Abstract. Currently, 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, based on the Voronoi
ICS model, we developed a terahertz remote sensing inversion algorithm of
the ice water path (IWP) and median mass diameter (Dme) of ice clouds.
This study utilized the single-scattering properties (extinction efficiency,
single-scattering albedo, and asymmetry factor) of the Voronoi, sphere, and
hexagonal column ICS models in the terahertz region. Combined with 14 408
groups of particle size distributions obtained from aircraft-based
measurements, we developed the Voronoi, sphere, and column ICS schemes based
on the Voronoi, sphere, and column ICS models. The three schemes were applied
to the radiative transfer model to carry out the sensitivity analysis
of the top-of-cloud (TOC) terahertz brightness temperature differences
between cloudy and clear skies (BTDs) on the IWP and Dme. The
sensitivity results showed that the TOC BTDs between 640 and 874 GHz are
functions of the IWP, and the TOC BTDs of 380, 640, and 874 GHz are
functions of the Dme. The Voronoi ICS scheme possesses stronger
sensitivity to the Dme than the sphere and column ICS schemes. Based on
the sensitivity results, we built a multi-channel look-up table for BTDs.
The IWP and Dme 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 that the
correlation coefficients of the retrieved IWP and Dme reached 0.99 and
0.98, respectively. As an application, we used the inversion algorithm to
retrieve the ice cloud IWP and Dme based on the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) airborne
terahertz radiation measurements. Validation against the retrievals of the
Bayesian algorithm reveals that the Voronoi ICS model performs better than
the sphere and hexagonal column ICS models, with enhancement of the mean
absolute errors of 5.0 % and 12.8 % for IWP and Dme, 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.
