KLIMAT-P
DashboardVerification
Forecast Verification

How accurate is the model?

A probability isn't a claim that something will happen — it's a statement about likelihood. A model that says "70% chance of above-normal temperature" should be right about 70% of the time it makes that prediction. Verifying this is the only honest way to know whether KLIMAT-P's numbers mean anything.

The standard metric for probabilistic forecast accuracy is the Brier Score: for each prediction, it computes (predicted probability − actual outcome)². A perfect score is 0.0. A completely uninformative model that always predicts 50% scores 0.25. Lower is better.

This page updates automatically every Monday. The system looks back at the previous week's IMGW station data, determines what actually happened for each indicator, compares it to what the model predicted, and records the result. No manual entry required.

Score Reference
0.00 – 0.05Excellent
0.05 – 0.10Good
0.10 – 0.20Fair
0.20 – 0.25Poor
> 0.25Worse than always saying 50%
What's automated: Temperature anomaly, precipitation deficit, frost occurrence, heat events — all computed directly from IMGW station readings in the database.

What's deferred: Drought and flood risk require IMGW hydrological data (soil moisture, river levels) — a separate ingestion job, added once the core model is stable.
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