Unified Forecast System
Earth Prediction Innovation Center

UFS Webinar

Ongoing Research and Developments for NOAA’s Next Generation Air Quality Model

Dr. Patrick Campbell George Mason University/NOAA-ARL Affiliate

Co-Authors: Dr. Wei Li, Dr. Beiming Tang, Dr. Youhua Tang, Dr. Barry Baker,  Dr. Irena Ivanova, Dr. Wei-Ting Hung, Dr. Zachary Moon, Dr. Chi-Tsan Wang, Dr. Daniel Tong, Dr. B.H. Baek, Dr. Siqi Ma, Dr. Paul Makar, Dr. Fanglin Yang, Dr. Jianping Huang, Dr. Ivanka Stajner, and Dr. Raffaele Montuoro

The next-generation Unified Forecast System’s Air Quality Model (UFS-AQM) has been developed at NOAA.  The UFS-AQM includes many novel advancements including a more flexible inline emissions modeling system and near real time, hourly biomass burning emissions that improve air quality predictions over the U.S. The UFS-AQM, however, is poised to benefit from recent scientific updates to its main chemical component (the Community Multiscale Air Quality model, i.e., CMAQ), as well as other research and developments to the emissions and air-surface exchange processes in the system.  Here we will present our work on major science updates to the UFS-AQM, which includes advancements to the chemistry, emissions, and air surface exchange processes such as atmosphere-biosphere interactions.

Dr. Patrick C. Campbell is a research associate professor at George Mason University (GMU), and a NOAA Air Resources Laboratory affiliate through the Cooperative Institute for Satellite Earth Systems Studies (CISESS). He received his PhD from the University of Wyoming and later received a postdoctoral fellowship at North Carolina State University and the U.S. EPA. He is currently the associate director of the Satellite and Earth System Studies (SESS) Program at GMU.  His area of research is atmospheric composition and air quality modeling, more specifically focusing on air-surface exchange processes including atmosphere-biosphere interactions.  He works closely within the Chemical Modeling and Emissions group at ARL for research and development of the next-generation atmospheric composition prediction models at NOAA.

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