Distinguishing cirrus cloud presence in autonomous lidar measurements

Abstract. 2012 Level-2 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite-based cloud data sets are investigated for thresholds that distinguish the presence of cirrus clouds in autonomous lidar measurements, based on temperatures, heights, optical depth and phase. A thermal threshold, proposed by Sassen and Campbell (2001) for cloud top temperature T_top ≤ −37 °C, is evaluated versus CALIOP algorithms that identify ice-phase cloud layers using polarized backscatter measurements. Derived global mean cloud top heights (11.15 vs. 10.07 km above mean sea level; a.m.s.l.), base heights (8.76 km a.m.s.l. vs. 7.95 km a.m.s.l.), temperatures (−58.48 °C vs. −52.18 °C and −42.40 °C vs. −38.13 °C, respectively, for tops and bases) and optical depths (1.18 vs. 1.23) reflect the sensitivity to this constraint. Over 99 % of all T_top ≤ −37 °C clouds are classified as ice by CALIOP Level-2 algorithms. Over 81 % of all ice clouds correspond with T_top ≤ −37 °C. For instruments lacking polarized measurements, and thus practical estimates of phase, T_top ≤ −37 °C provides sufficient justification for distinguishing cirrus, as opposed to the risks of glaciated liquid-water cloud contamination occurring in a given sample from clouds identified at relatively "warm" (T_top > −37 °C) temperatures. Although accounting for uncertainties in temperatures collocated with lidar data (i.e., model reanalyses/sondes) may justifiably relax the threshold to include warmer cases, the ambiguity of "warm" ice clouds cannot be fully reconciled with available measurements, conspicuously including phase. Cloud top heights and optical depths are investigated, and global distributions and frequencies derived, as functions of CALIOP-retrieved phase. These data provide little additional information, compared with temperature alone, and may exacerbate classification uncertainties overall.