Sebastian Lerch

发表

Forecaster's Dilemma: Extreme Events and Forecast Evaluation

Francesco Ravazzolo, Tilmann Gneiting, Thordis L. Thorarinsdottir, 2015, 1512.09244.

Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison pdf

Sebastian Lerch, Benedikt Schulz, S. Lerch, 2021, Monthly Weather Review.

Precipitation Sensitivity to the Uncertainty of Terrestrial Water Flow in WRF-Hydro: An Ensemble Analysis for Central Europe

S. Lerch, H. Kunstmann, B. Fersch, 2018, Journal of Hydrometeorology.

Evaluating Probabilistic Forecasts with scoringRules

Alexander Jordan, Fabian Kruger, Sebastian Lerch, 2017, Journal of Statistical Software.

Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting

Sebastian Lerch, S'andor Baran, Benedikt Schulz, 2021, Solar Energy.

Neural networks for post-processing ensemble weather forecasts pdf

Stephan Rasp, Sebastian Lerch, S. Lerch, 2018, Monthly Weather Review.

Statistical Postprocessing for Weather Forecasts: Review, Challenges, and Avenues in a Big Data World

S. Vannitsem, S. Lerch, Z. B. Bouallègue, 2020, Bulletin of the American Meteorological Society.

The EUPPBench postprocessing benchmark dataset v1.0

S. Vannitsem, O. Mestre, J. Bhend, 2023, Earth System Science Data.

Comparison of multivariate post‐processing methods using global ECMWF ensemble forecasts

S. Baran, S. Lerch, S. Hemri, 2022, Quarterly Journal of the Royal Meteorological Society.

Machine learning for total cloud cover prediction

Sebastian Lerch, Sándor Baran, Ágnes Baran, 2020, Neural Computing and Applications.

Simulation-based comparison of multivariate ensemble post-processing methods

Roman Schefzik, Sebastian Lerch, Annette Möller, 2020, Nonlinear Processes in Geophysics.

S. Baran, S. Lerch, Sebastian Lerch, 2015 .

Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop

S. E. Haupt, Samantha V. Adams, S. Lerch, 2021, Philosophical Transactions of the Royal Society A.

Probabilistic solar forecasting: Benchmarks, post-processing, verification

T. Gneiting, S. Lerch, Benedikt Schulz, 2023, Solar Energy.

Model Diagnostics and Forecast Evaluation for Quantiles

Alexander I. Jordan, T. Gneiting, V. Hagenmeyer, 2022, Annual Review of Statistics and Its Application.

Log‐normal distribution based Ensemble Model Output Statistics models for probabilistic wind‐speed forecasting

S. Baran, S. Lerch, Sebastian Lerch, 2014, 1407.3252.

Generative machine learning methods for multivariate ensemble post-processing

S. Lerch, Florian Steinke, Jieyu Chen, 2022, ArXiv.

Manuscript NPG-2019-62 Simulation-based comparison of multivariate ensemble post-processing methods Response to Reviewer Comments

S. Baran, Roman Schefzik, S. Lerch, 2022 .

Probabilistic Forecasting and Comparative Model Assessment Based on Markov Chain Monte Carlo Output

Tilmann Gneiting, Sebastian Lerch, Fabian Krüger, 2016, 1608.06802.

Convolutional autoencoders for spatially-informed ensemble post-processing

K. Polsterer, Sebastian Lerch, 2022, ArXiv.

Probabilistic Predictions from Deterministic Atmospheric River Forecasts with Deep Learning

S. Xie, L. D. Monache, S. Alessandrini, 2021, Monthly Weather Review.

Evaluating ensemble post‐processing for wind power forecasts

R. Mikut, S. Lerch, V. Hagenmeyer, 2020, Wind Energy.

Deep learning for post-processing global probabilistic forecasts on sub-seasonal time scales

Sebastian Lerch, Nina Horat, 2023, 2306.15956.

Aggregating distribution forecasts from deep ensembles

S. Lerch, Benedikt Schulz, Sebastian Lerch, 2022, ArXiv.

Forecasting wind gusts in winter storms using a calibrated convection‐permitting ensemble

Ulrich Corsmeier, Sebastian Lerch, Florian Pantillon, 2018, Quarterly Journal of the Royal Meteorological Society.

Comparison of non-homogeneous regression models for probabilistic wind speed forecasting

T. Thorarinsdottir, S. Lerch, Sebastian Lerch, 2013, 1305.2026.

Comparison of nonhomogeneous regression models for probabilistic wind speed forecasting

Thordis L. Thorarinsdottir, Sebastian Lerch, T. Thorarinsdottir, 2018 .

Learning to forecast: The probabilistic time series forecasting challenge

S. Lerch, Fabian Kruger, J. Bracher, 2022, The American Statistician.

Combining predictive distributions for the statistical post-processing of ensemble forecasts

Sebastian Lerch, S'andor Baran, S. Baran, 2016, International Journal of Forecasting.

Remember the past: A comparison of time-adaptive training schemes for non-homogeneous regression

Achim Zeileis, Thorsten Simon, Sebastian Lerch, 2019, Nonlinear Processes in Geophysics.

Probabilistic forecasting and comparative model assessment, with focus on extreme events

Sebastian Lerch, S. Lerch, Sebastian Lerch, 2016 .

Desublimation Frosting on Nanoengineered Surfaces.

S. Lerch, D. Poulikakos, C. Walker, 2018, ACS nano.

Waves to Weather Exploring the Limits of Predictability of Weather

B. Mayer, T. Janjić, P. Knippertz, 2021 .

Predictive Inference Based on Markov Chain Monte Carlo Output

Tilmann Gneiting, Thordis L. Thorarinsdottir, Fabian Kruger, 2016, International Statistical Review.

S. Baran, S. Lerch, Sebastian Lerch, 2015, 1509.03521.

Mixture EMOS model for calibrating ensemble forecasts of wind speed

S. Baran, S. Lerch, S. Baran, 2015, Environmetrics.