Conclusions
We have demonstrated that the choice of modules in transport processes interacts with other model configurations. Comparison with observations, especially with secondary species such as O3, may not be sufficient to allow selection of the best modules. For example, we have compared first layer ozone concentrations with those from EPA’s AIRS database. Figure 5 shows that the configuration F36 has least bias compared with observations. However, this alone is not sufficient to determine which transport algorithms are superior. Factors such as the representation of emissions inputs, the treatment of plume-in-grid, the use of different chemical mechanisms,the selection of different chemical solvers, and the model grid structure (i.e., vertical and horizontal resolutions and domain size), all contribute to different model results. Establishment of the best configuration of science process modules in a comprehensive AQM requires balanced representations of transport algorithms with other physical and chemical processes.
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Byun, D.W., Pleim, J.E. (2004). Sensitivity of Ozone and Aerosol Predictions to the Transport Algorithms in the Models-3 Community Multi-Scale Air Quality (CMAQ) Modeling System. In: Gryning, SE., Schiermeier, F.A. (eds) Air Pollution Modeling and Its Application XIV. Springer, Boston, MA. https://doi.org/10.1007/0-306-47460-3_21
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DOI: https://doi.org/10.1007/0-306-47460-3_21
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