Distinguishing cirrus cloud presence in autonomous lidar measurements.

Level 2 Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite-based cloud datasets from 2012 are investigated for metrics that help distinguish the cirrus cloud presence of in autonomous lidar measurements, using temperatures, heights, optical depth and phase. A thermal threshold, proposed by Sassen and Campbell (2001; SC2001) for cloud top temperature Ttop≤ -37 °C, is evaluated vs. CALIOP algorithms that identify ice-phase cloud layers alone using depolarized backscatter. Global mean cloud top heights (11.15 vs. 10.07 km a.m.s.l.), base heights (8.76 vs. 7.95 kma.m.s.l.), temperatures (-58.48 °C vs. -52.18 °C and -42.40 °C vs. -38.13 °C, 10 respectively for tops and bases) and optical depths (1.18 vs. 1.23) reflect the sensitivity to these competing constraints. Over 99% of all Ttop ≤-37 °C clouds are classified as ice by CALIOP Level 2 algorithms. Over 81% of all ice clouds correspond with Ttop &#8804-37 °C. For instruments lacking polarized measurements, and thus practical phase estimates, Ttop ≤-37 °C proves stable for distinguishing cirrus, as opposed 15 to the risks of glaciated liquid water cloud contamination occurring in a given sample from clouds identified at warmer temperatures. Uncertainties in temperature profiles use to collocate with lidar data (i.e., model reanalyses/sondes) may justifiably relax the Ttop ≤-37 °C threshold to include warmer cases. The ambiguity of "warm" (Ttop >-37 °C) ice cloud genus cannot be reconciled completely with available mea20 surements, however, conspicuously including phase. Cloud top heights and optical depths are evaluated as potential constraints, as functions of CALIOP-retrieved phase. However, these data provide, at best, additional constraint in regional samples, compared with temperature alone, and may exacerbate classification uncertainties overall globally. [ABSTRACT FROM AUTHOR]