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Ensemble-Based Data Assimilation and Forecasting of Volcanic Ash

  • Andreas UppstuEmail author
  • Julius Vira
  • Mikhail Sofiev
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

Volcanic ash and other aerosols such as desert dust form significant hazards for aviation and can cause both direct safety threats and significant economic losses. However, forecasts of aviation hazards have generally been deterministic, although the available computational resources would easily allow for them to be ensemble-based. In principle, ensemble-based forecasts can enable more accurate error estimates and thus an improved risk management framework. Advanced data assimilation methods, such the Ensemble Kalman Filter, coupled with a meteorological forecast ensemble, provide increased accuracy and the possibility to estimate the source term by taking into account its correlation with the observed ash concentration.

Notes

Acknowledgements

The authors acknowledge funding from the EUNADICS-AV and the Nordic Centre of Excellence EmblA projects. Initial volcano model development was performed with support from the VAST and SMASH projects of the European Space Agency (ESA).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Atmospheric Composition Research, Finnish Meteorological InstituteHelsinkiFinland
  2. 2.Cornell UniversityIthacaUSA

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