Chemistry transport models (CTMs) are essential tools for characterizing and predicting the role of atmospheric composition and chemistry in Earth’s climate system. This study demonstrates the use of airborne in situ observations to diagnose the representation of atmospheric composition by global CTMs. Process-based diagnostics are developed which minimize the spatial and temporal sampling differences between airborne in situ measurements and CTM grid points. The developed diagnostics make use of dynamical and chemical vertical coordinates as a means of highlighting areas where focused model improvement is needed. The chosen process is the chemical impact of the Asian summer monsoon (ASM), where deep convection serves a unique pathway for rapid transport of surface emissions and pollutants to the stratosphere. Two global CTM configurations are examined for their representation of the ASM upper troposphere and lower stratosphere (UTLS), using airborne observations collected over south Asia. Application of the developed diagnostics to the CTMs reveals the limitations of zonally-averaged surface boundary conditions for species with sufficiently short tropospheric lifetimes, and that species whose stratospheric loss rates are dominated by photolysis have excellent agreement compared to that observed. Overall, the diagnostics demonstrate the strength of airborne observations toward improving model predictions, and highlight the utility of highly-resolved CTMs to improve the understanding of reactive transport of anthropogenic pollutants to the stratosphere.