In commodities trading, weather isn't just a variable; it is the fundamental driver of price. Whether you are trading Natural Gas futures based on Heating Degree Days (HDD) or projecting corn yields in the Midwest, the market moves on the forecast.
But for years, the "reliable" forecast horizon has been capped at 10–14 days. Beyond that, traders are often forced to rely on historical averages or low-confidence climatology models.
At Superset, we are pushing that horizon out to a full quarter. Our machine learning architecture predicts temperature trends 3 months in advance, giving desk heads and PMs the ability to position for quarterly shifts before the rest of the market sees the pattern forming.
The Engine: Built on the Gold Standard
Garbage in, garbage out. That is why we don't scrape public weather apps. Our model is trained on ERA5 data from the ECMWF (European Centre for Medium-Range Weather Forecasts).
ERA5 is widely considered the "gold standard" in global climate monitoring, providing hourly estimates of atmospheric, land, and oceanic climate variables. By feeding our neural networks petabytes of this high-fidelity historical data, our system detects long-range teleconnections—subtle links between ocean heat content, pressure systems, and future surface temperatures—that standard meteorological models overlook.
The Metrics: Backtested Precision
A forecast is useless without a confidence interval. We have stress-tested our model over a 10-year historical period to ensure stability across diverse climate events (including El Niño and La Niña cycles).
The Alpha: 89.7% Accuracy over the last decade.
Key Performance Indicators:
| Metric | Value |
|---|---|
| Accuracy Rate | 89.7% |
| Average Error | 1.51°C |
| Forecast Horizon | 90 Days |
| Test Period | 10 Years |
In the context of the natural gas market, a 1.5°C deviation in a monthly average can determine whether storage draws miss or beat expectations. Having a 3-month lead on this deviation allows for significantly improved option pricing and spread trading strategies.
Where This Generates Alpha
This system is designed for traders who need to look beyond the prompt month.
1. Natural Gas & Power
Predict forward demand shocks by accurately modeling HDD/CDD (Heating/Cooling Degree Days) well into the next quarter.
2. Agriculture Futures
Anticipate heat stress or frost risks during critical planting and pollination windows for Corn, Soy, and Wheat.
3. Softs & Logistics
Manage supply chain risk for temperature-sensitive logistics or soft commodities like Coffee and Cocoa.
Conclusion
The market is efficient at pricing the 10-day forecast. It is inefficient at pricing the 90-day anomaly.
Stop trading off historical averages. Start trading off the future reality.
Want to Learn More?
If you're interested in accessing our temperature predictions:
- Check out our Marketplace to see the 3 Month Temperature Predictor
- Contact us at support@superset.ai
- Sign up to get started with Superset