Benedikt Schulz M.Sc.
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by appointment
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Kollegiengebäude Mathematik (20.30)
2.012
+49 721 608 45261
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benedikt.schulz2@kit.edu
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Karlsruhe Institute of Technology (KIT)
Institute of Stochastics
Englerstraße 2
76131 Karlsruhe
Within project C5 of the Transregional Collaborative Research Center Waves to Weather („Dynamical feature-based ensemble postprocessing of wind gusts within European winter storms“) I am working on methods for statistical postprocessing of weather forecasts. We focus on ensemble forecasts of wind gusts and apply modern machine learning methods like neural networks.
| Semester | Titel | Typ |
|---|---|---|
| Summer Semester 2021 | Nichtparametrische Statistik | Lecture |
| Einblicke in die Stochastik | Proseminar |
Working papers
- Schulz, B. and Lerch, S. (2021): Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison. arxiv:2106.09512.
Publications
- Schulz, B., El Ayari, M., Lerch, S. and Baran, S. (2021): Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting. Solar Energy, 220, 1016-1031. doi:10.1016/j.solener.2021.03.023.
Conferences and workshops
- 3rd NOAA Workshop on Leveraging AI in Environmental Sciences (2021), online, talk: Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison.
- International Symposium on Forecasting (ISF) 2021, online, talk: Calibrating and combining probability forecasts.
- EGU General Assembly 2021, online, talk: Statistical and machine learning methods for postprocessing ensemble forecasts of wind gusts. doi.org/10.5194/egusphere-egu21-1326.
- ICCARUS 2021, online, talk: Statistical and machine learning methods for postprocessing ensemble forecasts of wind gusts.
- Practical Operational implementation of Statistical Post-Processing for ensemble forecasts (2020), online, poster: Statistical post-processing of near-real-time ICON ensemble forecasts.
- VALPRED 2020, Aussois, talk: Calibrating and combining probability forecasts.