The University of Utah is one of a six-institution consortium recommended to receive up to $6.6 million from the National Oceanic and Atmospheric Administration (NOAA) to improve weather forecasting through enhanced data assimilation methods.
The new Consortium for Advanced Data Assimilation Research will support six institutions that have been recommended to receive funding and will work together collaboratively under the new Consortium for Advanced Data Assimilation Research and Education (CADRE). 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.
Dr. 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 Principal Investigator of the University of Utah for CADRE. "By improving data assimilation techniques, we can help make more accurate weather forecasting."
Data assimilation combines observational data sources like satellite, surface, air and ocean measurements with numerical weather prediction models to generate comprehensive analyses of evolving weather systems. This blending of information better estimates the atmospheric states and corrects forecast models in real-time, thus enhancing projections of weather extremes such as storm paths, intensities and precipitation.
Despite major forecasting accuracy improvements 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 be focusing their research 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 effective coupled data assimilation methods to 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, UK, and through on-campus lectures on data assimilation methods. Students from the City College of New York will also participate in training activities.
"Data assimilation is a comprehensive scientific topic involving various types of data, data science and numerical modeling strategies. I welcome interactions and collaborations in atmospheric sciences, mathematics, physics and AI data science disciplines both on campus and beyond," Pu stated.
The $6.6 million will be funded by the Inflation Reduction Act and is part of the Biden Administration's Investing in America initiative. To learn more about this announcement, read the official NOAA release here.
By Bianca Lyon