Alaska Volcano Observatory

Abstract Cascadia slow slip events (SSEs) are often envisioned as smooth, continuous ruptures, progressively activating tremor asperities as they propagate. Macroscopically, geodetic inversions and spatiotemporal maps of tremor epicenters show steady, uniform migration. In detail tremor is more chaotic and discontinuous. Larger long‐term SSEs observed in daily geodetic solutions are inferred to exhibit intermittent pauses that reflect temporary re‐locking of the fault, but this temporal resolution limits tests for similar re‐locking on shorter timescales. We use temporal measurements of the areal growth and radiated energy of tremor clusters to investigate SSE intermittence. We find that ruptures mirror tremor pauses. Areal growth rate, however, does not reset, and removing the pauses results in smoother and more similar growth measurements among all SSEs. The rupture similarity occurs regardless of size or location and hints at an underlying uniformity and lack of predeterminism in eventual SSE size. Epicentral uncertainty precludes quantifying early rupture stages, but for larger events areal growth follows a power‐law and slows with increasing size. Temporal correlations in tremor energy with inferred SSE propagation velocities and tremor rates suggest its use as a proxy for slip velocity. We find that tremor energy is tidally modulated at daily and sub‐daily frequencies, and this modulation is continuous through pauses, suggesting a memory of slip state is sustained through them. We argue these pauses reflect unsteady propagation of the slip front, marked by rapid re‐ and un‐locking, and excluding them removes rupture complexity to reveal a diffusive‐like slip process and underlying universality in growth.

The Backyard Buoys™ project (www.backyardbuoys.org) is empowering Indigenous and coastal communities with tools to gather and interpret wave data, enhancing their capacity for climate resilience and blue economy initiatives. While a parallel presentation will emphasize local stewardship and co-design, this session focuses on Backyard Buoys’ commitment to educating new generations through the hands-on use of low-cost, scalable marine technology. Engaging younger participants from these historically underserved communities in ocean science not only builds technical skills but fosters a lasting connection to their coastal environments, a necessity as climate change accelerates shifts in ocean conditions and wave predictability.Through partnerships with regional ocean observing networks and the U.S. Integrated Ocean Observing System (IOOS), Backyard Buoys facilitates the co-design of training programs and educational resources, emphasizing accessibility and relevance. Community members, particularly youth, gain experience deploying, managing, and analyzing data from buoys tailored to local needs. Complemented by Indigenous Knowledge, these programs deepen understanding and enhance participation in data-driven decision-making for sustainable ocean stewardship.By investing in future generations, Backyard Buoys aims to cultivate a lasting framework for community science, blending modern technology with traditional knowledge to build a resilient coastal future. This presentation will outline the project’s strategies and resources to educate, inspire, and empower the next wave of coastal innovators.

Geysers are natural geothermal features that episodically erupt hot water and steam due to the buildup and release of subsurface vapor bubbles. At Strokkur geyser, Iceland, eruptions begin with the growth of a surface bulge caused by rising bubble clusters, followed by gradual rupture and disintegration into a water fountain. In this study, we investigate the high-resolution acoustic and visual signatures of this initial phase of the eruption, providing detailed insights into the fluid dynamics that govern bulge formation and rupture. While similar eruptive behavior is sometimes observed in low-viscosity volcanic systems, Strokkur offers a uniquely transparent medium in which processes like bubble rise and clustering can be directly observed, providing analogies to otherwise obscured dynamics in lava or mud-dominated settings. We combine low-frequency infrasound and high-frequency audio recordings with high-speed video, using synchronized data to track the evolution of the bulge. The results demonstrate that infrasound effectively detects bulge growth, while the onset of rupture is marked by a rise in audio-frequency amplitude. A monopole model is used to simulate pressure variations during bulge growth. The observed decompression signal is associated with the downward water motion during bulge disintegration. These findings improve our understanding of geyser eruption dynamics and suggest how acoustic monitoring can provide valuable information about subsurface processes in both geysers and volcanoes, such as dome inflation or gas bubble accumulation beneath magma surfaces.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00445-025-01876-3.

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Abstract We apply a machine learning (ML) earthquake detection technique on over 21 yr of seismic data from on-continent temporary and long-term networks to obtain the most complete catalog of seismicity in Antarctica to date. The new catalog contains 60,006 seismic events within the Antarctic continent for 1 January 2000–1 January 2021, with estimated moment magnitudes (Mw) between −1.0 and 4.5. Most detected seismicity occurs near Ross Island, large ice shelves, ice streams, ice-covered volcanoes, or in distinct and isolated areas within the continental interior. The event locations and waveform characteristics indicate volcanic, tectonic, and cryospheric sources. The catalog shows that Antarctica is more seismically active than prior catalogs would indicate, examples include new tectonic events in East Antarctica, seismic events near and around the vicinity of David Glacier, and many thousands of events in the Mount Erebus region. This catalog provides a resource for more specific studies using other detection and analysis methods such as template matching or transfer learning to further discriminate source types and investigate diverse seismogenic processes across the continent.

In recent years, blooms of the neurotoxic dinoflagellate Alexandrium catenella have been documented in Pacific Arctic waters, and the paralytic shellfish toxins (PSTs) that this species produces have been detected throughout the food web. These observations have raised significant concerns about the role that harmful algal blooms (HABs) will play in a rapidly changing Arctic. During a research cruise in summer 2022, a massive bloom of A. catenella was detected in real time as it was advected through the Bering Strait region. The bloom was exceptional in both spatial scale and density, extending >600 km latitudinally, reaching concentrations >174,000 cells L-1, and producing high-potency PST congeners. Throughout the event, coastal stakeholders in the region were engaged and a multi-faceted community response was mobilized. This unprecedented bloom highlighted the urgent need for response capabilities to ensure safe utilization of critical marine resources in a region that has little experience with HABs.

Abstract Volcanic 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.

Abstract We report the oxide, element geochemistry and Nd isotopic geochemical data of apatite in the middle Pleistocene medium‐ and fine‐grained trachyte in the Tianchi volcanic area (TVA) of Changbai Mountain, discussing the relationship between apatite and the composition of the whole rock. The purpose is to use the apatite geochemical data to constrain the evolutionary process of trachytic magma and the petrogenesis of trachyte in the cone‐forming period of the Tianchi volcano. Apatite (Ca5(PO4)3(OH, F, Cl)) is a common accessory mineral that occurs widely in volcanic rocks in the TVA. The apatites in the trachyte are mainly subhedral–anhedral, having the characteristics of magmatic apatite. In terms of oxide and element geochemistry, they have homogeneous Al2O3, SiO2, MgO, P2O5, K2O, CaO and heterogeneous TiO2, with high F content. They are generally enriched in Th, U and LREEs, depleted in Nb, Ta, Zr, Hf and HFSEs, showing negative Ba, Sr and Ti anomalies, similar to those of the whole‐rock host trachytes. The ratios of high (La/Yb)N, low δEu (Eu/Eu*), Sr/Y value and ΣREE content in apatite, and the F, Sr, Y, Th/U, La/Sm, and Nd/Tb with ΣREE and δEu anomalies showed a linear correlation, all of those indicating that the host magma has the characteristic of high differentiation. The apatite grains generally having 147Sm/144Nd, 143Nd/144Nd ratios and εNd(t) values of 0.1072–0.1195, 0.5123–0.5126 and –3.49 to –0.10, respectively, are similiar to those of the host rock. The Nd model ages TDM1 are 949–803 Ma in apatite. Combined with the εNd(t) value of the apatite core (–7.06 to –3.49), we conclude that the initial magma of the host trachyte was derived from the partial melting of Proterozoic crustal material and there was an assimilation of wall rocks during its evolution.