Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling

Area of Science:

• Atmospheric Science
• Air Quality Modeling
• Computational Science

Background:

• The Community Multiscale Air Quality (CMAQ) model is a long-standing tool for air quality research and regulation.
• Previous coupled models like WRF-CMAQ improved aerosol-meteorology interactions but were limited in domain scope.
• Limited-area models restrict the scale of air quality simulations and their global applicability.

Purpose of the Study:

• To develop and evaluate a new global-scale coupled atmospheric and air quality model, MPAS-CMAQ.
• To extend air quality modeling capabilities to a global domain using the Model for Prediction Across Scales - Atmosphere (MPAS-A).
• To assess the performance of MPAS-CMAQ for simulating key air pollutants like ozone and PM2.5.

Main Methods:

• Coupling the Model for Prediction Across Scales - Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) model.
• Developing the Advanced Air Quality Modeling System (AAQMS) to facilitate the configuration of CMAQ, WRF-CMAQ, and MPAS-CMAQ.
• Conducting simulations using two global configurations: a 120 km uniform mesh and a 92-25 km variable mesh over North America.

Main Results:

• The MPAS-CMAQ model demonstrated good computational scalability.
• Simulations for 2014-2016 (uniform mesh) and Jan/Jul 2016 (variable mesh) showed reasonable performance for ozone and PM2.5 against observations.
• The variable mesh configuration exhibited a winter-time high bias in surface ozone over the US, but reduced bias in summer compared to the uniform mesh.

Conclusions:

• The MPAS-CMAQ global coupled model is a viable extension for large-scale air quality assessments.
• The system shows reasonable skill in reproducing observed ozone and PM2.5, including daily variability.
• Further refinement of the variable mesh configuration may be needed to address regional biases in wintertime ozone.