Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions

Abstract. Space profiling lidars offer a unique insight into cloud properties in Earth's atmosphere and are considered the most reliable source of total (column-integrated) amount (CA), true (geometrical) top height (CTH). However, lidar-based climatologies suffer from infrequent sampling: every n days, only along ground track. This study therefore evaluated four lidar missions, namely CALIPSO (revisit n=16 d), EarthCARE (n=25), Aeolus (n=7), ICESat-2 (n=91), to test hypothesis that each mission provides accurate data on CA CTH. CA/CTH values for hypothetical daily revisit were used as reference (data simulated with Meteosat 15 min observations, assumed be proxy truth). Our results demonstrated this is invalid, unless individual transects averaged over an area 10×10∘ longitude latitude (or larger). If not case, required accuracy 1 % (for CA) or 150 m CTH) cannot met, either single-year annual monthly mean, >10 year climatology. A CALIPSO-focused mean estimate very sensitive sampling, factor alone can result 14 7 average uncertainty 2.5∘ resolution data, respectively. Consequently, applications use gridded should consider calculating confidence intervals, similar measure uncertainty. suggest CALIPSO, its follow-on EarthCARE, likely produce consistent records despite difference sampling frequency.