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Ambient noise correlation analyses are largely used to monitor temporal medium changes generally associated with stress field variations and/or fluid movement. Here, we analyze the 2021 eruption of La Palma, the most active island in the Canary archipelago, to study its effects on the structure in a post-eruptive stage. To date, most of the studies, whether in volcanic environments or other geological systems, focus on determining seismic velocity changes that can be associated with precursory signals. In our study, we are interested in localizing the medium changes that permit constraining the depth of the most affected structure and suggesting possible mechanisms capable of inducing such alterations. The auto- and cross-correlation functions were computed using the phase cross-correlation strategy. The correlations were linearly stacked using a 3-day sliding window. The combination of these two approaches proved to render the best results. The analysis of 3 years of data resulted in the detection of occasional decorrelation before the eruption, followed by a well-defined decoherence period after the eruption. In addition, the relationship between the waveform correlation and lag time, using autocorrelations from before and after the eruption, permits identifying phase shifts and waveform distortion, which are sensitive to different parameters and, thus, have great importance in inferring the possible mechanism. Phase shifts occur when there is only velocity change without changing the structure, whereas waveform distortion is caused by a structural (geological) change. We also inferred the depths at which the most significant medium alterations occur. We observed that the decorrelation occurs at lag times corresponding to changes localized in depth. The surface structure appears to not have undergone significant medium changes for depths until approximately 8 km, either before or after the eruption. [ABSTRACT FROM AUTHOR]

In South Iceland, populated and agricultural areas are at risk of earthquakes due to their location within the South Iceland Seismic Zone (SISZ). In 2008, two moderate‐sized earthquakes (M5.8 and M5.9) occurred in Ölfus, the western end of this highly active transform zone. We analyze temporal seismic velocity variations (dv/v) related to the Ölfus earthquake doublet, using cross‐correlations of ambient noise in the frequency range of 0.1–3.0 Hz. The two mainshocks decrease the average velocity by 0.8% at the nearest stations. The co‐seismic changes are most noticeable from 0.7 to 1.7 Hz and affect a 40 km wide region. We present a first‐time comparison of dv/v to crustal deformation, seismicity, co‐seismic volumetric stress changes and reported PGA distribution for the Ölfus doublet. Ground accelerations caused by mainshocks at intermediate distances suggest that strong shaking‐related damage may contribute to the co‐seismic dv/v decrease. A rapid velocity increase (0.3%) in a month after the co‐seismic drop indicates crustal rock healing. We find 3‐months of post‐seismic decorrelation, followed by a nearly permanent velocity decrease (0.2%) confined to a shallow layer (1 km) until the end of the observation period. Afterslip and pore fluid effects in the near‐source region are likely to influence post‐seismic dv/v. We demonstrate that seismic interferometry can contribute to future fault‐zone monitoring operations in the SISZ by detecting small changes in velocity. Plain Language Summary: Strong earthquakes can occur in southwestern Iceland due to plate motions, posing a threat to human life and infrastructure. In 2008, two earthquakes struck the Ölfus region, causing widespread damage in the epicentral area. Sensitive instruments record naturally occurring ambient seismic signals which are originated from ocean waves, wind, and anthropogenic activity. A dramatic drop in seismic wave velocity is common during major quakes. The state‐of‐the‐art seismic methods based on these ambient waves allow us to detect minor changes in the velocity of seismic waves. We employ continuously recorded seismic data from three instruments to analyze for the first time such seismic velocity fluctuations related to moderate size earthquakes in Iceland. To interpret the complex mechanisms underlying these changes, we make use of multiple available data sets and compare them to our observations. Our findings suggest that seismic velocities decreased over a wide area, possibly due to earthquake‐induced ground shaking and rock damage. This study shows that velocity variations can be effectively measured with even sparsely placed seismometers and that they can be used in the future to monitor seismic zones in Iceland. Key Points: We apply ambient noise seismic interferometry to the 2008 Mw 6.1 south Iceland earthquake doubletTemporal seismic velocities decrease at the time of the earthquakes and recover post‐seismically up to 40 km in the upper crustThe co‐seismic and post‐seismic velocity changes correlate with GPS displacements [ABSTRACT FROM AUTHOR]

Passive seismic interferometry has become a popular technique towards monitoring. The method depends on the relative stability of background seismic sources in order to make repeatable measurements of subsurface properties. Such stability is typically assessed by examining the similarity of cross-correlation functions through time. Thus, techniques that can better assess the temporal similarity of cross-correlation functions may aid in discriminating between real subsurface processes and artificial changes related variable seismic sources. In this study, we apply agglomerative hierarchical clustering to cross-correlation functions computed using seismic networks at two volcanoes. This allows us to form groups of data that share similar characteristics and also, unlike common similarity measures, does not require a defined reference period. At Piton de la Fournaise (La Réunion island), we resolve distinct clusters that relate both to changes in the seismic source (volcanic tremor onset) and changes in the medium following volcanic eruptions. At Mt Ruapehu (New Zealand), we observe a consistency to cross-correlation functions computed in the frequency band of volcanic tremor, suggesting tremor could be useful as a repeatable seismic source. Our results demonstrate the potential of hierarchical clustering as a similarity measure for cross-correlation functions, suggesting it could be a useful step towards recognizing structure in seismic interferometry data sets. This can benefit both decisions in processing and interpretations of observed subsurface changes. [ABSTRACT FROM AUTHOR]