Progress towards development of a probabilistic, quantitative volcanic ash forecast model — Australian Meteorological and Oceanographic Society

Progress towards development of a probabilistic, quantitative volcanic ash forecast model (#270)

Chris Lucas 1 , Meelis Zidikheri 1 , Mey Manickam 1 , Rod Potts 1 , Maree Carroll 1
  1. Bureau of Meteorology, Docklands, VIC, Australia

In support of the operations in the Darwin Volcanic Ash Advisory Centre (VAAC), the Bureau of Meteorology (BoM) is investing in the development of the Dispersion Ensemble Prediction System (DEPS), an operational modelling system for forecasting volcanic ash dispersion. The current version of DEPS uses an ensemble of NWP forecast data, mostly from the BoM's ACCESS model suite, to drive the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model and produce a probabilistic forecast of ash dispersion that accounts for meteorological uncertainty. The ensemble is initialized from eruption parameters (e.g. plume height) input by the user via a web interface.

The next version of DEPS, currently in development, extends its capability by accounting for uncertainties in the source term. This is being done through the assimilation of observations into the ensemble forecast. Observations potentially come from two sources: i.) polygons of ash location produced by the VAAC as part of their advisories; and/or ii.) satellite-based estimates of the mass load from the NOAA Volcanic Cloud Analysis Toolbox (VOLCAT) system. Incorporating both types of observations will help to constrain the uncertainty in estimates of the top and bottom heights of the plume and the quantitative estimates of the mass load. These products are highly desired by the aviation industry to help manage the risks for flight operations and to ensure safety.

At the conference, case studies of recent eruptions will be analysed to explore the performance of the system under development, including the impact that incorporating these observations has on the resulting forecast. Practical issues around the use and interpretation of both quantitative satellite retrievals and advanced dispersion modelling techniques in an operational environment will also be discussed.

#AMOS2019