An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions

• Published in: Natural Hazards and Earth System Sciences
• Main Authors: M. Plu, B. Scherllin-Pirscher, D. Arnold Arias, R. Baro, G. Bigeard, L. Bugliaro, A. Carvalho, L. El Amraoui, K. Eschbacher, M. Hirtl, C. Maurer, M. D. Mulder, D. Piontek, L. Robertson, C.-H. Rokitansky, F. Zobl, R. Zopp
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: geo; envir; Eyjafjallajökull
• Online Access: https://doi.org/10.5194/nhess-21-2973-2021; https://nhess.copernicus.org/articles/21/2973/2021/nhess-21-2973-2021.pdf; https://doaj.org/article/c84a1ef738c94c3890896b106f3a0533

High-quality volcanic ash forecasts are crucial to minimize the economic impact of volcanic hazards on air traffic. Decision-making is usually based on numerical dispersion modelling with only one model realization. Given the inherent uncertainty of such an approach, a multi-model multi-source term ensemble has been designed and evaluated for the Eyjafjallajökull eruption in May 2010. Its use for flight planning is discussed. Two multi-model ensembles were built: the first is based on the output of four dispersion models and their own implementation of ash ejection. All a priori model source terms were constrained by observational evidence of the volcanic ash cloud top as a function of time. The second ensemble is based on the same four dispersion models, which were run with three additional source terms: (i) a source term obtained from a model background constrained with satellite data (a posteriori source term), (ii) its lower-bound estimate and (iii) its upper-bound estimate. The a priori ensemble gives valuable information about the probability of ash dispersion during the early phase of the eruption, when observational evidence is limited. However, its evaluation with observational data reveals lower quality compared to the second ensemble. While the second ensemble ash column load and ash horizontal location compare well to satellite observations, 3D ash concentrations are negatively biased. This might be caused by the vertical distribution of ash, which is too much diluted in all model runs, probably due to defaults in the a posteriori source term and vertical transport and/or diffusion processes in all models. Relevant products for the air traffic management are horizontal maps of ash concentration quantiles (median, 75 %, 99 %) at a finely resolved flight level grid as well as cross sections. These maps enable cost-optimized consideration of volcanic hazards and could result in much fewer flight cancellations, reroutings and traffic flow congestions. In addition, they could be used for route ...