AI Methods Enhance Rainfall And Ocean Forecasting In Climate Model

Artificial intelligence is opening new doors to Earth system modeling, offering new ways to improve predictions of precipitation and regional scale sea level rise. Two recent studies funded by the Climate Program Office’s Climate Variability & Predictability (CVP) program demonstrate how AI can enhance our understanding of climate variability. One study in JGR Atmospheres applies two AI methods (Self-Organizing Maps and Empirical Orthogonal Functions) to track shifting rainfall patterns in South America, leading to better extreme weather predictions. The other Geophysical Research Letters study applies a deep learning technique to improve forecasts of sea level changes in the Pacific and Atlantic Oceans. Both studies show that AI can enhance our ability to understand and predict complex weather and ocean patterns by uncovering hidden connections in climate data.

These findings have important implications for weather forecasting and climate research. More accurate rainfall and sea level predictions can help communities prepare for extreme storms, droughts, and coastal flooding. CVP grants help to drive cutting-edge, data-driven solutions to key scientific challenges in initiatives held in partnership with the National Weather Service – Office of Science and Technology (OSTI) Modeling Division and in support of NOAA’s Coastal Inundation Capability Framework.

About The Climate Program Office (CPO)
Americans' health, security and economic well being are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather.