EMS Annual Meeting Abstracts
Vol. 20, EMS2023-508, 2023, updated on 06 Jul 2023
https://doi.org/10.5194/ems2023-508
EMS Annual Meeting 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-parameter sensitivities along warm conveyor belt trajectories: A visual analysis using Met.3D

Maicon Hieronymus1, Christoph Neuhauser2, Michael Kern3, Marc Rautenhaus4, Annika Oertel5, and Rüdiger Westermann2
Maicon Hieronymus et al.
  • 1Institute of Computer Science, Johannes Gutenberg University, Mainz, Germany
  • 2School of Computation, Information and Technology, Technical University of Munich, München, German
  • 3Advanced Micro Devices GmbH, Dornach bei München, Germany
  • 4Regional Computing Centre, Visual Data Analysis Group, University of Hamburg, Hamburg, Germany
  • 5Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology Karlsruhe, Germany

Cloud microphysical processes are highly relevant for cloud and precipitation characteristics, cloud radiative properties and the latent heat release during phase changes of water can interact with atmospheric dynamics. These sub-grid scale processes are typically parameterized in numerical weather prediction models, introducing parametric uncertainty in weather forecasts. The analysis of uncertainties related to these parameterizations imposes multiple challenges: On the one hand, it requires robust quantification of the impact of hundreds of uncertain model parameters. On the other hand, it requires adequate tools to filter, visualize, and understand the parameter impacts. 
Algorithmic Differentiation (AD) is a tool to efficiently evaluate the magnitude and timing at which a model state is sensitive to a model parameter [1]. We demonstrate the capabilities of AD, focusing on uncertain parameters in a two-moment cloud microphysics scheme along trajectories of a warm conveyor belt, which is the primary cloud- and precipitation-forming airstream in extratropical cyclones. 
To understand the parameter influence, we here introduce methods to systematically analyze different impacts in different warm conveyor belt ascent scenarios [2]. For example, this includes an objective clustering of trajectories w.r.t to parameter sensitivities. Met.3D, an open-source tool for interactive, three-dimensional visualization of numerical atmospheric model datasets, then provides a visual interface to compare multiple sensitivities on multiple trajectories from each cluster, assess the spatio-temporal relationships between the sensitivities and the trajectories’ shapes and locations, and find similarities in the temporal development of sensitivities along various trajectories’ location and time for ascent. 

 

[1] Hieronymus, M., Baumgartner, M., Miltenberger, A. and Brinkmann, A.: Algorithmic Differentiation for Sensitivity Analysis in Cloud Microphysics, J. Adv. Model Earth Syst. (2022), 10.1029/2021MS002849. 

[2] Neuhauser, C., Hieronymus, M., Kern, M., Rautenhaus, M., Oertel, A., and Westermann, R.: Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar0), Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-27, in review, 2023. 

How to cite: Hieronymus, M., Neuhauser, C., Kern, M., Rautenhaus, M., Oertel, A., and Westermann, R.: Multi-parameter sensitivities along warm conveyor belt trajectories: A visual analysis using Met.3D, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-508, https://doi.org/10.5194/ems2023-508, 2023.