Abstract

Many chemical processes depend non-linearly on temperature. Gravity-wave-induced temperature perturbations have been shown to affect atmospheric chemistry, but accounting for this process in chemistry-climate models has been a challenge because many gravity waves have scales smaller than the typi... Show moreMany chemical processes depend non-linearly on temperature. Gravity-wave-induced temperature perturbations have been shown to affect atmospheric chemistry, but accounting for this process in chemistry-climate models has been a challenge because many gravity waves have scales smaller than the typical model resolution. Here, we present a method to account for subgrid-scale orographic gravity-wave-induced temperature perturbations on the global scale for the Whole Atmosphere Community Climate Model. Temperature perturbation amplitudes (T)over cap> consistent with the model's subgrid-scale gravity wave parameterization are derived and then used as a sinusoidal temperature perturbation in the model's chemistry solver. Because of limitations in the parameterization, we explore scaling of (T)over cap> between 0.6 and 1 based on comparisons to altitude-dependent (T) over cap distributions of satellite and reanalysis data, where we discuss uncertainties. We probe the impact on the chemistry from the grid-point to global scales, and show that the parameterization is able to represent mountain wave events as reported by previous literature. The gravity waves for example, lead to increased surface area densities of stratospheric aerosols. This increases chlorine activation, with impacts on the associated chemical composition. We obtain large local changes in some chemical species (e.g., active chlorine, NOx, N2O5) which are likely to be important for comparisons to airborne or satellite observations, but the changes to ozone loss are more modest. This approach enables the chemistry-climate modeling community to account for subgrid-scale gravity wave temperature perturbations interactively, consistent with the internal parameterizations and are expected to yield more realistic interactions and better representation of the chemistry. Show less