Uncrewed systems continued to prove their worth for storm prediction as Hurricanes Helene and Milton made landfall on Florida’s Gulf Coast in September and October.
“Gliders and other autonomous vehicles are not only the most cost-effective technology available to collect ocean condition data for months at a time, but we know they are also safer because we don’t need humans to be in the path of storm to gather the data,” said Dr. Jorge Brenner, GCOOS Executive Director. “And from a practical standpoint, it would be difficult for anyone to collect the complex tri-dimensional ocean data needed from throughout the water column that forecasters at the National Weather Service (NWS) need to develop their models.”
New data collected by gliders, Saildrones, buoys, satellite and radar are ingested each time new models are run to help forecasters better determine storm path and intensity. As the NWS continues to implement new operational models, data from these systems, along with AI and machine learning will become even more crucial to storm prediction, says Brian LaMarre, Program Manager for NWS Operations Model Implementation. “AI will be able to assimilate all of these data points even faster than ever before,” he said. “Having more data points will only help us improve our forecasts.”