Weather Forecasting

Ensemble Weather Forecast Accuracy: AI vs Traditional

1 / 5

EPT-2e, Jua’s 30-member ensemble, beats the 50-member ECMWF ENS mean on RMSE and CRPS at virtually every lead time using real ground-station observations.

2 / 5

Ensemble forecasts add probabilistic skill that deterministic models lack, which supports better risk management for energy trading and hedging.

3 / 5

EPT-2e keeps its accuracy edge across 0–2 days, 3–7 days, and 8–15 days for key variables such as 10 m wind speed and 2 m temperature.

4 / 5

Well-calibrated ensemble spread from EPT-2e provides a reliable uncertainty signal that traders can plug directly into position sizing without extra post-processing.

5 / 5

See EPT-2e benchmarked on your region and variables inside the Jua for Energy platform.

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Jua's EPT-2e outperforms ECMWF ENS at every lead time with sharper, well-calibrated ensemble forecasts for energy trading. Explore the benchmarks.

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