EGU21-13587
https://doi.org/10.5194/egusphere-egu21-13587
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Near real-time air quality forecasts using the NASA GEOS model

K. Emma Knowland1, Christoph Keller2,3, Krzysztof Wargan3,4, Brad Weir2,3, Pamela Wales2,3, Lesley Ott3, and Steven Pawson3
K. Emma Knowland et al.
  • 1USRA/GESTAR, NASA/GSFC GMAO, Greenbelt, United States of America (k.e.knowland@nasa.gov)
  • 2Universities Space Research Association (USRA), Columbia, Maryland, USA
  • 3NASA Goddard Space Flight Center (GSFC), Global Modeling Assimilation Office (GMAO), Greenbelt, Maryland, USA
  • 4Science Systems and Applications, Inc (SSAI), Lanham, Maryland, USA

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke. The assimilation system is being expanded to include chemically reactive trace gases. We discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions, notably incorporating new observations (TROPOMI, geostationary satellites) and machine learning techniques. We show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

How to cite: Knowland, K. E., Keller, C., Wargan, K., Weir, B., Wales, P., Ott, L., and Pawson, S.: Near real-time air quality forecasts using the NASA GEOS model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13587, https://doi.org/10.5194/egusphere-egu21-13587, 2021.

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