Aviation contrail climate effects in the North Atlantic from 2016–2021

• Main Authors: Teoh, Roger, Schumann, Ulrich, Gryspeerdt, Edward, Shapiro, Marc, Molloy, Jarlath, Koudis, George, Voigt, Christiane, Stettler, Marc
• Format: Text
• Language: English
• Published: 2022
• Subjects: North Atlantic
• Online Access: https://doi.org/10.5194/acp-2022-169; https://acp.copernicus.org/preprints/acp-2022-169/

Around 5 % of anthropogenic radiative forcing (RF) is attributed to aviation CO 2 and non-CO 2 impacts. This paper quantifies aviation emissions and contrail climate forcing in the North Atlantic, one of the world’s busiest air traffic corridors, over 5 years. Between 2016 and 2019, growth in CO 2 (+3.13 % per annum, p.a.) and nitrogen oxide emissions (+4.5 % p.a.) outpaced increases in flight distance (+3.05 % p.a.). Over the same period, the annual mean contrail cirrus net RF (204–280 mW m -2 ) showed significant interannual variability caused by variations in meteorology. Responses to COVID-19 caused significant reductions in flight distance travelled (-66 %), CO 2 emissions (-71 %), and the contrail net RF (-66 %) compared to the prior one-year period. Around 12 % of all flights in this region cause 80 % of the annual contrail energy forcing, and the factors associated with strongly warming/cooling contrails include seasonal changes in meteorology and radiation, time of day, background cloud fields, and engine-specific non-volatile particulate matter (nvPM) emissions. Strongly warming contrails in this region are generally formed in wintertime, close to the tropopause, between 15:00 and 04:00 UTC, and above low-level clouds. The most strongly cooling contrails occur in the spring, in the upper troposphere, between 06:00 and 15:00 UTC, and without lower-level clouds. Uncertainty in the contrail cirrus net RF (216–238 mW m -2 ) arising from meteorology in 2019, is smaller than the interannual variability. The contrail RF estimates are most sensitive to the humidity fields, followed by nvPM emissions and aircraft mass assumptions. This longitudinal evaluation of aviation contrail impacts contributes a quantified understanding of inter-annual variability and informs strategies for contrail mitigation.