Quantifying and addressing the uncertainties in tropospheric ozone and OH in a global chemistry transport model

The major physical and chemical processes governing the abundance of atmospheric oxidants such as ozone and hydroxyl radicals (OH) are largely understood, but quantitative assessment of their importance in different environments remains challenging. Atmospheric chemistry transport models allow exploration of these processes on a global scale, but weaknesses in process representation in these models introduces uncertainty, and model intercomparisons show considerable diversity even in representing current atmospheric composition. Formal constraint of models with atmospheric observations is needed to provide more critical insight into the causes of model weaknesses. In this study we perform a global sensitivity analysis on a chemistry transport model using Gaussian process emulation and identify the processes contributing most to uncertainty in tropospheric ozone and OH. We then explore the use of atmospheric measurements to calibrate the model and identify weaknesses in process representation and understanding. We find that the largest uncertainties are associated with photochemical kinetic data and with factors governing photolysis rates and surface deposition. Calibration constrains the uncertainty in key processes, improving comparisons with observations and informing model development, but we show that it is also valuable in identifying structural errors in models. We show that surface ozone measurements alone provide insufficient constraint, and we highlight the importance of applying a broad range of different observational metrics. While this study is exploratory in nature, focussing on a limited number of constraints, we clearly demonstrate the value of rigorous calibration for providing important new insight into key processes and their representation in atmospheric models.