Statistical emulators are a key tool for rapidly producing probabilistic hazard analysis of geophysical processes. Given output data computed for a relatively small number of parameter inputs, an emulator interpolates the data, providing the expected value of the output at untried inputs and an estimate of error at that point. In this work, we propose to fit Gaussian Process emulators to the output from a volcanic ash transport model, Ash3d. Our goal is to predict the simulated volcanic ash thickness from Ash3d at a location of interest using the emulator. Our approach is motivated by two challenges to fitting emulators—characterizing the input wind field and interactions between that wind field and variable grain sizes. We resolve these challenges by using physical knowledge on tephra dispersal. We propose new physically motivated variables as inputs and use normalized output as the response for fitting the emulator. Subsetting based on the initial conditions is also critical in our emulator construction. Simulation studies characterize the accuracy and efficiency of our emulator construction and also reveal its current limitations. Our work represents the first emulator construction for volcanic ash transport models with considerations of the simulated physical process.

中文翻译：

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具有物理激励措施的火山灰迁移模型 Ash3d 的新型统计仿真器构建

统计模拟器是快速生成地球物理过程概率危险分析的关键工具。给定为相对较少的参数输入计算的输出数据，仿真器对数据进行插值，提供未尝试输入的输出预期值以及该点的误差估计。在这项工作中，我们建议将高斯过程模拟器与火山灰传输模型 Ash3d 的输出相匹配。我们的目标是使用模拟器在感兴趣的位置预测来自 Ash3d 的模拟火山灰厚度。我们的方法受到拟合模拟器的两个挑战的启发——表征输入风场以及该风场与可变粒度之间的相互作用。我们通过使用有关火山灰传播的物理知识来解决这些挑战。我们提出了新的物理动机变量作为输入，并使用归一化输出作为拟合模拟器的响应。基于初始条件的子集在我们的模拟器构建中也很关键。仿真研究表征了我们仿真器结构的准确性和效率，并揭示了其当前的局限性。我们的工作代表了第一个考虑模拟物理过程的火山灰运输模型模拟器构建。