Fast Construction of Surrogates for UQ Central to DDDAS– Application to Volcanic Ash Transport1

Volcanic ash transport and dispersion (VATD) models simulate atmospheric transport of ash from a volcanic source represented by parameterized concentration of ash with height. Most VATD models represent the volcanic plume source as a simple line with a parameterized ash emission rate as a function of height, constrained only by a total mass eruption rate (MER) for a given total rise height. However, the actual vertical ash distribution in volcanic plumes varies from case to case, having complex dependencies on eruption source parameters, such as grain size, speed at the vent, vent size, buoyancy flux, and atmospheric conditions. We present here for the first time the use of a three-dimensional (3D) plume model based on conservation laws to represent the ash cloud source without any prior assumption or simplification regarding plume geometry. By eliminating assumed behavior associated with a parameterized plume geometry, the predictive skill of VATD simulations is improved. We use our recently developed volcanic plume model based on a 3D smoothed-particle hydrodynamic Lagrangian method and couple the output to a standard Lagrangian VATD model. We apply the coupled model to the Pinatubo eruption in 1991 to illustrate the effectiveness of the approach. Our investigation reveals that initial particle distribution in the vertical direction, including within the umbrella cloud, has more impact on the long-range transport of ash clouds than does the horizontal distribution. Comparison with satellite data indicates that the 3D model-based distribution of ash particles through the depth of the volcanic umbrella cloud, which is much lower than the observed maximum plume height, produces improved long-range VATD simulations. We thus show that initial conditions have a significant impact on VATD, and it is possible to obtain a better estimate of initial conditions for VATD simulations with deterministic, 3D forward modeling of the volcanic plume. Such modeling may therefore provide a path to better forecasts lessening the need for user intervention, or attempts to observe details of an eruption that are beyond the resolution of any potential satellite or ground-based technique, or a posteriori creating a history of ash emission height via inversion.

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“…The significance of the wind field has been confirmed by other researchers (e.g. Stefanescu et al, 2014).…”

Section: Sentitivity Of Other Input Parameterssupporting

confidence: 78%

Simulating the Transport and Dispersal of Volcanic Ash Clouds With Initial Conditions Created by a 3D Plume Model

et al. 2021

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“…Emulators or similar statistical strategies have been constructed or proposed for volcanic ash transport models in previous works [ 6 , 8 , 43 – 45 ]. The success of these studies comes from the use of novel techniques and ideas, and different ways to view and evaluate the data.…”

Section: Introductionmentioning

confidence: 99%

Novel statistical emulator construction for volcanic ash transport model Ash3d with physically motivated measures

et al. 2020

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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.

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“…we deal with large datasets (frequently data at high temporal and spatial resolution), b) the datasets contains many redundancies that add little important information beyond that of the primary data, and, c) the input is too large to fit in core memory -the cost of transferring the data to and from slow memory typically dominates the cost of performing the analysis. Such an analysis is much needed in complex environments, and provides Operational Decision Support using a Dynamic Data Driven Application System (DDDAS) paradigm [31,38]. To capture the possibility of a wide range of uncertainty in numerical model response, a large set of geostatistical model realizations needs to be processed.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Volcanic Plume Hazards With Fast UQ

Stefanescu

Patra

Bursik

et al. 2015

Procedia Computer Science

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This paper introduces a numerically-stable multiscale scheme to efficiently generate probabilistic hazard maps for volcanic ash transport using models of transport, dispersion and wind. The scheme relies on graph-based algorithms and low-rank approximations of the adjacency matrix of the graph. This procedure involves representing both the parameter space and physical space by a weighted graph. A combination of clustering and low rank approximation is then used to create a good approximation of the original graph. By performing a multiscale data sampling, a well-conditioned basis of a low rank Gaussian kernel matrix, is identified and used for out-of-sample extensions used in generating the hazard maps.

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Fast Construction of Surrogates for UQ Central to DDDAS– Application to Volcanic Ash Transport1

Cited by 9 publications

References 8 publications

Simulating the Transport and Dispersal of Volcanic Ash Clouds With Initial Conditions Created by a 3D Plume Model

Simulating the Transport and Dispersal of Volcanic Ash Clouds With Initial Conditions Created by a 3D Plume Model

Novel statistical emulator construction for volcanic ash transport model Ash3d with physically motivated measures

Forecasting Volcanic Plume Hazards With Fast UQ

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