Abstract
It is often necessary to decide which air quality model is “best” by comparison with observations at a specific site. Usually this decision is connected to a regulatory procedure, but it may also be part of a research and development program. The purpose of this project is to develop and test a simplified statistical procedure for determining whether one model is significantly better than another. In 1980, the American Meteorological Society and the Environmental Protection Agency sponsored a workshop in which a comprehensive set of performance measures for air quality models was outlined (Fox 1981, EPA 1981). These measures included several methods of determining model bias, error, and correlation. However, application of the full set of performance measures results in many tens of pages of tables of statistical measures (Murray et al. 1982). The full set of AMS/EPA performance measures is redundant, and it is difficult for anyone to assimilate all the figures in order to decide which model is best.
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© 1986 Springer Science+Business Media New York
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Hanna, S.R., Heinold, D.W. (1986). Simple Statistical Methods for Comparative Evaluation of Air Quality Models. In: De Wispelaere, C., Schiermeier, F.A., Gillani, N.V. (eds) Air Pollution Modeling and Its Application V. NATO · Challenges of Modern Society, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9125-9_29
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DOI: https://doi.org/10.1007/978-1-4757-9125-9_29
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