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Why weather forecasters are wrong so much of the time

A man stands in falling snow on West 42nd street in Times Square in New York, January 26, 2015. The National Weather Service (NWS) issued a blizzard warning for New York City and surrounding areas on Monday, and warned of two days of winter storms across the East Coast, from Pennsylvania to Maine. REUTERS/Mike Segar (UNITED STATES - Tags: ENVIRONMENT TPX IMAGES OF THE DAY) - RTR4N1C7
Reuters/Mike Segar
Misled.
By Zach Wener-Fligner

2014-15 Fellow. Quartz Things team.

This article is more than 2 years old.

On Jan. 26, it seemed like the whole US northeast was abuzz with worry about the blizzard coming that evening. New York City imposed a temporary transportation ban, and its mayor, Bill de Blasio, warned that the storm could be the worst the city had ever seen.

The results come Jan. 27? Royally underwhelming.

Sure, there’s snow on the ground. Eight inches in the city, to be precise, with more accumulation further east on Long Island. But it’s not nearly the devastating dump that was portended.

What gives?

Extreme weather may seem easy enough to spot ahead of time, given how broad-reaching and devastating it can be, not to mention all the eager news coverage leading up to it. But just like milder weather, it’s actually very difficult to predict. For instance, on average, predicted high temperatures diverge from actual high temperatures by three degrees Fahrenheit, and predictions of hurricanes are off by an average of about 100 miles, according to the US National Weather Service and the National Hurricane Center (via an article by Nate Silver for the New York Times Magazine).

And, according to new research, there are other factors that throw off meteorologists’ models. In a paper published in the journal Land, researchers from the University of Tel Aviv analyzed 15 years of prediction data to try to determine the errors that most impact the accuracy of weather forecasts.

According to their findings, some factors that can change relatively rapidly over the short-term, such as the prevalence or aerosols, the type and amount of vegetation in a region, and changes in how land is used, can lead to significant errors in temperature prediction.

For example, Professor Pinhas Alpert, an atmospheric scientist and one of the study’s authors, researched and documented how a national water pipeline in Israel that changed the landscape of the northern Negev affected the local climate enough to throw off weather forecasters.

So what happened with the New York blizzard? It turns out that it hit about 75 to 100 miles east of the predictions. So, on a small speck of the meteorologist’s map, some areas predicted to get walloped by snow only saw a fraction of the downfall expected.

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