Seismic velocity changes at White Island volcano, New Zealand, using ten years of ambient noise interferometry

<p>Seismic velocity changes at volcanoes carry information about stresses present within hydrothermal and magmatic systems. In this thesis, temporal velocity changes are measured at White Island volcano using ambient noise interferometry between 2007–2017. This period contains multiple well-documented eruptions starting in 2012, following an inactive period that extends back over a decade. Three primary objectives are identified: (1) investigate what seismic velocity changes can tell us about dynamic changes beneath the volcano, (2) investigate non-volcanic sources and their possible influence on interpretations, and (3) consider the potential for real-time monitoring using ambient-noise. These objectives extend beyond White Island volcano, with implications for ambient noise monitoring of volcanoes globally. Two different approaches are used to measure velocity changes at White Island. The first involves cross-correlating noise recorded by pairs of seismic stations. Velocity changes are sought by averaging changes recorded across ten station-pairs that consist of an onshore station and a station on the volcano. The second approach involves cross-correlating the different components of individual seismic stations. This represents a less traditional approach to monitoring volcanoes, but is well-suited to White Island which has one permanent station active throughout eruptive activity. Single seismic stations located onshore are also processed to investigate background regional changes. Two periods of long-term velocity increases are detected at the volcano. The first occurs during a highly active period in 2012–2013 and the second occurs in the months preceding an explosive eruption in April 2016. Comparison with velocities recorded by onshore stations suggest a meteorological source for these changes is unlikely. Velocity increases are therefore interpreted to reflect cracks closing under increased pressures beneath the volcano. Similarly, a rapid decline in the velocity within 2–3 months of the April 2016 eruption is interpreted to reflect depressurization of the system. In addition to volcanic sources, we also find clear evidence of non-volcanic processes influencing velocity changes at the volcano. Two clear co-seismic velocity decreases of approximately 0.05–0.1% are associated with a Mw 5.2 earthquake in 2008 — within 10 km of the volcano — and the Mw 7.1 East Cape earthquake in 2016. The East Cape earthquake — located 200 km away from the volcano — produces significant velocity decreases over a large region, as detected by stations onshore and on White Island. This likely reflects dynamic stress changes as a result of passing seismic waves, with an eruption two weeks later interpreted here to have been triggered by this event. Finally, we identify similarities between annual variations recorded by onshore stations and changes at the volcano, suggesting an environmental influence. Velocity changes at White Island therefore represent a complex interaction of volcanic and non-volcanic processes, highlighting the need for improved understanding of external sources of change to accurately detect short-term eruptive precursors.</p>

Seismic velocity changes at White Island volcano, New Zealand, using ten years of ambient noise interferometry

<p>Seismic velocity changes at volcanoes carry information about stresses present within hydrothermal and magmatic systems. In this thesis, temporal velocity changes are measured at White Island volcano using ambient noise interferometry between 2007–2017. This period contains multiple well-documented eruptions starting in 2012, following an inactive period that extends back over a decade. Three primary objectives are identified: (1) investigate what seismic velocity changes can tell us about dynamic changes beneath the volcano, (2) investigate non-volcanic sources and their possible influence on interpretations, and (3) consider the potential for real-time monitoring using ambient-noise. These objectives extend beyond White Island volcano, with implications for ambient noise monitoring of volcanoes globally. Two different approaches are used to measure velocity changes at White Island. The first involves cross-correlating noise recorded by pairs of seismic stations. Velocity changes are sought by averaging changes recorded across ten station-pairs that consist of an onshore station and a station on the volcano. The second approach involves cross-correlating the different components of individual seismic stations. This represents a less traditional approach to monitoring volcanoes, but is well-suited to White Island which has one permanent station active throughout eruptive activity. Single seismic stations located onshore are also processed to investigate background regional changes. Two periods of long-term velocity increases are detected at the volcano. The first occurs during a highly active period in 2012–2013 and the second occurs in the months preceding an explosive eruption in April 2016. Comparison with velocities recorded by onshore stations suggest a meteorological source for these changes is unlikely. Velocity increases are therefore interpreted to reflect cracks closing under increased pressures beneath the volcano. Similarly, a rapid decline in the velocity within 2–3 months of the April 2016 eruption is interpreted to reflect depressurization of the system. In addition to volcanic sources, we also find clear evidence of non-volcanic processes influencing velocity changes at the volcano. Two clear co-seismic velocity decreases of approximately 0.05–0.1% are associated with a Mw 5.2 earthquake in 2008 — within 10 km of the volcano — and the Mw 7.1 East Cape earthquake in 2016. The East Cape earthquake — located 200 km away from the volcano — produces significant velocity decreases over a large region, as detected by stations onshore and on White Island. This likely reflects dynamic stress changes as a result of passing seismic waves, with an eruption two weeks later interpreted here to have been triggered by this event. Finally, we identify similarities between annual variations recorded by onshore stations and changes at the volcano, suggesting an environmental influence. Velocity changes at White Island therefore represent a complex interaction of volcanic and non-volcanic processes, highlighting the need for improved understanding of external sources of change to accurately detect short-term eruptive precursors.</p>

A unified probabilistic framework for volcanic hazard and eruption forecasting

The main purpose of this article is to emphasize the importance of clarifying the probabilistic framework adopted for volcanic hazard and eruption forecasting. Eruption forecasting and volcanic hazard analysis seek to quantify the deep uncertainties that pervade the modeling of pre-, sin-, and post-eruptive processes. These uncertainties can be differentiated into three fundamental types: (1) the natural variability of volcanic systems, usually represented as stochastic processes with parameterized distributions (aleatory variability); (2) the uncertainty in our knowledge of how volcanic systems operate and evolve, often represented as subjective probabilities based on expert opinion (epistemic uncertainty); and (3) the possibility that our forecasts are wrong owing to behaviors of volcanic processes about which we are completely ignorant and, hence, cannot quantify in terms of probabilities (ontological error). Here we put forward a probabilistic framework for hazard analysis recently proposed by Marzocchi and Jordan (2014), which unifies the treatment of all three types of uncertainty. Within this framework, an eruption forecasting or a volcanic hazard model is said to be complete only if it (a) fully characterizes the epistemic uncertainties in the model's representation of aleatory variability and (b) can be unconditionally tested (in principle) against observations to identify ontological errors. Unconditional testability, which is the key to model validation, hinges on an experimental concept that characterizes hazard events in terms of exchangeable data sequences with well-defined frequencies. We illustrate the application of this unified probabilistic framework by describing experimental concepts for the forecasting of tephra fall from Campi Flegrei. Eventually, this example may serve as a guide for the application of the same probabilistic framework to other natural hazards.

On the Connection between the 2008–2009 Activation of the Koryakskii Volcano and Deep Magmatic Processes

Abstract—The last activation of the Koryakskii volcano in 2008–2009 was accompanied by intense fumarolic and seismic activity. Volcanic activity peaked in March–April 2009 when ash plume rose to a height of 5.5 km and extended laterally over more than 600 km. To understand the dynamics of the volcanic processes and to forecast the further course of the events, it is relevant to establish whether the eruption was associated with a rise of magma to beneath the volcanic edifice or caused by fracturing of the volcano’s basement and penetration of groundwater into a high temperature zone. Based on the analysis of the images from the Japanese satellite ALOS-1 using satellite radar interferometry methods, the slope displacements of the Koryakskii volcano during its last activation have been estimated for the first time. The displacements reach 25 cm and cannot be explained by the formation of a layer of volcanic ash deposits or by the slope processes. The most likely cause of the displacements should be recognized to be the intrusion of magmatic material into the volcano edifice with the formation of a fracture with its lower edge at a depth of 0.5 km above sea level, with a size of 1.0 and 2.4 km along the strike and dip, respectively, and with a dip angle from 45° to 60°. Therefore, the processes taking place beneath the volcano can be threatening to the nearby localities and infrastructure and require continuous monitoring.

The novel pushing gravity model and volcanic activity. Is alignment of planets with compact stars a possible cause of natural phenomena?

We developed the model, and carried out its discussion at the PIRT-2021 conference, within the framework of the research topic “External Forcing on Volcanoes and Volcanic Processes: Observations, Analysis and Implications” announced by the journal “Frontiers in Earth Science” in October 2020. Besides other, external processes considered in this Research Topic included astronomical. In this study, in the category “Hypothesis and Theory”, we investigate how changes in the position of large bodies of the Solar system can cause natural phenomena, associated with the movement of free masses, such as volcanism, earthquakes and landslides in the lithosphere, as well as various catastrophic events in the atmosphere and hydrosphere. The analysis has shown that the discovered phenomena of celestial bodies’ alignments accompanying manifestations of natural phenomena require going beyond the standard cosmological model and clarify the fundamental mechanism of gravity. We propose the novel Bidirectional Pushing Gravitation model (BPG), which, in addition to application in Earth Sciences, may occur useful in Astrophysics, Cosmology and Gravitation research.

Petrology of the opening eruptive phase of the 2021 Cumbre Vieja eruption, La Palma, Canary Islands

The first products of the current Cumbre Vieja eruption comprise simultaneous tephra fall from near-continuous, gas-rich eruption plumes and lava flows. From combined field, petrographic and geochemical analyses we identify: low percentage mantle melts with a variably-equilibrated multimineralic crystal-cargo and compositional fractionation by eruptive processes. Hence petrology can untangle complex magmatic and volcanic processes for this eruption, which through further study can assist in active decision making.

Terrestrial Analogs to Planetary Volcanic Processes

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Planetary Science. Please check back later for the full article. More than 50 years of solar system exploration has revealed the great diversity of volcanic landscapes beyond the Earth, be they formed by molten rock, liquid water, or other volatile species. Classic examples of giant shield volcanoes, solidified lava flows, extensive ash deposits, and volcanic vents can all be identified but, with the exception of eruptions seen on the Jovian moon Io, none of these planetary volcanoes have been observed in eruption. Consequently, the details of the processes that created these landscapes must be inferred from the available spacecraft data. Despite the increasing improvement in the spatial, temporal, compositional, and topographic characteristics of the data for planetary volcanoes, details of the manner in which they formed are not clear. However, terrestrial eruptions can provide numerous insights into planetary eruptions, whether they result in the emplacement of lava flows, explosive eruptions due to volatiles in the magma, or the interaction between hot lava and water or ice. In recent decades, growing attention has therefore been directed at the use of terrestrial analogs to help interpret volcanic landforms and processes on the terrestrial planets (Mercury, Venus, the Moon, and Mars) and in the outer solar system (the moons of Jupiter and Saturn, the larger asteroids, and potentially Pluto). In addition, terrestrial analogs not only provide insights into the geologic processes associated with volcanism, but they can also serve as test sites for the development of instrumentation to be sent to other worlds, as well as serve as a training ground for manned and unmanned explorers seeking to better understand volcanism throughout the solar system.

MagmaFOAM-1.0: a modular framework for the simulation of magmatic systems

Numerical simulations of volcanic processes play a fundamental role in understanding the dynamics of magma storage, ascent and eruption. The recent extraordinary progress in computer performance and improvements in numerical modeling techniques allow simulating multiphase systems in mechanical and thermodynamical disequilibrium. Nonetheless, the growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques. In this work we present MagmaFOAM, a library based on the open source computational fluid dynamics software OpenFOAM, that incorporates models for solving the dynamics of multiphase, multicomponent magmatic systems. Retaining the modular structure of OpenFOAM, MagmaFOAM allows run-time selection of the solution technique depending on the physics of the specific process, and sets a solid framework for in-house and community model development, testing and comparison. MagmaFOAM models thermo-mechanical non-equilibrium phase coupling and phase change, and implements state-of-the-art multiple volatile saturation models and constitutive equations with composition-dependent and space-time local computation of thermodynamic and transport properties. Code testing is performed using different multiphase modeling approches for processes relevant to magmatic systems: Rayleigh-Taylor instability, for buyoancy-driven magmatic processes; multiphase shock tube simulations, propedeutical to conduit dynamics studies; bubble growth and breakage in basaltic melts. Benchmark simulations illustrate the capabilities and potential of MagmaFOAM to account for the variety of non-linear physical and thermodynamical processes characterizing the dynamics of volcanic systems.

A Unified Probabilistic Framework for Volcanic Hazard and Eruption Forecasting

The main purpose of this article is to emphasize the importance of clarifying the probabilistic framework adopted for volcanic hazard and eruption forecasting. Eruption forecasting and volcanic hazard analysis seeks to quantify the deep uncertainties that pervade the modeling of pre-, sin- and post-eruptive processes. These uncertainties can be differentiated into three fundamental types: (1) the natural variability of volcanic systems, usually represented as stochastic processes with parameterized distributions (aleatory variability); (2) the uncertainty in our knowledge of how volcanic systems operate and evolve, often represented as subjective probabilities based on expert opinion (epistemic uncertainty); and (3) the possibility that our forecasts are wrong owing to behaviors of volcanic processes about which we are completely ignorant and, hence, cannot quantify in terms of probabilities (ontological error). Here we put forward a probabilistic framework for hazard analysis recently proposed by Marzocchi &amp; Jordan (2014), which unifies the treatment of all three types of uncertainty. Within this framework, an eruption forecasting or a volcanic hazard model is said to be complete only if it (a) fully characterizes the epistemic uncertainties in the model's representation of aleatory variability and (b) can be unconditionally tested (in principle) against observations to identify ontological errors. Unconditional testability, which is the key to model validation, hinges on an experimental concept that characterizes hazard events in terms of exchangeable data sequences with well-defined frequencies. We illustrate the application of this unified probabilistic framework by describing experimental concepts for the forecasting of tephra fall from Campi Flegrei. Eventually, this example may serve as a guide for the application of the same probabilistic framework to other natural hazards.