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University of Utah included in NOAA’s $7M weather forecasting initiative

U atmospheric scientists partner with five other universities to enhance data assimilation for better weather prediction models

With a goal of improving weather forecasting, researchers from the University of Utah and five other institutions have secured $6.6 million in federal funding to explore enhanced data assimilation methods.

The new Consortium for Advanced Data Assimilation Research and Education (CADRE), will support the six universities’ scientists whose research is being coordinated by the National Oceanic and Atmospheric Administration (NOAA).

Zhaoxia Pu

“This NOAA funding allows our researchers to collaborate with leading experts across the country to tackle a key challenge in data assimilation methodology,” said Atmospheric Sciences Professor Zhaoxia Pu, the U’s principal investigator on the project. “By improving data assimilation techniques, we can help make more accurate weather forecasting.”

Data assimilation combines observational data, such as satellite, surface, air and ocean measurements, with numerical weather prediction models to generate comprehensive analyses of evolving weather systems. This blending of information better characterizes the atmospheric states and corrects forecast models in real-time, thus enhancing projections of storm paths and intensities, precipitation and other weather extremes.

Despite major forecasting accuracy gains in recent decades, upgraded data assimilation methods are needed to leverage new technological capabilities like artificial intelligence. The CADRE consortium will focus its efforts on advancing the data assimilation components of NOAA’s Unified Forecast System (UFS), a community-based, coupled, comprehensive Earth- modeling system.

Pu’s team will focus on the coupled data assimilation efforts to improve weather forecasting from short-range to sub-seasonal to seasonal time scales. Atmospheric processes are significantly influenced by interactions with the land and ocean. Pu’s team will develop methods that better represent the land-atmosphere-ocean interactions within NOAA’s UFS. Pu will also dedicate time to training graduate students through research projects, outreach activities with NOAA Laboratories and the University of Reading in the United Kingdom and through on-campus lectures on data assimilation methods. Students from the City College of New York will also participate in her training activities.

“Data assimilation is a comprehensive scientific topic involving various types of data, data science and numerical modeling strategies,” Pu said. “I welcome interactions and collaborations in atmospheric science, mathematics, physics and AI data science disciplines both on campus and beyond.”

Funded by the Inflation Reduction Act, the CADRE is led by the University of Oklahoma and includes Colorado State University, Howard University, University of Maryland, Pennsylvania State University and the University of Utah. To learn more about this announcement, read the official NOAA release here.