Weather Forecasting

Accuracy of AI Weather Models: The Operational Challenge

1 / 5

Traditional NWP systems like ECMWF HRES remain accurate but are computationally expensive and update infrequently, which limits their value for intraday trading.

2 / 5

Most AI weather models miss record-breaking extremes because they lack explicit physical constraints and regress toward their training distribution.

3 / 5

EPT-2, Jua’s physics foundation model, outperforms ECMWF HRES on every lead time and energy-relevant variable while updating up to 24 times daily at about 0.25 kWh per simulation.

4 / 5

The Jua platform provides a unified benchmarking surface for 25+ models, so traders can run live head-to-head comparisons on their own regions and variables in seconds.

5 / 5

Run a live benchmark to compare EPT-2 with your current forecast provider and quantify P&L impact before the next model run.

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AI weather models miss extremes that move energy markets. See how Jua's EPT-2 outperforms ECMWF HRES on every lead time. Run a live benchmark today.

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