The influence of the physical properties of volcanic ash on their long range dispersion in the atmosphere and implications for forecasting ash cloud transport
To forecast the dispersion of volcanic ash requires that the sedimentation of ash particles through the atmosphere is effectively modelled. The settling velocity of an ash particle is a function of its size, shape and density, plus the density and viscosity of the air through which it is falling. At the London VAAC (Volcanic Ash Advisory Centre) forecasts of the transport and dispersion of volcanic ash clouds are produced using the Lagrangain atmospheric dispersion model, NAME (Numerical Atmospheric Dispersion Modelling Environment). In NAME ash particles are assumed to be spherical and to have a density of rhyolitic glass, 2300 kg m-3. We calculate the settling velocity, and hence travel distance, of ash particles as a function of their size, shape and density. We show that assuming particles are spherical with a density of rhyolitic glass can account for the mean measured particle size of deposits sampled across Europe following the eruption of Eyjafjallajökull in 2010, using appropriate meteorology. However, taking the minimum measured sphericity and the measured density distribution of the Eyjafjallajökull 2010 ash, particles can travel up to 40% further. This can help account for the largest particles observed in the deposits, with diameters up to 100 μm. We consider the impact of accounting for the measured particle characteristics on the forecasts of the transport and dispersion of the Eyjafjallajökull 2010 volcanic ash cloud. The meteorology that occurred during the event must also be accounted for as both vertical motions, such as convective uplift and turbulent mixing, and horizontal wind speeds vary both in time and space. We use NAME coupled with Numerical Weather Prediction (NWP) meteorological fields to model the particle size distribution (PSD) of the Eyjafjallajökull 2010 volcanic ash cloud, and resulting deposits. The initial input PSD, particle density distribution, and particle shape are varied and the model output compared to the PSD of the ash cloud measured by the FAAM research aircraft and to the measured PSD of ash deposits sampled on the Faroe Islands. We discuss the sensitivity of forecasts of the dispersion of volcanic ash to the representation of particle characteristics in NAME, the importance of representing the weather in ash fall models, and discuss the implications of these results for the operational forecasting of volcanic ash dispersion at the London VAAC.