Volcanic SO 2 and SiF 4 visualization using 2-D thermal emission spectroscopy – Part 2: Wind propagation and emission rates
Volcanic SO 2 and SiF 4 visualization using 2-D thermal emission spectroscopy – Part 2: Wind propagation and emission rates
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使用二维热发射光谱法实现火山 SO 2 和 SiF 4 可视化 – 第 2 部分：风传播和发射速率
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
M. Grutter
中科院分区：
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作者：
A. Krueger;W. Stremme;R. Harig;M. Grutter
抽象的。 Stremme 等人在第 1 部分中描述了一种利用热发射光谱法测量火山气体二维 (2-D) 羽流的技术。 （2012a）。该论文介绍了获取 SO2 和 SiF4 斜柱图像的仪器方面和检索策略，以及在波波卡特佩特火山观察到的特定事件的动画。这项工作的重点是确定气体传播速度并根据给定图像序列估计排放率的程序。火山气体的二维柱密度分布（可作为时间连续帧）提供了预测风场和火山羽流传播的平均速度的信息。该信息很有价值，因为使用遥感技术计算气体排放率时最大的不确定性来自于传播速度，而传播速度往往没有得到充分的假设。所提出的重构方法主要使用类吉洪诺夫正则化来解决连续性方程作为不适定问题的问题。从现有数据集中观察到，如果主传播方向垂直于视线，该算法对于信号最强的 SO2 效果很好，在某些有利的情况下也适用于 SiF4。由于这里使用的算法与基于最优估计理论的剖面检索重建方法的相似性，可以以类似的方式计算平均核等诊断工具，并且可以将信息量化为自由度。由此可见，风场和羽流柱分布的结合可以提供火山白天和夜间的排放率。
Abstract. A technique for measuring two-dimensional (2-D) plumes of volcanic gases with thermal emission spectroscopy was described in Part 1 by Stremme et al. (2012a). In that paper the instrumental aspects as well as retrieval strategies for obtaining the slant column images of SO2 and SiF4, as well as animations of particular events observed at the Popocatepetl volcano, were presented. This work focuses on the procedures for determining the propagation speed of the gases and estimating an emission rate from the given image sequences. A 2-D column density distribution of a volcanic gas, available as time-consecutive frames, provides information of a projected wind field and the average velocity at which the volcanic plume is propagating. This information is valuable since the largest uncertainties when calculating emission rates of the gases using remote sensing techniques arise from propagation velocities which are often inadequately assumed. The presented reconstruction method solves the equation of continuity as an ill-posed problem using mainly a Tikhonov-like regularisation. It is observed from the available data sets that if the main direction of propagation is perpendicular to the line-of-sight, the algorithm works well for SO2, which has the strongest signals, and also for SiF4 in some favourable cases. Due to the similarity of the algorithm used here with the reconstruction methods used for profile retrievals based on optimal estimation theory, diagnostic tools like the averaging kernels can be calculated in an analogous manner and the information can be quantified as degrees of freedom. Thus, it is shown that the combination of wind field and column distribution of the gas plume can provide the emission rate of the volcano both during day and night.