Investigating the role of 3D radiative effects in contrail cirrus and ice clouds.

The aviation sector contributes to anthropogenic radiative forcing via impacts from well-known CO2 effects and more uncertain non-CO2 effects. The largest contributor to aviation radiative forcing is one of the non-CO2 effects: induced cirrus cloudiness evolved from contrails generated by aircrafts that persist in the atmosphere. The latest assessment of the impacts of aviation on climate attributes a forcing of 149.1 (90% confidence range: 70, 229) mW/m² to global aviation, including 111.4 (33, 189) mW/m² from contrail cirrus (Lee et al, 2021). Those estimations are based on results from global climate models which use approximations for the description of clouds and radiative transfer, resulting in uncertainties of about 70% in aviation induced cloudiness radiative forcing. As of today, the 3D nature of clouds and the corresponding 3D radiative effects are neglected in climate models, as well as the size and shape of ice crystals in contrails.

In this poster, we present work aimed at improving the estimation of the radiative effect of ice clouds and contrail cirrus by studying its dependence on cloud geometry and size. This work uses a Monte Carlo radiative transfer code that takes into account the full 3D interactions between clouds and radiation (Villefranque et al 2019). Results are compared to a 1D, plane parallel calculation, which is the common assumption in climate models used to estimate radiative forcing.

Results show that 3D effects play a substantial role in the radiative effect of cirrus clouds. The plane parallel calculations always under-estimate cloud radiative effect compared to Monte Carlo calculations when the Sun is at zenith. We discuss the dependence of the results to solar angle. We find that the optical depth of the contrail is not the only driver of its radiative forcing, contrary to behavior in plane parallel calculations. This work contributes to reducing uncertainty in the radiative forcing of aviation, and may over ways to correct estimates of contrail cirrus radiative forcing and high clouds radiative effect in climate models.