The Use of a Numerical Weather Prediction Model to Simulate Near-field Volcanic Plumes

Ralph R Burton*, Mark J Woodhouse, Alan M Gadian, Stephen D Mobbs

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

6 Citations (Scopus)
202 Downloads (Pure)

Abstract

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. 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.
Original languageEnglish
Article number594
Number of pages27
JournalAtmosphere
Volume11
Issue number6
DOIs
Publication statusPublished - 4 Jun 2020

Keywords

  • volcanic plumes
  • atmospheric dispersion
  • numerical weather prediction models

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