Passive Remote Sensing of Ice Cloud Properties at Terahertz Wavelengths Based on Genetic Algorithm

Lei Liu,Pingyi Dong,Shulei Li,Chensi Weng,Letu Husi,Shuai Hu

doi:10.3390/rs13040735

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.

Highlights

Ice clouds play a key role in regulating the radiant energy flow in the earth–atmosphere radiation budget through scattering and absorption processes [1]
Focusing on the remote sensing technology at terahertz wavelengths, we demonstrated its feasibility in ice cloud detection and introduced an inversion method based on multiple lookup tables
We applied the genetic algorithm to the inversion of ice cloud properties at terahertz wavelengths

Summary

Introduction

Ice clouds play a key role in regulating the radiant energy flow in the earth–atmosphere radiation budget through scattering and absorption processes [1]. The physical characteristics of ice clouds are important parameters in climate and weather forecast models—for instance, cloud height, particle size and ice water path [2,3]. The current remote sensing of ice cloud parameters is insufficient, leading to considerable uncertainties in numerical weather prediction (NWP) and climate models, where accurate presentation of ice clouds is needed to optimize the assimilation [4,5]. The present methods to retrieve ice cloud parameters mainly include passive and active sensors, which have advanced our knowledge of ice clouds, but there is still a large degree of uncertainty in the measurements. Passive remote sensing in microwave bands displays better penetration for thick clouds, the channel frequencies in the existing sensors are generally no more than 190 GHz and relatively sensitive to large ice particles [10]

Objectives

Methods

Findings

Conclusion