4 citations · 4 across the 1 of their papers we have counts for
3 papers
Value of Adding AI Weather Model Ensembles to a Multi-model Probabilistic Blend
Harris Sop Nkuiate, Gavin Evans, Christopher A. T. Ferro +3
Many weather forecasting organizations use a multi-model blend of ensemble members from different prediction systems to obtain a more accurate forecast. Recent studies have shown t…
Enforcing tail calibration when training probabilistic forecast models
Jakob Benjamin Wessel, Maybritt Schillinger, Frank Kwasniok +1
Probabilistic forecasts are typically obtained using state-of-the-art statistical and machine learning models, with model parameters estimated by optimizing a proper scoring rule o…
Improving probabilistic forecasts of extreme wind speeds by training statistical post-processing models with weighted scoring rules
Jakob Benjamin Wessel, Christopher A. T. Ferro, Gavin R. Evans +1
Accurate forecasts of extreme wind speeds are of high importance for many applications. Such forecasts are usually generated by ensembles of numerical weather prediction (NWP) mode…