Abstract

Aircrafts emit exhaust gases and soot into the atmosphere, which may increase global cirrus cloudiness and as well change the properties of already existing cirrus. In the first COVID-19 lockdown in Europe, changes in cirrus cloud occurrence and properties were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO2 emissions and flight densities in Europe. In the current study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed. The Linear contrails and contrail cirrus induced by global aviation have long been known to contribute to climate change by warming the atmosphere. Besides increasing global cirrus cloudiness, aviation may change the properties of the natural cirrus clouds by soot emissions which leads to increased heterogeneous freezing. In the first COVID-19 lockdown in Europe, changes in cirrus cloud properties and occurrence were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO2 emissions and flight densities in Europe. In this study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed to determine the seasonality and long-term trends in cirrus clouds as well as their correlations with the ambient temperatures and air traffic. Cirrus clouds follow a distinct seasonal cycle in their occurrence rate (OR) and particle linear depolarization ratio (PLDR) δp. Cirrus clouds appear within a broader altitude range in winter than in summer and they are characterized by larger OR and δp values in winter than in summer. The monthly medians of δp as well as the deseasonalized time series of them in the 10-year period before COVID show both positive trends which are statistically significant according to the Mann-Kendall (MK) significance test. However, the cirrus occurrence shows a negative trend, which might be connected with the background meteorological conditions. Since the cirrus δp strongly depends on the ambient temperatures in cirrus, we further remove the contributions induced by temperatures from the cirrus δp with a simple linear regression model. The derived residuals show significant positive trends with the MK test. To compare the cirrus δp and the air traffic densities, the deseasonalization of the data have previously been conducted since the seasonal cycles in both are not consistent. The deseasonalized time series of the cirrus δp and CO2 emissions from aviation both show an increasing trend and their correlation coefficients are r = 0.54 at the confidence level above 99.5 %. Finally, the comparisons between the cirrus δp and aviation in every season were carried out and revealed a strong correlation in other seasons than in summer.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call