A proof-of-concept for linking the global meteorological model, MPAS-A with the air quality model, CMAQ
Citation:
Wong, David-C, Jon Pleim, R. Bullock, R. Gilliam, J. Herwehe, C. Hogrefe, AND G. Pouliot. A proof-of-concept for linking the global meteorological model, MPAS-A with the air quality model, CMAQ. ITM 2018 - 36 th International Technical Meeting on Air Pollution Modelling and its Application, Ottawa, CANADA, May 14 - 18, 2018.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
Researchers who perform air quality modeling studies usually do so on a regional scale. Typically, the boundary conditions are generated by another model which might have a different chemical mechanism, spatial resolution, and/or map projection. Hence, a necessary conversion/interpolation takes place which introduces additional error. In a broader sense, air pollution is a global issue, thus, limited area modeling on the regional scale is not well suited to represent long-range transport from key source regions in other parts of the world. We have developed a prototype system to link the Model for Prediction Across Scales - Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) model to address these shortcomings. Pollutant transport is conducted within MPAS-A, rather than in CMAQ, to provide consistency with the meteorological processes. A coupler has been constructed to facilitate data exchange between the two models. Initial test simulations show reasonable results when compared with observational data
