Abstract
Abstract. Accurate determination of thermodynamic cloud phase is critical for establishing the radiative impact of clouds on climate and weather. Depolarization of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm signal provides a useful addition to other methods of thermodynamic phase discrimination that rely on temperature, cloud top altitude or a temperature-based cloud phase climatology. Active detection of the thermodynamic phase of multiple cloud layers in a vertical column using cloud layer-integrated depolarization and backscatter also alleviates ambiguities in cloud phase determination by passive radiometers. The CALIOP phase algorithm primarily uses vertically integrated cloud layer depolarization and attenuated backscatter to determine the dominant thermodynamic phase of hydrometeors present in a cloud layer segment, at horizontal resolutions for cloud layer detection varying between 333 m and 80 km, with cloud layer vertical resolutions between 60 m and 8 km. CALIOP ice cloud backscatter observations taken with a 0.3∘ near-nadir view between June 2006 and November 2007 include a significant amount of specular reflection from hexagonal smooth crystal faces that are oriented perpendicularly to the incident lidar beam (horizontally oriented ice – HOI). These specular reflections from HOI are shown here to occur between 0 and −40 ∘C, with a peak in the CALIOP distribution observed globally at −15 ∘C. Recent viewing angle testing occurring during 2017 at 1, 1.5 and 2∘ and reported here quantifies the impact of changing the viewing angle on these specular reflections and verifies earlier observations by POLDER. These viewing angle tests show that at the −15 ∘C peak of the HOI distribution the mean backscatter from all ice clouds decreases by 50 % and depolarization increases by a factor of 5 as the viewing angle increases from 0.3 to 3∘. To avoid these specular reflections, the CALIOP viewing angle was changed from 0.3 to 3∘ in November 2007, and since then CALIOP has been observing clouds almost continuously for 12–13 more years. This has provided more data for a thorough re-evaluation of phase determination and has motivated changes to the CALIOP cloud phase algorithm for Version 4 (V4). The V4 algorithm now excludes over-identification of HOI at 3∘, particularly in cold clouds. The V4 algorithm also considers cloud layer temperature at the 532 nm centroid and has been streamlined for more consistent identification of water and ice clouds. In V4 some cloud layer boundaries have changed because 532 nm layer-integrated attenuated backscatter in V4 has increased due to improved calibration and extended layer boundaries, while the corresponding depolarization has stayed about the same. There are more V4 cloud layers detected and, combined with increasing cloud edges, the V4 total atmospheric cloud volume increases by 6 %–9 % over V3 for high-confidence cloud phases and by 1 %–2 % for all cloudy bins. Collocated CALIPSO Imaging Infrared Radiometer (IIR) observations of ice and water cloud particle microphysical indices complement the CALIOP ice and water cloud phase determinations.
Highlights
Cloud ice crystals and water droplets have very different absorption and scattering properties (Sassen, 1991) and so accurate knowledge of the thermodynamic phase of clouds is needed to characterize the transfer of radiation through Earth’s cloudy atmosphere
At 0.3◦ there is a weakly negative correlation of −0.07 between backscatter and depolarization in the water sector, in contrast to a positive correlation of 0.38 at 3◦, indicating a significant misidentification of water as horizontally oriented ice (HOI) when the spatial coherence test is applied at the larger viewing angle. Since it is clear from the viewing angle tests shown above that the 3◦ view greatly reduces the amount of specular reflections from horizontally oriented planar ice crystal faces, it is likely that the Version 3 (V3) algorithm is mistaking randomly oriented ice (ROI) for HOI in the ROI sector as well as water for HOI in the water sector because of natural variability or variation due to noise occurring in γ532 and δp,eff
An additional adjustment to cloud–aerosol partitioning has been added in Version 4 (V4) to identify features that have been classified by the cloud–aerosol discrimination algorithm (CAD) algorithm as aerosols but which occur in spatial proximity to ice cloud layers (Liu et al, 2019)
Summary
Cloud ice crystals and water droplets have very different absorption and scattering properties (Sassen, 1991) and so accurate knowledge of the thermodynamic phase of clouds is needed to characterize the transfer of radiation through Earth’s cloudy atmosphere. While microwave radars for large particle and precipitation detection preceded lidars in using polarization to deduce cloud microphysics (Schotland et al, 1971), radar retrievals of cloud microphysical properties for the relatively longer-wavelength CPR use a temperature-based climatology to approximate the ratio of ice vs water in observations made in bins between 0 and −40 ◦C (Austin et al, 2009). Active and passive remote sensors that can detect linear polarization changes in scattered light from water and ice clouds have the advantage of determining thermodynamic phase without depending on temperature, pressure or detailed assumptions about ice particle habits. Ice and water clouds occurring in the same column can be differentiated using linear polarization changes and layerintegrated backscatter (Hu et al, 2009) to determine phase independently of the atmospheric state and particle size.
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