NOAA's air quality forecasting capabilities have been adapted, developed, tested and implemented into operations, in partnership with the US EPA and US Forest Service. Daewon Byun, one of the original developers of Community Multiscale Air Quality (CMAQ) model, was involved in reviews from the earliest initial operation capabilities, through 50-state deployment of ozone prediction capabilities. NOAA has produced forecast guidance for surface ozone concentrations and smoke concentrations throughout the lower 48 states (CONUS) since 2007. Ozone and smoke forecast guidance have been expanded to Alaska (AK) and Hawaii (HI) by 2010. Dr. Byun's group at NOAA's Air Resources Laboratory developed and contributed to testing of the expansion of ozone guidance to AK and HI.

NOAA's hour by hour forecast guidance at 12 km grid resolution out to 48 hours shows when and where predicted values of ozone and smoke are expected to reach harmful levels in cities, suburbs, and rural areas. Operational forecast guidance is available on the web at http://www.weather.gov/aq/, and experimental guidance at http://www.weather/gov/aq-expr. Ozone forecasts are produced with a linked numerical prediction system run operationally at the National Centers for Environmental Prediction (NCEP) supercomputing facility: North American Mesoscale (NAM) weather predictions are used in the CMAQ model. The next upgrade of operational NAM, to the Non-hydrostatic Mesoscale Model on Arakawa B grid (NMM-B), is planned in 2011. Therefore, NOAA modified the coupling of NAM to CMAQ: first with a minor adaptation of CMAQ's vertical structure to that of NMM-B, to be followed by a new version of CMAQ on the rotated longitude-latitude NMM-B grid. Dr. Byun envisioned and initiated the effort in reformulating CMAQ on the B-grid to facilitate tighter horizontal coupling between the meteorological and air quality models in order to improve fidelity of air quality predictions at higher horizontal resolution.

NWS is developing capabilities for quantitative predictions of fine particles (PM2.5). Challenges that are being addressed include: (1) Specification of intermittent sources. Predictions of PM2.5 from inventoried emissions show substantial seasonal biases that are consistent with missing intermittent sources in the summertime. Dr. Byun's group has worked on including real-time emissions of smoke from wildfires and airborne dust in CMAQ. This work builds upon operational standalone predictions of smoke from wildfires. Standalone experimental testing of dust predictions over CONUS relies on source regions with dust-emissions potential that are estimated from climatology of satellite-observed dust events during 2003-2006 and real time information on surface moisture. When surface winds exceed entrainment thresholds dust is emitted and transported by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by NAM meteorology to predict surface and column dust concentrations. Long-range transport of dust impacting CONUS domain is being incorporated through boundary-conditions to help capture events like springtime Asian dust transport and summertime trans-Atlantic transport of Saharan dust. (2) Chemical mechanisms for inventory-based predictions. More comprehensive chemical mechanisms are needed to account for reactive chemical transport and secondary formation of aerosols from pollutants. Updated chemical mechanism CB05 in CMAQ has been tested, leading to higher ozone biases. Dr. Byun's group proposed modifications to dry deposition, lateral boundary conditions and limiting the minimum planetary boundary layer height, which reduced these ozone biases.

Dr. Byun's contributions, advice and leadership have helped shape the development and expansion of NOAA's air quality predictions and his vision will help guide our future efforts.