CALIOP V4 Cloud Thermodynamic Phase Assignment and the Impact of Near-Nadir Viewing Angles

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 an independent piece of information for determining cloud phase, a critical addition to other methods of thermodynamic phase discrimination that rely on temperature, cloud top altitude or a temperature-based cloud phase climatology. The CALIOP phase algorithm primarily uses layer-integrated depolarization and attenuated backscatter to determine the dominant thermodynamic phase of hydrometeors present in a vertical cloud layer segment, at horizontal resolutions varying between 333 m and 80 km. Ice cloud backscatter observations taken with a 0.3° near-nadir view include a significant amount of specular reflection from hexagonal smooth crystal faces that are oriented perpendicularly to the incident lidar beam. These specular reflections are often caused by horizontally oriented ice crystals (HOI), and are shown to occur between 0 and −40° C, with a peak in the distribution globally at −15° C. To avoid these reflections, the viewing angle was changed from 0.3 to 3° in November 2007. Since then the instrument has been observing clouds almost continuously for almost 12 more years. Recent viewing angle testing occurring during 2017 at 1, 1.5 and 2° quantifies the impact of changing the viewing angle to CALIOP global observations of attenuated backscatter and depolarization. These CALIOP results verify earlier observations by POLDER, showing that at the peak of the HOI distribution the mean backscatter from ice clouds decreases by 50 % and depolarization increases by a factor of 5 as the viewing angle increases from 0.3 to 3°. This has provided more data for a thorough evaluation of phase determination at the 3° viewing angle and suggested changes to the CALIOP cloud phase algorithm for Version 4 (V4). Combined with extensive calibration changes that impact the 532 nm and 1064 nm backscatter observations, V4 represents the first major Level 2 phase algorithm adjustment since 2009. For V4 the algorithm has been simplified to exclude over-identification of HOI at 3°, particularly in cold clouds. The V4 algorithm also considers temperature at the 532 nm cloud layer centroid, as opposed to cloud top or mid-cloud temperature as a secondary means of determining cloud phase and has been streamlined for more consistent identification of water and ice clouds. In this paper we summarize the major Version 3 (V3) to V4 cloud phase algorithm changes. We also characterize the impacts of applying the V4 phase algorithm globally and describe changes that can be expected when comparing V4 with V3. In V4 there are more cloud layers detected in V4, with edges that may extend further than in V3, for a combined increase in total atmospheric cloud volume of 6–9 % for high confidence cloud phases and 1–2 % for all cloudy bins. 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. Collocated CALIPSO Imaging Infrared Radiometer (IIR) observations of ice and water cloud particle microphysical indices complement the CALIOP ice and water cloud phase determinations.

Hemispheric and Seasonal Contrast in Cloud Thermodynamic Phase From A‐Train Spaceborne Instruments

“…For 2° × 30°, the uncertainty in FPR is higher for GOCCP (±0.13; sample size n = 64,640) than for DARDAR (±0.05; n = 58,289). This higher uncertainty in GOCCP appears to be associated with a lower FPR from CALIOP during 2007, before the off‐nadir angle was adjusted to decrease the specular reflection from ice crystals, which resulted in a bias in the detection of cloud‐phase (Avery et al., 2020, see also supporting information). In addition, the uncertainty for PM‐L2 (±0.04; n = 662,690) is similar to DARDAR despite a much higher sample size.…”

Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS+CrIS data fusion

“…To make use of the full potential of CALIPSO/CALIOP data, the 1 and 5 km products are combined when clouds are not reported in the 5 km product. While both version 3 and 4 CALIPSO/CALIOP products are available, the latest version (4-20) cloud layer product is used (Vaughan et al, 2018;Avery et al, 2020). In this paper, the true CALIPSO/CALIOP cloud top height for the uppermost cloud layer is used for validation instead of an ad-Table 1.…”