The effect of wind and plume height reconstruction methods on the accuracy of simple plume models — a second look at the 2010 Eyjafjallajökull eruption

• Published in: Bulletin of Volcanology
• Main Authors: Dürig, Tobias, Guðmundsson, Magnús T., Ágústsdóttir, Thorbjörg, Högnadóttir, Thórdís, Schmidt, Louise
• Other Authors: Jarðvísindastofnun (HÍ), Institute of Earth Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Háskóli Íslands, University of Iceland
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer 2022
• Subjects: Geochemistry and Petrology; Volcanology; Explosive volcanism; volcanic ash plumes; plume modelling; mass eruption rate; Jarðefnaeldsneyti; Eldgosið í Eyjafjallajökli; Gosmökkur; Eyjafjallajökull
• Online Access: https://hdl.handle.net/20.500.11815/3722; https://doi.org/10.1007/s00445-022-01541-z

Real-time monitoring of volcanic ash plumes with the aim to estimate the mass eruption rate is crucial for predicting atmospheric ash concentration. Mass eruption rates are usually assessed by 0D and 1D plume models, which are fast and require only a few observational input parameters, often only the plume height. A model’s output, however, depends also on the plume height data handling strategy (sampling rate, gap reconstruction methods and statistical treatment), especially in long-term eruptions with incomplete plume height records. Representing such an eruption, we used Eyjafjallajökull 2010 to test the sensitivity of six simple and two explicitly wind-affected plume models against 22 data handling strategies. Based on photogrammetric measurements, the wind deflection of the plume was determined and used to re-calibrate radar height data. The resulting data was then subjected to different data handling strategies, before being used as input for the plume models. The model results were compared to the erupted mass measured on the ground, allowing us to assess the prediction accuracy of each combination of data handling strategy and model. Combinations that provide highest prediction accuracies vary, depending on data coverage, eruptive strength, and fragmentation style. However, for this type of moderate to weak eruption, the most important factor was found to be the prevailing windspeed. When windspeeds exceed 20 m/s, most combinations of strategies and models provide predictions that underestimate the erupted mass by more than 40%. Under such conditions, the optimal choice of data handling strategy and plume model is of particularly relevance. The geo-referencing and photo analysis was conducted under the EU Framework 7 FutureVolc project (2012–2016). This work contributes to project MAXI-Plume, supported by the Icelandic Research Fund (Rannís), grant Nr. 206527-051. TD was supported by the IRF (Rannís) Postdoctoral project grant 206527–051. Pre-print (óritrýnt handrit)