Understanding volcanic eruption triggers is critical towards anticipating future activity. While internal magma dynamics typically receive more attention, the influence of external processes remains less understood. In this context, we explore the relationship between seasonal snow cycles and eruptive activity at Ruapehu, New Zealand. This is motivated by apparent seasonality in the eruptive record, where a higher than expected proportion of eruptions (post-1960) occur in spring (including the two previous eruptions of 2006 and 2007). Employing recent advancements in passive seismic interferometry, we compute sub-surface seismic velocity changes between 2005–2009 using the cross-wavelet transform approach. Opposite trends in velocities are identified on and off the volcano, with stations closest to the summit recording a winter high closely correlated with the presence of snow. Inverting for depth suggests these changes occur within the upper 200–300 m. Reduced water infiltration (as precipitation falls as snow) is considered the likely control of seasonal velocities, while modeling also points to a contribution from snow-loading. We hypothesise that this latter process may play a crucial role towards explaining seasonality in the eruptive record. Specifically, loading/unloading may influence the volcanic system through increased degassing, thereby increasing the likelihood of small, gas-driven, eruptions. Our findings shed light on the complex interactions between volcanoes and external environmental processes, highlighting the need for more focused research in this area. Pursuing this line of inquiry has significant implications towards improved risk and hazard assessments at not just Ruapehu, but also other volcanoes globally that experience seasonal snow cover.

Passive seismic methods are considered as cost-effective and environmental-friendly alternatives to active (reflection) seismic methods. We have acquired co-located active and passive seismic surveys over a metal-endowed Archean granite-greenstone terrane in the Larder Lake area to investigate the reliability of the estimated elastic properties using the passive seismic methods. The passive seismic data was processed using two different data processing approaches, the ambient noise surface wave tomography (ANSWT) and receiver function analysis methods to generate shear-wave velocity and P- to S-wave (P-S) convertibility profiles of the subsurface, respectively. The Cadillac-Larder Lake Fault (CLLF) was imaged as a south-dipping sub-vertical zone of weak reflectivity in the reflection seismic profile. To the north of the CLLF, a package of north-dipping reflections in the upper-crust (at depths of 5-10 km) resides on the boundary of high (on the top) and low (on the bottom) shear-wave velocity zones estimated using the ANSWT method. This package of reflections is most likely caused by overlaying mafic volcanic and underlying felsic intrusive rocks. The P-S convertibility profile imaged the Moho boundary at ~40 km depth as well as a south-dipping slab that penetrates into the mantel which was interpreted to be either caused by the delamination of the lower crust or a possible deeper extension of the Porcupine-Destor Fault. Overall, the reflectivity, shear-wave velocity, and P-S convertibility profiles exhibited a good correlation and provided a detailed image of the subsurface lithological structure to a depth of 10 km.

Ambient noise surface wave tomography is an environmentally friendly and cost-effective seismic technique for subsurface imaging. However, noise sources acting from preferential azimuths may introduce bias in the Green’s function reconstruction and in the resultant velocity models. This study, focused at the deposit scale, investigates how to correctly merge the different phase velocity measurements at various frequencies, in order to fill the gap between natural and anthropogenic noise sources while adjusting the bias caused by changes in the azimuth of the source. The target is the Marathon PGE-Cu deposit (Ontario, Canada), an alkaline intrusion containing gabbros and syenites (ø = 25 km). Mineralisation is hosted by gabbros close to the inward-dipping footwall of the intrusion. The country rocks are Archaean volcanic breccias. 1024 vertical-component receivers were deployed for 30 days in two overlapping grids: a 200 m x 6040 m dense array with node spacing of 50 m, and a 4000 m x 2500 m sparse array with node spacing of 150 m. Beamforming analysis of the recorded data indicates variations in the distribution of noise. Below 5 Hz, the Lake Superior (SSW) is the dominant source of noise, while above 12 Hz, noise from the Canadian Pacific Railway and Trans-Canada highway (SW) is prominent. In the 5 - 12 Hz frequency band, surface-wave energy is dominant, and it comes from the Lake Superior and vehicle traffic. Between 12 Hz and 20 Hz, the signal is characterized by body-wave energy combined with less energetic surface waves, while above 20 Hz the imprint of body waves is dominant. We retrieved the fundamental mode of Rayleigh wave propagation from the recorded data set. The signal was down-sampled to 50 Hz, divided into segments of 30 minutes, cross-correlated and stacked. Surface wave dispersion curves were extracted from 2-km-long arrays. Besides, various phase velocity measurements were applied. Phase-velocities were inverted to S-wave velocity structures using different probabilistic approaches. The overall results show a high-velocity shallow anomaly, probably related to the gabbro intrusion hosting the mineralization, as well as other structures consistent with the geological model inferred from surface mapping and drill logs.