Current and Future Advances in NOAA’s Air Quality Predictions from a regional to global perspective

The U.S. National Oceanic and Atmospheric Administration (NOAA) provides operational air quality (AQ) predictions over the United States and global aerosol forecasts.  The current operational model, the National Air Quality Forecast Capability (NAQFC) at NOAA, has undergone a fundamental paradigm shift through its integration into the Earth system modeling Unified Forecast System (UFS) as a coupled component, the Air Quality Modeling component (AQMv7). AQMv7 embeds the U.S. EPA Community Multiscale Air Quality Model (CMAQ) and it  has been operational at the National Weather Service (NWS) since May 2024. The model was also updated with a larger domain size and new emissions, including the development of the NOAA Emission and eXchange Unified System (NEXUS) along with dynamic processes such as using Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 and the FENGSHA dust scheme, and the Regional Advanced Baseline Imager (ABI)-Visible Infrared Imaging Radiometer Suite (VIIRS) Emissions (RAVE) biomass burning algorithm. Operational global aerosol modeling is performed through the NOAA Global Ensemble Forecast System with Aerosols and has been operational in this manner since 2020. Planned future advances include upgrading to a fully coupled atmosphere/land/ocean/sea-ice/wave/aerosols systems developed within the Unified Forecast System (UFS) framework. In its final configuration, the coupled UFS system will consist of: (1)  FV3 dynamical core and CCPP atmospheric physics package using the Noah-MP land model, (2) MOM6 ocean model, (3) CICE6 sea ice model, (4) WAVEWATCH III wave model, and (5) the UFS-Aerosol component, based on NASA’s 2nd generation GOCART aerosol model. GOCART is a simplified chemistry and aerosol component that predicts the major aerosol species including dust, organic and black carbon, sea salt, and sulfate aerosols.  In this presentation we will discuss NOAA’s current and future AQ and air composition forecasting capabilities and the performance of each system.