Yes, your weather app’s forecasts have become increasingly inaccurate in recent years—but only if you live in the U.S. John Tlumacki/The Boston Globe via Getty Images
You don’t have to be a placid Californian cast into the merciless chaos machine that is the East Coast’s summer to bemoan humans’ inability to accurately predict when it will rain, and for how long.
And the more you know about how weather forecasts work in the United States, the more annoyed and less patriotic you may become.
This even applies to members of Congress, who appear to have scared the nation’s meteorologists into seeking weather-predicting innovations whenever (and wherever) they can be found.
The national inferiority complex dates to 2012. Late that fall, while tracking the progress of a storm across the Atlantic, the American Global Forecast System (GFS) predicted this weather pattern would break up and fizzle over the ocean.
Instead, what became Hurricane Sandy turned straight toward the New York metropolitan area.
The storm flooded streets and subways, many of which are still feeling the effects, killed 233 people and caused $75 billion in damage—just as the European weather computer model guessed it might.
SEE ALSO: Why Do People Believe in Weather Control Conspiracy Theories?
The very bad miscalculation about Sandy has set off what’s become a years-long effort to improve U.S. weather predictions—and to leverage whatever advances in technology or technique there may be to do it, no matter the source.
As acting National Oceanic and Atmospheric Administration (NOAA) administrator Neil Jacobs admitted, even after a recent upgrade, NOAA’s GFS still lags behind both the European Centre for Medium Range Weather Forecasts (ECMWF) and the UK Met Office in forecast accuracy—and nobody is happy about it. Particularly not Congress, which, as the American Institute on Physics (AIP) recently observed, is running short on patience for NOAA to fix its forecasts.
Congress “is perturbed, frustrated, if not downright angry” at NOAA, said Antonio Busalacchi, president of the University Corporation for Atmospheric Research, according to AIP.
(Lest you start believing that the private sector would be inherently better at predicting the weather, remember: the data that everyone uses to guess about rainfall comes from government-funded sources, and the Europeans seem to be doing just fine with a public model.)
One reason why the Europeans are better, as Jacobs said in a recent public address, is that Europe allocate five times as much “computing resources” to “weather research” as America does. The Europeans also benefit from a centralized approach. Whereas Americans have more money, the extra resources just create “parallel modeling programs” that aren’t any more accurate, Jacobs said.
To fix this, NOAA is trying to coordinate more closely with both existing federally funded weather modeling—bolstering what NOAA is calling the “Unified Forecast System” and what Jacobs envisions as a “single seamless system” for predicting weather—as well as comb academia for under-utilized advances.
Meteorologist Scott Entrekin is monitoring weather patterns at NOAA Boulder on Wednesday, October 24, 2018. Hyoung Chang/The Denver Post via Getty Images
Another more fundamental problem is NOAA’s reliance on older computer models, which Jacobs calls “legacy forecasting products” that persist in large part because whoever runs them has a direct line to a member of Congress, who then “calls and yells at me” for trying to abandon an obsolete product.
So there’s a lot going on! Maybe one way to fix it is to allow anyone with the expertise to jump in the pool and see if their toy will float.
Earlier this year, using money and clout secured thanks to the Weather Research and Forecasting Innovation Act approved by Congress in 2017, NOAA inked a deal with the nonprofit, federally funded National Center for Atmospheric Research (NCAR) to improve computer modeling.
At the same time, NOAA announced the creation of a $15 million “Earth Prediction Innovation Center,” or EPIC—essentially a cloud-based clearinghouse for researchers developing “new and emerging model technology” to “quickly transition” those computer models into making more accurate weather forecasts for NOAA. In other words, if any innovations are happening in weather modeling, NOAA wants to be able to use them—immediately.
This will allow NOAA to “crowdsource model development,” as Jacobs said. It will also allow EPIC “to live outside of NOAA,” essentially allowing weather forecasting in the United States to take both inspiration and direction from outside of the federal government.
Will it work? It could. If NOAA and GFS are ever to “regain global leadership in weather forecasting,” EPIC might be the way to do it, the American Institute of Physics observed this week.
If that doesn’t happen, if academia isn’t able to offer a model and NOAA isn’t able to harness it in time to prevent the next city-wrecking miscalculation, an even angrier—and wetter, or drier, as the case may be—Congress may come back with a vengeance. Or less money. In either event, Americans would be left guessing at what to wear that day, while gazing ruefully at Europeans’ confident choice of linen and umbrella.
Why do weather forecasters get it wrong so often?
James Matkin, former Deputy Minister at Government of British Columbia (1974-1983)
Updated 46w ago · Author has 755 answers and 658.5k answer views
The weather and climate are unpredictable because of the complexity and diversity of the driving forces causing climate change. This means UNCERTAINTY RULES.
Everyone knows first hand you cannot depend on weather forecasts for more than few days yet somehow Alarmists have convinced the public that with fancy computer models they can predict what the earth’s climate will be in 100 years. This is anti-intellectual, anti scientific rubbish.
I suggest the views of Camille Paglia regarding the climate debate are a relevant introduction to the question.
Camille Paglia is a second-wave feminist and …
Why the weather forecast will always be a bit wrong
The science of weather forecasting falls to public scrutiny every single day. When the forecast is correct, we rarely comment, but we are often quick to complain when the forecast is wrong. Are we ever likely to achieve a perfect forecast that is accurate to the hour?
There are many steps involved in preparing a weather forecast. It begins its life as a global “snapshot” of the atmosphere at a given time, mapped onto a three-dimensional grid of points that span the entire globe and stretch from the surface to the stratosphere (and sometimes higher).
Using a supercomputer and a sophisticated model that describes the behaviour of the atmosphere with physics equations, this snapshot is then stepped forward in time, producing many terabytes of raw forecast data. It then falls to human forecasters to interpret the data and turn it into a meaningful forecast that is broadcast to the public.
The whether in the weather
Forecasting the weather is a huge challenge. For a start, we are attempting to predict something that is inherently unpredictable. The atmosphere is a chaotic system – a small change in the state of the atmosphere in one location can have remarkable consequences over time elsewhere, which was analogised by one scientist as the so-called butterfly effect.
Any error that develops in a forecast will rapidly grow and cause further errors on a larger scale. And since we have to make many assumptions when modelling the atmosphere, it becomes clear how easily forecast errors can develop. For a perfect forecast, we would need to remove every single error.
The Great Storm of October 1987: when forecasters got it wrong.
Forecast skill has been improving. Modern forecasts are certainly much more reliable than they were before the supercomputer era. The UK’s earliest published forecasts date back to 1861, when Royal Navy officer and keen meteorologist Robert Fitzroy began publishing forecasts in The Times.
Why Weather Forecasts Are Still Wrong Despite Complex Computers
It was March 2017, and a winter storm named Stella promised to deliver up to a foot and a half of snow to New York City and parts of New Jersey. Officials pushed out blizzard warnings, suggesting the city was under imminent snowy siege.
But only 7 inches fell. Then-Gov. Chris Christie blasted forecasters. “I don’t know how much we should be paying these weather guys,” he said. “I’ve had my fill of the National Weather Service after seven and a half years.”
For anyone following the weather, forecasts for big storms are sometimes still roller-coaster rides – with sudden shifts in track or intensity.
As a meteorologist who forecasts for a large urban market, I can attest to the frustration.
Why can’t we get it right every time, given this era of 24/7 weather data, dozens of satellite and sophisticated computer models? The answer lies in the quirks between the most popular forecasting models.
Battle of the Models
Computer forecast models have become the mainstay of weather prediction across North America and many other parts of the world. Run on fast supercomputers, these sophisticated mathematical models of the atmosphere have gotten better over the past couple decades.
Human forecast skill has improved by approximately one day per decade. In other words, today’s four-day forecast is as accurate as a three-day forecast was a decade ago.
Forecasters in the U.S. routinely examine several models, but the two most discussed ones are the American and the European. When the models disagree on the track of a big storm, forecasters must often choose which they believe is most correct. This decision can make or break a critical forecast.
Most meteorologists agree that the European model is the most skillful. This was cemented in March 1993, when it correctly forecast the track and intensity of a historical Nor’easter. Called the “Storm of the Century,” the storm dropped a blanket of heavy snow from the Gulf Coast to the northern tip of Maine.
The storm was a milestone for what is termed medium-range forecasting, or forecasts made three to seven days out. The European model nailed the prediction five days in advance. That meant officials could declare states of emergency before the first flakes ever flew.
Fast forward to 2012, and the Euro was still making correct calls on big, dramatic storms. But this time, the lead time went beyond eight days. The storm was Hurricane Sandy, a massive Atlantic storm.
More than a week in advance, the European model predicted an oddball westward jog in Sandy’s track, whereas the American model arced it eastward and harmlessly away from the East Coast.
Score: another major victory for the European.
Forecasts before Hurricane Sandy disagreed on the storm’s track.National Hurricane Center
Why does the European do so well, compared to its American counterpart?
For one, it’s run on a more powerful supercomputer. Two, it has a more sophisticated mathematical system to handle the “initial conditions” of the atmosphere. And three, it’s been developed and refined at an institute whose singular focus is on medium-range weather prediction.
In the U.S., the medium-range American model is part of a suite of several models, including several short-range prediction systems that run as frequently as every hour. The time, intellectual focus and costs are shared among as many as four or five different types of models.
The public has heard about the European model’s victories. But forecasters also know that the American model is quite skillful; it’s had its share of wins, albeit less high-profile.
One of these was Winter Storm Juno, a 2015 Nor’easter that severely impacted the New England coast. Forecasters put out a dire warning for 24 to 36 inches of snow across all of New York City.
In an unprecedented move, Governor Andrew Cuomo shut down the subway system in advance, a move never done for an impending snowstorm.
Why is the weather so hard to predict?
Has this ever happened to you? You check the weather forecast. It predicts rain. And you end up carrying your umbrella around on a beautiful, sunny day.
Back in 2015, the New York Post warned Big Apple residents of Snowmageddon 2015. But what actually happened? A light snowfall.
Meteorologists use computer models to predict the weather. And computational power has come a long way. Yet meteorologists still have trouble correctly predicting the weather over a period of a few days. Sometimes they don’t even get it right over a 24-hour period! Why does this happen? Well, their ability to predict the weather is limited by three factors:
- the amount of available data;
- the time available to analyze it; and
- the complexity of weather events.
Let’s look in detail at the process of predicting the weather.
Where do meteorologists get their information?
Today, weather forecasting or meteorology relies on a huge data collection network. This network includes land-based weather stations, weather balloons, and weather satellites.
Weather forecasters also use data from offshore buoys and ships operating at sea. All of these sources combined create an observational network of data. This data is entered into computers to create computer models.
Meteorologists use these computer models to make weather forecasts.
Land-based weather station on the left and weather station buoy on the right (Sources: JIRAROJ PRADITCHAROENKUL via iStockphoto and Aneese via iStockphoto).
Did you know?
Don’t be mad at your meteorologist for a poor forecast. We’re mad enough at ourselves
So often the story is the same: Meteorologist predicts foot of snow. Audience plans for snow day. Last-minute change to storm track means only two inches falls. Public bitterly complains.
“A massive WELL DONE,” one man declared to AccuWeather, where I work as a meteorologist and blogger, “for your incredibly BAD forecast for today’s weather.”
“Isn’t Accuweather located in State College? How is it possible they got the forecast wrong? #3inchesmyass #blizzard,” read a tweet from one Pennsylvania man.
And of course there are the calls for meteorologists to be fired for incorrect forecasts, including “every meteorologist” in Portland, Phoenix, Oklahoma City, Alabama, the New York Metro area, Houston, Orlando, Augusta, Seattle, Knoxville, Spokane, El Paso and Baltimore, to name a few.
I’m always amazed at the vitriolic comments aimed at forecasters when a storm underperforms. (I know there are a lot of snow lovers out there, and I’m one of them.
But you wanted a storm to dump a ton of snow on your city, shutting it down, making roads impassable and potentially killing or hurting people?) Even before the storm happens, people seem to have made up their minds that we are going to be wrong.
“I’m beginning to think it isn’t going to snow at all, since they are so sure,” one reader commented on a forecast on our site. Wrote another: “Maybe 3-6 inches. 99% of the time they are always wrong. This only helps the supermarkets and hardware stores.”
The accusation that we meteorologists have some kind of agenda, whether it’s increasing sales of shovels or something more political, when forecasting high-impact storms happens more than you might think.
“They’re beginning to use their hyperbolic terminology, so it’ll probably be a wimp storm,” one reader wrote.
“I think the more fear they can ‘wolf’ up the more money they can get in their budget next year to hype ‘Global Warming’ and/or ‘Climate Change,’ which conjures up more fear and more money.”
The tricky business of weather prediction: Why forecasters sometimes get it wrong
No matter what the TV weatherman says, it’s probably always worth packing an extra jumper or maybe even that umbrella you don’t think you’ll need.
It’s less common than it used to be, but the weather forecast isn’t always right.
Just ask anyone living in Melbourne. In 2017, in one of the more famous recent cases of the Bureau of Meteorology getting it a bit wrong, Victorians were told to brace for a biblical storm with severe weather warnings issued and 7.4 million text messages sent out warning residents of flooding.
In the end it passed Melbourne and surrounding areas with little excitement but later drenched the north of the state. Many were left wondering what all the fuss was about, forcing the Bureau of Meteorology to defend its forecasting.
A satellite image provided by NASA from the International Space Station shows Hurricane Dorian earlier this month. Source: NASA
- The physics and technology of weather forecasting have advanced significantly in recent years but perfect accuracy remains a quixotic notion.
- In the age of satellites and super computers we’ve got more observational data and more power to crunch it than ever before.
- As a result we can now predict seven days ahead with about the same accuracy as we could to three days at the turn of the century.
- “Fifteen years ago when I started at the BoM, we’d get one satellite image every hour,” senior bureau forecaster Steven McGibbony told Fairfax in May.
“Some of the older forecasters here in the '90s said we’d get one every six hours. We now get a satellite image every 10 minutes.”