National Air Quality Forecast Capability: Predictions of Fine Particulate Matter

NOAA’s National Air Quality Forecast Capability (NAQFC) has been providing operational air quality predictions for ozone and wildfire smoke over the United States (U.S.) and predictions of airborne dust over the contiguous 48 states at http://airquality.weather.gov. Predictions of fine particulate matter (PM2.5) are provided publicly since February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast model (NAM).  Smoke and dust predictions are produced by NOAA’s HYSPLIT model. Verification of NAQFC predictions uses AIRNow compilation of surface measurements for ozone and PM2.5. Retrievals of smoke from GOES satellites are used for verification of smoke predictions. Retrievals of dust from MODIS are used for verification of dust predictions.

Recent updates to NAQFC predictions have focused on public release of fine particulate matter PM2.5 predictions from the NAM-CMAQ modeling system and bias-corrected PM2.5 predictions using an analog ensemble post-processing algorithm.  Some of previous seasonal biases in PM2.5 prediction were reduced by suppression of soil emissions in wintertime and the addition of intermittent wildfire smoke and dust emissions. Nevertheless, biases in the seasonal and diurnal cycles of PM2.5 remained substantial, so a new bias correction procedure based on an analog ensemble approach was introduced. The upgrade in February 2016 included addition of dynamic lateral boundary conditions from NOAA’s global dust predictions and an increased number of model layers.

Current NAQFC efforts are focused on updating CMAQ model to version 5.0.2 and improving PM2.5 predictions. Testing includes wildfire smoke emissions from a newer version of USFS BlueSky system and a new configuration of NAQFC CMAQ-system to re-run previous 24 hours, to coincide with observations of wildfires from satellites, in order to better represent wildfire emissions prior to beginning 48 hour predictions. Anthropogenic emissions updates are focused on NOx emissions to capture recent observed trends.  Bias correction for PM2.5 is being refined to better capture day-to-day variability in PM2.5 and to improve corrections for infrequent events.  We will present an overview of recent updates and evaluation of predictions within a changing emissions environment and tightening air quality standards, which necessitate improved modeling and linkages across scales.