Probabilistic & ensemble forecasting
Pressure: reimagining the D‐Day forecast through machine learning
In one sentence. Recreates the 1944 D-Day forecasts with ECMWF's AIFS-ENS, showing the ML ensemble moves the storm too fast and gives overconfident landing conditions.
Abstract
Abstract The new film ‘Pressure’ brings renewed attention to one of the most dramatic weather forecasts ever. In June 1944, James Stagg faced the unenviable task of advising whether conditions would allow the D‐Day landings to proceed, with the lives of 160 000 troops and the fate of the war in the balance. Using AIFS‐ENS, the ECMWF machine‐learning ensemble forecast system, we recreate the forecasts in the days before 6th June. Even at short range, AIFS‐ENS moves the storm too rapidly into the Norwegian Sea giving undue confidence for favourable conditions for the landing in Normandy.
Labels
- Topic
- Probabilistic & ensemble forecasting, Applications & impacts
- Type
- Application study
- Method
- Transformer / ViT
- Time scale
- 3–15 days
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Operational
- Identifiers
- DOI:10.1002/wea.70123 OpenAlex:W7205006445
- Added
- 2026-10-22
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