Verification for Different Contrail Parameterizations Based on Integrated Satellite Observation and ECMWF Reanalysis Data

Aviation induced cloud termed contrail plays a more and more important role in the climate change, which makes a significant contribution to anthropogenic climate forcing through impacting the coverage of cirrus in the intersection of troposphere and stratosphere. In this paper, we propose one novel automatic contrail detecting method based on Himawari-8 stationary satellite imagery and two kinds of potential contrail coverage (PCC1 and PCC2) from contrail parameterization in ECHAM4 and HadGEM2. In addition, we propose one new climatological index called contrail occurrence and persistence (COP). According to the algorithm identification (AI) and artificial visual inspection (AVI), COP measured from Himawari-8 stationary satellite imagery is related to upper tropospheric relative humidity over ice (RHI) computed with the ECMWF reanalysis data by simple linear regression. Similarly, we compared the linear correlation between COP and PCCs fractions and found that PCC1 has better correspondence with COP than PCC2