64 citations · 111 across the 5 of their papers we have counts for
6 papers
Operational convection-permitting COSMO/ICON ensemble predictions at observation sites (CIENS)
Sebastian Lerch, Benedikt Schulz, Reinhold Hess +4
We present the CIENS dataset, which contains ensemble weather forecasts from the operational convection-permitting numerical weather prediction model of the German Weather Service.…
Comparison of Model Output Statistics and Neural Networks to Postprocess Wind Gusts
Cristina Primo, Benedikt Schulz, Sebastian Lerch +1
Wind gust prediction plays an important role in warning strategies of national meteorological services due to the high impact of its extreme values. However, forecasting wind gusts…
Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks
Kevin Höhlein, Benedikt Schulz, Rüdiger Westermann +1
Statistical postprocessing is used to translate ensembles of raw numerical weather forecasts into reliable probabilistic forecast distributions. In this study, we examine the use o…
Aggregating distribution forecasts from deep ensembles
Benedikt Schulz, Lutz Köhler, Sebastian Lerch
The importance of accurately quantifying forecast uncertainty has motivated much recent research on probabilistic forecasting. In particular, a variety of deep learning approaches…
Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison
Benedikt Schulz, Sebastian Lerch
Postprocessing ensemble weather predictions to correct systematic errors has become a standard practice in research and operations. However, only few recent studies have focused on…
Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting
Benedikt Schulz, Mehrez El Ayari, Sebastian Lerch +1
In order to enable the transition towards renewable energy sources, probabilistic energy forecasting is of critical importance for incorporating volatile power sources such as sola…