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www.geosci-model-dev-discuss.net/2/1375/2009/
doi:10.5194/gmdd-2-1375-2009
© Author(s) 2009. This work is distributed
under the Creative Commons Attribution 3.0 License.
Assessment of bias-adjusted PM2.5 air quality forecasts over the continental United States during 2007
1Computer Science Corporation, Research Triangle Park, 79 T.W. Alexander Drive, NC 27709, USA
2Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC, USA
Abstract. To develop fine particular matter (PM2.5) air quality forecasts, a National Air Quality Forecast Capability (NAQFC) system, which linked NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, was deployed in the developmental mode over the continental United States during 2007. This study investigates the operational use of a bias-adjustment technique called the Kalman Filter Predictor approach for improving the accuracy of the PM2.5 forecasts at monitoring locations. The Kalman Filter Predictor bias-adjustment technique is a recursive algorithm designed to optimally estimate bias-adjustment terms using the information extracted from previous measurements and forecasts.
The bias-adjustment technique is found to improve PM2.5 forecasts (i.e. reduced errors and increased correlation coefficients) for the entire year at almost all locations. The NAQFC tends to overestimate PM2.5 during the cool season and underestimate during the warm season in the eastern part of the continental US domain, but the opposite is true for the pacific coast. In the Rocky Mountain region, the NAQFC system overestimates PM2.5 for the whole year. The bias-adjustment forecasts can quickly (after 2–3 days' lag) adjust to reflect the transition from one regime to the other. The modest computational requirements and systematical improvements in forecast results across all seasons suggest that this technique can be easily adapted to perform bias-adjustment for real-time PM2.5 air quality forecasts.
Discussion Paper (PDF, 2609 KB) Interactive Discussion (Closed, 4 Comments) Final Revised Paper (GMD)
Citation: Kang, D., Mathur, R., and Trivikrama Rao, S.: Assessment of bias-adjusted PM2.5 air quality forecasts over the continental United States during 2007, Geosci. Model Dev. Discuss., 2, 1375-1406, doi:10.5194/gmdd-2-1375-2009, 2009. Bibtex EndNote Reference Manager XML
