AMS science preview: New lightning record, fewer hurricanes, fire forecasts
Peer-Reviewed Publication
Updates every hour. Last Updated: 17-Aug-2025 08:11 ET (17-Aug-2025 12:11 GMT/UTC)
Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that the new tool makes the models more accurate at both the global and regional level. This advance should provide policymakers with improved climate projections that can be used to inform policy and planning decisions.
Tiny droplets of sea spray generated at the ocean surface can affect the intensity and evolution of hurricanes and other tropical storms.
Their impact, however, is not well understood because of the difficulty of measuring spray concentration and the size and velocity of individual droplets under high wind conditions.
At The University of Texas at Dallas, researchers are studying sea spray, particularly spume, or foam, droplets, in the lab to develop a model based on machine learning to improve hurricane forecasting. The model incorporates the effects of the spray generation function, which quantifies the rate at which droplets form.