Postdoctoral Fellowship: EAR-PF: Establishing a new eruption classification with a multimethod approach

爆炸性的火山喷发产生包围地面的热岩石和气体雪崩（火山碎屑密度流，PDCs），摧毁当地社区，形成伞状的火山灰和气体云（伞状云），威胁航空，并可能导致持续数年的突然气候变化。火山喷发对社会造成的危害可能持续数年并影响整个地球，其严重程度和持续时间取决于喷发物离开火山的速度（大规模喷发率）和微米尺度过程的波动。目前的喷发分类没有考虑喷发期间不同的大规模喷发速率的影响，也没有考虑微米尺度的喷发过程对喷发危险的影响，因此无法为喷发响应计划提供信息。卫星和地面遥感方法的进步，实时监测火山喷发，结合日益复杂的火山喷发计算机模拟，为火山喷发行为分类和实时火山喷发反应提供了令人兴奋的新方法。然而，利用火山喷发监测和建模方法的这些进步，需要发展基本的多相流体力学理论，以简单地描述大规模喷发速率变化的影响和控制喷发行为的微米尺度过程。约翰·吉尔克里斯特博士建议发展新的流体力学理论，这将形成一个新的“喷发稳定性图”分类的基础，该分类捕捉了不同质量喷发速率和微米尺度过程的影响，以预测喷发期间危害的演变。吉尔克里斯特博士将进行下一代的实验室实验和计算机模拟，并将结果与火山爆发的遥感观测结果进行比较，以探索火山爆发稳定性图中历史、古代和未来火山爆发的预期行为和危害的全部范围。实验室实验将提供丰富的学习经验，为不同群体的就业本科研究人员。该项目包括与国家自然历史博物馆（史密森学会）合作，开发公众友好版本的喷发稳定性图，以便向决策者和公众清楚地传达喷发行为、危害和缓解策略。在火山爆发期间，岩石、火山灰和气体在大气中以伞状火山灰云的形式扩散，在地面上以致命的火山碎屑密度流（PDCs）的形式扩散，威胁着人类、基础设施，并导致气候发生重大变化。在大规模喷发中，火山物质同时被分割成扩散的伞状火山灰云和pdc。此外，在个别喷发阶段，与时间平均平均速率（“不稳定喷发源参数”，ESPs）相比，火山喷发物质向大气输送的速率可能有很大差异，导致质量分配高度依赖于时间。流行的喷发分类既没有考虑喷发质量的划分，也没有解决大多数喷发阶段固有的时间依赖性。Gilchrist博士建议与Josef Dufek博士（俄勒冈大学）和Benjamin Andrews博士(史密森学会；SI)更详细地开发了Gilchrist博士在博士期间发现的两个新的喷发源参数指标：用于捕获多相射流强度的射流稳定性数和用于捕获源不稳定性的源脉动数，并将它们与源颗粒体积分数结合起来形成一个新的三维（3D）“喷发稳定性图”分类方案。在UO博士。Gilchrist和Dufek将设计、建造并进行下一代多相喷流模拟实验，以测试喷发稳定性图在预测扩散云和拥抱地面的重力流之间多相喷流质量分配方面的可靠性。同时，他们将与Eric Breard博士（爱丁堡大学）合作，利用实验数据集验证下一代3D多相流（MFIX）计算机模拟。他们还将与火山雷达专家Franck Donnadieu博士（法国Clermont Auvergne大学）合作，使用基于多普勒雷达的非定常esp数据集，该数据集是在秘鲁萨班卡亚火山（2018年）现场测量的，用于运行和验证3D MFIX喷发模拟。该研究项目与美国国家科学基金会地球科学部岩石学和地球化学项目的火山学研究以及EAR的研究主题“与尺度有关的问题”相一致。喷发稳定性图将是第一个根据平均或时变喷发源参数对所有喷发类型进行分类的构造，预测喷发质量传递给伞状云和pdc，从而总体上提高对喷发危害和火山气候影响的预测。此外，许多喷发阶段典型的喷发源参数的特征演化将通过喷发稳定性图追踪独特的路径，从而通过喷发演化来理解喷发类别，这是一种新的喷发分类方法。第二种分类喷发的方法可以揭示喷发演化路径，诊断特定的火山、火山类型或构造环境。火山爆发稳定性图将取代目前最流行的火山爆发指数分类，该分类被广泛用于了解地球上火山爆发的规模和影响。该项目还将推进采用互补模拟实验和经实地数据验证的数值模拟的多方法方法来研究火山现象。模拟实验将首次有助于对不同源参数的多相射流构造的矿床进行解剖，以确定诊断喷发柱型和状态转换的矿床特征，从而指导喷发矿床的野外研究。同时，新的3D MFIX模拟将突破多相流模拟的极限，通过明确地模拟厘米尺度颗粒惯性和浮力对公里尺度体流的影响。对于火山监测至关重要的是，由MFIX模拟火山喷发产生的ESP和合成多普勒雷达数据集将公开，为火山雷达数据的解释提供信息。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Explosive volcanic eruptions produce ground-hugging hot rock and gas avalanches (pyroclastic density currents, PDCs) that devastate local communities and umbrella-shaped ash and gas clouds (umbrella clouds) that threaten aviation and can cause abrupt climate shifts lasting years. The severity and duration of eruption hazards to society, which can last years and affect the entire globe, depend on fluctuations in the rate at which erupted mass exits the volcano (mass eruption rate) and micrometer scale processes. Current eruption classifications do not consider the effects of varying mass eruption rate during an eruption nor micrometer-scale processes on eruption hazards and are, therefore, ill-equipped for informing eruption response plans. The advancements of satellite and ground-based remote-sensing methods to monitor eruptions in real-time combined with increasingly sophisticated eruption computer simulations provide exciting new ways to classify eruption behavior and inform real-time eruption response. However, leveraging these advances in eruption monitoring and modelling methods requires development of basic multiphase fluid mechanics theory to simply characterize the effects of variations in mass eruption rate and micrometer-scale processes in governing eruption behavior. Dr. Johan Gilchrist proposes to develop new fluid mechanics theory that will form the basis for a new “Eruption Stability Diagram” classification that captures the effects of varying mass eruption rate and micrometer-scale processes to predict the evolution of hazards during an eruption. Dr. Gilchrist will conduct the next generation of laboratory experiments and computer simulations and compare the results with remote-sensing observations of eruptions to explore the full range of expected eruption behaviors and hazards for historical, ancient, and future eruptions in the Eruption Stability Diagram. The laboratory experiments will provide a rich learning experience for a diverse group of employed undergraduate researchers. The project includes a collaboration with the National Museum of Natural History (Smithsonian Institute) to develop public-friendly versions of the Eruption Stability Diagram to clearly communicate eruption behaviors, hazards, and mitigation strategies to policymakers and the public. During explosive volcanic eruptions rocks, ash and gases spreading in the atmosphere as umbrella ash clouds and along the ground as deadly pyroclastic density currents (PDCs) threaten people, infrastructure and drive major shifts in climate. In large eruptions volcanic material is simultaneously partitioned to spreading umbrella ash-clouds and PDCs. Furthermore, during individual eruptive phases the rate at which erupted material is delivered to the atmosphere from a volcano can vary significantly compared to time-averaged mean rates (“unsteady eruption source parameters”, ESPs), causing mass partitioning to be highly time-dependent. Popular eruption classifications neither consider eruptive mass partitioning nor address the time-dependence that is inherent to most eruptive phases. Dr. Gilchrist proposes to work with Dr. Josef Dufek (University of Oregon; UO) and Dr. Benjamin Andrews (Smithsonian Institute; SI) to develop in greater detail two new eruption source parameter metrics that Dr. Gilchrist discovered during his PhD: the jet stability number to capture multiphase jet strength and the source Pulsation number to capture source unsteadiness, and combine them with the source particle volume fraction to form a new three-dimensional (3D) “Eruption Stability Diagram” classification scheme. At UO Drs. Gilchrist and Dufek will design, build and conduct the next generation of analog experiments on multiphase jets to test the Eruption Stability Diagram’s reliability for predicting mass partitioning in multiphase jets between spreading clouds and ground-hugging gravity currents. Concurrently, they will work with Dr. Eric Breard (U. of Edinburgh) to validate the next generation of 3D multiphase flow (MFIX) computer simulations using the experimental dataset. They will also collaborate with volcano radar expert Dr. Franck Donnadieu (U. Clermont Auvergne, France) to use a Doppler radar-based dataset of unsteady ESPs that were measured in-situ at Sabancaya volcano, Peru (2018) to run and validate 3D MFIX eruption simulations. This research project aligns with the study of volcanology in the Petrology and Geochemistry program in the Earth Science division of NSF and the EAR research theme “issues related to scales”. The Eruption Stability Diagram will be the first construct to classify all eruption styles on the basis of mean or time-varying eruption source parameters, predict erupted mass delivered to umbrella clouds and PDCs and, in turn, improve forecasting of eruption hazards and volcano-climate effects, generally. Moreover, characteristic evolutions of eruption source parameters typical of many eruptive phases will trace unique paths through the Eruption Stability Diagram allowing classes of eruptions to be understood through their evolution, a novel new way to classify eruptions. This second way of classifying eruptions may reveal eruptive evolutionary paths diagnostic of specific volcanoes, types of volcanoes, or tectonic environments. The Eruption Stability Diagram will replace the current most popular Volcanic Explosivity Index classification used widely to understand the size and effects of volcanic eruptions on Earth. This project will also advance the multimethod approach of using complementary analog experiments and numerical simulations validated with field data to investigate volcanic phenomena. The analog experiments will be the first to facilitate dissection of the deposit constructed by multiphase jets with varying source parameters to identify deposit features that are diagnostic of eruption column regimes and regime transitions, which will guide eruption deposit field studies. In parallel, the new 3D MFIX simulations will push the limits of multiphase flow simulations by explicitly modeling centimeter-scale particle inertial and buoyancy effects on the kilometer-scale bulk flow. Crucial for eruption monitoring, the ESP and synthetic Doppler radar datasets produced by MFIX simulations of eruptions will be publicly available to inform interpretation of volcanic radar data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.