Abstract
The curation of seismic datasets is the cornerstone of seismological research and the starting point of machine-learning applications in seismology. We present a 21-year-long AI-ready dataset of diverse seismic event parameters, instrumentation metadata, and waveforms, as curated by the Pacific Northwest Seismic Network and ourselves. The dataset contains about 190,000 three-component (3C) waveform traces from more than 65,000 earthquake and explosion events, and about 9,200 waveforms from 5,600 exotic events. The magnitude of the events ranges from 0 to 6.4, while the biggest one is 20 December 2022 M6.4 Ferndale Earthquake. We include waveforms from high-gain (EH, BH, and HH channels) and strong-motion (EN channels) seismometers and resample to 100 Hz. We describe the earthquake catalog and the temporal evolution of the data attributes (e.g., event magnitude type, channel type, waveform polarity, and signal-tonoise ratio, phase picks) as the network earthquake monitoring system evolved through time. We propose this AI-ready dataset as a new open-source benchmark dataset.
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