Atmosphere (Jul 2023)

Implementing and Improving CBMZ-MAM3 Chemistry and Aerosol Modules in the Regional Climate Model WRF-CAM5: An Evaluation over the Western US and Eastern North Pacific

  • Xiaokang Wu,
  • Yan Feng,
  • Cenlin He,
  • Rajesh Kumar,
  • Cui Ge,
  • David Painemal,
  • Yangyang Xu

DOI
https://doi.org/10.3390/atmos14071122
Journal volume & issue
Vol. 14, no. 7
p. 1122

Abstract

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The representation of aerosols in climate–chemistry models is important for air quality and climate change research, but it can require significant computational resources. The objective of this study was to improve the representation of aerosols in climate–chemistry models, specifically in the carbon bond mechanism, version Z (CBMZ), and modal aerosol modules with three lognormal modes (MAM3) in the WRF-CAM5 model. The study aimed to enhance the model’s chemistry capabilities by incorporating biomass burning emissions, establishing a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs), and evaluating its performance against observational benchmarks. The results of the study demonstrated the effectiveness of the enhanced chemistry capabilities in the WRF-CAM5 model. Six simulations were conducted over the western U.S. and northeastern Pacific region, comparing the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The findings revealed a significant reduction in root-mean-square errors (RMSE) for surface concentrations of black carbon (BC) and organic carbon (OC). Specifically, the model exhibited a 31% reduction in RMSE for BC concentrations and a 58% reduction in RMSE for OC concentrations. These outcomes underscored the importance of accurate aerosol representation in climate–chemistry models and emphasized the potential for improving simulation accuracy and reducing errors through the incorporation of enhanced chemistry modules in such models.

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