Ice crystal orientation strongly influences cloud radiative properties and remote sensing retrievals, but long-term, high-resolution quantitative observations remain scarce. This study presents comprehensive case studies and statistical analyses of horizontally oriented ice crystals (HOICs) based on full-year (2022) synergistic observations in Beijing, China, combining a zenith-pointing micropulse lidar, a collocated 15° off-zenith polarization lidar, and a Ka-band cloud Doppler radar. Applying a novel height-resolved classification method based on dual-angle polarization lidars, HOICs are identified with high spatiotemporal resolution. HOICs are found to be common, accounting for 15.0 % of all ice-containing cloud data points annually with a peak of 24.6 % in summer, and showing maximum occurrence at temperatures from −20 to −10 °C. Macroscopically, typical HOIC layers exhibit horizontal extents of 10–100 km and durations of several hours within their optimal formation temperature ranges. Furthermore, the Euclidean-distance analysis between HOICs and past overlying cloud layers reveals a strong linkage of HOIC occurrence to supercooled liquid water clouds (SWCs), being much closer to HOIC events than randomly oriented ice crystals (ROICs). Dynamically, cloud radar observations further reveal that HOICs preferentially occur in stable environments with turbulent eddy dissipation rates below 10−2 m2 s−3 and exhibit lower fall velocities than ROICs. Estimates based on radar-observed vertical velocity indicate typical HOIC equivalent diameters of approximately 1200 µm with Reynolds numbers predominantly below 100. These findings provide key observational constraints for improving ice cloud microphysics and orientation parameterizations in numerical models.

The orientation of ice crystals plays a significant role in determining their radiative and precipitating effects; horizontally oriented ice crystals (HOICs) reflect up to ∼40 % more shortwave radiation back to space than randomly oriented ice crystals (ROICs). This study introduces an automatic range-resolved algorithm for HOIC identification using a combination of ground-based zenith-pointing and 15° off-zenith-pointing polarization lidars. The lidar observations provided high-resolution cloud-phase information. The data were collected in Beijing over 354 d in 2022. A case study from 13 October 2022 is presented to demonstrate the effectiveness and the feasibility of the detection method. The synergy of lidars and collocated Ka-band cloud radar, radiosonde, and ERA5 data provides phenomenological insights into HOIC events. While cloud radar Doppler velocity data allowed the estimation of ice crystal size, Reynolds numbers, and turbulent eddy dissipation rates, corresponding environmental and radar-detected variables are also provided. HOICs were present, accompanied by weak horizontal wind of 0–20 m s−1 and relatively high temperature between −8 and −22 °C. Compared to the ROICs, HOICs exhibited larger reflectivity, larger spectral width, a larger turbulent eddy dissipation rate, and a median Doppler velocity of about 0.8 m s−1. Ice crystal diameters (1029 to 1756 µm for 5th and 95th percentiles) and Reynolds numbers (28 to 88 for 5th and 95th percentiles) are also estimated with the help of cloud radar Doppler velocity using an aerodynamic model. One interesting finding is that the previously found switch-off region of the specular reflection in the region of cloud base shows a higher turbulence eddy dissipation rate, probably caused by the latent heat released due to the sublimation of ice crystals in the cloud-base region. The newly derived properties of HOICs have the potential to aid the derivation of the likelihood of their occurrence in output from general circulation models (GCMs) of the atmosphere.