This study presents a spectral scaling method that utilizes transfer functions to generate ground motions for larger magnitude earthquakes using data from smaller events or swarms occurring in the same seismic source region. The method is based on Aki’s theory of universal similarity of earthquake radiation in which the Fourier amplitude spectra (FAS) of far-field radiated body waves can be approximated as a truncated power law with frequency, and far-field body-wave displacements scale as the moment-rate function together with constants that account for radiation pattern and geometric spreading. Assuming self-similarity in earthquake source properties, an FAS of a smaller magnitude earthquake can be scaled through a transfer function to predict the FAS of a larger magnitude earthquake. We assessed the performance of our spectral scaling approach by analyzing large datasets from the 2019 Ridgecrest and 2010 El Mayor-Cucapah earthquake sequences, comparing it with the performance of a commonly used ground motion model (GMM). The results demonstrate the effectiveness of the spectral scaling method compared with the GMM in predicting ground motions, particularly for long-period response in basin areas.
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