IDR/Collaborative Research: Characterizing Uncertainty in the Motion of Volcanic Plumes Advected by Wind Fields

这笔赠款为制定定量评估火山喷发引起的火山灰云运动预测的可信度的方法提供了支助。通过将统计建模、随机分析和计算科学的工具与广泛使用的火山颗粒扩散代码相结合，这笔赠款将提供工具，以评估对火山灰云运动的实时预测，该预测考虑到了不同的风况和一系列模型变量。更具体地说，烟尘计算机代码将被用作火山灰云模拟工具。喷雾传播的是空气中的火山灰羽流，它将与名为Bent的火山喷发模型整合在一起。弯曲输出灰分分布作为时间和高度的函数。这种集成替代了未知的烟团输入参数，这些参数更好地(但不是完全)受物理约束。这个综合模式将被用来开发一个框架，用于分析不确定参数和不同风场模式对云位置输出分布的影响。多项式混沌求积和随机积分技术将被用来提供这些预测的可靠性(即误差)的定量测量。了解扩散模型预测中不确定性的影响对于评估和减轻与火山灰云有关的潜在危险很重要。火山附近和远离火山喷发的顺风向都有经济和社会影响。例如，航空业决定航班时刻表、航线和燃油消耗估计，部分基于分散模型预测。这项研究的结果将为决策者和民防当局提供一个评估危险风险的框架。重要的是，这种方法的发展独立于特定的喷烟代码，因此预测和可靠性分析的框架可以直接应用于其他火山灰云代码，更广泛地应用于其他危险模型--例如放射性和化学烟羽扩散，以及卡车或铁路事故的气体释放。

This grant provides support to develop a methodology for the quantitative assessment of confidence in predictions of the motion of ash clouds caused by volcanic eruptions. By combining statistical modeling, stochastic analysis, and the tools of computational science together with a widely-used volcanic particle dispersion code, this grant will provide tools to assess real time predictions of ash cloud motion that accounts for varying wind conditions and a range of model variables. More specifically, the PUFF computer code will be used as the ash cloud simulation tool. PUFF, which propagates an airborne ash plume, will be integrated with a volcanic eruption model called BENT. BENT outputs ash distribution as a function of time and height. This integration substitutes for the unknown PUFF input parameters several BENT inputs that are better (but not entirely) constrained by physics. This integrated model will be used to develop a framework for analyzing the effects of uncertain parameters and of differing windfield models, on the output distribution for the cloud location. Polynomical chaos quadrature and stochastic integration techniques will be used to provide a quantitative measure of the reliability (i.e. error) of those predictions. Understanding the effects of uncertainty in dispersion model predictions are important to assess and mitigate potential hazards associated with volcanic ash clouds. There are economic and sociologic impacts both near the volcano and far downwind from the eruption. For example, the airline industry decides flight schedules, routes, and fuel consumption estimates, based in part on dispersion model forecasts. The results of this research will provide decision makers and civil protection authorities with a framework for evaluating hazard risk. Importantly, this methodological development is independent of the specific PUFF code, so the framework for prediction and reliability analysis can be directly applied to other ash cloud codes, and more generally to other hazard models -- such as radiological and chemical plume dispersion, and gas release from truck or rail accidents.