A multi-lead-time self-attention Transformer postprocesses gridded ECMWF ensemble forecasts of 2m temperature and 10/100m wind speed, improving CRPS by 16.5%, 10%, and 9% over raw forecasts.
Messori, 2021: Ensemble methods for neural network-based weather forecasts
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Self-attentive Transformer for Fast and Accurate Postprocessing of Temperature and Wind Speed Forecasts
A multi-lead-time self-attention Transformer postprocesses gridded ECMWF ensemble forecasts of 2m temperature and 10/100m wind speed, improving CRPS by 16.5%, 10%, and 9% over raw forecasts.