EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

A feature-based perspective on upscale error growth.

Sören Schmidt1, Michael Riemer1, and Jorge de Heuvel1,2
Sören Schmidt et al.
  • 1Institut für Physik der Atmosphäre, Johannes Gutenberg-Universität, Mainz, Germany
  • 2Current affiliation: Intelligent Systems and Robotics, University of Bonn Computer Science VI, Bonn, Germany

How to cite: Schmidt, S., Riemer, M., and de Heuvel, J.: A feature-based perspective on upscale error growth., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7551,, 2022.

This abstract has been withdrawn on 22 May 2022.