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首页> 外文期刊>Journal of Volcanology and Geothermal Research >Detection of plumes at Redoubt and Etna volcanoes using the GPS SNR method
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Detection of plumes at Redoubt and Etna volcanoes using the GPS SNR method

机译:使用GPS SNR方法检测堡垒和埃特纳火山的羽流

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摘要

Detection and characterization of volcanic eruptions is important both for public health and aircraft safety. A variety of ground sensors are used to monitor volcanic eruptions. Data from these ground sensors are subsequently incorporated into models that predict the movement of ash. Here a method to detect volcanic plumes using GPS signals is described. Rather than carrier phase data used by geodesists, the method takes advantage of attenuations in signal to noise ratio (SNR) data. Two datasets are evaluated: the 2009 Redoubt Volcano eruptions and the 2013/2015 eruptions at Mt. Etna. SNR-based eruption durations are compared with previously published seismic, infrasonic, and radar studies at Redoubt Volcano. SNR-based plume detections from Mt. Etna are compared with L-band radar and tremor observations. To place these SNR observations from Redoubt and Etna in context, a model of the propagation of GPS signals through both water/water vapor and tephra is developed. Neither water nor fine ash particles will produce the observed attenuation of GPS signals, while scattering caused by particles >1 cm in diameter potentially could. (C) 2017 Elsevier B.V. All rights reserved.
机译:火山喷发的检测和表征对于公共卫生和飞机安全都是重要的。各种地面传感器用于监测火山喷发。来自这些地面传感器的数据随后被合并到预测灰烬运动的模型中。这里描述了一种使用GPS信号检测火山羽流的方法。该方法利用了信噪比(SNR)数据的衰减,而不是大地测量师使用的载波相位数据。对两个数据集进行了评估:2009年重生火山喷发和2013/2015年山山喷发。埃特纳火山。将基于SNR的喷发持续时间与Redoubt Volcano先前发表的地震,次声和雷达研究进行了比较。来自山的基于SNR的羽流检测。将Etna与L波段雷达和震颤观测进行比较。为了将来自Redoubt和Etna的这些SNR观测值放在上下文中,建立了GPS信号通过水/水蒸气和特非拉传播的模型。水和细粉尘颗粒都不会产生GPS信号的衰减,而直径大于1 cm的颗粒可能会引起散射。 (C)2017 Elsevier B.V.保留所有权利。

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