[ 1 ] We investigate the global variation of earthquake stress drops using spectra of about 2000 events of m b 5.5 between 1990 and 2007. We use an iterative least squares method to isolate source displacement spectra from travel path and receiver contributions, based on ac onvolutional model. The observed P wave source spectra are corrected with a globally averaged empirical correction spectrum and estimates of near-source attenuation. Assuming aBrune-type source model, we estimate corner frequencies and compute stress drops. Stress drop estimates for individual earthquakes range from about 0.3 to 50 MPa, but the median stress drop of about 4M Pa does not vary with moment, implying earthquake self-similarity over the M w =5.2 to 8.3 range of our data. Acomparison of our results with previous studies confirms this observation over most of the instrumentally observable magnitude range. While the absolute values of our estimated stress drops depend upon the assumed source model, we identify relative regional variations of stress drop that are robust with respect to the processing parameters and modeling assumptions, which includes an inherent assumption of constant rupture velocity.W efind ad ependence of median stress drop on focal mechanism, with af actor of 3-5t imes higher stress drops for strike-slip earthquakes and also find afactor of 2times higher stress drops for intraplate earthquakes compared to interplate earthquakes.Citation: Allmann, B. P., and P. M. Shearer (2009), Global variations of stress drop for moderate to large earthquakes, J. Geophys.

We estimate source parameters from spectra of 42367 earthquakes between 1984 and 2005 that occurred in the Parkfield segment of the San Andreas Fault in central California. We use a method that isolates the source term of the displacement spectra based on a convolutional model and correct the observed P wave source spectra with a spatially varying empirical Green's function (EGF). Our Brune‐type stress drop estimates vary from 0.1 to over 100 MPa with a median value of 6.75 MPa, which is nearly constant with moment, implying self‐similarity over the ML = 0.5 to 3.0 range of our data. The corner frequency decreases for earthquakes at shallower depths, consistent with slower rupture velocities and reduced shear wave velocities in local velocity models. The estimated median stress drops show significant lateral variations: we find lower stress drops in the Middle Mountain asperity and along the creeping fault section, and higher stress drops in the hypocentral region of the 2004 M6.0 Parkfield earthquake. The main shock did not alter the overall pattern of high and low stress drop regions. However, a statistical test reveals areas with significant changes in computed stress drops after the main shock, which we compare to estimated absolute shear stress changes from a main shock slip model. By calculating Δt* from the spectral EGF ratio, we also identify areas with increased attenuation after the main shock, and we are able to distinguish source effects and near‐source attenuation effects in the spectral analysis. These results are confirmed independently from spectral ratios of repeating microearthquake clusters.

S U M M A R YMoment magnitudes (M W ) are computed for small and moderate earthquakes using a spectral fitting method. 40 of the resulting values are compared with those from broadband moment tensor solutions and found to match with negligible offset and scatter for available M W values of between 2.8 and 5.0. Using the presented method, M W are computed for 679 earthquakes in Switzerland with a minimum M L = 1.3. A combined bootstrap and orthogonal L1 minimization is then used to produce a scaling relation between M L and M W . The scaling relation has a polynomial form and is shown to reduce the dependence of the predicted M W residual on magnitude relative to an existing linear scaling relation. The computation of M W using the presented spectral technique is fully automated at the Swiss Seismological Service, providing real-time solutions within 10 minutes of an event through a web-based XML database. The scaling between M L and M W is explored using synthetic data computed with a stochastic simulation method. It is shown that the scaling relation can be explained by the interaction of attenuation, the stress-drop and the Wood-Anderson filter. For instance, it is shown that the stress-drop controls the saturation of the M L scale, with low-stress drops (e.g. 0.1-1.0 MPa) leading to saturation at magnitudes as low as M L = 4.