Using the C3M Satellite Data Product to Evaluate and Constrain the Cloud Fields in the HadGEM3-UKCA Model with an Aim to Enhance Understanding of the Effects of Clouds on Atmospheric Composition via Photolysis

What drives the variability of trace gases in the troposphere is not well understood, as is the role of clouds in modulating this variability via radiative, transport, deposition, heterogeneous chemistry, and lightning effects that are associated with them. Accurately simulating tropospheric composition and its variability is of utmost importance as both could have a significant effect on the region's temperature and circulation, as well as on surface climate and the amount of UV radiation in the troposphere. In this presentation, we will examine how clouds can influence tropospheric and lower stratospheric composition through modifying solar radiation leading to changes in the local actinic flux and subsequently to photolysis, a key driver of chemistry. We will utilize C3M (a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center to evaluate the cloud fields and their vertical distribution in the HadGEM3-UKCA model developed by the Natural Environment Research Council (NERC, UK) and the Met Office. This evaluation will involve 1) comparing the effective cloud optical depth (ECOD) as calculated from C3M and the model using the approximate random overlap method, 2) applying 3-D scaling factors from C3M to the model's ECOD and analyzing the changes this makes to the model's cloud fields, and 3) running the scaled model and analyzing the impacts of this cloud field adjustment on the model's estimates of photolysis rates and key tropospheric oxidants such as ozone and OH.