Articles | Volume 16, issue 16
Methods for assessment of models
17 Aug 2023
Methods for assessment of models |  | 17 Aug 2023

Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)

Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann

Related authors

An objective identification technique for potential vorticity structures associated with African easterly waves
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228,,, 2024
Short summary
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev. Discuss.,,, 2024
Preprint under review for GMD
Short summary
The effect of lossy compression of numerical weather prediction data on data analysis: a case study using enstools-compression 2023.11
Oriol Tintó Prims, Robert Redl, Marc Rautenhaus, Tobias Selz, Takumi Matsunobu, Kameswar Rao Modali, and George Craig
EGUsphere,,, 2024
Short summary
An ERA5 Climatology of Synoptic-Scale Negative Potential Vorticity-Jet Interactions over the Western North Atlantic
Alexander Lojko, Andrew Charles Winters, Annika Oertel, Christiane Jablonowski, and Ashley Elizabeth Payne
EGUsphere,,, 2024
Short summary
The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450,,, 2023
Short summary

Related subject area

Atmospheric sciences
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330,,, 2024
Short summary
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247,,, 2024
Short summary
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189,,, 2024
Short summary
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039,,, 2024
Short summary
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056,,, 2024
Short summary

Cited articles

Afzal, S., Hittawe, M., Ghani, S., Jamil, T., Knio, O., Hadwiger, M., and Hoteit, I.: The State of the Art in Visual Analysis Approaches for Ocean and Atmospheric Datasets, Comput. Graph. Forum, 38, 881–907,, 2019. a
Bader, R., Sprenger, M., Ban, N., Radisuhli, S., Schar, C., and Günther, T.: Extraction and Visual Analysis of Potential Vorticity Banners around the Alps, IEEE T. Vis. Comput. Gr., 26, 259–269,, 2019. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905,, 2011. a
Barklie, R. H. D. and Gokhale, N. R.: The freezing of supercooled water drops, Stormy Weather Group, McGill Univ., Sci. Rep. MW-30, Part 3, 43–64, 1959. a
Baumgartner, M., Sagebaum, M., Gauger, N. R., Spichtinger, P., and Brinkmann, A.: Algorithmic differentiation for cloud schemes (IFS Cy43r3) using CoDiPack (v1.8.1), Geosci. Model Dev., 12, 5197–5212,, 2019. a
Short summary
Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.