Product
1 / 5
AI weather models like EPT-2 beat traditional NWP such as ECMWF HRES across all lead times for wind speed and solar radiation.
2 / 5
Hindcasting delivers leak-free validation by simulating real-time forecasts on historical data, unlike reanalysis that uses future observations.
3 / 5
Jua SDK supports a 5-step backtesting flow: install, fetch hindcasts, align with ERA5, compute RMSE and CRPS, then simulate trading strategies in seconds.
4 / 5
Key metrics show the EPT-2e ensemble outperforms ECMWF ENS on probabilistic scores, enabling an estimated €1.5M annual ROI per GW wind portfolio from accuracy gains.
5 / 5
Jua provides 25+ hindcasts and the Athena agent for instant multi-model backtests. Book a demo to validate your trading edge today.
Master AI weather hindcasts backtesting with Python. Validate models for energy trading edge. Get started with Jua SDK today.