EAST GREENSBORO, N.C. (June 1, 2020) – As another hurricane season begins, a computational science and engineering faculty member and two Ph.D. students at North Carolina Agricultural and Technical State University aim to improve tropical forecasting and modeling by deploying drones to collect data from the eye of hurricanes.
Hyoshin Park, Ph.D., and Ph.D. candidates Larkin Folsom and Justice Darko will explore ways to maximize the data collection and possible flight paths in future storms in this project supported by NASA’s Jet Propulsion Laboratory (JPL). During the summer of 2019, Park visited JPL and formulated the problem of efficient hurricane data collection using drones in collaboration with Masahiro Ono, Ph.D., a research technologist at the laboratory.
“Our department’s innovative, artificial intelligence-based model explores the search space to improve the hurricane track and intensity,” said Park, an assistant professor in the College of Engineering.
In 2014, the National Oceanic and Atmospheric Administration (NOAA) released two unmanned aerial vehicles (UAVs) into the eye of Hurricane Edouard, at the time the first category 3 or stronger storm to form in the Atlantic Ocean since Hurricane Sandy. The UAVs were the first-ever deployed into the eye of a tropical system and collected data inside the eye and the storm’s outer vortex, enduring for 68 minutes before plunging into the ocean.
The team will use early measurements from NOAA when the hurricane is forming to determine the storm’s wind-field and other important data. The crew will then know the ideal location to drop up to 10 drones, which will communicate with each other and to their base on the plane, effectively collecting as much data as possible.
For years, hurricane hunters have launched dropsondes into the center of the storm, near its eyewall, to determine the boundaries and structures of a hurricane. The device contains a GPS receiver, along with pressure, temperature and humidity (PTH) sensors to capture atmospheric profiles and thermodynamic data.
This method, while critical to yield important data for forecasting, requires aircraft and crew to drop to unsafe altitudes for a better view of the drop zone. This maneuver takes more time and fuel and puts the crew at risk. Additionally, the process requires numerous dropsondes to gather sufficient data about the hurricane and its forecast.
The team will repurpose the methodology from Park and Folsom’s 2018 proposal funded by the National Science Foundation’s Division of Information and Intelligent Systems Robust Intelligence program. The study focused on maximizing data collection for a Mars mission exploration of an unexplored environment with no flow of humans or traffic.
“This research is important because it will help improve hurricane forecasts, saving local economies money by more precisely constraining the forecast track and intensity,” said Folsom. “Locations that will not be impacted can keep their economies open, and those that will be impacted can more effectively prepare.”
Additionally, the research will help improve public trust in tropical forecasting. The A&T team members are also joined by Hui Sui, Ph.D., principal investigator and JPL engineering and science directorate Stratosphere and Upper Troposphere, Masahiro Ono, Ph.D., JPL research technologist from Robotic Surface Mobility and Masashi Minamide, Ph.D., an assistant professor at the University of Tokyo.