Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post-eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10(-12) km asl and 1.5-2 x 10(6) kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (similar to 12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization. (c) 2021 Elsevier B.V. All rights reserved.

An important aspect of volcanic hazard assessment is determination of the level and character of background activity at a volcano so that deviations from background (called unrest) can be identified. Here, we compile the instrumentally recorded eruptive and noneruptive activity for 161 US volcanoes between 1978 and 2020. We combine monitoring data from four techniques: seismicity, ground deformation, degassing, and thermal emissions. To previous work, we add the first comprehensive survey of US volcanoes using medium-spatial resolution satellite thermal observations, newly available field surveys of degassing, and new compilations of seismic and deformation data. We report previously undocumented thermal activity at 30 volcanoes using data from the spaceborne ASTER sensor during 2000-2020. To facilitate comparison of activity levels for all US volcanoes, we assign a numerical classification of the Activity Intensity Level for each monitoring technique, with the highest ranking corresponding to an eruption. There are 96 US volcanoes (59%) with at least one type of detected activity, but this represents a lower bound: For example, there are 12 volcanoes where degassing has been observed but has not yet been quantified. We identify dozens of volcanoes where volcanic activity is only measured by satellite (45% of all thermal observations), and other volcanoes where only ground-based sensors have detected activity (e.g., all seismic and 62% of measured degassing observations). Our compilation provides a baseline against which future measurements can be compared, demonstrates the need for both ground-based and remote observations, and serves as a guide for prioritizing future monitoring efforts.

Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn- and post-eruptive behaviour. The Rabaul Volcano Observatory recorded similar to 24 h of seismicity and detected SO2 emissions similar to 16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC similar to 38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with similar to 6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn-eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes. (C) 2021 Elsevier B.V. All rights reserved.

An Excel spreadsheet compiling published major and trace element data for all important sublithospheric (upper mantle, transition zone and lower mantle) inclusion phases in diamond. Major element data are obtained by EPMA, trace element data by SIMS (ion microprobe) and LA-ICPMS. For additional details, please refer to Chapter 7: Geochemistry of Silicate and Oxide Inclusions in Sublithospheric Diamonds by Walter et al. in the RiMG volume "Diamond - Genesis, Mineralogy, and Geochemistry ", https://doi.org/10.2138/rmg.2022.88.07

Understanding the timing of critical changes in volcanic systems, such as the beginning and end of eruptive behavior, is a key goal of volcanic monitoring. Traditional approaches to forecasting these changes have used models motivated by the underlying physics of eruption onset, which assume that geophysical precursors will consistently display similar patterns prior to transition in volcanic state. We present a machine learning classification approach for detecting significant changes in patterns of volcanic activity, potentially signaling transitions during the onset or end of volcanic activity, which does not require a model of the physical processes underlying critical changes. We apply novelty detection, where models are trained only on data prior to eruption, to the precursory unrest at Augustine Volcano, Alaska in 2005. This approach looks promising for geophysically monitored volcanic systems which have been in repose for some time, as no eruptive data is required for model training. We compare novelty detection results with multi-class classification, where models are trained on examples of both non-eruptive and eruptive data. We contextualize the results of these classification models using constraints from petrological, satellite and visual observations from the 2006 eruption of Augustine Volcano. The transition from non-eruptive to eruptive behavior we identify in mid-November 2005 is in agreement with previous estimates of the initiation of dike intrusion prior to the 2006 eruption. We find that models which include multiple types of data (seismic, deformation, and gas emissions) can better distinguish between non-eruptive and eruptive data than models formulated on single data types.

Vanguard efforts in forecasting volcanic eruptions are turning to physics-based models, which require quantitative estimates of magma conditions during pre-eruptive storage. Below active arc volcanoes, observed magma storage depths vary widely (similar to 0 to 20 kilometers) and are commonly assumed to represent levels of neutral buoyancy. Here we show that geophysically observed magma depths (6 +/- 3 kilometers) are greater than depths of neutral buoyancy, ruling out this commonly assumed control. Observed depths are instead consistent with predicted depths of water degassing. Intrinsically wetter magmas degas water and crystallize deeper than dry magmas, resulting in viscosity increases that lead to deeper stalling of ascending magma. The water-depth relationship provides a critical constraint for forecasting models by connecting depth of eruption initiation to its volatile fuel.

On June 15, 2020, at 21:16 UTC, a locally-felt earthquake of magnitude 4.2 struck Unalaska Island, Alaska,similar to 15 km west of the town of Unalaska and the large fishing port of Dutch Harbor. The event was followed by a M4.1 earthquake at 00:34 UTC and several M3+ aftershocks, initiating a prolific sequence with hundreds of earthquakes recorded into late December. The earthquakes all locate about 12 km southeast of the summit of Makushin Volcano at 7 to 10 km depth. To date, no eruptive activity or other surface changes have been observed at the volcano in webcam images, GPS or InSAR. Seismic bursts close to volcanoes are often associated with the onset of unrest that can lead to eruption. However, determining whether seismicity reflects magmatic rather than tectonic stresses is often challenging, although critical for hazard assessments and risk management strategies. To investigate the triggering mechanisms of the recent Makushin seismicity, we integrate information from space-time patterns of the earthquake hypocenters with their fault-plane solutions. We relocate the swarm events using double-difference relocation techniques and a 3D velocity model and find that the earthquakes, although they seem to follow two predominant orientations (NW-SE and SW-NE), do not show clear clustering into preferred alignments. Similarly, we do not observe pronounced migration in time and space. Fault-plane solutions (FPS) for all but one M2.5+ earthquakes have P-axis orientations consistent with subhorizontal NW-SE oriented regional maximum compression, whereas many of the lower-magnitude earthquakes have P-axes perpendicular to regional maximum compression. This provides evidence for the presence of a local stress field likely induced by magma intrusion. Results from Coulomb stress modeling are also consistent with dike inflation modulated by stresses induced by the M4+ earthquakes. The seismic swarm is thus likely linked to a superposition of driving stresses from both magmatic and tectonic processes on pre-existing faults. The case of the 2020 Makushin swarm, with its unusual characteristics, challenges traditional swarm classification schemes and suggests that a reconsideration of the definition of seismic swarms as having the maximum magnitude event in the middle of the swarm is warranted. (c) 2022 The Authors. Published by Elsevier B.V.

Understanding the subsurface processes that generate volcanic unrest, including surface deformation, earthquakes, temperature increase, and gas emissions, is essential to improve the forecasting of volcanic eruptions. Volcanic gases exsolved from magma reservoirs can transfer heat towards the surface when the system is open, or pressurize the volcano and lead up to eruptions when the system is closed. Hence, the nature of the observed precursory signals is greatly dependent on whether exsolved volatiles accumulate or escape. In this study, we develop a two-dimensional finite element model to calculate the thermal and poroelastic responses of a volcano to gases that exsolve from depth and migrate to the surface through a pre-existing fractured conduit. This model is explored through a set of sensitivity tests to quantify the controls of gas fluxes and permeability on geophysical observables; and is used to interpret surface deformation (GPS), ground temperature, and seismicity data recorded before the 2006 eruption of Augustine volcano, Alaska, by utilizing the Ensemble Kalman Filter data assimilation technique and Coulomb stress calculations. Our results show that the permeable transfer of gas through a fractured conduit can yield a measurable thermal anomaly at the surface for at least one year before the eruption, consistent with ground- and remote sensing-based data. Moreover, gas flux increased about ten times around three months before the eruption, which might have accelerated hydrothermal alteration and reduced permeability of the conduit by several orders of magnitude, thus accumulating gases inside the volcanic edifice, generating surface deformation, and triggering volcano-tectonic earthquakes. Eventually, failure of the sealed pathways due to high overpressure led to the eruption. Multi-physical numerical models coupling gas flow with host rock deformation and heat transfer are useful tools to understand the triggering mechanisms of volcanic eruptions driven by volcanic gases. (c) 2022 Elsevier B.V. All rights reserved.

To examine controls on the local stress field at Augustine Volcano, Alaska, before its 2006 eruption, we calculated fault plane solutions for volcano-tectonic earthquakes from 2002 to 2006. The P-axis orientation was first aligned to the regional maximum compression (NW) and then rotated by about 90 degrees (perpendicular to the dike alignment) after the onset of surface deformation in mid-August 2005. Using 3D finite element models, we systematically evaluated the effects of tectonic stresses, volcanic edifice densities, and dike overpressures on the local stress field orientation. Combining data and models to generate "phase diagrams" of different stress controls by these competing effects, we argue that moderate tectonic stress of 2-3 MPa at 600 m above sea level slightly exceeded the edifice loading before the precursory deformation and was then overprinted by a local stress field from dike opening with an overpressure of similar to 15 MPa.

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles (Goldman et al., 2021, https://doi.org/10.1029/2021ea002099) in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.