Explosive eruptions are the surface manifestation of dynamics that involve transfer of magma from the underground regions of magma accumulation. Evidence of the involvement of compositionally different magmas from different reservoirs is continuously increasing to countless cases. Yet, models of eruption dynamics consider only the uppermost portion of the plumbing system, neglecting connections to deeper regions of magma storage. Here we show that the extent and efficiency of the interconnections between different magma storage regions largely control the size of the eruptions, their evolution, the causes of their termination, and ultimately their impact on the surrounding environment. Our numerical simulations first reproduce the magnitude-intensity relationship observed for explosive eruptions on Earth and explain the observed variable evolutions of eruption mass flow rates. Because deep magmatic interconnections are largely inaccessible to present-day imaging capabilities, our results imply a limit to eruption size forecasts based on observations and measurements during volcanic unrest.
Exponential Decay Of Concentration Variance During Magma Mixing: Robustness Of A Volcanic Chronometer And Implications For The Homogenization Of Chemical Heterogeneities In Magmatic Systems
Toward Forecasting Volcanic Eruptions using Seismic Noise
在喷发期间，岩浆加压产生微妙的变化，火山机构的弹性性能。我们使用记录在Piton de la Fournaise火山上的环境地震噪声的再现性特性来测量小于0.1%的相对地震速度变化，时间分辨率为一天。我们的研究结果表明，五个研究的火山爆发之前，明显可检测的地震速度下降的岩浆注入区。这些前兆反映了岩浆加压引起的沉积扩张，可以作为改进火山喷发预测的有用指标。
Unveiling magma plumbing systems for volcanic eruptions and crustal accretion via active-seismic matrix imaging
Institut Langevin, ESPCI, PSL University, CNRS（朗之万研究所，ESPCI巴黎高等物理化工学院，PSL大学，法国国家科学研究中心）；Institut de Physique du Globe de Paris, Université Paris Cité, CNRS UMR 7154（巴黎地球物理研究所，巴黎西岱大学，法国国家科学研究中心）
Matrix imaging as a tool for high-resolution monitoring of deep volcanic plumbing systems with seismic noise
Institut Langevin, ESPCI Paris, PSL University, CNRS（朗之万研究所，巴黎高等物理化工学院，巴黎文理研究大学，法国国家科学研究中心）；Institut de Physique du Globe de Paris, Université Paris Cité, CNRS（巴黎地球物理研究所，巴黎西岱大学，法国国家科学研究中心）
Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano
火山震颤是我们理解活跃岩浆系统的关键，但由于其复杂性，关于其起源以及如何将其用于表征喷发动力学仍存在争议。在这项研究中，我们利用机器学习（ML）技术，使用来自Piton de la Fournaise火山（La Réunion岛）的6年连续地震资料来描述喷发期间记录的地震信号的特定模式。这些结果揭示了我们解释为与火山各种喷发动力学相关的信号，包括2015年8月至10月喷发期间大量熔岩的渗出，以及2018年9月至11月喷发期间喷发口的关闭。我们描述的ML工作流程可以很容易地应用于其他活火山，从而可能增强对火山爆发时间和空间演变的理解
Enhanced Seismicity Monitoring in the Rapid Scientific Response to the 2025 Santorini Crisis
The Lyell Centre, British Geological Survey（英国地质调查局利尔中心）；School of GeoSciences, The University of Edinburgh（爱丁堡大学地球科学学院）；Department of Geophysics, Stanford University（斯坦福大学地球物理学系）；GFZ Helmholtz Centre for Geosciences（GFZ德国地学研究中心赫尔姆霍茨）；RWTH Aachen University（亚琛工业大学）；Dipartimento di Fisica Ettore Pancini, Università degli Studi di Napoli Federico II（那不勒斯费德里科二世大学埃托雷·潘奇尼物理系）；Istituto Nazionale di Geofisica e Vulcanologia (INGV)（意大利国家地球物理学和火山学研究所）；U.S. Geological Survey, Volcano Disaster Assistance Program（美国地质调查局火山灾害援助计划）；Department of Earth Sciences, University of Oxford（牛津大学地球科学系）；Department of Civil and Environmental Engineering, University of Southern California（南加州大学土木与环境工程系）；Division of Natural Sciences, Academy of Athens（雅典科学院自然科学部）；U.S. Geological Survey, Pacific Coastal and Marine Science Center（美国地质调查局太平洋沿海与海洋科学中心）；Institute of Geodynamics, National Observatory of Athens（雅典国立天文台地球动力学研究所）；Dipartimento di Geoscienze, Università degli Studi di Padova（帕多瓦大学地球科学系）；Dipartimento di Scienze della Terra, dell’ Ambiente e delle Risorse, Università degli Studi di Napoli Federico II（那不勒斯费德里科二世大学地球、环境与资源科学系）
Accelerating unrest at Campi Flegrei signals a critical transition within the next decade
Southern University of Science and Technology (SUSTech)（南方科技大学）；Istituto Nazionale di Geofisica e Vulcanologia (INGV)（意大利国家地球物理与火山学研究所）；Federico II University（那不勒斯费德里科二世大学）；Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS（意大利国家海洋与实验地球物理学研究所）
Syneruptive sequential fragmentation of pyroclasts from fractal modeling of grain size distributions of fall deposits: The Cretaio Tephra eruption (Ischia Island, Italy)
