EGU2020-15011, updated on 21 Apr 2023
EGU General Assembly 2020
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Interactive 3D visual analysis in weather forecasting

Marc Rautenhaus1, Timothy Hewson2, Kameswar Rao Modali1, Andreas Beckert1, and Michael Kern3
Marc Rautenhaus et al.
  • 1Universität Hamburg, Regional Computing Centre, Hamburg, Germany
  • 2European Centre for Medium Range Weather Forecasts, Reading, UK
  • 3Computer Graphics and Visualization Group, Technical University of Munich, Germany

Visualization of numerical weather prediction data and atmospheric observations has always been an important and ubiquitous tool in weather forecasting. Visualization research has made much progress in recent years, in particular with respect to techniques for ensemble data, interactivity, 3D depiction, and feature-detection. Transfer of new techniques into weather forecasting, however, is slow.

In this contribution, we will discuss the potential of recent developments in 3D and ensemble visualization research for weather forecasting. We will introduce our work on 3D feature-detection methods for jet-stream and front features, which facilitate analysis of the evolution of jet-stream core lines and frontal surfaces in an (ensemble) forecast. The techniques have been integrated into the 3D visual ensemble analysis framework Met.3D (, in which they can be combined with traditional 2D depictions as well as further 3D visual elements and be displayed in an interactive 3D context. We will present and discuss 3D ensemble forecast products created with Met.3D based on forecast data from ECMWF and DWD, and demonstrate their use in the exploration of example cases including an extratropical transition over the North Atlantic and a European winter storm.

In addition, we will introduce new semi-operational 3D forecast products based on our techniques that we provide experimentally on the web, in order to gather user feedback and to initiate discussion about potential benefit of such products for operations.

How to cite: Rautenhaus, M., Hewson, T., Modali, K. R., Beckert, A., and Kern, M.: Interactive 3D visual analysis in weather forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15011,, 2020.


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