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Abstract Liu et al. (2022,https://doi.org/10.1029/2021GL093691) used Rayleigh waves extracted from the cross‐correlation of ambient noise recorded by two stations to monitor the seismic velocity variations associated with the 2018 Kı̄lauea eruption. However, their study ignored the fact that the tremors on the Island of Hawai'i were dominated by a source at the Kı̄lauea summit before the eruption. Close inspection of the waveforms of the station pair PAUD‐STCD shows a simple, mistakenly identified wave traveling direction in Liu et al. (2022,https://doi.org/10.1029/2021GL093691). A correct wave traveling direction agrees with the noise source model, where the dominant tremor source should be at the Kı̄lauea summit. Because of the drastic change in the tremor source after the eruption, the cross‐correlation of the tremor records may reflect predominantly changes in the source rather than in the medium properties between the two stations. 

Abstract Seismic tomography of shield volcanoes can be used to better understand its structure, formation, and evolution. Previous tomographic studies on the Island of Hawai'i used body waves from earthquakes and active sources and had limited resolution in the shallow crust. In this study, we obtained the empirical Green Functions (EGFs) and empirical Green Tensors (EGTs) from cross‐correlating and stacking of multiyear seismic ambient noise recorded on the island. The EGFs/EGTs contained fundamental mode and first higher mode Rayleigh waves. The different modes were separated with a new algorithm and their group velocities were measured. Using the group arrival times, we inverted for two‐dimensional group velocity maps, which provide, for the first time, a full coverage of the Island of Hawai'i. From the group velocity maps, we inverted for a three‐dimensional shear wave velocity model, which shows strong lateral variations and yields new insights into the structure and growth of the volcanoes on the island: Kı̄lauea's East Rift Zone has prominent high velocities at all depths, whereas the current rift zones of Mauna Loa are characterized by intermediate to high velocities only at depths greater than 1 km below ground surface, which may be attributed to their relatively short history and less developed state. The flanks of the volcanoes, some cut by fault zones, displayed low velocities at over a range of depths, generally interpreted as consisting of extrusive rocks, which could be further shattered by faulting. 

Abstract Empirical Green Functions (EGFs) obtained from ambient noise cross‐correlation are important for imaging and monitoring underground structures. The EGFs on the Island of Hawai'i in different years are similar at low frequencies (0.1–0.4 Hz), but very different at high frequencies (0.4–1.0 Hz): Only the EGFs after the 2018 Kı̄lauea eruption show clear P waves. Grid search reveals a strong noise source near the Kı̄lauea summit before the eruption, which contaminated the EGFs but became silent after the eruption. Modeling of the P waves identifies the direct arrival and post‐critical reflections from two velocity discontinuities at 4.7 and 7.2 km depth beneath the island, which we interpret as the base of volcanic edifices and deposits and the boundary between basaltic dikes and gabbros, respectively. The P waves in EGFs could provide valuable high‐resolution constraints for monitoring deep magmatic changes and imaging the volcano structures. 

Abstract On 3 May 2018, Kīlauea Volcano, one of the most active volcanoes in the world, entered a new eruptive phase because of a dike intrusion in the East Rift zone. One day later, an Mw 6.9 earthquake, which was likely trigged by the dike intrusion, occurred in the submarine south flank of Kīlauea Volcano. In mid-July, an ocean-bottom seismometer (OBS) array consisting of 12 stations was deployed on the submarine south flank of Kīlauea Volcano to monitor the aftershocks and lava–water interaction near the ocean entry. Eleven OBSs were recovered in mid-September. Preliminary evaluation of the data reveals a large number of seismic and acoustic events, which provide a valuable dataset for understanding flank deformation and stability as well as lava–water interaction. Here, we introduce this dataset and document notable instrument malfunctions along with some initial seismic and acoustic observations.