Evaluation of Hydrometeor Phase and Ice Properties in Cloud-Resolving Model Simulations of Tropical Deep Convection Using Radiance and Polarization Measurements

Abstract

Satellite measurements are used to evaluate the glaciation, particle shape, and effective radius in cloudresolving model simulations of tropical deep convection. Multidirectional polarized reflectances constrain the ice crystal geometry and the thermodynamic phase of the cloud tops, which in turn are used to calculate nearinfrared reflectances so as to constrain the simulated ice effective radius, thereby avoiding inconsistencies between retrieval algorithms and model simulations. Liquid index values derived from Polarization and Directionality of the Earth's Reflectances (POLDER) measurements indicate only ice-topped clouds at brightness temperatures (BTs) lower than -40°C, only liquid clouds at BT > -20°C, and both phases occurring at temperatures in between. Liquid index values calculated from model simulations generally reveal too many ice-topped clouds at BT > -20°C. The model assumption of platelike ice crystals with an aspect ratio of 0.7 is found consistent with POLDER measurements for BT < -40°C when very rough ice crystals are assumed, leading to an asymmetry parameter of 0.74, whereas measurements indicate more extreme aspect ratios of -0.15 at higher temperatures, yielding an asymmetry parameter of 0.84. MODIS-retrieved ice effective radii are found to be 18-28 fim at BT < -40°C, but biased low by about 5 fim owing primarily to the assumption of pristine crystals in the retrieval. Simulated 2.í3-fim reflectances at BT < -40°C are found to be about 0.05-0.1 too large compared to measurements, suggesting that model-simulated effective radii are 7-15 /xm too small. Two simulations with contrasting ice nucleation schemes showed little difference in simulated effective radii at BT < -40°C, indicating that homogeneous nucleation is dominating in the simulations. Changes around -40°C in satellite observations suggest a change in cloud-top ice shape and/or size in natural deep convection possibly related to a change in the freezing mechanism.

Remote sensing of ice crystal asymmetry parameter using multi-directional polarization measurements – Part 2: Application to the Research Scanning Polarimeter

“…3.1. As particle size generally increases with decreasing height (Lawson et al, 2010;van Diedenhoven et al, 2012b) and particle aspect ratio is expected to increase somewhat with size (Auer and Veal, 1970;Korolev and Isaac, 2003), asymmetry parameters might be expected to increase with decreasing height rather than decrease, as found here. We speculate that the slight increase of asymmetry parameter with decreasing height might result from an increase of particle distortion or surface roughness.…”

Satellite retrieval of the liquid water fraction in tropical clouds between −20 and −38 °C

“…However, neither the TC4 flight plans nor the microphysics data processing algorithm was designed to look for the presence of liquid water (R. P. Lawson, personal communication, 2010). Conversely, recent ground-based and satellite remote sensing studies have detected liquid water between −20 and −36 • C in tropical cloud fields (Ansmann et al, 2009;Yoshida et al, 2010;Hu et al, 2010;van Diedenhoven et al, 2012), and in situ measurements in strong updrafts of deep convective clouds have shown sustained liquid water down to −37.5 • C (Rosenfeld and Woodley, 2000). Liquid water at these temperatures was almost always detected at the tops of tropical altocumulus during the Saharan Mineral Dust Experiment (Ansmann Fig.…”

“…(6) using the g parameterization given in Yang et al (2005), which is parameterized in terms of D e and assumes a certain combination of ice particle shapes. While this shape assumption affects the wave resonance contribution to absorption, ice particle shape for a given D e has a very weak impact on g at thermal wavelengths where g depends primarily on forward scattering as determined by the particle's area cross-section (van de Hulst, 1981). The effective emissivity is related to β eff as described in Inoue (1985):…”

“…To our knowledge, this type of information did not previously exist regarding widespread tropical cloud fields characterized by deep convection. However, a recent study by van Diedenhoven et al (2012) describes a "liquid index" that was used to qualitatively assess the level of liquid water present in tropical clouds resulting from deep convection. Their results are qualitatively similar to those shown here.…”

“…For example, an Arctic mixed phase cloud algorithm has been developed for distinguishing cloud radar Doppler spectra into liquid and ice components . Optically thin (visible optical thickness < 6), single layer, Arctic, mixed phase clouds have been characterized in terms of their optical thickness, their ice water fraction, and the effective diameter for water and ice particles using high-resolution infrared radiance and lidar cloud boundary observations (Turner, 2005). Still needed are retrievals that can simultaneously characterize the water phase, liquid water content (LWC) and ice water content (IWC), and the effective particle size D e for water and ice at all altitudes.…”