Barahona D., Breen K., Block K., Darmenov A.: Deep learning representation of the aerosol size distribution, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-482, 2025.
Hartung, K., Kern, B., Dreier, N.-A., Geisbüsch, J., Haghighatnasab, M., Jöckel, P., Kerkweg, A., Loch, W. J., Prill, F., and Rieger, D.: ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01), Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, 2025
2024
Bach, D., Rueda-Ramírez, A., Kopriva, D.A. and Gassner, G.J., 2024. Mimetic Metrics for the DGSEM. arXiv preprint arXiv:2410.14502. https://arxiv.org/abs/2410.14502
Bishnoi, A., Stein, O., Meyer, C. I., Redler, R., Eicker, N., Haak, H., Hoffmann, L., Klocke, D., Kornblueh, L., and Suarez, E.: Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc, Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, 2024.
Braun, D., Chang, R., Gleicher, M. and von Landesberger, T., 2024. Beware of validation by eye: Visual validation of linear trends in scatterplots. IEEE transactions on visualization and computer graphics. https://ieeexplore.ieee.org/abstract/document/10670522
Koldunov, N., Rackow, T., Lessig, C., Danilov, S., Cheedela, S.K., Sidorenko, D., Sandu, I. and Jung, T., 2024. Emerging AI-based weather prediction models as downscaling tools. arXiv preprint arXiv:2406.17977. https://arxiv.org/abs/2406.17977
Lu, Y.S., Caviedes-Voullième, D., Stein, O. and Hoffmann, L., 2024. Challenges of applying an embedded domain specific language for performance portability to Earth system models. https://eartharxiv.org/repository/view/6767/
To, D., Quinting, J., Hoshyaripour, G.A., Götz, M., Streit, A. and Debus, C., 2024. Architectural insights into and training methodology optimization of Pangu-Weather. Geoscientific Model Development, 17(23), pp.8873-8884. https://gmd.copernicus.org/articles/17/8873/2024/
2023
Braun, D., Borgo, R., Sondag, M. and von Landesberger, T., 2023. Reclaiming the horizon: Novel visualization designs for time-series data with large value ranges. IEEE Transactions on Visualization and Computer Graphics, 30(1), pp.1161-1171. https://ieeexplore.ieee.org/abstract/document/10290958
Braun, D., Suh, A., Chang, R., Gleicher, M. and von Landesberger, T., 2023, October. Visual validation versus visual estimation: A study on the average value in scatterplots. In 2023 IEEE Visualization and Visual Analytics (VIS) (pp. 181-185). IEEE. https://ieeexplore.ieee.org/abstract/document/10360882
Conference contributions
2024
Block K., Quaas J., Haghighatnasab M., Partridge D.G., Stier P., 2024. Constraining cloud modeling with reanalysis derived cloud condensation nuclei. In ICCP 2024 conference abstracts (p. 95). https://iccp2024.kr/admin/data/product/240730112147238_pdf_1.pdf
Modali, K., Peters-von Gehlen, K., Ziemen,F., Saini, R., Grasse, S., and Schultz, M., 2024, April. A cascaded framework for unified access to and analysis of kilometer scale global simulations across a federation of data centers. In EGU General Assembly Conference Abstracts (p. 19677). https://meetingorganizer.copernicus.org/EGU24/EGU24-19677.html
Pelchmann, L., Bremm, S., Ebell, K. and von Landesberger, T., 2023. Explorative Study on Semantically Resonant Colors for Combinations of Categories with Application to Meteorological Data. In EuroVis (Posters) (pp. 33-35). https://diglib.eg.org/bitstream/handle/10.2312/evp20231061/033-035.pdf