Retrieval of Terahertz Ice Cloud Properties from airborne measurements based on the irregularly shaped Voronoi ices cattering models.

Currently, the terahertz remote sensing technology is one of the best ways to detect the microphysical properties of ice clouds. Influenced by the representativeness of the ice crystal scattering (ICS) model, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. In this study, we developed a terahertz remote sensing inversion algorithm of the ice water path (IWP) and effective particle radius (Re) of ice clouds based on the Voronoi ICS model. This study utilized the single-scattering properties (extinction efficiency, single-scattering albedo and asymmetry factor) of the Voronoi and Sphere ICS models in the terahertz region. Combined with 14,408 groups of particle size distributions obtained from aircraft-based measurements, we completed the Voronoi and Sphere ICS schemes based on the Voronoi and Sphere ICS models. The two schemes were applied to the RSTAR radiative transfer model to carry out the sensitivity analysis of the top of cloud (TOC) terahertz brightness temperature differences (BTDs) on the IWP and Re. The sensitivity results showed that the TOC BTDs between 640 and 874 GHz are functions of the IWP, and the TOC BTDs between 380, 640 and 874 GHz are functions of the Re. The Voronoi ICS scheme possesses stronger sensitivity to the Re than the Sphere ICS scheme. Based on the sensitivity results, we built a multi-channel look-up table for BTDs. The IWP and Re were searched from the look-up table using an optimal estimation algorithm. We used 2000 BTD test data randomly generated by the RSTAR model to assess the algorithm’ s accuracy. Test results showed the correlation coefficients of the retrieved IWP and Re reach 0.99 and 0.98, respectively. As an application, we used the inversion algorithm to retrieve the ice cloud IWP and Re based on the CoSSIR airborne terahertz radiation measurements. Validation against the retrievals of the Bayesian algorithm reveals that the Voronoi ICS model performs better than the Sphere ICS model, with the enhancement of the Mean absolute error of 5.0 % and 12.8 % for IWP and Re, respectively. In summary, the results of this study confirmed the practicality and effectiveness of the Voronoi ICS model in the terahertz remote sensing inversion of ice cloud microphysical properties. [ABSTRACT FROM AUTHOR]