Abstract
A 5year (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.
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Eder, B., Appel, W., Pierce, T. (2011). On the Use of Principal Component and Spectral Density Analyses to Evaluate the Community Multiscale Air Quality (CMAQ) Model. In: Steyn, D., Trini Castelli, S. (eds) Air Pollution Modeling and its Application XXI. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1359-8_74
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DOI: https://doi.org/10.1007/978-94-007-1359-8_74
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