Atmospheric Composition

Team Leads:

Barry Baker 
Air Resources Laboratory,
(NOAA/OAR), College Park, MD

Fanglin Yang
Environmental Modeling Center,
NCEP, NWS College Park, MD

In 2020, the Atmospheric Composition team successfully implemented substantially improved 5-day aerosol prediction capability in the GEFSv12-Aerosol member, demonstrating a successful R2O transition. Since that time, the 2016 National Academies Study on the Future of Atmospheric Chemistry Research identified a priority to “Advance the integration of atmospheric chemistry within weather and climate models to improve forecasting in a changing Earth system”. Furthermore, the European Center for Medium-Range Weather Forecasts (ECMWF) demonstrated that incorporating aerosols in their model improves prediction of weather for weeks 3 and 4 (Benedetti and Vitart, 2018), motivating the goals proposed here.

Pursuant to these priorities, the UFS R2O is developing an improved representation of atmospheric aerosols in the MRW/S2S system targeted for future global subseasonal prediction applications. Potential use of predicted aerosol in atmospheric physics, starting with aerosol feedback on radiation, is being coordinated with the Physics team. Assimilation of aerosol optical depth (AOD) to constrain aerosols and potential use of aerosols in radiance assimilation is being coordinated with the Data Assimilation (DA) team.The 5-year vision for UFS includes CAM-resolution inline air quality predictions for the U.S. and atmospheric composition prediction beyond aerosols globally, including aerosol feedback on weather and S2S prediction.

The key goals for the atmospheric composition effort are to improve the representation of global aerosol spatial/temporal distributions and to include aerosol interactions with radiation on S2S timescales for potential future NCEP operations, contingent on resource availability. - The team is also working on developing a prototype of global chemistry and aerosol prediction system that is both scientifically advanced for research and computationally efficient for potential future NCEP operations.

  • Contribute to development of a 6-way coupled system for UFS S2S applications, focusing on the representation of aerosols and aerosol-radiation interactions.
  • Improved aerosol process descriptions; realistic aerosol spatial distributions and temporal variability; realistic representation of aerosol radiative impacts on meteorology.
  • Improved dust predictions.
  • Improved biomass burning emission climatology;  Blended biomass burning emissions prediction with climatological emissions.
  • Bias corrected aerosol optical depth (AOD) observations for data assimilation (DA)
  • Improved aerosol speciation and vertical profiles for AOD DA
  • 3D-Variational (3DVar) AOD DA capability
  • Ensemble AOD DA capability
  • Evaluated interactive prognostic aerosols
  • Detailed metrics on meteorological impacts of including prognostic aerosols that interact with radiation
  • A prototype of a global chemistry and aerosol prediction system.