Ian Vandevert

Earthquakes of similar magnitude can generate different amounts of high‐frequency radiation, contributing to variability in peak ground acceleration and uncertainties in ground‐motion prediction. These source differences are expressed in their P‐ and S‐wave spectra and affect spectral estimates of earthquake stress drop. Relative variations in spectra and related stress‐drop estimates among events are better resolved than their absolute values, and thus provide useful measurements for distinguishing earthquakes and their high‐frequency radiation content. Here, we quantify these differences in spectra using the frequency index (FI), defined as the logarithmic ratio of the average spectral amplitude in a high‐frequency band to that in a low‐frequency band. We then empirically correct for path and station effects to compute a new quantity, the normalized frequency index (nFI). We identify spatial variations in nFI values for aftershocks of the 2019 Ridgecrest earthquakes that correlate with published stress‐drop estimates. Our data‐driven approach can robustly identify variations in high‐frequency energy among different earthquakes and source regions, providing an observation‐based alternative to commonly applied stress‐drop estimation methods for characterizing source behavior at high frequencies.

Seismic moment and stress drop are crucial for understanding earthquake rupture processes, but their estimates often have large uncertainties for small earthquakes. Stress drop is typically inferred from an earthquake’s source spectrum based on theoretical models, but poorly constrained path corrections and other modeling assumptions limit the accuracy of stress-drop estimates. Here, we compute stress drops using both P and S waves for the 2019 Ridgecrest earthquake sequence, compare their estimates, and evaluate the associated uncertainties. We use spectral decomposition and apply the analysis to both types of waves for the same set of earthquakes, adjusting some S-wave parameter choices to obtain overall consistency with our P-wave results. Our approach fixes the corner frequency of small calibration earthquakes to reduce scatter in the estimated source parameters of the larger earthquakes. We find that assuming a lower high-frequency fall-off rate for S waves yields more consistent absolute stress-drop estimates between P and S waves. Our stress-drop estimates appear to increase slightly with magnitude for earthquakes with magnitudes >∼3.4. Furthermore, we find that the stress-drop estimates using both types of data exhibit coherent spatial variations. Earthquakes near the Coso geothermal field tend to have lower stress drops, and earthquakes near the M 7.1 hypocenter have higher stress-drop estimates. This spatial pattern is consistently observed in both the P- and S-wave results. We find no strong correlation between our stress-drop estimates and the M 7.1 Ridgecrest earthquake slip distribution, suggesting a heterogeneous stress environment for the Ridgecrest fault system.