1 code implementation • 8 Apr 2022 • Sebastian Lerch, Kai L. Polsterer
Ensemble weather predictions typically show systematic errors that have to be corrected via post-processing.
1 code implementation • 5 Apr 2022 • Benedikt Schulz, Sebastian Lerch
The importance of accurately quantifying forecast uncertainty has motivated much recent research on probabilistic forecasting.
2 code implementations • 17 Jun 2021 • Benedikt Schulz, Sebastian Lerch
Postprocessing ensemble weather predictions to correct systematic errors has become a standard practice in research and operations.
no code implementations • 5 Mar 2021 • Kai Lars Polsterer, Antonio D'Isanto, Sebastian Lerch
We present what we achieved when using proper scoring rules to train deep neural networks as well as to evaluate the model estimates and how this work led from well calibrated redshift estimates to improvements in probabilistic weather forecasting.
Weather Forecasting
Instrumentation and Methods for Astrophysics
no code implementations • 16 Jan 2020 • Ágnes Baran, Sebastian Lerch, Mehrez El Ayari, Sándor Baran
We further assess whether improvements in forecast skill can be obtained by incorporating ensemble forecasts of precipitation as additional predictor.
1 code implementation • 23 May 2018 • Stephan Rasp, Sebastian Lerch
Ensemble weather predictions require statistical post-processing of systematic errors to obtain reliable and accurate probabilistic forecasts.
1 code implementation • 14 Sep 2017 • Alexander Jordan, Fabian Krüger, Sebastian Lerch
Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields including meteorology, hydrology, economics, and demography.
Computation Applications
no code implementations • 24 Aug 2016 • Fabian Krüger, Sebastian Lerch, Thordis L. Thorarinsdottir, Tilmann Gneiting
Based on proper scoring rules, we develop a notion of consistency that allows to assess the adequacy of methods for estimating the stationary distribution underlying the simulation output.
Methodology