Volcano Observatory Research Articles

Improving communication between volcano observatories and volcanic ash advisory centres in Europe—outcomes from a first workshop

AbstractEffective aviation response to atmospheric emissions from volcanic eruptions relies upon timely communication and information exchange. To explore the current and best practices in this area, a workshop was held in February 2019 under the framework of the European H2020 EUROVOLC project (2018–2021). The objective of the workshop was to bring together the volcano observatories (VOs), volcanic ash advisory centres (VAACs), and volcanological research institutes in Europe. The workshop included scientists and operational staff from six of Europe’s VOs (Iceland, Italy, France, Spain, Portugal, and Greece), the London and Toulouse VAACs, and seven supporting institutions and organisations. During the workshop, participants identified future improvements to the way the VOs and VAACs communicate and share information. Recommendations include refining the guidance and local documentation on the correct use of the Volcano Observatory Notice for Aviation (VONA), improving the two-way feedback between the VAAC and VOs, regular sharing of volcano status updates by the VO, and inclusion of all VOs in regular VAAC and aviation exercises. These are applicable to VOs and VAACs elsewhere in the world.

A Case for Improved Global Coordination of Volcano Observatories

The distribution of volcano monitoring networks and volcano expertise does not correlate well with the global distribution of volcanic risk. All countries have cultural, financial, bureaucratic, political, and logistical barriers to effective risk reduction. The lack of parity amongst volcano observatories jeopardizes public safety and curtails scientific research and understanding. Having global data compiled daily to retain a full record of volcanic unrest would lead to large and meaningful improvements in future eruption forecasts. To make progress on these issues, the volcanological community needs greater collaboration, standardization, and support..

Twenty years of volcano data at GeoNet—collection, custodianship, and evolution of open data on New Zealand’s volcanoes

The GeoNet programme at GNS Science has monitored and managed data for volcanoes, earthquakes, landslides, and tsunami in Aotearoa New Zealand since 2001. Volcano monitoring data are collected from seismometers, acoustic sensors, GNSS receivers, webcams, remote gas monitoring sensors, and a range of environmental sensors, as well as manually during visits to volcanoes. The primary user of volcano data is the internal cross-specialised Volcano Monitoring Group (VMG), which fulfils the role of the national volcano observatory. GeoNet concentrates on automatic data collection and analysis, while supporting members of the VMG with manual data collection and interpretation. The application of open-data principles to both data and metadata has always been a core aspect of GeoNet; responses have been overwhelmingly positive, despite concerns regarding some high value, manually collected datasets. The website www.geonet.org.nz represents the primary data access portal. Data analysis and delivery applications are organised by data type rather than hazard, with no volcano-specific data applications. Most datasets have web-based and API delivery application options; both provide standard data formats from a cloud-based archive. One of the challenges for volcano data collection and management has been shifting from a reliance on manually collected data to automatic collection. Additionally, awareness of important questions related to Indigenous Māori data governance is increasing, although the associated impact is not yet understood. Overall, the current centralised, cooperative volcano monitoring and data collection and management system, which benefits from improved efficiency, interoperability, and data quality, has proved effective in Aotearoa New Zealand. Ongoing work aims to ensure optimal data collection and management for volcano monitoring and downstream activities.

From field station to forecast: managing data at the Alaska Volcano Observatory

From field station to forecast: managing data at the Alaska Volcano Observatory

Recent Expansion of the Cascades Volcano Observatory Geophysical Network at Mount Rainier for Improved Volcano and Lahar Monitoring

Abstract The U.S. Geological Survey Cascades Volcano Observatory (CVO) recently expanded its continuous geophysical monitoring at Mount Rainier, an active stratovolcano in Washington state. CVO monitors volcanoes in Oregon, Washington, and Idaho to characterize volcanic systems and detect unrest. Mount Rainier has a history of large lahar occurrences in the Holocene, including at least one that may not have been associated with volcanic activity. Pierce County, Washington, is one of the areas most at risk from large lahars. In the 1990s, CVO collaborated with Pierce County to install the Rainier lahar detection system (RLDS), an automated system designed to detect large lahars in high-risk drainages and mitigate hazards to heavily populated areas. The system was designed to detect lahars within 5–10 min of their occurrence and alert authorities of the need to evacuate populated low-lying areas before lahar arrival. In addition, CVO and the Pacific Northwest Seismic Network (PNSN) maintained and expanded a network of seismic and geodetic monitoring stations on and near the edifice to provide adequate volcano monitoring capabilities. Since 2016, CVO has worked to upgrade the existing RLDS and to expand its capabilities into other drainages around Mount Rainier. This expansion includes installation of 25 new broadband seismic stations with many including infrasound along high-risk drainages, as well as support for equipment upgrades at existing PNSN and CVO volcano monitoring sites. All stations transmit continuous, near-real-time data with dramatically improved spatial coverage for volcano monitoring and lahar hazard mitigation compared to the previous system.

Hydroacoustic Monitoring of Mayotte Submarine Volcano during Its Eruptive Phase

Submarine volcanoes are more challenging to monitor than subaerial volcanoes. Yet, the large eruption of the Hunga Tonga-Hunga Ha’apai volcano in the Tonga archipelago in 2022 was a reminder of their hazardous nature and hence demonstrated the need to study them. In October 2020, four autonomous hydrophones were moored in the sound fixing and ranging channel 50 km offshore Mayotte Island, in the North Mozambique Channel, to monitor the Fani Maoré 2018–2020 submarine eruption. Between their deployment and July 2022, this network of hydrophones, named MAHY, recorded sounds generated by the recent volcanic activity, along with earthquakes, submarine landslides, marine mammals calls, and marine traffic. Among the sounds generated by the volcanic activity, impulsive signals have been evidenced and interpreted as proxy for lava flow emplacements. The characteristics and the spatio-temporal evolution of these hydroacoustic signals allowed the estimation of effusion and flow rates, key parameters for volcano monitoring. These sounds are related to the non-explosive quenching of pillow lavas due to the rapid heat transfer between hot lava and cold seawater, with this process releasing an energy equivalent to an airgun source as used for active seismic exploration. Volcano observatories could hence use autonomous hydrophones in the water column to detect and monitor active submarine eruptions in the absence of regular on-site seafloor survey.

Detection and Characterization of Seismic and Acoustic Signals at Pavlof Volcano, Alaska, Using Deep Learning

AbstractVolcanic tremor is a semi‐continuous seismic and/or acoustic signal that occurs at time scales ranging from seconds to years, with variable amplitudes and spectral features. Tremor sources have often been related to fluid movement and degassing processes, and are recognized as a potential geophysical precursor and co‐eruptive geophysical signal. Eruption forecasting and monitoring efforts need a fast, robust method to automatically detect, characterize, and catalog volcanic tremor. Here we develop VOlcano Infrasound and Seismic Spectrogram Network (VOISS‐Net), a pair of convolutional neural networks (one for seismic, one for acoustic) that can detect tremor in near real‐time and classify it according to its spectral signature. Specifically, we construct an extensive data set of labeled seismic and low‐frequency acoustic (infrasound) spectrograms from the 2021–2022 eruption of Pavlof Volcano, Alaska, and use it to train VOISS‐Net to differentiate between different tremor types, explosions, earthquakes and noise. We use VOISS‐Net to classify continuous data from past Pavlof Volcano eruptions (2007, 2013, 2014, 2016, and 2021–2022). VOISS‐Net achieves an 81.2% and 90.0% accuracy on the seismic and infrasound test sets respectively, and successfully characterizes tremor sequences for each eruption. By comparing the derived seismoacoustic timelines of each eruption with the corresponding eruption chronologies compiled by the Alaska Volcano Observatory, our model identifies changes in tremor regimes that coincide with observed volcanic activity. VOISS‐Net can aid tremor‐related monitoring and research by making consistent tremor catalogs more accessible.

Quantitative Assessment of Volcanic Thermal Activity from Space Using an Isolation Forest Machine Learning Algorithm

Understanding the dynamics of volcanic activity is crucial for volcano observatories in their efforts to forecast volcanic hazards. Satellite imager data hold promise in offering crucial insights into the thermal behavior of active volcanoes worldwide, facilitating the assessment of volcanic activity levels and identifying significant changes during periods of volcano unrest. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, aboard NASA’s Terra and Aqua satellites, provides invaluable data with high temporal and spectral resolution, enabling comprehensive thermal monitoring of eruptive activity. The accuracy of volcanic activity characterization depends on the quality of models used to relate the relationship between volcanic phenomena and target variables such as temperature. Under these circumstances, machine learning (ML) techniques such as decision trees can be employed to develop reliable models without necessarily offering any particular or explicit insights. Here, we present a ML approach for quantifying volcanic thermal activity levels in near real time using thermal infrared satellite data. We develop an unsupervised Isolation Forest machine learning algorithm, fully implemented in Google Colab using Google Earth Engine (GEE) which utilizes MODIS Land Surface Temperature (LST) data to automatically retrieve information on the thermal state of volcanoes. We evaluate the algorithm on various volcanoes worldwide characterized by different levels of volcanic activity.

A fast compilation of the VONA messages using a computer-assisted procedure

Mt. Etna, in Italy, is one of the most active volcanoes in the world, producing several explosive events in recent years. Those eruptions form high eruption columns that often reach the top of the troposphere (and sometimes even the lower part of the stratosphere) and create several disruptions to air traffic, mainly to the Fontanarossa International Airport in Catania, which is about 20 NM (~ 37 km; NM = Nautical Miles) away from the summit craters and is located in the main wind direction. In Italy, the institution responsible for volcano monitoring is the Istituto Nazionale di Geofisica e Vulcanologia (INGV). In 2007, the INGV, Osservatorio Etneo (INGV-OE) in Catania was appointed as “State Volcano Observatory” (SVO) and, in 2014, sent the first Volcano Observatory Notice for Aviation (VONA) message. Since that moment, several VONA messages have been sent, mainly due to the high frequency of Etna activity. In order to facilitate and speed in the generation and the dispatch of the VONA messages, a computer-assisted procedure has been designed and built to help the work done by the volcanologist on duty and by the two shift workers of the 24/7 Control Room of INGV-OE. Consequently, information on the explosive activity can be quickly provided to the Volcanic Ash Advisory Center (VAAC) in Toulouse and national air traffic offices, reducing risks to aviation operations. In this work, we describe how the computer-assisted procedure works, addressing the main advantages and possible improvements. We retain that a similar approach could be easily applied to other volcano observatories worldwide.

The European Volcano Observatories and their use of the aviation colour code system

Volcano observatories (VOs) around the world are required to maintain surveillance of their volcanoes and inform civil protection and aviation authorities about impending eruptions. They often work through consolidated procedures to respond to volcanic crises in a timely manner and provide a service to the community aimed at reducing the potential impact of an eruption. Within the International Airways Volcano Watch (IAVW) framework of the International Civil Aviation Organisation (ICAO), designated State Volcano Observatories (SVOs) are asked to operate a colour coded system designed to inform the aviation community about the status of a volcano and the expected threats associated. Despite the IAVW documentation defining the different colour-coded levels, operating the aviation colour code in a standardised way is not easy, as sometimes, different SVOs adopt different strategies on how, when, and why to change it. Following two European VOs and Volcanic Ash Advisory Centres (VAACs) workshops, the European VOs agreed to present an overview on how they operate the aviation colour code. The comparative analysis presented here reveals that not all VOs in Europe use this system as part of their operational response, mainly because of a lack of volcanic eruptions since the aviation colour code was officially established, or the absence of a formal designation as an SVO. We also note that the VOs that do regularly use aviation colour code operate it differently depending on the frequency and styles of eruptions, the historical eruptive activity, the nature of the unrest, the monitoring level, institutional norms, previous experiences, and on the agreement they may have with the local Air Transport Navigation providers. This study shows that even though the aviation colour code system was designed to provide a standard, its usage strongly depends on the institutional subjectivity in responding to volcano emergencies. Some common questions have been identified across the different (S)VOs that will need to be addressed by ICAO to have a more harmonised approach and usage of the aviation colour code.

Chemistry, Growth, and Fate of the Unique, Short‐Lived (2019–2020) Water Lake at the Summit of Kīlauea Volcano, Hawaii

AbstractLess than a year after the 2018 Kīlauea caldera collapse and eruption, water appeared in newly deepened Halemaʻumaʻu crater. The lake—unprecedented in the written record—grew to a depth of ∼50 m before lava from the December 2020 eruption boiled it away. Surface water heightened concerns of potential phreatic or phreatomagmatic explosions but also offered a new means of possibly identifying eruption precursors. The U.S. Geological Survey Hawaiian Volcano Observatory (HVO) monitored the lake via direct visual observation, webcams, thermal imaging, colorimetry, and laser rangefinders. HVO also employed uncrewed aircraft systems to sample the water and measure near‐lake gas composition. The lake's δD and δ18O indicate a groundwater source with substantial evaporation. The initial sample had a salinity (total dissolved solids concentration) of 71,000 mg/L and was rich in sulfate (∼53,000 mg/L), iron (∼500 mg/L), and magnesium (∼10,000 mg/L). Subsequent samples were slightly more dilute. The water's pH (∼4), δ34S (+4.3‰), and surface temperatures (up to 85°C) suggest, rather than significant scrubbing of magmatic volatiles, leaching of basalt and reactions with sulfate minerals resulted in high concentrations of sulfate and other solutes. Thermodynamic modeling and precipitate mineralogy indicate that water composition was controlled by iron oxidation and sulfate dissolution. Although the lake exhibited no detectable precursors before the next eruption, and phreatic or phreatomagmatic explosions did not materialize, our multi‐parameter approach to monitoring yielded an enhanced understanding of the hydrologic, geologic, and magmatic conditions that led to the formation of the unique and short‐lived lake.

USGS and social media user dialogue and sentiment during the 2018 eruption of Kīlauea Volcano, Hawai‘i

Responsive and empathic communication by scientists is critical for building trust and engagement with communities, which, in turn, promotes receptiveness toward authoritative hazard information during times of crisis. The 2018 eruption of Hawai‘i's Kīlauea Volcano was the first volcanic crisis event in which communication via the U.S. Geological Survey (USGS) social media group, “USGS Volcanoes,” played a major role in providing eruption information to publics. Providing a concrete assessment of the social media effort during the eruption is necessary for optimizing future social media hazard crisis communication. We present qualitative and quantitative analyses of USGS Volcanoes' Facebook posts and over 22,000 follow-on comments spanning the 2018 eruption. Our analyses reveal that, for the 16 posts with the highest user engagement, USGS Volcanoes and informed non-USGS users directly answered 73% of questions and directly corrected or called out inaccuracies in over 54% of comments containing misinformation. User sentiments were 66% positive on average per comment thread regarding eruption information, and user feedback toward USGS Volcanoes, USGS scientists, or the Hawaiian Volcano Observatory was 86% positive on average. Quantitative sentiment analysis reveals a 61% correlation between users' overall expressed sentiments and frequency of the word “thank,” providing further evidence that social media engagement by USGS Volcanoes and informed users positively impacted collective user sentiment. Themes emerging from our qualitative thematic analysis illustrate how communication strategies employed by USGS Volcanoes successfully engaged and benefitted users, providing insights for communicating with publics on social media during crisis situations.

The global volcano monitoring infrastructure database (GVMID)

Monitoring volcanoes is of the most importance in volcano risk mitigation to safeguard lives and economies. Thanks to recent technological advances, both on-ground and in space, our understanding of volcanic processes has improved significantly. Though there is no one-system-fits-all, optimizing infrastructure for efficient monitoring stands as key objective. The impacts of volcanic hazards can span from local to global scales, affecting us both in the short and long term. This highlights the worldwide significance of improving volcano monitoring. Previously reliant on local ground-based instruments, today’s monitoring approach is enhanced by remote and space-based techniques such as satellite remote sensing, scanning-Differential Optical Absorption Spectroscopy (DOAS), and infrasound. Designing an effective monitoring infrastructure for volcano observatories involves careful consideration of various factors such as network coverage, type of sensors, data transmission, and power supply to ensure that the targeted parameters meet the specific needs of each volcano (e.g., type of activities, early warning systems). Additionally, fostering collaboration and information sharing within the global scientific community is essential for addressing the current challenges in volcanology. In line with this, we’ve established the Global Volcano Monitoring Infrastructure Database (GVMID) to compile data from volcano monitoring across the globe. Global Volcano Monitoring Infrastructure Database serves as an integral component of WOVOdat, the global volcano unrest database, aiming to enhance our understanding of eruptive processes and improve eruption forecasts. The database incorporates monitoring metadata comprising networks, stations, and instruments, all standardized and managed using a MySQL relational database management system. Accessed through a web-based interface (https://wovodat.org/gvmid/home.php), GVMID offers an informative snapshot and foundational overview of the techniques and instruments in place at diverse volcanoes. This interactive platform allows for queries, visualizations, and downloads, serving as a valuable resource for the volcano community. GVMID can assist observatories in various ways, by: (a) Facilitating the setup or enhancement of monitoring systems for specific volcanoes. (b) Providing insights into the latest monitoring technologies and instrumentation. (c) Identifying existing monitoring gaps that could be addressed through remote sensing infrastructure and future instrument deployments. We extend an invitation to the global volcano community to actively participate in the development and enrichment of GVMID. Our aim is for it to become a continually updated and indispensable resource that caters to diverse needs within the volcanology community.

Open Science Initiatives by Sakurajima Volcano Observatory

The sudden eruption and tragedy of Mt. Ontake in 2014, a volcano located in central Japan, showed the fact that the volcanic eruption is the event with uncertainty, and it is important to let citizen to be aware of such uncertainty. To find measures to raise citizen’s disaster awareness, this study focuses on the risk communication between citizens and volcano observatories, which are attached to universities. It examines the role of observatories, focusing on the activities of the Sakurajima Volcano Research Center, which monitors Mt. Sakurajima, one of the most active volcanoes in Japan, and suggests the necessity of human resource development that is able to connect citizen and science.

Open-Door Events of the Sakurajima Volcano Observatory, Kyoto University in the Last Ten Years

Sakurajima Volcano Observatory, with a history exceeding 60 years, is recognized by researchers in Japan and overseas for conducting frontier research centering on Sakurajima, the most active volcano in Japan. It is owned by Kyoto University and represents the university in the surrounding communities. This paper reviews the open-door events, which have been conducted yearly for the last ten years as a part of a university-wide effort by Kyoto University. They make use of the facilities at Sakurajima Volcano Observatory, which aims to enhance the understanding of volcanoes among the general public in collaboration with geo-guides as “boundary workers.”

Structure of shallow magma sources beneath Augustine Volcano (Alaska) inferred from local earthquake tomography

Augustine is an active stratovolcano occupying almost entirely a small island in the Cook Inlet in Alaska. In this study, we use the arrival time data from local seismicity recorded by 15 permanent seismic stations deployed on the flanks of Augustine Volcano by the Alaska Volcano Observatory and invert them by the body wave local earthquake tomography. The resulting model includes the 3D distributions of the P and S wave velocities (Vp and Vs), Vp/Vs ratio and the relocated seismic events. The resolved area extends down to the depth of 2 km below sea level (b.s.l). At shallow depths, within the edifice, we observe a contrasted anomaly with very high Vp, low Vs and very high Vp/Vs, which represents the rigid volcano core composed of igneous rocks (high Vp), but strongly fractured and saturated with fluids and melts (low Vs). At larger depths, below sea level, we retrieve a columnar anomaly of high Vp/Vs ratio representing the magma conduit. On the top of this anomaly, there is a zone with low Vp/Vs coinciding with the strong seismicity cluster, which is associated with the degassing of deep fluids.

Cleaning volcano-seismic event catalogues: a machine learning application for robust systems and potential crises in volcano observatories

Cleaning volcano-seismic event catalogues: a machine learning application for robust systems and potential crises in volcano observatories

Distinguishing shallow from mid-crustal magmatic processes at Soufrière Hills Volcano using Finite Element Modelling and co-analysis of EDM and GPS data

We modelled ground deformation at Soufrière Hills Volcano (SHV), using data collected by the Montserrat Volcano Observatory from 2010–2019. We investigate the combined use of Electronic Distance Measuring (EDM) and Global Positioning System (GPS) to distinguish shallow from mid-crustal magmatic processes and their surface deformation profiles. Our results suggest that the EDM network responds predominantly to changes in the shallow magmatic system, whereas GPS records variation at mid-crustal levels. In addition, we show that the behaviour of the EDM network, and of the GPS site HERM, can be explained by underpressurisation in a shallow dyke conduit orientated NNW–SSE, while the mid-crustal system was still undergoing pressurisation. The modelled dyke may be responding to magma cooling and contraction associated with a previous intrusion. We find that geodetic monitoring coverage of multiple flanks within 1 km of the vent can improve our understanding of shallow magmatic system processes with asymmetric deformation fields.

The Museum of the Osservatorio Vesuviano: inviting the public to explore the geoheritage of the world’s first volcano observatory

The Osservatorio Vesuviano (OV) is the oldest volcano observatory in the world having been founded in 1841 by the King of the Two Sicilies Ferdinand II of Bourbon. The historical building, located on the western slope of Vesuvius, hosts a museum with important collections of remarkable scientific, historical and artistic value, including pioneering instruments, rocks and minerals, photos and films of Vesuvius’ eruptions and many other memorabilia. Visitors discover this heritage through permanent exhibitions, and a multimedia path, across the history of Vesuvius and the origin of volcano monitoring. The museum lies within the protected area of Vesuvius National Park, established in 1995. The park’s network of trails allows visitors to enjoy the geodiversity of Somma-Vesuvius, whose activity has been intertwined with that of humans from Bronze Age to modern times, as testified by many important archaeological sites around the volcano, the most famous among them being Pompeii and Herculaneum. The “Grand Tour” was the cultural journey undertaken in the eighteenth century by European intellectuals, in which Italy was an essential destination; we consider the Museum of the OV an essential stop in a modern “Vesuvius Grand Tour”, a journey through the geological and archaeological heritage of Vesuvius territory. Since 2001, the OV is the Naples section of the Istituto Nazionale di Geofisica e Vulcanologia (INGV), which is primarily tasked with monitoring the three active volcanoes of the Neapolitan area—Vesuvius, Campi Flegrei and Ischia—through an advanced surveillance network.

Surveying volcanic crises exercises: From open-question questionnaires to a prototype checklist

Volcanic crisis exercises are usually run to test response capabilities, communication protocols, and decision-making procedures by agencies with responsibilities to cope with scenarios of volcanic unrest with inherent uncertainty, such as volcano observatories and/or civil protection authorities. During the last decades, the use of questionnaires has been increased to evaluate people's knowledge on volcanic hazards and their perception of risk, to better understand their preparedness to respond to emergency measures plans.In this paper, we present a study carried out within the European Network of Observatories and Research Infrastructures for Volcanology project (EUROVOLC) focused on extracting information on the experience gained during volcanic-crisis exercises by the project's participants and beyond. An open-ended question questionnaire was firstly distributed for a survey within the project community. Through the results obtained, we developed a user-friendly online multi-choice questionnaire that was submitted to the volcanological communities within and outside EUROVOLC. Analyzing the answers to the online questionnaire, we extracted a prototype checklist for guiding the design of such exercises in the future. Our results confirm this type of survey as a very useful tool for gathering information on participants' experience and knowledge, able to understand which data and information may be useful when designing exercises for scientists, emergency managers and decision makers. In particular, the main lessons learnt regard the need i) to increase training activities involving people exposed to volcanic hazards and media, ii) to improve external communication tools (between players and public/media), equipment and protocols and iii) to better define decision-makers' needs.