What is a spaghetti model?

We break down science behind how meteorologists predict path of storm

By Tom Sorrells - Chief Meteorologist, Donovan Myrie - Investigative/Special Projects Producer

ORLANDO, Fla. - Ever wonder why it’s so hard to predict where and when a hurricane will exactly make landfall?

It’s not always from a lack of information available; it’s sometimes from having too much information. 

“Computer modeling forecasts have come very far in the last few years,” said WKMG-TV chief meteorologist Tom Sorrells. “Models in the past helped, but the error in the cone of projected movement still had errors along 300 to 400 miles on day five of the forecast. 

“With today’s models, computing and increased forecast knowledge, the cone is now down to about 150 miles on day four and 220 on day five. The main difference is the amount of information going in and the computing strength of computers.”

Hurricane forecasters have many different computer models to aid in predicting a storm’s path. Meteorologists refer to these as “spaghetti models” because when laid out on a map, the storm paths resemble strings of spaghetti. All of them are good, but they each consider many variables, and when looking at a five-day and beyond forecast, predictions can vary widely.

“We use the graphic presentation for easy and quick comparison between the models,” said Sorrells. “If we didn’t put them up on a screen, or page in a graphic setting, then we would not be able to see the differences without plotting them on paper.”

In its simplest form, a spaghetti plot is nothing more than a compilation of different computer models predicting the path of a hurricane or tropical storm. Sometimes meteorologists will use just five or six models. Other times, forecasters will show a storm forecast with more than a dozen different paths.

“This is a huge area of discussion among many in the profession,” said Sorrells. “One camp feels like it does do a disservice because it opens the door to people who are not trained to interpret the information the chance to get a false impression of possible safety. Others feel like it doesn’t give a false impression. 

“Personally, I feel like anyone can find them on the internet and if I don’t show them, people will simply go to the web and find them anyway. I’d rather show the ones I use the most and explain what I feel is happening.”

There are more than 100 different models available to forecasters.

“We use the ones we use because they are the most reliable ones in the business,” says Sorrells. “I usually show fewer than more, most of the time limiting models on the screen to five to 10.”

And are some better than others?
 
“I favor the standards of the Euro and the (American) GFS,” said Sorrells. “I also love to see the HWRF and I like to show the TVCN as well. I favor that one for most storms because they are the workhorses of the industry.” 
 
GFS? HWRF? TVCN? Euro? 
 
And therein lies the problem- What does all of that mean?
 
In the infographic below, we’ve broken down details for each of the models (what the acronym stands for, who runs it and a brief history of it) so you, our audience, can have a better understanding of the information that comes across your screen and your smartphone.

 

 


 
Before you dive into the infographic, here are several points specifically about a term (interpolated) that you’ll often see when trying to understand computer weather models: 
 
•    An interpolated computer model is something of a very educated guess used to help forecasters adjust paths and intensities of hurricanes to catch up with current conditions. 
 
•    Why would this be done? Usually it’s a time crunch issue. Because of the availability of information from a variety of resources (satellites, aircraft and other models), new conclusive data might not exist for up to half a day. 
 
•    Forecasters sometimes can't wait that long and need a more up-to-date model run. Interpolated adjustments are up to six hours before the next full analysis. If a computer model acronym ends in the letter “I”, it’s more than likely an interpolated model. 
 

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