Robot’s Sandy Voyage May Aid Hurricane Forecasts
While many at the Jersey Shore were putting gasoline in their cars and tying down patio furniture the weekend before Superstorm Sandy, Rutgers University graduate students Greg Seroka and Travis Miles tracked their robot swimming around in the storm’s path.
In the days that followed, they got a rare glimpse into erupting undersea conditions as the storm swept ashore. Data the probe collected – including currents and sharp drops in sea surface temperature – might help scientists reconstruct Sandy’s behavior and better predict how hurricanes change in the critical hours before landfall.
“The big impact of this will be in forecasts … Weather models don’t resolve that temperature drop,” Seroka told the Asbury Park Press last week. He was speaking at the Institute of Marine and Coastal Sciences laboratory that operates and maintains a fleet of Slocum electric gliders, including the one the two grad students set loose for a spin Oct. 25.
The undersea gliders are long-range, battery-powered probes that move through the sea in an up-and-down pattern, like a slow roller coaster. Using ballast water to change depth, descents lend the machines forward speed, and their wings “fly” underwater just like a glider in the atmosphere. Sensors constantly gather information on water quality, temperature and other parameters, and periodically the gliders surface to transmit data to the lab.
The most famous glider in the fleet is RU-27, which made a historic trans-Atlantic crossing to Spain in 2009. But the machines are at work constantly now in the world’s oceans because they can operate at a cost of around $300 a day compared to $50,000 a day for an oceanographic ship and crew.
“We’ve had a few gliders in storms, by opportunity, not design,” said Miles, 27, a native of Wilmington, N.C., who has seen his share of hurricanes at home. Gliders survived bouts with hurricanes Ida and Irene in recent years, “so I wrote a short study proposal to do a mission like that,” he said.
Miles and Seroka thought their opportunity would come this fall or winter with a nor’easter. But a week before Sandy, Seroka and another Rutgers forecaster realized how big the storm could get.
“We decided right away we wanted to put a glider out to get this critical data,” said Seroka, 26, a native of Burke, Va. A glider had come back to the lab from a mission off California, so they refitted the machine, took it to Belmar and got on Capt. Jared Polick’s charter boat Fin-Ominal. About eight miles offshore, just past the shipping lanes, they launched.
Experience in past storms showed that operating at around 120 feet down ensured waves “won’t thrash your glider,” Miles said. But there was still risk because the robot had to surface hourly to transmit information, and to plot its position and figure out currents, he said, “you need that hour sampling time.”
On Nov. 5, they headed back out on Fin-Ominal.
“I think we were one of the first boats back out of Shark River,” Miles said. They cruised south, photographing damage onshore and the sunken roller coaster at Seaside Heights, then turned east and rendezvoused with the glider about 15 miles offshore.
The probe’s data are a picture of the ocean in utter tumult.
In the days before the storm, water of different temperatures lay in sharply defined layers, from 50 degrees Fahrenheit on the bottom to 64 degrees at the surface, Seroka and Miles said.
Then, “you see that all completely mixed, in 12 hours,” he said. As the storm approached, surface water began rushing toward shore and cold deep waters headed in the opposite direction. The mixing of waters dropped the surface temperature rapidly.
“Think about the ocean as the heat engine driving these storms as they approach shore,” Miles said. Measuring that change is a problem; satellite imaging of sea surface temperature is blocked by storm clouds and there are only a few scattered buoys with temperature sensors.
Miles and Seroka have a lot of analysis ahead of them before they can publish results. They hope the findings can be useful for forecasters and for post-storm analysis of Sandy and its monster storm surge.