NOAA’s hurricane gliders are returning home after a successful journey during the 2020 hurricane season. These gliders were deployed off the coasts of Puerto Rico, Dominican Republic, the U.S. Virgin Islands, the Gulf of Mexico, and the eastern U.S. to collect data for scientists to use to improve the accuracy of hurricane forecast models.
Glider SG609 is one of four gliders that are part of the Hurricane Field Program at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. AOML launched its glider project in 2014 with the goal of enhancing the understanding of air-sea interaction processes during tropical cyclones. Scientists and technicians from AOML and the University of Puerto Rico at Mayagues run the deployments and recoveries out of Isla Magueyes Marine Laboratories in Puerto Rico, which neighbors the colorful coastal island community of La Paguera.
Hurricane Danny & Tropical Storm Erika Provide Wealth of Research Opportunities for the 2015 Hurricane Field Program
AOML’s hurricane researchers conducted a number of field activities in August that provided data and critical insights into two Atlantic tropical cyclones, Danny and Erika. The two storms enabled researchers to test new instruments in support of the 2015 Hurricane Field Program and conduct research that will benefit future forecasts. Among the highlights were more than 15 successful manned and unmanned aircraft missions into Danny and Erika to collect and provide real-time data to the National Hurricane Center (NHC), as well as evaluate forecast models.
Scientists at NOAA’s Atlantic Oceanographic and Meteorological Laboratory are in the Caribbean to launch two underwater gliders from a vessel off Puerto Rico to collect temperature and other weather data to improve hurricane forecasting.One of the gliders will collect observations in the Caribbean Sea, and another in the North Atlantic Ocean. They are positioned to operate over the next six months (June-November) collecting data in areas where hurricanes are common and areas where there is a lack of environmental data.