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Windyty adds access to European model forecasts to beef up its forecasting skills

Meteorologists imagine the atmosphere in 3D to make a forecast, and a host of new online tools have popped up to help make that easier. Czech company Windyty is one of the options in this space, and recent changes make it even more useful in visualizing the weather, even for those who might not be so meteorologically inclined.

The highly accurate ECMWF, or the European, was added to its suite of forecast models this week, bringing the number of options to four. Original versions of Windty had relied on the American GFS model and the NEMS model for Europe, with support for the U.S.-only NAM model added soon after. Windyty says it will offer access to the European model at no charge to consumers,

Including the European model in your commercial apps is no easy — or cheap — task. Unlike the GFS and NAM, the European is the product of a commercial entity. Licensing runs into the tens of thousands of dollars, and is necessary because the “free” data options aren’t as useful.

Windyty alluded to “considerable data acquisition costs” in a statement announcing the addition of the European. It’s also a move aimed at giving Windyty a competitive advantage — especially considering its own service and others like Nullschool typically use the GFS.

“Major wind-forecasting services for kiters and sailors rely on GFS as the only global model, and that is the reason why they fail so often,” Windyty founder Ivo Lukacovic said.

Meteorologists measure model accuracy out five days by using something called “anomaly correlation.” A score of 1 is perfect, meaning the forecast matched up correctly with the actual observed weather. Over the past year, the GFS has a score of .886, according to WeatherBell, with the European at .918. So, while statistically significant, it’s not a massive difference.

Windyty is available through its website, as well as an Android app. The company says it plans to release an app for iOS — which will also include European model data — “soon,” according to a statement.

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