“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. Locations that will not be impacted can keep their economies open, and those that will be impacted can more effectively prepare.”said Folsom
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.
EAST GREENSBORO, N.C. (June 1, 2020) –
written by Alexander Saunders