July 1, 2016 | Last spring, scientists at the National Center for Atmospheric Research (NCAR) flipped the switch on a first-of-its-kind weather forecasting system. For more than a year, NCAR's high-resolution, real-time ensemble forecasting system has been ingesting 50,000 to 70,000 observations every six hours and creating a whopping 90,000 weather maps each day.

The system has become a favorite among professional forecasters and casual weather wonks: Typically more than 200 people check out the site each day with more than a thousand coming during major weather events. During this experimental period, the NCAR ensemble has also become a popular source of guidance within the National Weather Service, where it has already been referenced several hundred times by forecasters at more than 50 different offices. 

But perhaps more important, the data accumulated from running the system daily — and there is lots of it — is being used by researchers at universities across the country to study a range of topics, from predicting hail size to anticipating power outages for utilities.

"We wanted to demonstrate that a real-time system of this scale was feasible," said NCAR scientist Craig Schwartz. "But it's also a research project that can help the community learn more about the predictability of different kinds of weather events."

Schwartz is a member of the team that designed and operates the system, along with NCAR colleagues Glen Romine, Ryan Sobash, and Kate Fossell.

This animation shows the forecast for accumulated snowfall made by each of the NCAR ensemble's 10 members for the 48-hour period beginning on Jan. 22, 2016. In the run-up to the blizzard, which ultimately dropped more than 30 inches of snow on parts of the Mid-Atlantic, more than 1,000 people visited the NCAR ensemble's website. (©UCAR. This animation is freely available for media & nonprofit use.)

Testing a unique tool

NCAR's high-resolution ensemble forecasting system is unique in the country for a couple of reasons, both of which are revealed in its name: It's an ensemble, and it's high resolution.

Instead of producing a single forecast, the system produces an "ensemble" of 10 forecasts, each with slightly different (but equally likely) starting conditions. The degree to which the forecasts look the same or different tells scientists something about the probability that a weather event, like rain, hail, or wind, will actually occur.

By comparing the actual outcomes to the forecasted probabilities, scientists can study the predictability of particular weather events under different circumstances. 

The forecasting system's high resolution (the grid points are just 3 kilometers apart) allows it to simulate small-scale weather phenomena, like the creation of individual storms from convection — the process of moist, warm air rising and then condensing into clouds. 

The combination of fine grid spacing and ensemble predictions in the NCAR system offers a sneak peek at what the future of weather forecasting might look like, and weather researchers across the country have noticed. 

Cliff Mass, a professor of atmospheric sciences at the University of Washington whose specialty is forecasting, said: "It's extremely important for the United States to have a convection-allowing ensemble system to push our forecasting capabilities forward. We were delighted that NCAR demonstrated that this could be done."

'The cat's meow'

The treasure trove of accruing weather data generated by running the NCAR ensemble is already being used by researchers both at NCAR and in the broader community. Jim Steenburgh, for instance, is a researcher at the University of Utah who is using the system to understand the predictability of mountain snowstorms.

"NCAR's ensemble not only permits the 'formation' of clouds, it can also capture the topography of the western United States," he said. "The mountains control the weather to some degree, so you need to be able to resolve the mountains' effects on precipitation."

Steenburgh has also been using the ensemble with his students. "We’re teaching the next generation of weather forecasters," he said. "In the future, these high-resolution ensemble forecasts will be the tools they need to use, and this gives them early, hands-on experience." 

Like Steenburgh, Lance Bosart, an atmospheric researcher at the University of Albany, State University of New York, has used the ensemble both in his own research — studying the variability of convective events — and with his students. He said having 10 members in the ensemble forecast helps students easily see the great spread of possibilities, and the visual emphasis of the user interface makes it easy for students to absorb the information.

"What makes it an invaluable tool is the graphical display," he said. "It's visually compelling. You don't have to take a lot of time to explain what you're looking at; you can get right into explaining the science. I like to say it's the cat's meow." 

Setting an example

The NCAR ensemble is also enabling the researchers running it to further their own research. 

"We're collecting statistics on the misfit between the model predictions and observations and then we're trying to use that to improve our model physics," Romine said. 

The ensemble project is also teaching the team about the strengths and weaknesses of the way they've chosen to kick off, or "initialize," each of the ensemble members. 

"The NCAR ensemble happens to produce a pretty good forecast, but we realize there are some shortcomings," Schwartz said. "For example, if we were trying to make the best forecast in the world, we would probably not be initializing the model the way we are. But then we wouldn’t learn as much from a research perspective." 

The NCAR ensemble began as a yearlong trial, but the project is continuing to run for now. The team would like to keep the system online until next summer, but they don't yet have the computing resources they need to run it past September.

If the system does continue to run, the researchers who are using it say there's still more that they and their students can learn from the project. And if not, there's loads of data already collected that are still waiting to be mined. 

In any case, Mass says NCAR's ensemble has been a valuable project. "It set a really good example for the nation," he said.

Community members interested in collaborating or helping support the NCAR ensemble project are encouraged to contact the team at ensemble@ucar.edu.

Writer/contact:
Laura Snider, Senior Science Writer and Public Information Officer 

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