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Model-Based Weather Radar Remote Sensing of Explosive Volcanic Ash Eruption

机译:基于模型的爆炸性火山灰喷发气象雷达遥感

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摘要

Microphysical and dynamical features of volcanic ash clouds can be quantitatively monitored by using ground-based microwave weather radars. These systems can provide data for determining the ash volume, total mass, and height of eruption clouds. In order to demonstrate the unique potential of this microwave active remote-sensing technique, the case study of the eruption of Augustine Volcano in Alaska in January 2006 is described and analyzed. Volume scan data, acquired by a NEXRAD WSR-88D S-band ground-based weather radar, are processed to automatically classify and estimate eruptive cloud particle concentration. The numerical results of the coupled model Z-reflectivity from Active Tracer High resolution Atmospheric Model (ATHAM), including particle aggregation processes and simulation of radar reflectivity from the ATHAM microphysical model, are exploited to train the inversion algorithm. The volcanic ash radar retrieval based on the ATHAM algorithm is a physical-statistical approach based on the backscattering microphysical model of volcanic cloud particles (hydrometeors, ash, and aggregates), used within a Bayesian classification and optimal regression algorithm. A sensitivity analysis is carried out to evaluate the overall error budget. The evolution of the Augustine eruption is discussed in terms of radar measurements and products, pointing out the unique features, the current limitations, and future improvements of radar remote sensing of volcanic plumes.
机译:火山灰云的微物理和动力学特征可以通过使用地面微波天气雷达进行定量监测。这些系统可以提供用于确定灰烬量,总质量和喷发云团高度的数据。为了证明这种微波有源遥感技术的独特潜力,对2006年1月在阿拉斯加的奥古斯丁火山爆发的案例进行了描述和分析。由NEXRAD WSR-88D S波段地面气象雷达获取的体扫描数据经过处理后,可以自动分类和估算火山云中的粒子浓度。利用Active Tracer高分辨率大气模型(ATHAM)耦合模型Z反射率的数值结果,包括粒子聚集过程和ATHAM微物理模型对雷达反射率的模拟,来训练反演算法。基于ATHAM算法的火山灰雷达检索是一种物理统计方法,基于贝叶斯分类和最佳回归算法中使用的火山云粒子(水气,灰分和聚集体)的反向散射微物理模型。进行敏感性分析以评估总体误差预算。从雷达测量和产品的角度讨论了奥古斯丁喷发的演变过程,指出了火山羽的雷达遥感的独特功能,当前局限性和未来改进。

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