Aircraft condensation trails (contrails) are currently estimated to contribute a similar effective radiative forcing as all CO2 yet emitted from the aviation sector. They also constitute the ultimate short-lived forcer, with lifetimes estimated in hours and local radiative forcings on the order of several watts per meter squared. This has made them the subject of a recent explosion in interest from the scientific, aviation, and regulatory communities, including ongoing debate regarding potential measurement and regulation of contrail formation alongside aircraft CO2 emissions.
Although there have been several recent in-situ measurement campaigns and significant recent advances in the detection of contrails using remote sensing data, understanding their overall climate effects - as well as the development of effective strategies to mitigate said impacts - requires accurate models of contrail formation and evolution. This is a substantial challenge, given that contrails form at the scale of an aircraft engine exhaust but can spread to be tens or hundreds of kilometers wide. Furthermore there remains relatively little observational data to directly constrain contrails due to the difficulty of directly sampling contrail ice and the high degree of temporal and spatial variability in cruise altitude conditions.
With these concerns in mind, this session aims to bring together the growing community of contrail modellers who are seeking to advance our ability to represent and understand the full lifetime of a contrail and its long term impacts. This includes those who are working on: high-fidelity modelling of contrail formation in the exhaust plume; LES or RANS models of the exhaust plume and contrail; 0-, 1-, 2-, or 3-D models of long-term contrail behaviour; models of regional- and global-scale contrail evolution and climate responses, including potential cloud feedbacks; and studies using new datasets to evaluate the performance of existing contrail models. Particular attention will be given to research using open-source models and data.