They have published their findings in peer-reviewed journals, given talks all over the world, shared their research with other academic institutions, and made their case repeatedly to government agencies involved in hurricane forecasting.
Part of their goal is to make sure officials know when expensive and difficult evacuations are warranted and when they’re not. To do so, the data need to be assimilated into existing models that atmospheric scientists use for hurricane predictions. Glenn and others say the current computer models are so faulty that the Rutgers temperature data have typically been rejected because they have been so different—a disconnect that exposed a longtime rift between the atmospheric and oceanographic camps.
But the Rutgers team has strong allies. One is the Integrated Ocean Observing System, or IOOS, part of NOAA’s National Ocean Service. Rutgers is a member of one of its 11 regional partnerships, the Mid-Atlantic Regional Association Coastal Ocean Observing System, a consortium of academic, governmental, and industry partnerships that runs from Cape Hatteras to Cape Cod.
“We see this as a huge opportunity to make a major impact at a relatively modest cost,” says Gerhard Kuska, the mid-Atlantic consortium’s executive director. “I think it’s a missing link in our region and may be in others.”
A critical mass of glider data from the 2018 hurricane season may finally convince hurricane forecasters and researchers that there is a large enough body of data to show that Glenn’s findings are more than isolated instances.
He has the Navy to thank for that. This past hurricane season, it tripled its glider-fleet deployment to about 100, making 30 of them available for hurricane patrol. That enabled Glenn’s team to collect data from dozens of gliders—at least 10 times more than it had ever had—in observational “picket lines” off Africa, where hurricanes form, as well as in the Caribbean, the Gulf, and the Atlantic.
“The key is that they’re there. If there’s any uncertainty in the track—it’s not like they’re going to miss one glider and then not hit any,” says Miles. “This is the first year where I didn’t have anxiety that we were going to have a storm and not capture data.”
Gliders were sent in as both Hurricanes Florence and Michael made landfall. The team’s initial analysis found that Florence de-intensified very rapidly and came ashore weaker than expected, though the major issue was still rain, which caused catastrophic damage. Michael did the opposite—rapidly intensifying as it came ashore.
“I can’t tell you why Florence de-intensified,” says Glenn. “There was no cold pool—the water was all warm.” As for Michael, the water around the storm was also quite warm. “Eighty percent of cooling was after the eye passed,” he says.
Glenn’s team expects to have that figured out by late spring, after they sort through 123,000 data profiles from gliders and an additional 7,800 data sets from floating monitors. The live data from the 2018 gliders were added for the first time to a database called the Global Telecommunication System, which is accessible to forecasters worldwide. But it’s unknown whether anyone has used it or even knows how.