Source Parameter Estimation Using Site‐Corrected Source Spectra for the 2019 Ridgecrest Earthquake Sequence in Southern California Available to Purchase

We estimated source parameters, such as corner frequency (⁠$fc$⁠), stress drop (⁠$Δσ$⁠), and seismic moment (⁠$M0$⁠) for the 2019 Ridgecrest earthquake sequence in southern California. Source spectra used to estimate the source parameters were corrected with the site decay parameter (⁠$κ0$⁠) along with geometrical spreading and inelastic attenuation. The Ridgecrest dataset consisting of 12,943 events from the 2019 Ridgecrest earthquake sequence, distributed by the Community Stress Drop Validation Study of the Southern California Earthquake Center, offers opportunities to explore self‐similarity between events and compare source parameter estimates across multiple studies. Using the dataset, $κ$‐values were measured from a linear slope of the natural logarithm of acceleration Fourier spectrum at high frequencies (6–39 Hz). Consequently, the $κ0$‐values of 46 stations were obtained using two methods based on the distance dependence of $κ$⁠. The source parameters for 9966 events were estimated using the Snoke method (Snoke, 1987). The measurement of $κ$ revealed an obvious magnitude dependence at most stations, and depth dependence at shallower depths (∼3 km) was observed at 31 stations. By correcting source spectra with $κ0$⁠, alignment with the Brune model was improved, increasing the accuracy of $fc$ and $Δσ$⁠. Across 736 selected events with a magnitude range of $Mw$ 2.0–4.9, we found negligible dependence between magnitude and $Δσ$ (with a median value of 12.6 MPa), consistent with event self‐similarity. We attribute the observed depth dependence of $Δσ$ to vertically heterogeneous attenuation with depth. Despite uncertainties in the estimation of $κ0$ and the source parameters, the median of $Δσ$ falls within the range of those of previous studies, but we found stronger evidence of self‐similarity (Trugman, 2020; Shearer et al., 2022; Bindi et al., 2023a,b). Collectively, these findings suggest that our method for correcting the spectrum is sound.