REDPy Catalogs for Mauna Loa (2012-2024)

REDPy (short for Repeating Earthquake Detector in Python) is a seismic tool for automatically detecting and grouping earthquakes based on the similarity of their waveforms into "families" of related events. It can be used in near real-time for monitoring or for research. The catalogs in this release bracket the late-2022 eruption of Mauna Loa, Island of Hawaiʻi; two separate catalogs are provided for different uses. The REDPy "Canonical" Catalog spans from 2012-01-01 to 2024-01-01 (UTC). Early 2012 is the start of openly available data from the "HV" network archived in the NSF SAGE Facility (https://service.iris.edu/). Waveforms from the vertical components of six seismometers near the summit of Mauna Loa (i.e., ALEP, MOKD, WILD, SWRD, TRAD, and DAND) were downloaded and filtered from 1 to 10 Hz. Triggers were created at the time of known local earthquakes or when four of the six stations exceed the default threshold for the STA/LTA triggering algorithm. Events were considered part of a family if they cross-correlate above 0.7 with at least one other member of the family on at least three of the six stations. This catalog most closely resembles the configuration that was used for near real-time monitoring in the lead-up to the eruption, but has been processed for reproducibility. The REDPy "HF" (Higher Frequency) Catalog spans from 2022-01-01 to 2023-01-01 (UTC). Apart from the shorter time span, the fundamental difference from the "Canonical" catalog is that the waveforms were filtered from 5 to 15 Hz after download. During the eruption, volcanic tremor dominated the recorded seismograms from 1 to 5 Hz, and this setting aimed to filter that out and allow discrete earthquakes to trigger during the eruption. The ~11 months of time prior to the eruption are included for comparison with the "Canonical" catalog. This release contains the inputs and commands used to generate the catalogs, as well as both the text catalogs and interactive outputs. See README.txt for further documentation.