On the relation between ice-crystal scattering phase function at 180° and particle size: implication to lidar-based remote sensing of cirrus clouds

The lack of knowledge of the relation between a lidar backscatter signal and particle size makes it challenging to retrieve ice-cloud particle size from spaceborne lidar observations. This study employs a synergistic combination of the state-of-the-art invariant imbedding T-matrix method and the physical geometric-optics method (PGOM) to investigate the relation between the ice-crystal scattering phase function at 180° (P₁₁(180°)) and particle size (L) for typical ice-crystal shapes. In particular, the P₁₁(180°) -L relation is quantitatively analyzed. The dependence of the P₁₁(180°) -L relation on particle shape can be used with spaceborne lidar observations to detect ice-cloud particle shapes.

Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations

The backscattering optical properties of an ensemble of randomly oriented dust particles at a wavelength of 355 nm were comprehensively studied by examining the invariant imbedding T-matrix results of the super-spheroid dust model. In particular, we focused on the lidar ratio ( S ) and depolarization ratio ( δ ) relations of dust aerosols to aid interpretation of data from the Atmospheric Lidar (ATLID) instrument that will be onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite. Super-spheroid models with various aspect ratios ( α ), roundness parameters ( n ) , and refractive indices were investigated over a wide range of particle sizes and compared to the observation data of the National Aeronautics and Space Administration (NASA) Langley 355-nm airborne high spectral resolution lidar. We found that super-spheroid dust particles with different sets of n and α could be used to model almost the entire range of the observed joint distributions of S and δ . The S - δ relation could effectively discriminate among dust particle types. The observed S and δ values with the largest population density were best covered by models with n > 2, especially by those with n varying from 2.4 to 3.0.

Development of a 355-nm high-spectral-resolution lidar using a scanning Michelson interferometer for aerosol profile measurement

A simple 355-nm high-spectral-resolution lidar (HSRL) is developed for continuous observation of aerosol profiles. A scanning Michelson interferometer is used to separate the Rayleigh and Mie scattering components. The interferometer is periodically scanned in the range of one fringe. Interference contrast, which contains aerosol backscatter information, is estimated at each height through fitting analysis of the scan data. The interference contrast and fringe position are calibrated with the reference signals taken from the transmitted laser. Furthermore, the 1-day continuous measurement of aerosol backscatter and extinction coefficients is demonstrated. Comparison with a nighttime Raman lidar indicates a good performance of the scanning method.

Interpretation of lidar ratio and depolarization ratio of ice clouds using spaceborne high-spectral-resolution polarization lidar

The backscattering coefficient (β), lidar ratio (S), and depolarization ratio (δ) of ice particles were estimated over a wide range of effective radii to interpret spaceborne 355-nm high-spectral-resolution lidar data from the ATLID sensor onboard the EarthCARE satellite. Five randomly oriented ice particle shapes (3D ice) and two quasi-horizontally oriented particle types (2D ice) were analyzed using five effective angles. The size dependence of β, S, and δ was examined using physical optics and geometrical optics integral equation methods. Differences in β for the same effective radius and ice water content among particle types exceeded one order of magnitude. S-δ relations are useful for inferring ice particle habit and orientation using ATLID data from EarthCARE.

Modeling the depolarization of space-borne lidar signals

A physical model was extended with a polarization function to create a vectorized physical model (VPM) to analyze the vertical profile of the observed depolarization ratio due to multiple scattering from water clouds by space-borne lidar. The depolarization ratios due to single scattering, on-beam multiple scattering, and pulse stretching mechanisms are treated separately in the VPM. The VPM also includes a high-order scattering matrix and accommodates mechanisms that modify the polarization state during multiple scattering processes. The estimated profile of the depolarization ratio from the VPM showed good agreement with Monte Carlo simulations, with a mean relative error of about 2% ± 3%.

Physical model for multiple scattered space-borne lidar returns from clouds

A practical model for determining the time-dependent lidar attenuated backscattering coefficient β was developed for application to global lidar data. An analytical expression for the high-order phase function was introduced to reduce computational cost for simulating the angular distribution of the multiple scattering irradiance. The decay rate of the multiple scattering backscattered irradiance was expressed by incorporating the dependence on the scattering angle and the scattering order based on the path integral approach. The estimated β over time and the actual range showed good agreement with Monte Carlo simulations for vertically homogeneous and inhomogeneous cloud profiles, resulting in about 15% mean relative error corresponding to 4 times improved accuracy against the Ornstein-Fürth Gaussian approximation method.

Active sensor synergy for arctic cloud microphysics

In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA) [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.

Development of Algorithm for Discriminating Hydrometeor Particle Types with a Synergistic Use of CloudSat and CALIPSO

We developed a method for classifying hydrometeor particle types, including cloud and precipitation phase and ice crystal habit, by a synergistic use of CloudSat/Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). We investigated how the cloud phase and ice crystal habit characterized by CALIOP globally relate with radar reflectivity and temperature. The global relationship thus identified was employed to develop an algorithm for hydrometeor type classification with CPR alone. The CPR-based type classification was then combined with CALIPSO-based type characterization to give CPR-CALIOP synergy classification. A unique aspect of this algorithm is to exploit and combine the lidar's sensitivity to thin ice clouds and the radar's ability to penetrate light precipitation to offer more complete picture of vertically resolved hydrometeor type classification than has been provided by previous studies. Given the complementary nature of radar and lidar detections of hydrometeors, our algorithm delivers thirteen hydrometeor types: warm water, supercooled water, randomly-oriented ice crystal (3D-ice), horizontally-oriented plate (2D-plate), 3D-ice+2D-plate, liquid drizzle, mixed-phase drizzle, rain, snow, mixed-phase cloud, water+liquid drizzle, water+rain and unknown. The global statistics of three-dimensional occurrence frequency of each hydrometeor type revealed that 3D-ice contributes the most to the total cloud occurrence frequency (53.8%), followed by supercooled water (14.3%), 2D-plate (9.2%), rain (5.9%), warm water (5.7%), snow (4.8%), mixed-phase drizzle (2.3%), and the remaining types (4.0%). This hydrometeor type classification provides useful observation-based information for climate model diagnostics in representation of cloud phase and their microphysical characteristics.

Development of a multiple-field-of-view multiple-scattering polarization lidar: comparison with cloud radar

We developed a multiple-field-of-view multiple-scattering polarization lidar (MFMSPL) to study the microphysics of optically thick clouds. Designed to measure enhanced backscattering and depolarization ratio comparable to space-borne lidar, the system consists of four sets of parallel and perpendicular channels mounted with different zenith angles. Depolarization ratios from water clouds were large as observed by MFMSPL compared to those observed by conventional lidar. Cloud top heights and depolarization ratios tended to be larger for outer MFMSPL channels than for vertically pointing channels. Co-located 95 GHz cloud radar and MFMSPL observations showed reasonable agreement at the observed cloud top height.

Backscattering Mueller matrix for quasi-horizontally oriented ice plates of cirrus clouds: application to CALIPSO signals

A general view of the backscattering Mueller matrix for the quasi-horizontally oriented hexagonal ice crystals of cirrus clouds has been obtained in the case of tilted and scanning lidars. It is shown that the main properties of this matrix are caused by contributions from two qualitatively different components referred to the specular and corner-reflection terms. The numerical calculation of the matrix is worked out in the physical optics approximation. These matrices calculated for two wavelengths and two tilt angles (initial and present) of CALIPSO lidar are presented as a data bank. The depolarization and color ratios for these data have been obtained and discussed.