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Reading a Forecast

ECMWF vs GFS: what actually separates the two forecast models

Open two weather apps and check the same afternoon in the same town. Sometimes they match. Sometimes one says light rain and the other says nothing at all. Most of the time, what you're actually comparing isn't the apps. It's two different weather models running underneath them. The two you'll run into most often are ECMWF and GFS.

We build AerisCast around showing both, side by side, for any point on the map. Here's what each one actually is, and where each pulls ahead.

ECMWF

Run by the European Centre for Medium-Range Weather Forecasts, an intergovernmental body based in Reading, England, with a data centre in Bologna. Its main forecast, the IFS, runs at 9km resolution, four times a day, and pushes out to 10 days at full detail. The ensemble version extends further, out to 15 days.

Pros

  • Consistently ranks at or near the top of global verification scores, particularly for the 4-7 day range
  • Higher native resolution than GFS, which matters for how it resolves terrain-driven weather, useful in mountain regions where local elevation changes the picture fast
  • 137 vertical levels, which helps it handle atmospheric structure with more precision

Cons

  • Data access has historically been more restricted than GFS. Some of the higher-resolution output sits behind a paywall or requires an institutional account, though open-data access has expanded in recent years
  • Shorter raw forecast range at full resolution than GFS
  • The model naming is mid-change. What's been called "HRES" for years is being folded into something called the ensemble control run, which won't mean much to most people checking a forecast, but it can cause confusion if you're reading raw ECMWF documentation

GFS

Run by NOAA's National Weather Service, the Global Forecast System is the US government's global model. It runs at 13km native resolution, four times a day (00, 06, 12, 18 UTC), and reaches out to 16 days, though confidence that far out is limited for any model.

Pros

  • Fully open data, no restrictions, no paywall. This is the reason so many apps and websites default to it
  • Longer raw forecast range, out to 16 days
  • Updated frequently and widely cross-checked, since so many independent tools run on the same feed
  • Backed by GEFS, its ensemble companion, which runs 31 members and helps quantify how much uncertainty is in a given forecast

Cons

  • Coarser native resolution than ECMWF, 13km versus 9km, which shows up most in areas with complex terrain or fast-moving small-scale weather
  • Tends to lag ECMWF slightly in medium-range verification scores, particularly days 4 through 7
  • Because it's the default for so many free tools, you'll sometimes see the same GFS run repeated across five different apps, which can create a false sense of agreement. It's not five independent opinions confirming each other. It's one model, five interfaces.

Where this actually matters

Both models are solving the same physics with the same goal, and for the first two or three days, they usually land in a similar place. The gap opens up further out. That's not really a flaw in either model. It's a property of the atmosphere. Small differences in the starting conditions compound over time, and by day seven, two models that started close together can be telling different stories.

Neither model is right or wrong to check first. If you want the longer view, GFS gives you more days. If you want the sharper picture in mountainous terrain over the next week, ECMWF's resolution and ensemble depth tend to add value there. A lot of forecasters, ourselves included, just get in the habit of checking both and paying closest attention when they agree.

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Chart Parameters

MSLP & 3h Precipitation
Mean Sea Level Pressure contours overlaid with 3-hourly precipitation shading. Shows where weather systems are located and where rain or snow is falling.
Thickness & Precipitation
Atmospheric thickness contours overlaid with precipitation. Blue contours indicate cold air masses; red/purple contours indicate warm air. A useful guide to whether precipitation is falling as rain or snow.
850 hPa Temperature
Temperature at approximately 1,500 metres above sea level. A good indicator of the overall warmth or coldness of an air mass affecting a region.
500 hPa Temperature
Temperature at approximately 5,500 metres above sea level. Cold air at this level is associated with instability, thunderstorms and heavy precipitation.
700 hPa Relative Humidity
Humidity at approximately 3,000 metres above sea level. High values indicate moist air and cloud at mid-levels, often associated with significant rainfall or snowfall.
Accumulated Precipitation
Total rainfall and snowfall accumulation from the start of the model run. Useful for identifying regions receiving persistent or heavy precipitation over the forecast period.
Snow Level
The altitude (metres above sea level) where precipitation is falling as snow. Lower values mean snow is reaching lower elevations. Only shown where precipitation is occurring.

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