A video showing Sandy’s life from October 23 to October 31: As Hurricane Sandy moved up the East Coast, a ridge of high pressure north of New Foundland blocked her from moving north and generated clockwise winds that pushed her into the East Coast, where she morphed with a cold front that had been moving east across the Eastern U.S. “The big picture of what made Sandy move north and then curve back northwest was really not having anywhere else to go,” says Brian McNoldy.
It was as a nine-year-old kid in Reading, Pennsylvania, that University of Miami scientist Brian McNoldy developed a fascination with hurricanes. “I think most of us have a storm,” he says. “Mine was Hurricane Gloria, in 1985.”
TV newscasters warned about the impending winds and rain. Local officials cancelled school for a few days. When the storm hit, it knocked out power. McNoldy went outside. “I can still remember how strong the winds were,” he says. “We didn’t get hit by the eyewall—just by the rainbands, but even that was pretty impressive.”
After earning undergraduate degrees in physics and astronomy at Lycoming College, a graduate degree in atmospheric science at Colorado State University, and picking up research experience at Colorado State University, he landed at the University of Miami in January of 2012. “This is an up-and-coming school in hurricane research, and there’s a lot of momentum going here,” he says. “I’m happy to have the opportunity to be part of it.”
For his job, he works on something called “vortex initialization code” for a joint project with the Navy. It’s a series of sophisticated computer programs that allow scientists to take a crudely-represented hurricane out of a model analysis, replace it with a more realistic hurricane that has tuneable factors (such as intensity, size of the storm, etc.), and see how changes affect the forecast.
When he’s not working on the vortex code, he writes about hurricanes. “I started what, at the time, wasn’t called a blog, because they weren’t really there yet, in 1996,” he says. “For any storm—not even a storm, for any wave in the Atlantic, I would have my little list of people who were interested in what was going on, and I would send updates to them during hurricane season. I’ve been doing that for 16 years now.”
His audience has grown. From 2007 to 2010, he was invited to blog about hurricanes for The New York Times. In 2012, he started blogging for the Washington Post and the Rosenstiel School of Marine and Atmospheric Science. On October 22, when Sandy was still Tropical Depression 18, he was one of the first to report on the likelihood of it turning into the Northeast U.S. with possibly devastating consequences. We caught up with him to learn a bit more about the science behind Sandy.
When did you start watching Sandy?
I think some of the models were picking up on something forming in the Western Caribbean probably by about October 12 or 13. Some models picked up, run after run, something that would form in the Western Caribbean, and then would move north toward Cuba. That persisted and they ended up being right. The National Hurricane Center issued the first advisory on Tropical Depression 18 on October 22, then upgraded it to Tropical Storm Sandy later the same day. It eventually headed north over Jamaica and Cuba. I thought, Wow, that’s extremely impressive for those models.
[Editor’s Note: Models are computer programs used to help forecast the formation and movement of tropical storms and hurricanes.]
On October 22, you blogged that there was a possibility it could hit the East Coast. How did you know that?
There are a few rather reliable global models. They’re models that run all the time, all year long, so they don’t focus on any one storm. They run for the entire globe, not just for North America. There are two types of runs these models can be configured to do. One is called a deterministic run and that’s where you get one forecast scenario. Then the other mode, and I think this is much more useful, especially at longer ranges where things become much more uncertain, is ensemble—where 20 or 40 or 50 runs can be done. They are not run at as high of a resolution as the deterministic run, otherwise it would take forever, but it’s still incredibly helpful to look at 20 runs.
Because you have variation? Do the ensemble runs include different winds, currents, and temperatures?
You can tweak all sorts of things to initialize the various ensemble members: the initial conditions, the inner-workings of the model itself, etc. The idea is to account for observational error, model error, and other sources of uncertainty. So you come up with 20-plus different ways to initialize the model and then let it run out in time. And then, given the very realistic spread of options, 15 of those ensemble members all recurve the storm back to the west when it reaches the East coast, and only five of them take it northeast. That certainly has some information content. And then, one run after the next, you can watch those. If all of the ensemble members start taking the same track, it doesn’t necessarily make them right, but it does mean it’s more likely to be right. You have much more confidence forecasting a track if the model guidance is in in good agreement. If it’s a 50/50 split, that’s a tough call.
To read the rest of the interview, click here.
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