Development of the next-generation air quality prediction system in the Unified Forecast System framework: Enhancing predictability of wildfire air quality impacts

Details

• Journal Title:
  Bulletin of the American Meteorological Society
• Personal Author:
  Huang, Jianping ; Stajner, Ivanka ; Montuoro, Raffaele ; Yang, Fanglin ; Wang, Kai ; Huang, Ho-Chun ; Jeon, Chan-Hoo ; Curtis, Brian ; McQueen, Jeff ; Liu, Haixia ; Baker, Barry ; Tong, Daniel ; Tang, Youhua ; Campbell, Patrick ; Grell, Georg ; Frost, Gregory ; Schwantes, Rebecca ; Wang, Siyuan ; Kondragunta, Shobha ; Li, Fangjun ; Jung, Youngsun
• NOAA Program & Office:
  NESDIS (National Environmental Satellite, Data, and Information Service) ; NWS (National Weather Service) ; OAR (Oceanic and Atmospheric Research) ; ARL (Air Resources Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; CSL (Chemical Sciences Laboratory) ; EMC (Environmental Modelling Center) ; GSL (Global Systems Laboratory) ; NCEP (National Centers for Environmental Prediction) ; OSTI (Office of Science and Technology Integration) ; STAR (Center for Satellite Applications and Research) ; WPO (Weather Program Office)
• Description:
  The National Oceanic and Atmospheric Administration (NOAA) has developed an advanced regional air quality prediction system (AQPS) within the Unified Forecast System (UFS) framework to improve representations of wildfire emissions and their impacts on air quality predictions. This innovative system integrates the Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) model as a column chemistry model with the UFS-based atmospheric model, operating in an online mode. The calculation of wildfire gas and particulate emissions relies on satellite-derived fire products, high-resolution Regional Hourly Advanced Baseline Imager (ABI) and Visible Infrared Imaging Radiometer Suite (VIIRS) Emissions (RAVE). A period in June and July 2023 with Quebec Canadian wildfires, which severely impacted air quality in the United States (US), was chosen as a case study to assess the predictive capability of the UFS-AQM system. The UFS-AQM predictions of fine particulate (PM2.5) and ozone (O3) were evaluated against AirNow observations from June 15 to July 14, 2023. The results indicate a substantial improvement in PM2.5 predictions when compared to the previous operational forecast. Meanwhile, the system demonstrates a strong ability of predicting O3 exceedance events during the dissipation phase of the wildfire. Furthermore, the online system shows more realistic predictions of aerosol optical depth (AOD) as compared to the previous operational forecast and satellite retrieval data. Finally, this study outlines a plan for further advancing a comprehensive regional AQPS at NOAA.
• Source:
  Bulletin of the American Meteorological Society (2025)
• DOI:
  https://doi.org/10.1175/BAMS-D-23-0053.1
• ISSN:
  0003-0007 ; 1520-0477
• Format:
  pdf
• Publisher:
  American Meteorological Society
• Document Type:
  Journal Article
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:3afa7e06d9094c8ec665848741e0d1e8545dbc42549de386f34f38b27b5de69d1970674f647f46d9e12c7ad6b444d2eb6ea764d7338033ed7d5f05b8bf8ac3c6
• Download URL:
  https://repository.library.noaa.gov/view/noaa/71508/noaa_71508_DS1.pdf
• File Type:
  [PDF - 2.44 MB ]