AI Engineering for Weather and Climate

Q: How do we compare an AI weather model fairly with our numerical prediction system?

We set up standard deterministic and probabilistic verification scores stratified by lead time, region and regime, including extremes.

Q: Can forecast verification run automatically every cycle?

We build verification into a pipeline that runs every forecast cycle and keeps the history.

Verification that compares AI and numerical forecasts fairly, run every cycle, on compute that keeps up.

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Weather services and weather-dependent businesses bring us two questions. Is an AI forecasting model actually better than the numerical system it might replace, for the events and lead times we care about? And can we run it, and score it, every cycle on the compute we have?

How It Connects

Continuous verification lands in the Production AI Monitoring Harness and Production AI Reliability; compute for model runs and ensembles in GPU Performance Engineering.

We have not published a weather or climate case study. Tell us the forecast you need to verify.

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Weather and Climate AI FAQ

How do we compare an AI weather model fairly with our numerical prediction system?

With verification that matches the question. We set up standard deterministic and probabilistic scores (for example CRPS, RMSE and Brier score) and stratify them by lead time, region and regime, including extremes, so a smooth model is not rewarded for avoiding the events that matter.

Can forecast verification run automatically every cycle?

Yes. We build the scoring into a pipeline that runs on every forecast cycle and keeps the history, so model comparisons stay current without manual rework.