A Near-Real-Time Method for Estimating Volcanic Ash Emissions Using Satellite Retrievals

• Published in: Atmosphere
• Main Authors: Rachel Pelley, David Thomson, Helen Webster, Michael Cooke, Alistair Manning, Claire Witham, Matthew Hort
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2021
• Subjects: volcanic ash emissions; source inversion; atmospheric dispersion; satellite ash retrievals; Eyjafjallajökull
• Online Access: https://doi.org/10.3390/atmos12121573

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions.