Improving NOAA NAQFC PM2.5 Predictions with a Bias Correction Approach

AbstractParticulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) is a critical air pollutant with important impacts on human health. It is essential to provide accurate air quality forecasts to alert people to avoid or reduce exposure to high ambient levels of PM2.5. The NOAA National Air Quality Forecasting Capability (NAQFC) provides numerical forecast guidance of surface PM2.5 for the United States. However, the NAQFC forecast guidance for PM2.5 has exhibited substantial seasonal biases, with overpredictions in winter and underpredictions in summer. To reduce these biases, an analog ensemble bias correction approach is being integrated into the NAQFC to improve experimental PM2.5 predictions over the contiguous United States. Bias correction configurations with varying lengths of training periods (i.e., the time period over which searches for weather or air quality scenario analogs are made) and differing ensemble member size are evaluated for July, August, September, and No...