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Abstract A new configuration of the Community Earth System Model (CESM)/Community Atmosphere Model with full chemistry (CAM‐chem) supporting the capability of horizontal mesh refinement through the use of the spectral element (SE) dynamical core is developed and called CESM/CAM‐chem‐SE. Horizontal mesh refinement in CESM/CAM‐chem‐SE is unique and novel in that pollutants such as ozone are accurately represented at human exposure relevant scales while also directly including global feedbacks. CESM/CAM‐chem‐SE with mesh refinement down to ∼14 km over the conterminous US (CONUS) is the beginning of the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). Here, MUSICAv0 is evaluated and used to better understand how horizontal resolution and chemical complexity impact ozone and ozone precursors over CONUS as compared to measurements from five aircraft campaigns, which occurred in 2013. This field campaign analysis demonstrates the importance of using finer horizontal resolution to accurately simulate ozone precursors such as nitrogen oxides and carbon monoxide. In general, the impact of using more complex chemistry on ozone and other oxidation products is more pronounced when using finer horizontal resolution where a larger number of chemical regimes are resolved. Large model biases for ozone near the surface remain in the Southeast US as compared to the aircraft observations even with updated chemistry and finer horizontal resolution. This suggests a need for adding the capability of replacing sections of global emission inventories with regional inventories, increasing the vertical resolution in the planetary boundary layer, and reducing model biases in meteorological variables such as temperature and clouds.

Abstract An advanced aerosol treatment, with a focus on semivolatile nitrate formation, is introduced into the Community Atmosphere Model version 5 with interactive chemistry (CAM5‐chem) by coupling the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) with the 7‐mode Modal Aerosol Module (MAM7). An important feature of MOSAIC is dynamic partitioning of all condensable gases to the different fine and coarse mode aerosols, as governed by mode‐resolved thermodynamics and heterogeneous chemical reactions. Applied in the free‐running mode from 1995 to 2005 with prescribed historical climatological conditions, the model simulates global distributions of sulfate, nitrate, and ammonium in good agreement with observations and previous studies. Inclusion of nitrate resulted in ∼10% higher global average accumulation mode number concentrations, indicating enhanced growth of Aitken mode aerosols from nitrate formation. While the simulated accumulation mode nitrate burdens are high over the anthropogenic source regions, the sea‐salt and dust modes respectively constitute about 74% and 17% of the annual global average nitrate burden. Regional clear‐sky shortwave radiative cooling of up to −5 W m−2 due to nitrate is seen, with a much smaller global average cooling of −0.05 W m−2. Significant enhancements in regional cloud condensation nuclei (at 0.1% supersaturation) and cloud droplet number concentrations are also attributed to nitrate, causing an additional global average shortwave cooling of −0.8 W m−2. Taking into consideration of changes in both longwave and shortwave radiation under all‐sky conditions, the net change in the top of the atmosphere radiative fluxes induced by including nitrate aerosol is −0.7 W m−2.

Abstract The global chemistry‐climate model (CAM4‐Chem) overestimates the surface ozone concentration over the conterminous U.S. (CONUS). Reasons for this positive bias include emission, meteorology, chemical mechanism, and solver. In this study, we explore the last possibility by examining the sensitivity to the numerical methods for solving the chemistry equations. A second‐order Rosenbrock (ROS‐2) solver is implemented in CAM4‐Chem to examine its influence on the surface ozone concentration and the computational performance of the chemistry program. Results show that under the same time step size (1800 s), statistically significant reduction of positive bias is achieved by the ROS‐2 solver. The improvement is as large as 5.2 ppb in Eastern U.S. during summer season. The ROS‐2 solver is shown to reduce the positive bias in Europe and Asia as well, indicating the lower surface ozone concentration over the CONUS predicted by the ROS‐2 solver is not a trade‐off consequence with increasing the ozone concentration at other global regions. In addition, by refining the time step size to 180 s, the first‐order implicit solver does not provide statistically significant improvement of surface ozone concentration. It reveals that the better prediction from the ROS‐2 solver is not only due to its accuracy but also due to its suitability for stiff chemistry equations. As an added benefit, the computation cost of the ROS‐2 solver is almost half of first‐order implicit solver. The improved computational efficiency of the ROS‐2 solver is due to the reuse of the Jacobian matrix and lower upper (LU) factorization during its multistage calculation.