An overview of the National Oceanic and Atmospheric Administration’s (NOAA) current operational Smoke Forecasting System (SFS) is presented. This system is intended as guidance to air quality forecasters and the public for fine particulate matter (≤2.5 μm) emitted from large wildfires and agricultural burning, which can elevate particulate concentrations to unhealthful levels. The SFS uses National Environmental Satellite, Data, and Information Service (NESDIS) Hazard Mapping System (HMS), which is based on satellite imagery, to establish the locations and extents of the fires. The particulate matter emission rate is computed using the emission processing portion of the U.S. Forest Service’s BlueSky Framework, which includes a fuel-type database, as well as consumption and emissions models. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to calculate the transport, dispersion, and deposition of the emitted particulate matter. The model evaluation is carried out by comparing predicted smoke levels with actual smoke detected from satellites by the HMS and the Geostationary Operational Environmental Satellite (GOES) Aerosol/Smoke Product. This overlap is expressed as the figure of merit in space (FMS), the intersection over the union of the observed and calculated smoke plumes. Results are presented for the 2007 fire season (September 2006–November 2007). While the highest FMS scores for individual events approach 60%, average values for the 1 and 5 μg m−3 contours for the analysis period were 8.3% and 11.6%, respectively. FMS scores for the forecast period were lower by about 25% due, in part, to the inability to forecast new fires. The HMS plumes tend to be smaller than the corresponding predictions during the winter months, suggesting that excessive emissions predicted for the smaller fires resulted in an overprediction in the smoke area.
NOAA and the U.S. Environmental Protection Agency (EPA) have developed a national air quality forecasting (AQF) system that is based on numerical models for meteorology, emissions, and chemistry. The AQF system generates gridded model forecasts of ground-level ozone (O3) that can help air quality forecasters to predict and alert the public of the onset, severity, and duration of poor air quality conditions. Although AQF efforts have existed in metropolitan centers for many years, this AQF system provides a national numerical guidance product and the first-ever air quality forecasts for many (predominantly rural) areas of the United States. The AQF system is currently based on NCEP’s Eta Model and the EPA’s Community Multiscale Air Quality (CMAQ) modeling system. The AQF system, which was implemented into operations at the National Weather Service in September of 2004, currently generates twice-daily forecasts of O3 for the northeastern United States at 12-km horizontal grid spacing. Preoperational testing to support the 2003 and 2004 O3 forecast seasons showed that the AQF system provided valuable guidance that could be used in the air quality forecast process. The AQF system will be expanded over the next several years to include a nationwide domain, a capability for forecasting fine particle pollution, and a longer forecast period. State and local agencies will now issue air quality forecasts that are based, in part, on guidance from the AQF system. This note describes the process and software components used to link the Eta Model and CMAQ for the national AQF system, discusses several technical and logistical issues that were considered, and provides examples of O3 forecasts from the AQF system.
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