No abstract

Ice clouds play a critical role in the balance of the earth–atmosphere radiation system, but there are some limitations in the existing remote sensing methods for ice clouds. Terahertz wave is expected to be the best waveband for retrieving ice clouds, with terahertz wavelengths in the order of the size of typical ice cloud particles. An inversion method for the remote sensing of ice clouds at terahertz wavelengths based on genetic algorithm is proposed in this paper. First, suitable channel sets in the terahertz band, which are mainly a combination of absorption lines and window regions, are determined. Then, to improve the efficiency of the generation of the retrieval database, based on the brightness temperature simulated by the atmospheric radiative transfer simulator (ARTS) for different cloud parameters, a fast forward operator is constructed using three-dimensional interpolation to simulate the brightness temperature difference between clear sky and a cloudy scene. Finally, an inversion model to retrieve the ice cloud base height, the effective particle diameter and the ice water path is established based on the genetic algorithm, and an analysis of the inversion errors is performed. The results show that the forward operator, constructed by the nearest interpolation, can accurately calculate the brightness temperature difference at a high speed. The proposed inversion method at terahertz wavelengths based on the genetic algorithm can achieve the expected scientific requirement. The absolute error of the cloud height is around 0.2 km, and the absolute error of the low ice water path (below 20 g/m2) is small, while the relative error of the high ice water path is generally maintained at around 10%, and the absolute error of the effective particle diameter is mostly around 4 μm.

Retrieval of ice cloud properties using passive terahertz wave radiometer from space has gained increasing attention currently. A multi-channel regression inversion method for passive remote sensing of ice water path (IWP) in the terahertz band is presented. The characteristics of the upward terahertz radiation in the clear-sky and cloudy-sky are first analyzed using the Atmospheric Radiative Transfer Simulator (ARTS). Nine representative center frequencies with different offsets are selected to study the changes of terahertz radiation caused by microphysical parameters of ice clouds. Then, multiple linear regression method is applied to the inversion of IWP. Combinations of different channels are selected for regression to eliminate the influence of other factors (i.e., particle size and cloud height). The optimal fitting equation are obtained by the stepwise regression method using two oxygen absorption channels (118.75 ± 1.1 GHz, 118.75 ± 3.0 GHz), two water vapor absorption channels (183.31 ± 1.0 GHz, 183.31 ± 7.0 GHz), and two window channels (243.20 ± 2.5 GHz, 874.4 ± 6.0 GHz). Finally, the errors of the proposed inversion method are evaluated. The simulation results show that the absolute errors of this method for the low IWP cases are below 7 g/m2, and the relative errors for the high IWP cases are generally ranging from 10 to 30%, indicating that the multi-channel regression inversion method can achieve satisfactory accuracy.

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.

Cirrus clouds play an important role in the energy budget and the hydrological cycle of the atmosphere. It is still one of the largest uncertainties in the global climate change studies. This is mainly attributable to the measurement discrepancies of cirrus parameters, especially the microphysical parameters, which are constrained by the existing methods. With THz wavelengths on the order of the size of typical cirrus cloud particles and therefore being sensitive to cirrus clouds, THz region is expected to have a promising prospect concerning measuring cirrus microphysical parameters (ice water path and effective particle size). In order to evaluate the effects of cirrus microphysical parameters on THz transmission characteristics and the sensitivity of cirrus in THz region, the THz radiation spectra at the top of atmosphere in the clear sky and the cloudy situations are simulated and calculated based on the atmospheric radiative transfer simulator. The effects of cirrus particle shape, particle size and ice water path on THz transmission characteristics are obtained by analyzing the brightness temperature difference between the two situations, and the sensitivity parameters that quantitatively describ the effects. The results indicate that cirrus particle shape, particle size and ice water path have different effects on the THz wave propagation. The cirrus effect varies also with channel frequency. Overall, in the low frequency channels, cirrus effects are enhanced with the increases of particle size and ice water path; in the high frequency channels, cirrus effects are more complicated and vary with particle size and ice water path. The effects are first enhanced and then turned into saturation. The THz wave is sensitive to cirrus cloud ice water path and effective particle size, and THz wave may be the best waveband for remote sensing of cirrus microphysical parameters in theory. For thin clouds, the sensitivity parameters are approximately constant, indicating that the spectral brightness temperature at the top of the atmosphere almost shows linear relationship with ice water path, and the sensitivity parameters increase with frequency increasing. For thick clouds, the sensitivity of cirrus to ice water path decreases and gradually becomes saturated, and the higher the frequency, the more quickly it tends to saturation level. Compared with the microwave and infrared, THz wave can provide many detailed information about cirrus. The two-channel look-up table indicates that THz wave passive remote sensing of cirrus may be a stable and effective method. The results will be conducible to developing the technology of THz wave remote sensing of cirrus microphysical parameters. Moreover, it is also beneficial to improving the cirrus detection precision.