| 12 Aug 2026
Development and Evaluation of Online Gas-Phase Chemistry in the Global Variable-Resolution Atmospheric Model iAMAS (v2.5.1): Resolution-Dependent Surface Ozone over North China
Abstract. Atmospheric composition is governed by multiscale processes spanning global transport to local chemistry. Simultaneously capturing these scales is essential, yet conventional modeling trades global coverage for regional detail restricted by artificial boundaries. Global variable-resolution (VR) modeling provides a unified alternative, yet online gas-phase chemistry within nonhydrostatic VR frameworks remains limited, and how mesh refinement alters coupled physical–chemical responses is not fully understood. Here, we develop and evaluate an online gas-phase chemistry framework in the VR model iAMAS (v2.5.1). Operating on a unified unstructured mesh without lateral boundaries, the modular framework couples KPP-generated SAPRC-99 tropospheric chemistry, Linoz stratospheric ozone, Fast-J photolysis, emissions, transport, and deposition. Global baseline simulations at ~60 km resolution (U60km) for July 2019 validate large-scale tracer distributions (O3, NO2, HCHO, CO) and surface ozone diurnal cycles across China. Regionally refined simulations at ~4 km over North China (V4km) demonstrate how online VR chemistry resolves cross-scale physical–chemical coupling over complex terrain. V4km recovers the observed ridge-high/valley-low nighttime ozone pattern, reversing spatial correlation from R=−0.40(U60km) to R=+0.46 by resolving slope circulations and heterogeneous NOx emissions within a shallow nocturnal boundary layer. Refinement also reorganizes urban–rural and day–night ozone responses: higher urban NOx suppresses daytime ozone peak under VOC-limited conditions, whereas reduced coarse-grid NOx dilution weakens rural nighttime titration and sustains higher ozone. These results demonstrate that mesh refinement in a global VR model alters the coupled dynamical–chemical state rather than merely sharpening concentration gradients, establishing iAMAS as a modular platform for seamless global-to-regional atmospheric-composition studies.
