“NYC bracing for up to 3 feet of snow” and “Potentially historic snow storm takes aim at Northeast this week” were typical news headlines on January 25, 2015, Over 43 million people were under either a blizzard or storm warning. Both AccuWeather and the National Weather Service, predicted the storm to dump between 20 and 30 inches of snow on NYC.
New York Governor Cuomo urged residents to take necessary safety precautions, and shut down the NY subway system for snow for the first time in its history. NY Mayor Bill de Blasio warned, “Prepare for something worse than we have seen before.” All non-emergency vehicles were ordered off the roads by late Monday. Schools were closed and employees were sent home early. Port Authority employees were ordered to work 12-hour shifts to get ready for snowfall. Over 7,000 flights were canceled ahead of the expected storm and travel bans were put into place.
Mayor De Blasio approved the use of 225,000 tons of salt while 2,400 city employees were set to drive 500 salt spreaders and 1800 snow plows. None of these preparations came cheap, but based on the predictions, they were the responsible things to do.
Meteorologist Dave Bowers warned New Yorkers not to be fooled by the calm before the storm. As it turned out, it was the meteorologists who were fooled this time when at the last minute the Nor’easter tracked farther east, slamming much of New England but leaving New Yorkers to wake up to only a few inches of snow. Snowmageddon headlines were replaced with “The Blizzard That Wasn’t.”
The prudent closing of the subway system later became a controversial topic while mocking memes flourished in cyberspace.
Winter Storm Juno serves as a case study on how easy it can be to get things noticeably wrong, even when the data is only slightly off. Although temperature forecasts are around 80% accurate, snow forecasts have a much lower rate of accuracy.
Weather predictions are not an exact science
Computer model predictions can be highly accurate, but the devil is in the details. “In the big picture, this was not a bad forecast,” said Adam Sobel, an atmospheric scientist at Columbia University, quoted in the New York Times. “The bigger the event, the bigger the bust potential,” Sobel said. For this storm, the distance between areas swamped with snow or receiving only a few inches was a mere 30 miles.
Retired meteorologist Ira Brenner says reporting accuracy for the path, timing and intensity of big storms becomes quite reliable within three days of a storm but even slight deviations of the storm’s path can make a huge difference to areas affected. That’s why he quips, “I am a non-prophet meteorologist.”
Simply tracking weather is very complicated as it depends on hundreds of different factors and variables. Making a correct forecast is even trickier. Forecasts are made by supercomputers using complex mathematical equations. A far cry from the Farmer’s Almanac.
Where Do Weather Forecasts Come From?
The National Weather Service, a government agency, makes predictions and issues alerts. It is a division of the NOAA, the National Oceanic and Atmospheric Administration. Meteorologists are trained to make predictions based on major computer forecast models, which while highly accurate, can completely be changed by unpredictable causes which can just slightly change the tracking.
The primary used forecast models in the U.S. are the North American Mesoscale Model or NAM , the Global Forecast System or GFS, with support from European and Canadian models. News sources such as Accuweather, Weatherworks, and Weather 24/7 are informed by models such as these.
The GFS is run four times a day and can make predictions up to 16 days in advance. Its supercomputers are able to process eight quadrillion calculations per second. In comparison, it’s calculated that the human brain can perform about 10,000 trillion calculations in that amount of time.
Why you can depend on Y&L
Y&L Landscaping specialists form a consensus based on these highly accurate models before deciding when and how to activate their snow removal equipment, including snow plows, trucks and teams. Careful planning of the best way to treat the surfaces of its many commercial property parking lots and walkways assures the quickest, most cost-effective and efficient service for its many satisfied customers.
So the next time you hear a snow forecast for a few days in the future, be assured that there is a very good degree of accuracy. It’s a good idea to be prepared and take forecasts seriously but realize nothing is certain until it happens. All the more so when reading the Farmer’s Almanac, which you should take with quite a few grains of salt — or even better salt brine.
