ALBERT

Description: Optical probes are frequently used for the detection of microphysical cloud particle properties such as liquid and ice phase, size and morphology. These properties can eventually influence the angular light scattering properties of cirrus clouds as well as the growth and accretion mechanisms of single cloud particles. In this study we compare four commonly used optical probes to examine their response to small cloud particles of different phase and asphericity. Cloud simulation experiments were conducted at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at European Organisation for Nuclear Research (CERN). The chamber was operated in a series of multi-step adiabatic expansions to produce growth and sublimation of ice particles at super- and subsaturated ice conditions and for initial temperatures of −30, −40 and −50 °C. The experiments were performed for ice cloud formation via homogeneous ice nucleation. We report the optical observations of small ice particles in deep convection and in situ cirrus simulations. Ice crystal asphericity deduced from measurements of spatially resolved single particle light scattering patterns by the Particle Phase Discriminator mark 2 (PPD-2K, Karlsruhe edition) were compared with Cloud and Aerosol Spectrometer with Polarisation (CASPOL) measurements and image roundness captured by the 3View Cloud Particle Imager (3V-CPI). Averaged path light scattering properties of the simulated ice clouds were measured using the Scattering Intensity Measurements for the Optical detectioN of icE (SIMONE) and single particle scattering properties were measured by the CASPOL. We show the ambiguity of several optical measurements in ice fraction determination of homogeneously frozen ice in the case where sublimating quasi-spherical ice particles are present. Moreover, most of the instruments have difficulties of producing reliable ice fraction if small aspherical ice particles are present, and all of the instruments cannot separate perfectly spherical ice particles from supercooled droplets. Correlation analysis of bulk averaged path depolarisation measurements and single particle measurements of these clouds showed higher R2 values at high concentrations and small diameters, but these results require further confirmation. We find that none of these instruments were able to determine unambiguously the phase of the small particles. These results have implications for the interpretation of atmospheric measurements and parametrisations for modelling, particularly for low particle number concentration clouds.

Description: A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, ϑs, ϑz, and RBRτc, θ0, ϑs, ϑz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasϑs, ϑz, in addition to RBRmeasϑs, ϑz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI  have an RMSE of 2.2, which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.