GFS vs ECMWF Demand-Hub Outlook: 2026-05-24T00:00Z

Executive Summary

The 15-day outlook shows a notable divergence between models, with the GFS forecasting significantly more total weather-driven demand (110.4 TDD) than the ECMWF (94.2 TDD). This difference is almost entirely due to a colder GFS outlook in the high-weighted Midwest hub. Confidence in this forecast is low, reflected by a poor convergence score of 0.40, and both models have trended warmer versus their prior runs.

Hub-Level Weather

The primary drivers of the national demand forecast are the Midwest and East hubs, which account for 65% of the demand weighting.

• Midwest (Chicago, 35% weight): This is the key point of disagreement. The GFS is materially colder, forecasting 31.8 HDDs and 64.4 CDDs. In stark contrast, the ECMWF is much warmer, showing only 1.0 HDD and a higher 88.0 CDDs. The split is most pronounced from May 28 to June 1.
• East (New York City, 30% weight): Models are in closer agreement on heating demand (GFS: 20.6 HDDs, ECMWF: 22.7 HDDs). However, the GFS is warmer later in the period, forecasting significantly more cooling demand (58.0 CDDs) compared to the ECMWF (33.5 CDDs).
• South Central (Houston, 15% weight): Both models show strong, consistent cooling demand. The GFS is slightly hotter, accumulating 225.6 CDDs versus 197.8 CDDs for the ECMWF.

Demand Implications (Natural Gas)

The model differences imply conflicting risks for natural gas demand.

• The GFS outlook (24.2 weighted HDDs) suggests a risk of unseasonable late-May/early-June heating demand (res/comm load), concentrated in the Midwest.
• The ECMWF forecast (12.2 weighted HDDs) points to a more seasonal pattern, with minimal heating load and a stronger transition to cooling demand (power burn), especially in the Midwest.
• Both models support robust power burn in the South, though the GFS's hotter solution implies a stronger call on gas for generation.
• Run-over-Run Change: The demand signal has weakened since the last cycle. The GFS total demand forecast dropped by 8.1 weighted TDD (delta_weighted_cumulative_hdd_gfs: -7.0, delta_weighted_cumulative_cdd_gfs: -1.1). The ECMWF also trended warmer, losing 5.0 weighted TDD (delta_weighted_cumulative_hdd_ecmwf: +1.5, delta_weighted_cumulative_cdd_ecmwf: -6.5).

Model Agreement & Caveats

Confidence in the 15-day forecast is low due to significant model disagreement.

• Convergence: The overall convergence score is 0.40, indicating poor agreement between the GFS and ECMWF solutions. The weighted_mean_abs_hdd_diff_by_day is 1.48, highlighting the material daily differences in the heating load forecast.
• Uncertainty: The large split, particularly in the Midwest, suggests high uncertainty for the Day 6-15 period. Traders should treat both model outcomes as plausible scenarios until they begin to converge.
• Source Limitations: This analysis is based on deterministic runs from Open-Meteo's API. It does not incorporate ensemble model data, which would provide a fuller probabilistic range of potential temperature outcomes. The demand-weighting is a simplified representation of complex regional consumption patterns.