Global and regional impacts of clouds on photolysis rates and atmospheric oxidants

• Main Author: Varma, Sunil
• Format: Text
• Language: unknown
• Published: Imperial College London 2019
• Subjects: Southern Ocean
• Online Access: https://dx.doi.org/10.25560/76533; http://spiral.imperial.ac.uk/handle/10044/1/76533

Clouds influence the composition and chemistry of the atmosphere in several ways but of particular importance is the way they modify solar radiation (a key driver of photochemistry) leading to changes in photolysis rates of several species. This in turn affects the oxidising capacity of the atmosphere, concentrations of greenhouse gases and pollutants, from the surface and well into the stratosphere. This study is the first extensive analysis which quantifies the radiative effect of clouds on photolysis rates and key trace species using a state of the art global chemistry-climate model of the current generation (HadGEM3-UKCA), multi-model output, and extensive observational information. It is also unique in that the effects of replacing the model’s clouds in the photolysis calculation of a global chemistry-climate model with observational clouds is examined, to evaluate and constrain the magnitude and vertical distribution of the clouds globally and regionally and to quantify the influence of the model’s clouds on its simulation of trace gases. Four core simulations are run to explore the effect of 1) removing clouds from the photolysis calculation, 2) replacing the model clouds with observations and 3) ignoring the interannual variability (IAV) of clouds. I demonstrate that the model satisfactorily captures the pattern and magnitude of mean ozone, CO and NO2 observations as well as their IAV. Evaluation of the model’s cloud fields with C3M, a unique cloud data product from NASA, showed that the regions where model performance is most likely to be improved are the tropics, sub-tropics and the Southern Ocean. I show that clouds have the strongest effect on photolysis rates and OH by enhancing these variables above-cloud and reducing them below-cloud with the region most sensitive to clouds being the southern extratropics. Scaling the model’s clouds to observational values boosts this photolytic effect. Through exploring a simulation where clouds are fixed, I examine the impact of clouds on the IAV and trend of photolysis, oxidants and their associated species in recent decades calculated from the model as well as several models taking part in the Chemistry-Climate Model Initiative, allowing further comparison and evaluation of HadGEM3-UKCA, and identification of inter-model diversity. These results show that cloud modification of photolysis IAV drives between 40–95% of JNO2 IAV in the troposphere and lower stratosphere, up to 40% of OH IAV in the lower troposphere and up to 40% of JO1D IAV in the lower and middle troposphere. The cloud effect on ozone, CO and NO2 IAV is weaker but still accounts for up to 10% of the variability of ozone and 20% of the variability of CO and NO2.