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By Glaucileine Vieira
Spire Global is expanding its AI weather forecasting platform for energy trading desks. The new forecast stack covers everything from intraday weather events to 45-day outlooks. The company says the move is aimed at helping traders better manage the growing volatility tied to renewable energy generation and shifting weather patterns.
The new offering combines high-resolution forecasting, AI-based sub-seasonal models, and trader-focused analytics through Spire’s Cirrus platform. In addition, the company claims its proprietary AI-S2S model can outperform forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) in the difficult three to six-week forecasting window.
For eeNews Europe readers, the announcement highlights how satellite data and AI are becoming increasingly important in energy infrastructure and electricity markets. It also reflects the growing demand for more accurate weather intelligence as renewable energy sources continue to reshape grid operations and power trading strategies across Europe.
According to Spire, energy traders are under pressure as weather increasingly drives pricing and risk in European and North American electricity markets. Wind ramps, cold snaps, and unexpected weather regime changes can all have direct financial consequences for utilities and trading desks.
The company’s expanded forecast stack includes several layers of weather intelligence. A high-resolution forecast model provides twice daily 3 km forecasts for the US, Europe, and Southeast Asia, while optimized point forecasts deliver hourly updated weather predictions with 15-minute granularity for more than 10,500 global sites.
Spire is also offering power generation forecasts that translate weather data into projected wind and solar generation curves. These are designed to help traders compare Spire’s models with public benchmark forecasts and identify market divergences more quickly.
The headline addition is Spire AI-S2S, a 200-member generative AI ensemble trained on satellite-derived GNSS radio occultation data and historical atmospheric datasets. The company says the model operates independently from public forecast systems and provides probabilistic forecasts with quantified uncertainty for up to 45 days ahead.
Spire said validation tests carried out earlier this year showed the AI-S2S model outperforming ECMWF’s sub seasonal ensemble forecasts by 14.2% for surface temperature predictions in the three to six week range.
“Weather is now the single biggest unpriced variable in energy markets — and the traders who forecast it better win,” said Shawn Mechelke, General Manager, Weather, Climate and Aviation at Spire. “Spire AI-S2S gives desks a validated, independent signal at the extended range, when public models lose reliability and the value of being right is highest.”
The full forecast stack is available through the company’s Cirrus platform as well as via API integration for existing trading systems.
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