smaller than those for iasp91 by 37%. We conclude that a priori models are directly applicable where data coverage limits tomographic and empirical approaches, and the development of the uncertainty model enables merging of a priori and data-driven approaches using Bayesian techniques.

Online material: Correction surfaces and histograms of travel-time residuals for 40 stations.