Measurement and simulation of the 16/17 April 2010 Eyjafjallajökull volcanic ash layer dispersion in the northern Alpine region

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Emeis, S., Forkel, R., Junkermann, W., Schäfer, K., Flentje, H., Gilge, S., Fricke, W., Wiegner, M., Freudenthaler, V., Groβ, S., Ries, L., Meinhardt, F., Birmili, W., Münkel, C., Obleitner, F., Suppan, P.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2011
• Subjects: article; Verlagsveröffentlichung; Eyjafjallajökull
• Online Access: https://doi.org/10.5194/acp-11-2689-2011; https://noa.gwlb.de/receive/cop_mods_00046729; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00046349/acp-11-2689-2011.pdf; https://acp.copernicus.org/articles/11/2689/2011/acp-11-2689-2011.pdf

The spatial structure and the progression speed of the first ash layer from the Icelandic Eyjafjallajökull volcano which reached Germany on 16/17 April is investigated from remote sensing data and numerical simulations. The ceilometer network of the German Meteorological Service was able to follow the progression of the ash layer over the whole of Germany. This first ash layer turned out to be a rather shallow layer of only several hundreds of metres thickness which was oriented slantwise in the middle troposphere and which was brought downward by large-scale sinking motion over Southern Germany and the Alps. Special Raman lidar measurements, trajectory analyses and in-situ observations from mountain observatories helped to confirm the volcanic origin of the detected aerosol layer. Ultralight aircraft measurements permitted the detection of the arrival of a second major flush of volcanic material in Southern Germany. Numerical simulations with the Eulerian meso-scale model MCCM were able to reproduce the temporal and spatial structure of the ash layer. Comparisons of the model results with the ceilometer network data on 17 April and with the ultralight aircraft data on 19 April were satisfying. This is the first example of a model validation study from this ceilometer network data.