Multiscale Method for Hazard Map Construction

Stefanescu, E. R.; Patra, Abani; Pitman, E. Bruce; Bursik, Marcus; Singla, Puneet; Singh, Tarunraj

doi:10.1007/978-3-319-25138-7_5

Cited by 1 publication

(1 citation statement)

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“…In developing a probabilistic forecast for ash location with time, we thus investigate the effects of aleatoric uncertainty associated with volcanic eruption source parameters and the wind field using suitable ensembles, and epistemic uncertainty associated with the advective equations of motion by investigating outputs of both multiphysics and spectral ensembles. Such an analysis is much needed in complex environments and provides Operational Decision Support using a Dynamic Data‐Driven Application System (DDDAS) paradigm [ Patra et al ., ; Stefanescu et al ., ]. Operational and research flood forecasting systems around the world are increasingly moving toward using ensembles of NWPs, rather than single deterministic forecasts, to drive their flood forecasting systems.…”

Section: Introductionmentioning

confidence: 99%

Temporal, probabilistic mapping of ash clouds using wind field stochastic variability and uncertain eruption source parameters: Example of the 14 April 2010 Eyjafjallajökull eruption

Stefanescu

Patra

Bursik

et al. 2014

J Adv Model Earth Syst

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Uncertainty in predictions from a model of volcanic ash transport in the atmosphere arises from uncertainty in both eruption source parameters and the model wind field. In a previous contribution, we analyzed the probability of ash cloud presence using weighted samples of volcanic ash transport and dispersal model runs and a reanalysis wind field to propagate uncertainty in eruption source parameters alone. In this contribution, the probabilistic modeling is extended by using ensemble forecast wind fields as well as uncertain source parameters. The impact on ash transport of variability in wind fields due to unresolved scales of motion as well as model physics uncertainty is also explored. We have therefore generated a weighted, probabilistic forecast of volcanic ash transport with only a priori information, exploring uncertainty in both the wind field and the volcanic source.

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Section: Introductionmentioning

confidence: 99%