A composite source model is presented for convolution with synthetic Green's functions, in order to synthesize strong ground motions due to a complex rupture process of a large earthquake. Subevents with a power‐law distribution of sizes are located randomly on the fault. Each subevent radiates a displacement pulse with the shape of a Brune's pulse in the far field, at a time determined by a constant rupture velocity propagating from the hypocenter. Thus, all the input parameters have a physical basis. We simulate strong ground motions for event‐station pairs that correspond to records obtained in Mexico by the Guerrero accelerograph network. The synthetic accelerations, velocities, and displacements have realistic amplitudes, durations, and Fourier spectra.

The network of strong motion accelerographs in Mexico includes instruments that were installed, under an international cooperative research program, in sites selected for the high potenial of a large earthquake. The 19 September 1985 earthquake (magnitude 8.1) occurred in a seismic gap where an earthquake was expected. As a result, there is an excellent descripton of the ground motions that caused the disaster.

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A deep earthquake swarm in late 2003 at Lake Tahoe, California (Richter magnitude < 2.2; depth of 29 to 33 kilometers), was coeval with a transient displacement of 6 millimeters horizontally outward from the swarm and 8 millimeters upward measured at global positioning system station Slide Mountain (SLID) 18 kilometers to the northeast. During the first 23 days of the swarm, hypocentral depths migrated at a rate of 2.4 millimeters per second up-dip along a 40-square-kilometer structure striking north 30° west and dipping 50° to the northeast. SLID's transient velocity of 20 millimeters per year implies a lower bound of 200 nanostrains per year (parts per billion per year) on local strain rates, an order of magnitude greater than the 1996 to 2003 regional rate. The geodetic displacement is too large to be explained by the elastic strain from the cumulative seismic moment of the sequence, suggesting an aseismic forcing mechanism. Aspects of the swarm and SLID displacements are consistent with lower-crustal magma injection under Lake Tahoe.

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Wills, who reviewed the documentation, data, methods, and models, and provided excellent feedback that helped us to improve the quality of this product. We thank the National Earthquake Hazard Reduction Program (NEHRP) for funding the development of the maps. We also thank Teri Losano, Jill McCarthy, and Janet Slate for editing the manuscript.

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Kappa is a one-parameter estimator of the spectral amplitude decay with frequency of a seismogram. Low values (∼5 ms) indicate limited attenuation of highfrequency energy whereas higher values (∼40 ms) indicate high-frequency energy has been removed. Kappa is often assumed to be a site term and used in seismic designs. We address two key questions about kappa: (1) how to identify source, path, and site contributions to kappa; and (2) can kappa estimates from smaller earthquakes, and more readily accessible weak-motion recordings, be reasonably extrapolated to estimate kappa of larger earthquakes? The use of small earthquakes (M L < 1) presents many challenges and requires new approaches. We develop estimates of kappa for seismograms from 1137 small earthquakes recorded by the ANZA seismic network in southern California, and compare these to results from the stronger recorded shaking generated by 43 M L > 3:5 earthquakes inside the network. We find kappa from small earthquakes predicts the relative values of kappa for larger earthquakes (e.g., measurements at stations PFO and KNW are small compared with those at stations TRO and SND). For the SND and TRO data, however, kappa values from small earthquakes overpredict those from moderate and large earthquakes. Site effects are the most important contributor to kappa estimates, but the scatter within kappa measurements at a given station is likely caused by a significant contribution from near the source, perhaps related to near-source scattering. Because of this source-side variability, care is recommended in using individual small events as Green's functions to study source-time effects of moderate and large events.