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On the Use of Principal Component and Spectral Density Analysis to Evaluate the Community Multiscale Air Quality (CMAQ) Model
Citation:
EDER, B. K., W. APPEL, AND T. E. PIERCE. On the Use of Principal Component and Spectral Density Analysis to Evaluate the Community Multiscale Air Quality (CMAQ) Model. XXI, Chapter 5, NATO/ITM Air Pollution Modeling and Its Application. Springer Netherlands, , Netherlands, Series C:439-445, (2011).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
A 5 year (2002-2006) simulation of CMAQ covering the eastern United States is evaluated using principle component analysis in order to identify and characterize statistically significant patterns of model bias. Such analysis is useful in that in can identify areas of poor model performance across space and time; facilitate understanding of the probable mechanisms (emissions, meteorological, and/or chemical) responsible for said poor performance; and designate specific locations that can be used in providing in depth diagnostic analysis.