Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 17, 1187-1205, 2017
https://doi.org/10.5194/acp-17-1187-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
25 Jan 2017
Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption
Guangliang Fu1, Fred Prata2, Hai Xiang Lin1, Arnold Heemink1, Arjo Segers3, and Sha Lu1 1Delft University of Technology, Delft Institute of Applied Mathematics, Mekelweg 4, 2628 CD Delft, the Netherlands
2Nicarnica Aviation AS, Gunnar Randers vei 24, 2007 Kjeller, Norway
3TNO, Department of Climate, Air and Sustainability, P.O. box 80015, 3508 TA Utrecht, the Netherlands
Abstract. Using data assimilation (DA) to improve model forecast accuracy is a powerful approach that requires available observations. Infrared satellite measurements of volcanic ash mass loadings are often used as input observations for the assimilation scheme. However, because these primary satellite-retrieved data are often two-dimensional (2-D) and the ash plume is usually vertically located in a narrow band, directly assimilating the 2-D ash mass loadings in a three-dimensional (3-D) volcanic ash model (with an integral observational operator) can usually introduce large artificial/spurious vertical correlations.

In this study, we look at an approach to avoid the artificial vertical correlations by not involving the integral operator. By integrating available data of ash mass loadings and cloud top heights, as well as data-based assumptions on thickness, we propose a satellite observational operator (SOO) that translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The 3-D SOO makes the analysis step of assimilation comparable in the 3-D model space.

Ensemble-based DA is used to assimilate the extracted measurements of ash concentrations. The results show that satellite DA with SOO can improve the estimate of volcanic ash state and the forecast. Comparison with both satellite-retrieved data and aircraft in situ measurements shows that the effective duration of the improved volcanic ash forecasts for the distal part of the Eyjafjallajökull volcano is about 6 h.


Citation: Fu, G., Prata, F., Lin, H. X., Heemink, A., Segers, A., and Lu, S.: Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption, Atmos. Chem. Phys., 17, 1187-1205, https://doi.org/10.5194/acp-17-1187-2017, 2017.
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Short summary
A Satellite Observational Operator (SOO) is proposed to translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The SOO makes the analysis step of assimilation comparable in the 3-D model space, and thus it avoids the artificial vertical correlations by not involving the integral operator in directly assimilating 2-D data. The results show that satellite data assimilation with SOO can efficiently improve the estimate of volcanic ash state and the forecast.
A Satellite Observational Operator (SOO) is proposed to translates satellite-retrieved 2-D...
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