In this paper, a state-of the art numerical weather prediction (NWP) model is used to simulate the near-field plume of a Plinian-type volcanic eruption. The NWP model is run at very high resolution (of the order of 100 m) and includes a representation of physical processes, including turbulence and buoyancy, that are essential components of eruption column dynamics. Results are shown that illustrate buoyant gas plume dynamics in an atmosphere at rest and in an atmosphere with background wind, and we show that these results agree well with those from theoretical models in the quiescent atmosphere. For wind-blown plumes, we show that features observed in experimental and natural settings are reproduced in our model. However, when comparing with predictions from an integral model using existing entrainment closures there are marked differences. We speculate that these are signatures of a difference in turbulent mixing for uniform and shear flow profiles in a stratified atmosphere. A more complex implementation is given to show that the model may also be used to examine the dispersion of heavy volcanic gases such as sulphur dioxide. Starting from the standard version of the weather research and forecasting (WRF) model, we show that minimal modifications are needed in order to model volcanic plumes. This suggests that the modified NWP model can be used in the forecasting of plume evolution during future volcanic events, in addition to providing a virtual laboratory for the testing of hypotheses regarding plume behaviour.

中文翻译：

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数值天气预报模型在模拟近场火山羽中的应用

在本文中，使用了最新的数值天气预报（NWP）模型来模拟Plinian型火山喷发的近场羽流。NWP模型以非常高的分辨率（大约100 m）运行，并且包括物理过程的表示，包括湍流和浮力，这是喷发柱动力学的基本组成部分。结果表明，在静止大气和背景风环境中，气体羽流的浮力是动态的，并且我们证明这些结果与静态大气中理论模型的结果吻合良好。对于风吹羽流，我们表明在模型中再现了在实验和自然环境中观察到的特征。但是，当与使用现有夹带闭合的整体模型的预测进行比较时，存在明显差异。我们推测这些是层状大气中均匀和剪切流动剖面湍流混合差异的标志。给出了一个更复杂的实现方式，以显示该模型也可以用于检查诸如二氧化硫之类的重火山气体的扩散。从天气研究和预报（WRF）模型的标准版本开始，我们显示了对火山羽建模所需的最小修改。这表明，除了提供虚拟实验室来测试有关羽流行为的假设之外，改进的NWP模型还可以用于预测未来火山事件中的羽流演变。给出了更复杂的实现，以表明该模型还可以用于检查诸如二氧化硫之类的重火山气体的扩散。从天气研究和预报（WRF）模型的标准版本开始，我们显示了对火山羽建模所需的最小修改。这表明，除了提供虚拟实验室来测试有关羽流行为的假设之外，改进的NWP模型还可以用于预测未来火山事件中的羽流演变。给出了一个更复杂的实现方式，以显示该模型也可以用于检查诸如二氧化硫之类的重火山气体的扩散。从天气研究和预报（WRF）模型的标准版本开始，我们显示了对火山羽建模所需的最小修改。这表明，除了提供虚拟实验室来测试有关羽流行为的假设之外，改进的NWP模型还可以用于预测未来火山事件中的羽流演变。