Reducing the Impact of Aircraft-Induced Clouds on Climate –Development of the Contrail Avoidance Tool (CoAT)

Abstract

Civil aviation is estimated to contribute ∼90 mW m−2 (∼ 4 %) towards the global anthropogenic radiative forcing of ∼2.38 W m−2. Compared to the radiative forcing caused by aviation CO2 emissions estimated at 35 mW m−2, aviation-induced clouds formed behind aircraft have a larger forcing and a large uncertainty. These clouds form when the emissions from the aircraft exhaust mix with the environmental air, cool rapidly and increase the humidity such that the air becomes supersaturated over water. Aviation-induced clouds are categorized as persistent contrails and contrail cirrus of which the latter spread horizontally and can be kilometers-wide and has the largest forcing. Therefore, to reduce the radiative forcing of the aviation industry, we are developing the Contrail Avoidance Tool (CoAT) to mitigate the formation of contrails. Within the development of CoAT, we are working towards tracking the evolution of contrail cirrus using Environment and Climate Change Canada’s (ECCC) High-Resolution Deterministic Prediction System at a horizontal resolution of 1 km x 1 km. The model utilizes the Particle Properties (P3) bulk three-moment microphysics scheme with three "free" ice categories. This scheme enables the physical properties to evolve smoothly through the changes of five prognostic variables, which include total ice mass, rime ice mass, total ice number, rime ice volume and reflectivity factor (Milbrandt et al., 2021). Part of developing CoAT involves developing a contrail model. This model consists of first simulating contrail formation regions using the Schmidt-Appleman criteria (Schumann, 1996). We then simulate the contrail volume to estimate the contrail ice number concentration (Unterstrasser, 2016). We then track the evolution of ice number concentration in the control model and its radiative forcing, independent of whether contrail cirrus forms within cirrus. Next, we’ve applied our contrail model within CoAT to a case study. An important challenge in modeling contrails is the extent to which contrail cirrus and cirrus clouds may overlap and become indistinguishable. To understand the radiative forcing from contrail cirrus, we modified P3 by designating the contrail ice from the contrail model to one of the three free ice categories which does not interact with the other two ice categories. The ultimate goal is to implement CoAT into ECCC’s Global Deterministic Prediction System (GDPS). The GDPS will cover the Canadian air space, the North Atlantic and Arctic Oceans to predict and mitigate contrail formation, thus reducing the impact of aircraft-induced clouds on climate.