By NOAA Research

Ali Hochberg/BIOS

On September 30, 2021, a saildrone uncrewed surface vehicle made history by intercepting the eyewall of Hurricane Sam in the northwestern tropical Atlantic, recording a viral video of what it’s like to be tossed around by 100 mile-per-hour winds and 30-foot high waves.

The Guinness Book of World Records later certified that a 126.4 mile-per-hour wind gust recorded by the bright orange 23-foot saildrone in the core of the Category 4 storm was a new world record for an uncrewed surface vehicle.

But the most long-lasting impact of Saildrone Explorer SD 1045’s trailblazing research voyage may come from the continuous readings collected by the craft’s temperature sensors. Timely, accurate upper-ocean observations like those collected during the mission could directly benefit hurricane intensity forecasts – if they can be swiftly provided to weather forecast systems, according to new research by NOAA oceanographers published in Frontiers of Marine Science.

“Sam turned out to be one of the longest and strongest hurricanes in our historical record,” said Andrew Chiodi, a CICOES oceanographer affiliated with NOAA’s Pacific Marine Environmental Laboratory (PMEL). “We were targeting the northeast eyewall and the intercept was a bulls-eye. Until now, we haven’t had a surface platform that we can steer into a hurricane while it continuously measures air-sea interactions, and transmits data in near real-time for use by numerical hurricane forecast models.”

Early and accurate forecasts of storm tracks and intensity are vital for protecting life and property from hurricane impacts. During the past decade, however, the accuracy of hurricane track predictions has substantially outpaced those for storm intensity, which is influenced by transfers of heat and momentum across the ocean surface during tropical cyclone development. Sea surface temperature has long been used as a statistical predictor of intensity.

Analysis by Chiodi and his research team found that the observations and measurements collected by the ocean robot revealed surface ocean temperatures had unexpectedly risen during the first half of the storm. These changes were not captured by satellites, profiling floats, or hurricane-hunting aircraft that provide the data used by hurricane forecast models, said co-author Greg Foltz, a NOAA oceanographer with the Atlantic Oceanic and Meteorological Laboratory.

As a result, the forecast model predicted surface waters to be cooler than they actually were.  This caused the model to underestimate the flow of heat from the ocean into the storm near the eyewall, which reduced the forecasted potential intensity of the storm.

Hardy, adaptable, and cost-effective

Enter the saildrone. Remotely piloted and powered by wind and solar energy, these rugged ocean robots can make multiple simultaneous environmental observations including wind speed, wave height, temperature, pressure and salinity in places too dangerous for people to venture. Saildrones are equipped with Global Positioning System and an onboard computer, enabling the vehicles to navigate to prescribed waypoints, autonomously adjusting for wind direction and current. Each vehicle is supervised 24/7 by operators at Saildrone Mission Control in Alameda, California.