Publications

Adrian Rojas-Campos, Martin Wittenbrink, Pascal Nieters, Erik J. Schaffernicht, Jan D. Keller and Gordon Pipa: Postprocessing of NW Precipitation Forcasts Using Depp Learning, Research Article https://doi.org/10.1175/WAF-D-21-0207.1, March 2023
Rojas-Campos, A., Langguth, M., Wittenbrink, M., and Pipa, G.: Deep learning models for generation of precipitation maps based on Numerical Weather Prediction, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-648, 2022
A. Mozaffari, M. Langguth, B. Gong, J. Ahring, A. R. Campos, P. Nieters, O. J. Campos Escobar, M. Wittenbrink, P. Baumann, M. G. Schultz; HPC-oriented Canonical Workflows for Machine Learning Applications in Climate and Weather Prediction. Data Intelligence 2022; 4 (2): 271–285. doi: https://doi.org/10.1162/dint_a_00131
B. Gong, M. Langguth, Y. Ji, A. Mozaffari, S. Stadtler, K. Mache, and M. G. Schultz, (preprint) Temperature forecasting by deep learning methods, Geoscientific Model Development Discussions, 2022, 1—35, https://doi.org/10.5194/gmd-2021-430
S. Kesselheim, A. Herten, K. Krajsek, J. Ebert, J. Jitsev, M. Cherti, M. Langguth, B. Gong, S. Stadtler, A. Mozaffari, G. Cavallaro, R. Sedona, A. Schug, A. Strube, R. Kamath, M. G. Schultz, M. Riedel, T. Lippert (2021). JUWELS Booster – A Supercomputer for Large-Scale AI Research. In: Jagode, H., Anzt, H., Ltaief, H., Luszczek, P. (eds) High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science(), vol 12761. Springer, Cham. https://doi.org/10.1007/978-3-030-90539-2_31
M.G. Schultz, C. Betancourt, B. Gong, F. Kleinert, M. Langguth, L.H. Leufen, A. Mozaffari, S. Stadtler, “Can deep learning beat numerical weather prediction?” Philosophical Transactions of the Royal Society, Series A, 20200097, 2021. doi: 10.1098/rsta.2020.0097
R. Glowienka-Hense, A. Hense, S. Brune, and J. Baehr, “Comparing forecast systems withmultiple correlation decomposition based on partial correlation” Advances in Statistical Climatology, Meteorology and Oceanography, 6(2):103–113, 2020.doi:10.5194/ascmo-6-103-2020.
Sebastian Villarroy, Peter Baumann “On the Integartion of Machine Learning and Array Databases, 2020 IEEE 36th International Conference on Data Engineering (ICDE), April 2020
Jonas Rebstadt, “Deep Hyperresolution for Weather Forecasting”, Master thesis, Osnabrück University, August, 16, 2019.
Severin Hußmann, “Deep Learning for Future Frame Prediction of Weather Maps”, Master thesis, Humboldt-University of Berlin, August 01, 2019.
Andreas Hense and Felix Kleinert, “DeepRain – Improving local scale rainfall prediction through deep learning”, Presentation at the BMBF status meeting in the field of machine learning in Dortmund, Germany, June 05., 2019.
Poster for the Presentation ” DeepRain – Improving local scale rainfall prediction through deep learning” at the BMBF status meeting in the field of machine learning in Dortmund
Martin Schultz, “DeepRain – Improved local-scale prediction of precipitation through deep Learning”, Presentation at the European Geophysical Union General Assembly in Vienna, April 11., 2019.
Rita Glowienka-Hense and Andreas Hense, “Partial correlation the natural correlation skill score”, Presentation at the Meteorologentagung DACH in Garmisch-Partenkirchen, Germany, March 18.–22., 2019.