Point sampling
The value is taken from the model’s own grid and the sampling method is recorded. No height correction is applied silently.
Lead-time steps
The same valid time is viewed from the T+6, T+12, T+24 and T+48 runs, so you see how forecast skill changes with lead time.
Time alignment
Forecast and observation are matched at the exact valid time. Unmatched samples are left out, with the reason recorded.
Uncertainty
The range between models is shown openly, never as a probability.
Metrics
Mean error, mean absolute error and root-mean-square error, by lead time, station and model. Missing data stays missing.
No ranking
Models are ranked only after a verification campaign is complete and published.
- e = F − O
- forecast minus observation
- Bias = (1/n) Σ e
- mean error
- MAE = (1/n) Σ |e|
- mean absolute error
- RMSE = √[(1/n) Σ e²]
- root-mean-square error
Temperatures are handled in kelvin. Observations come from official national station networks: AEMET in Spain, Météo-France in France.
Verification campaign · 2 m air temperature
8stations×4lead times×3models×56runs
=5,376expected samples · 14 days
The campaign uses a selected set of stations and does not represent a whole country. Results will be published when it is complete.