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Near-Real-Time Detection of Tephra Eruption Onset and Mass Flow Rate Using Microwave Weather Radar and Infrasonic Arrays

机译:使用微波天气雷达和次声阵列近实时地检测特非拉火山爆发和质量流量

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摘要

During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grímsvötn eruption in 2011, the Eyjafjallajökull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential of MW weather radar for ash plume monitoring in near real time and its complementarity with infrasonic array for early-warning system design.
机译:在爆发事件期间,对火山爆炸开始及其质量流率(MFR)的近实时监控是预测灰羽散布并减轻空中交通风险的关键因素。微波(MW)气象雷达已被证明是导出爆发源参数的基本工具。我们将这种能力扩展到包括在整个火山灰雷达检索方法中的预警检测方案。该方案称为火山灰检测(VAD)算法,它基于同时使用模糊逻辑和条件概率的混合技术。在一些案例研究中显示了VAD应用的示例,包括2011年的冰岛Grímsvötn喷发,2010年的Eyjafjallajökull喷发以及意大利的Mt.Mt。 2013年的埃特纳火山喷发。将基于雷达的VAD模块的喷发开始估计与次声阵列数据进行比较。还讨论了MFR的一维数值模拟和分析模型估计,并将其与基于传感器的检索进行了比较。结果在所有情况下均证实了兆瓦级气象雷达具有近实时监测烟灰羽的潜力,并且与次声阵列的互补性可用于预警系统设计。

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