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. As a candidate for the next-generation National Air Quality ForecastCapability (NAQFC), the meteorological forecast from the Global Forecast Systemwith the new Finite Volume Cube-Sphere dynamical core (GFS–FV3) will beapplied to drive the chemical evolution of gases and particles described bythe Community Multiscale Air Quality modeling system. CMAQv5.0.2, ahistorical version of CMAQ, has been coupled with the North American MesoscaleForecast System (NAM) model in the current operational NAQFC. An experimentalversion of the NAQFC based on the offline-coupled GFS–FV3 version 15 withCMAQv5.0.2 modeling system (GFSv15–CMAQv5.0.2) has been developed by theNational Oceanic and Atmospheric Administration (NOAA) to provide real-timeair quality forecasts over the contiguous United States (CONUS) since 2018. Inthis work, comprehensive region-specific, time-specific, and categoricalevaluations are conducted for meteorological and chemical forecasts from theoffline-coupled GFSv15–CMAQv5.0.2 for the year 2019. The forecast system showsgood overall performance in forecasting meteorological variables with theannual mean biases of −0.2 ∘C for temperature at 2 m,0.4 % for relative humidity at 2 m, and 0.4 m s−1 forwind speed at 10 m compared to the METeorological Aerodrome Reports(METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts,particularly in spring. Although the monthly accumulated precipitationforecasts show generally consistent spatial distributions with those from theremote-sensing and ensemble datasets, moderate-to-large biases exist in hourlyprecipitation forecasts compared to the Clean Air Status and Trends Network(CASTNET) and METAR. While the forecast system performs well in forecastingozone (O3) throughout the year and fine particles with a diameter of2.5 µm or less (PM2.5) for warm months (May–September),it significantly overpredicts annual mean concentrations ofPM2.5. This is due mainly to the high predicted concentrations offine fugitive and coarse-mode particle components. Underpredictions in thesoutheastern US and California during summer are attributed to missingsources and mechanisms of secondary organic aerosol formation from biogenicvolatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This workdemonstrates the ability of FV3-based GFS in driving the air qualityforecasting. It identifies possible underlying causes for systematic region-and time-specific model biases, which will provide a scientific basis forfurther development of the next-generation NAQFC.

geoscientific model development

Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States