Polar Liquid Cloud Base Detection Algorithms for High Spectral Resolution or Micropulse Lidar Data

Abstract

Liquid layers in clouds affect their microphysical processes, as well as the surface energy budget. Studies focusing on these and other areas of research are often in need of skillful estimation of liquid‐bearing cloud layer boundaries. The bases of these layers are predominantly determined by ground‐based lidar instruments. Most studies requiring liquid cloud base height (LCBH) information use either fixed lidar parameter (depolarization and/or backscatter cross section) thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBH. In this paper, two explicit LCBH detection algorithms are presented. The first algorithm uses the high spectral resolution lidar (HSRL) data. Examination of this algorithm in multiple cases and scenarios during numerous days and first‐order comparison with microwave‐radiometer data show satisfactory results. The second algorithm incorporates widely available micropulse lidar (MPL) data for the LCBH detection. A 1‐year long comparison of data gathered at Barrow, Alaska, and McMurdo Station, Antarctica, which includes other cloud base detection methodologies (ceilometer, MPL value‐added product cloud base height, and LCBHs detected using a fixed MPL depolarization threshold), emphasizes the merits of the presented MPL algorithm. Examination of several unusual LCBH configurations suggests that the current practice of operating lidar at a tilting angle of 4° off zenith may not be sufficient to avoid specular reflection from oriented ice crystals. Data collected at Madison Wisconsin are used to show that specular reflection may impact measurements even at 4°.

Persistent Supercooled Drizzle at Temperatures Below −25 °C Observed at McMurdo Station, Antarctica

“…The upper q c peak is supported by the ample cloud‐top radiative cooling that invigorates the turbulence below, while the evaporation of the lower q c peak is hindered by the local drizzle‐driven q t maximum (Figure d). We thus speculate that drizzle evaporating in quiescent air may play a key role in the redistribution of moisture necessary to support the formation and persistence of multipeaked cloud water content profiles, which are occasionally observed both over Antarctica (e.g., Silber, Verlinde, Eloranta, Flynn, & Flynn, , Figure ) and the Arctic (e.g., Silber, Verlinde, Eloranta, Flynn, & Flynn, , Figure S2; Verlinde et al, , Figures and 8).…”

“…The low LDR values just below the LCBH suggest that the backscattered lidar signal from these air volumes is dominated by nearly spherical scatterers, for example, falling drizzle drops (diameter <0.5 mm per Pruppacher & Beard, 1970). While specular reflection by plate ice crystals may induce similar low LDR values (see Appendix A in Silber, Verlinde, Eloranta, Flynn, & Flynn, 2018b), the cloud layer temperatures (T; Figure 3h, left panel) were well below the plate crystal growth regime (Bailey & Hallett, 2009). Aerosol particles and cloud droplets may also produce low LDR, but the measured β p values are too high and low for aerosol particles and cloud droplets, respectively (e.g., Silber, Verlinde, Eloranta, & Cadeddu, 2018, Figure 2).…”

Microphysics of summer clouds in central West Antarctica simulated by the Polar Weather Research and Forecasting Model (WRF) and the Antarctic Mesoscale Prediction System (AMPS)

“…The advanced research Weather Research and Forecasting Model (WRF) is an extensively used community numerical weather prediction model for numerous applications worldwide (e.g., Skamarock et al, 2008). Most of the polar optimizations for Polar WRF are added in the Noah land surface model (Barlage et al, 2010) and improve the representation of heat transfer through snow and ice (Hines and Bromwich, 2008;Hines et al, 2015).…”

Antarctic Cloud Macrophysical, Thermodynamic Phase, and Atmospheric Inversion Coupling Properties at McMurdo Station: I. Principal Data Processing and Climatology

“…This population is attributed to liquid water returns, which, with (typically) high droplet concentrations, produce large β p values (e.g., de Boer et al, 2009;Eloranta, 2005). The higher values of the upper LDR limit of liquid-dominated volumes can be attributed to multiple scattering effects (Bissonnette, 2005;Eloranta, 1998) or ice particles in the same volume as the liquid droplets (e.g., Silber et al, 2018, Figure S1). Both March and August histograms reveal enhanced counts in the lowest LDR column.…”