A Novel Ice Cloud Optical Property Model for Passive and Active Remote Sensing Applications

A new broad‐spectrum ice cloud optical property model, namely the Passive‐Active Remote Sensing Consistent (PARSC) model, is developed to achieve consistency between passive and active sensor‐based ocean‐occurring ice cloud property retrievals. This is made possible in part by using an advanced single‐scattering property computational method known as the Physical Geometric Optics Method (PGOM). The PGOM provides accurate phase matrix backscatter calculations for moderate and large particle size parameters, which are critical for obtaining accurate active sensor‐based (e.g., LiDAR) retrievals. The model is developed to be optically consistent with the original Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (MC6) model currently being utilized to retrieve ice cloud properties from MODIS observations without involving backscatter. For passive sensor‐based validation of the PARSC model, we performed a spectral consistency test of ice cloud optical thickness (ICOT) retrievals using MODIS, Visible Infrared Imaging Radiometer Suite (VIIRS), and Geostationary Operational Environmental Satellites‐17 (GOES‐17) observations. For active sensor‐based validation, we performed consistency tests of the backscatter‐dependent parameters of the LiDAR ratio, integrated attenuated backscatter (IAB), and linear depolarization ratio calculated from the PARSC and MC6 models and measured by the Cloud‐Aerosol LiDAR with Orthogonal Polarization (CALIOP). Due to PARSC being optically consistent with the original MC6 model, the passive sensor‐based spectral consistencies of ICOT retrievals using MODIS, VIIRS, and GOES‐17 observations show negligible changes in the error analyses. LiDAR ratios, IABs, and linear depolarization ratios calculated by the PARSC model show significantly improved consistencies relative to the corresponding frequency distributions of collocated CALIOP and MODIS observations.