The Impact of Eruption Source Parameter Uncertainties on Ash Dispersion Forecasts During Explosive Volcanic Eruptions

Open Access

Abstract

Publisher's version (útgefin grein) ; Volcanic ash in the atmosphere is a hazard to aviation. To predict which areas of airspace are most likely to be affected by the presence of ash, Volcanic Ash Advisory Centers (VAACs) use observations and atmospheric dispersion models. These models are initialized with, among other parameters, a mass eruption rate (MER), which quantifies the emission rate into the atmosphere at the source. This influences the predicted spatial–temporal evolution and concentration of the ash cloud. Different models are available to estimate MER from the volcanic plume height and some models also include the weather conditions (e.g., wind speed). The REFIR software tool uses time-series of plume height estimated from observations and weather data to provide estimates of MER through time. Here we present an updated version of REFIR that can now be used also to calculate MER for past eruptions and produce output parameters in a format suitable for use with the NAME dispersion model (UK Met Office—London VAAC). We also investigate how uncertainty in input parameters is propagated through to dispersion model output. Our results show that a +/−1 km uncertainty on a 6 km high plume can result in the affected area ranging by a factor of three between the minimum and maximum estimates. Additionally, we show that using wind-affected plume models results in affected areas that are five times larger than using no-wind-affected models. This demonstrates the sensitivity of MER to the type of plume model chosen (no-wind- vs. wind-affected). ; We thank Larry Mastin, Arnau Folch, and an anonymous reviewer for their comments and suggestions that contributed to the improvement of the manuscript, and Lynn Russell for the editorial handling. We also thank Dr. Susan Loughlin (British Geological Survey), Dr. Susan Leadbetter (UK Met Office) and Dr. Claire Witham (UK Met Office) for their valuable suggestions. Fabio Dioguardi and John A. Stevenson have been supported from UK National Capability funding (BGS Innovation Flexible Fund). Fabio Dioguardi has also been supported by the European Union's Horizon 2020 project EUROVOLC (grant agreement no 731070). Tobias D?rig's work is supported by the Icelandic Research Fund (Rann?s) grant no. 206527-051. This work is published with permission of the Executive Director of British Geological Survey (UKRI) ; Peer Reviewed