Abstract
Volcanic ash advisories are produced by specialised forecasters who combine several sources of observational data and volcanic ash dispersion model outputs based on their subjective expertise. These advisories are used by the aviation industry to make decisions about where it is safe to fly. However, both observations and dispersion model simulations are subject to various sources of uncertainties that are not represented in operational forecasts. Quantification and communication of these uncertainties are fundamental for making more informed decisions. Here, we develop a data assimilation technique which combines satellite retrievals and volcanic ash transport and dispersion model (VATDM) output, considering uncertainties in both data sources. The methodology is applied to a case study of the 2019 Raikoke eruption. To represent uncertainty in the VATDM output, 1000 simulations are performed by simultaneously perturbing the eruption source parameters, meteorology and internal model parameters (known as the prior ensemble). The ensemble members are filtered, based on their level of agreement with Himawari satellite retrievals of ash column loading, to produce a posterior ensemble that is constrained by the satellite data and its uncertainty. For the Raikoke eruption, filtering the ensemble skews the values of mass eruption rate towards the lower values within the wider parameters ranges initially used in the prior ensemble (mean reduces from 1 Tg h−1 to 0.1 Tg h−1). Furthermore, including satellite observations from subsequent times increasingly constrains the posterior ensemble. These results suggest that the prior ensemble leads to an overestimate of both the magnitude and uncertainty in ash column loadings. Based on the prior ensemble, flight operations would have been severely disrupted over the Pacific Ocean. Using the constrained posterior ensemble, the regions where the risk is overestimated are reduced potentially resulting in fewer flight disruptions. The data assimilation methodology developed in this paper is easily generalisable to other short duration eruptions and to other VATDMs and retrievals of ash from other satellites.
Highlights
IntroductionVolcanic ash in the atmosphere poses a hazard to aircraft (Casadevall, 1994)
volcanic ash transport and dispersion model (VATDM) solve dynamic equations to evolve the system state forward in time. Such simulated volcanic ash distributions are subject to errors due to inaccurate parametrisations of physical processes, errors in the driving meteorological fields and errors in the volcanic eruption source parameters
Compared to the parameter ranges used for the prior ensemble (Table 1), the range of eruption source parameters used to produce simulated ash clouds that represent a good approximation to the observed volcanic ash cloud reduces as the posterior ensembles become more constrained by the satellite retrievals
Summary
Volcanic ash in the atmosphere poses a hazard to aircraft (Casadevall, 1994). It is important to accurately forecast the evolution of volcanic ash cloud in the atmosphere for the aviation industry. Forecasting the distribution of volcanic ash in the atmosphere at a given time is typically performed using a volcanic ash transport and dispersion model (VATDM). VATDMs solve dynamic equations to evolve the system state (volcanic ash cloud) forward in time. Such simulated volcanic ash distributions are subject to errors due to inaccurate parametrisations of physical processes, errors in the driving meteorological fields and errors in the volcanic eruption source parameters. Observations of volcanic ash distributions may be obtained from ground-based, aircraft or satellite-based instruments
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