A project co-led by NSF NCAR that will use artificial intelligence models to predict storm evolution has received funding through NSF's Collaborations in Artificial Intelligence and Geosciences (CAIG) program.

More accurately predicting periods of increased hurricane activity weeks in advance may become possible due to new research published this month. Research from NSF NCAR shows that twice as many hurricanes form two days after the passing of large-scale atmospheric waves called Kelvin waves than in the days before.

Researchers have found that the turbulent movements of air in clouds play a key role in the growth of water droplets and the initiation of rain.

Forecasters can use images in social media to better communicate weather related hazards of hurricanes, according to a pair of new studies.

A flexible, next-generation atmospheric model with the capability to accurately model weather, both regionally and globally, has been garnering increasing interest from user groups around the world, including weather forecasters, government agencies, climate scientists, private companies, and beyond.