GFS vs ECMWF Demand-Hub Outlook: 2026-11-11 12:00 UTC

Executive Summary

The 12:00 UTC cycle reflects significant mid-to-late-range divergence between the GFS and ECMWF models across key U.S. gas-consuming regions. On a national demand-weighted basis over the 15-day period, ECMWF projects a materially colder profile with 265.97 heating degree days (HDDs) compared to 239.17 HDDs on the GFS (a 26.81 HDD spread). However, in the near term (days 1–6), the raw ECMWF–GFS spread of +11.65 HDDs sits slightly below the seasonal expected spread of +13.856 HDDs, registering as typical model bias rather than a meaningful cold signal.

Hub-Level Weather

Model divergence is heavily concentrated in the East and South, with sharp synoptic disagreement emerging after Day 10:

• Midwest (Chicago, 35% weight): Cumulative HDDs are relatively close at 330.48 on the GFS vs. 326.72 on the ECMWF (daily mean absolute difference of 4.07 HDDs). However, daily timing diverges sharply: ECMWF holds cooler weather between November 14–19, whereas the GFS drives an aggressive cold plunge late in the window, dropping temperatures to 32.51°F (32.49 HDDs) on November 24 and 30.46°F (34.54 HDDs) on November 25, against ECMWF's milder 42.23°F (22.77 HDDs) and 37.77°F (27.23 HDDs).
• East (New York City, 30% weight): ECMWF is significantly colder over the 15-day horizon, totaling 295.53 HDDs versus 236.32 HDDs on the GFS (+59.21 HDDs). The discrepancy peaks during November 22–24, where the GFS projects an anomalous warm surge (reaching 58.98°F and 6.02 HDDs on November 24), while ECMWF models an intensifying cold pattern (39.22°F and 25.78 HDDs).
• Northeast (Boston, 10% weight): Tracks the New York pattern, with ECMWF delivering 320.46 HDDs versus 276.63 HDDs on the GFS (+43.83 HDDs). The largest variance occurs on November 24, when ECMWF projects 34.70°F (30.30 HDDs) versus the GFS at 58.24°F (6.76 HDDs).
• South (Atlanta, 10% weight): ECMWF maintains sustained chill across November 14–22, producing 235.18 HDDs against the GFS's 179.87 HDDs (+55.31 HDDs; daily divergence of 3.74 HDDs).
• South Central (Houston, 15% weight): HDDs are aligned at 46.37 (GFS) and 49.34 (ECMWF). Late-spring-like warmth mid-run yields small cooling degree days (CDDs) of 18.20 on GFS and 21.76 on ECMWF.

Demand Implications (Natural Gas)

Overall weather profiles point to seasonal to above-normal space heating requirements for natural gas, led by Midwest and Eastern population centers. If the colder ECMWF solution verifies—particularly in the high-weight NYC and Atlanta corridors—aggregate residential and commercial heating burns will track well above baseline assumptions. Conversely, the GFS presents a more bifurcated demand picture: subdued heating load in the East offset by late-cycle Arctic delivery into the Midcontinent. Across both models, cooling load remains negligible nationally (GFS 2.73 CDDs vs. ECMWF 3.26 CDDs), leaving heating requirements as the primary fundamental driver for NG.

Model Agreement & Caveats

• Convergence Score: The overall convergence score stands at a low 0.214, with a weighted mean absolute daily HDD difference of 3.67 HDDs, underscoring substantial model disagreement and low confidence in Days 8–15 synoptic evolution.
• Run-over-Run Deltas: Compared to the 00:00 UTC cycle, the 12:00 UTC ECMWF run trended warmer, shedding 7.78 weighted cumulative HDDs and adding 2.82 weighted CDDs, while the convergence score softened by -0.0181.
• Days 1–6 Spread Significance: The raw Days 1–6 demand-weighted spread shows ECMWF at 118.90 HDDs versus GFS at 107.25 HDDs (+11.65 HDDs). Evaluated against historical behavior where Open-Meteo's ECMWF systematically runs colder than station data in November, the expected spread for this window is +13.856 HDDs. The anomaly is -2.206 HDDs ($z = -0.43$, 38.3 percentile), receiving a typical label. This gap reflects normal model climatological bias rather than an actionable weather anomaly. Historically, past anomalies in this window have realized a share of 32.3% ($p = 0.038$, statistically significant at the 5% level); this metric characterizes past verification windows and is not an HDD forecast adjustment or price directional signal.
• Caveats: Open-Meteo uses gridded NWP model runs (GFS seamless 0.13° and ECMWF IFS 0.25°) which can smooth localized urban heat island effects. Day 11–15 solutions exhibit high structural variance and should not be relied upon without ensemble clustering verification.