A Middle Atmospheric Chemistry-Climate Model MACO: Model Description and Simulation Evaluation

Abstract. Developing chemistry-climate models (CCMs) is crucial for advancing our understanding of middle atmosphere and improving whole-atmosphere weather and climate forecasting. Chemical processes play a critical role in shaping the middle atmospheric thermodynamic and dynamic structures. Therefore, CCMs require explicit representation of atmospheric chemistry and must be fully coupled to physical climate components. To this end, a new middle atmosphere chemistry module based on the atmospheric general circulation model ECHAM6 has been developed, ultimately establishing a fully coupled chemistry-radiation-dynamics CCM named MACO (Middle Atmospheric Chemistry with Ozone). This paper introduces the model framework and systematically evaluates its performance through a historical simulation (1970–2014), validated vs. reanalysis and satellite datasets. MACO demonstrates robust capabilities in simulating the key dynamical and chemical processes in the middle atmosphere. The model reasonably reproduces the climatology distributions of major stratospheric chemical constituents, effectively captures the annual cycle of the Antarctic ozone hole and Arctic ozone depletion, and realistically simulates the historical evolution of stratospheric ozone and HCl. However, significant biases persist in the upper stratosphere and mesosphere. Analysis identifies two primary bias sources. First, dynamical biases, including a weak polar night jet and polar vortex, lead to a pronounced warm bias near the polar stratopause. This is likely linked to the model’s moderate vertical resolution, which impacts the representation of atmospheric wave dynamics. Second, biases in the chemical scheme primarily manifest as an overestimation of CH₄ and N₂O and an underestimation of H₂O and O₃ in the upper stratosphere and mesosphere. These chemical biases are partly attributed to the omission of photolysis below 177 nm, particularly the Lyman-α line. Future model development will prioritize enhancing vertical resolution and refining the photolysis scheme to address these identified shortcomings.