A method for estimating optical properties of dusty cloud

Based on the scattering properties of nonspherical dust aerosol, a new method is developed for retrieving dust aerosol optical depths of dusty clouds. The dusty clouds are defined as the hybrid system of dust plume and cloud. The new method is based on transmittance measurements from surface-based instruments multi-filter rotating shadowband radiometer （MFRSR） and cloud parameters from lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. This new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on lidar-based total dusty cloud properties.     

Identification of cloud phase from PICASSO-CENA lidar depolarization: a multiple scattering sensitivity study

A fast Monte Carlo simulation scheme is developed to assess the impact of multiple scattering on space-based lidar backscattering depolarization measurements. The specific application of our methodology is to determine cloud thermodynamic phase from satellite-based lidar depolarization measurements. Model results indicate that multiple scattering significantly depolarizes backscatter return from water clouds. Multiple scattering depolarization is less significant for non-spherical particles. There are sharp contrasts in the depolarization profile between a layer of spherical particles and a layer of non-spherical particles. Although it is not as obvious as ground-based lidar observations, it is likely that we can identify cloud phase not only for a uniform cloud layer, but also for overlapping cloud layers where one layer contains ice and the other water droplets.     

高斯光束在双层云中传输的蒙特卡罗模拟

基于辐射传输理论, 利用蒙特卡罗方法模拟了无限窄(冲击函数)准直光束入射到典型水云以及冰水双层云时的后向散射特性, 进而将得到的冲击响应与高斯光束卷积, 得到高斯光束在云层中传输的多次散射特性. 文中给出了两种波束入射时水云以及冰水双层云的反射函数随径向r和天顶角α的变化关系, 并给出了光强在云层内部的二维分布图. 计算结果表明, 高斯光束入射时, 云层反射函数的特点与无限窄准直光束入射时有较大区别. 因此在利用激光雷达进行云层探测时需要考虑激光的散斑, 文中的方法可以为此提供理论依据.     

CALIPSO validation using ground-based lidar in Hefei (31.9°N, 117.2°E), China

Validation measurement in collaboration with existing lidar sites is a very important part of CALIPSO validation program, lidar site in Hefei is invited to collaborate in the CALIPSO validation program. In this paper, ground-based lidar measurements in Hefei performed in coincidence with CALIPSO overpass are presented, attenuated backscatter profiles at 532 nm and 1064 nm, as well as volume depolarization ratio profile at 532 nm measured by CALIPSO are compared with the ones measured by ground-based lidar. The comparisons indicate that CALIPSO measurements are consistent with the ground-based lidar measurements. However, due to the fact that horizontal distributions of aerosols in the lower troposphere and clouds are in most cases inhomogeneous, there are some differences between two lidar measurements in the boundary layer and clouds. The aerosol layer below the semi-transparent thick cloud can be detected by the 532 nm channel of CALIPSO in daytime.     

Lidar Multiple Scattering in Water Droplet Clouds: Toward an Improved Treatment

Although it has long been recognized that the effects of photon multiple scattering generally need to be accounted for in the analysis of lidar cloud returns, this is a difficult problem and current approaches are still rudimentary. The multiple scattering process is controlled by the size of the lidar beamwidth and the distance to the cloud, which jointly determine the lidar footprint, but cloud microphysical content (i.e., particle size, concentration, and shape) exerts a strong influence on the range distribution and depolarization of the returned energy. Since clouds are inherently inhomogeneous with height, it is our premise that vertically homogeneous cloud simulations based on idealized particle size distributions lead to misleading results. We offer a more realistic approach based on the contents of growing water droplet clouds predicted by a sophisticated adiabatic cloud model, which are offered for use as new standard vertically-inhomogeneous cloud models. Lidar returned signal and depolarization profiles derived from our analytical double-scattering method are given for inter-comparison purposes.Presented at the 7th International Workshop on Multiple Scattering Lidar/Light Experiments (MUSCLE7), July 21–23 1994, Chiba, Japan.     

Lidar model with parameterized multiple scattering for retrieving cloud optical properties

Cirrus clouds play an important role in the climate through their optical and microphysical properties. The problem with measuring optical properties of these clouds can be partially addressed by using lidar systems. This paper presents a new model for describing the multiple scattering contribution to the backscatter signal measured by the lidar system. The new lidar equation introduced this way, expresses the backscatter signal in terms of a polynomial function of the cloud scattering coefficient. Cloud optical properties such as the extinction coefficient and lidar ratio can be deduced from the new proposed lidar equation. Moreover, some cloud microphysical properties can also be inferred from these optical properties. The method is applied to lidar data collected by the micropulsed lidar operating at Nauru under the auspices of the US Department of Energy ARM program.     

基于粒子谱的多波长激光雷达近场大气光学参数校正方法

非同轴激光雷达由于存在发射激光与接收望远镜之间的不完全重叠区, 造成近场回波信号与真实大气信号不一致. 对于多波长激光雷达, 这种不一致更为突出和复杂. 然而, 近场大气是人类活动最集中的区域, 因此对多波长激光雷达近场信号进行校正, 对于了解和探究边界层大气具有十分重要的意义. 提出了一种利用粒子谱仪测量近地层气溶胶尺度谱分布并运用Mie 散射理论和低层大气指数衰减规律, 进而直接校正多波长激光雷达消光系数廓线近场信号的新方法. 通过对晴天、多云天气和雾天多波长气溶胶消光系数廓线近场信号的校正, 证明了该方法的可行性和实用性. 该方法着重考虑了多波长激光雷达比的波长依赖性和气溶胶粒子谱分布的天气相关性, 将该方法用于近地层大气消光系数廓线校正, 减少了由于不考虑这两个因素带来的消光系数廓线反演和校正的不确定性. 该方法对于研究不同天气情况下边界层内的大气气溶胶物理、光学特性具有一定的实用价值和借鉴意义.     

New dust aerosol identification method for spaceborne lidar measurements

Classification is a critical step in the backscatter lidar data processing to accurately retrieve extinction and backscatter profiles of atmospheric aerosols and clouds. Different schemes, such as the probability distribution functions (PDFs) method, have been used in the cloud and aerosol classification. In this paper, we attempt to use the support vector machine (SVM) to discriminate aerosols from clouds, with a focus on dust aerosol classification in China. To demonstrate the feasibility of the SVM classifier, we chose dust storms that occurred in the Gobi and Taklimakan deserts and observed by the CALIPSO lidar in spring time 2007. The results show that the SVM can correctly identify the dust storms.     

三波长激光雷达拟合卷云的粒子形状

卷云在全球出现的概率可达30%,其散射特性在气候模式、光辐射传输和遥感领域都具有非常重要的意义。卷云的散射特性主要由冰晶粒子形状、尺度谱、折射率等因素所决定。利用355, 532和1 064 nm三个波长激光雷达数据反演卷云的后向散射系数颜色比,利用模拟计算获得不同形状冰晶粒子的卷云在上述三个波长上的后向散射系数颜色比,通过拟合得出被测卷云的冰晶粒子形状。拟合结果表明,合肥上空卷云中冰晶粒子大部分可能呈聚合物状。     

Raman激光雷达探测气溶胶光学特性

介绍了武汉大学自行研制的Raman多通道激光雷达系统,给出了整个系统的设计原理及主要技术参量.详细描述了利用Raman激光雷达原理反演大气气溶胶消光系数、后向散射系数和激光雷达比等光学特性的方法,并对求解消光系数过程中的关键部分做了讨论分析.同时对武汉上空对流层低空大气气溶胶、云以及边界层等光学特性进行了实时探测反演.实验结果表明:该Raman多通道激光雷达系统在夜晚对低空气溶胶的垂直分布特性具有较好的探测能力,工作性能可靠.     

一种无需定标的地基激光雷达气溶胶消光系数精确反演方法

如何对低云下雾霾的激光雷达探测数据进行准确定标,一直是米散射激光雷达数据反演中一个有待解决的问题.对于低云和雾霾同时出现的天气,激光很难穿透云层,不能利用大气清洁层对激光雷达信号定标.而对于探测高度小于6 km的便携式米散射激光雷达,由于探测高度较低,也很难利用大气清洁层对激光雷达数据进行定标.本文根据Fernald前向积分方程的特点,提出了一种气溶胶消光系数迭代算法.通过对反演过程进行特定设置,每经过一次迭代,利用气溶胶消光系数迭代算法得到的气溶胶消光系数反演值与其真实值之间的差值就会相应减小.经过几次迭代后,气溶胶消光系数反演值与真实值之间的差值就会小到可以忽略不计.初步反演结果表明:利用气溶胶消光系数迭代算法,无需对激光雷达探测数据定标就能精确反演出气溶胶消光系数廓线.     

Mie理论递推公式计算散射相位函数

在激光雷达探测中,关于多次散射雷达回波的研究,散射相位函数是个非常重要的物理量。本文利用Mie理论的递推公式,对单一粒径介质的散射相位函数进行了计算,计算结果与散射理论中前、后向散射峰值大小随粒子半径的增大而增大相一致。同时,对非单一粒径介质的散射相位函数进行了计算,可用于大气、雾和云等气溶胶多次散射的研究。     

星载激光雷达云和气溶胶分类反演算法研究

激光探测对于获取云和气溶胶的垂直廓线,研究大气中云和气溶胶的垂直分布特征以及对全球气候变化的影响意义重大。而星载大气激光雷达云气溶胶分类算法的研究,对于激光雷达数据的参数反演及应用极为重要。针对激光条件下探测的云和气溶胶特有的光学信息和空间分布,结合概率统计与机器学习算法,提出了一种对于云/气溶胶、云相态及气溶胶子类型识别的分类算法,实现了星载激光雷达的大气特征层快速、有效分类。算法采用中国地区2016年CALIOP的观测数据作为样本数据,主要由三部分组成：（1）基于激光探测的云和气溶胶层不同的光学特性以及地理空间分布特征,分别构建了云和气溶胶的γ₅₃₂,χ,δ,Z和lat的五维概率密度函数,以此为基础构建云气溶胶的分类置信函数,并基于此实现了云和气溶胶类型的反演;（2）选取支持向量机(SVM)作为随机朝向冰晶粒子(ROI)和水云分类的算法模型基础,结合云层的γ₅₃₂,χ,δ Z和云顶温度T的概率密度函数构建ROI,水平朝向冰晶粒子(HOI)和水云的分类置信函数以修正SVM误分的特征层以及筛选出水云中少部分的HOI冰云,获得云相态的分类结果;（3）以各气溶胶子类型的光学以及空间分布特性为基础,采用决策树策略的气溶胶子类型识别算法实现了对气溶胶子类型的区分,完成气溶胶子类型的识别。利用现有CALIOP观测结果作为样本数据构建分类数据库,避免了对于地面以及航测数据的依赖,而机器学习则大大简化了算法的实现过程,使得云气溶胶分类更加高效。算法结果与正交极化云气溶胶激光雷达垂直特征层分布数据(CALIPSO VFM)产品对比分析：云层有98.51%一致性,气溶胶有88.43%的一致性,且白天比夜间一致性高。对于云相态分类,可以有效区分出水云和冰云,其中二者水云一致性高达93.44%。在气溶胶子类型反演结果中,可以准确识别出大多数气溶胶特征层子类型。霾、沙尘以及晴空三种典型情况下的反演结果均与CALIOP VFM产品数据具有较好的一致性。其中,霾天的大部分煤烟型以及污染型（污染沙尘以及污染大陆）气溶胶反演结果与VFM具有较好的一致性。沙尘天也能够获得较好的沙尘以及污染沙尘的结果。晴空为数不多的气溶胶层也取得了较为一致的结果。对于实现的星载大气激光雷达特征层分类算法,针对CALIOP激光测量的云气溶胶层的分类进行了重要的改进,在保证一定精度的基础上,简化了算法,提高了数据处理的效率,在下一步工作中,将分别构建不同时段和季节的分类模型以及提高两种不同偏振特性的冰云和气溶胶子类型的分类精度。     

An algorithm to determine cirrus properties from analysis of multiple-scattering influence on lidar signals

A Monte Carlo-based evaluation of the multiple-scattering influence on ground-based Raman lidar measurements is presented. The lidar returns from cirrus clouds are analyzed in order to evaluate vertical profiles of the extinction and backscattering coefficients. Results show that for the typical cirrus cloud, the presence of the multiple scattering can lead to an underestimation of the extinction coefficient by as large as 200% whereas the backscattering coefficient is almost unaffected for the Raman lidar technique. An algorithm to select one or a set of phase functions which fit to the lidar data is also presented. It is an iterative procedure based on Monte Carlo scattering simulation. By comparison of the experimental value of the lidar ratio, corrected for the multiple scattering influence, and the phase function used in the Monte Carlo simulation, one can determine a suitable phase function. The validity and sensitivity of the algorithm have been demonstrated by applying it to simulated cases. The application to some real cases indicates that our procedure allows for the establishing of a practical scattering model for the cirrus clouds.     

Two-Color Dual-Polarization Pulsed Bistatic Lidar for Measuring Water Cloud Droplet Size

The concept of a pulsed bistatic lidar for measuring water cloud particle size is presented. The method uses a two-color laser and a receiver with a polarization analyzer located at a suitable scattering angle. The dependence of Mie scattering on scattering angle, wavelength, and polarization is used to derive water cloud droplet size. The measurement was simulated for the C₁ and C₂ clouds, and the technique for determining mode radius was studied. The result shows the lidar system with a two-wavelength laser (1064 nm and 532 nm) and a dual-polarization receiver fixed at a scattering angle of around 178 deg can be used to measure a cloud particle size (mode radius) of 4 to 12 μm. Evaluation of the effect of multiple scattering showed that the method can be applied not only for the measurement at the cloud base but also in the cloud where multiple scattering is not negligible.     

Double-scattering calculations and laboratory dye-laser multiple scattering measurements

The multiple-scattering effects on laser pulses transmitted through and scattered by clouds and aerosol layers were calculated and discussed by several authors. Special attention has been given to the case of double-scattering and its effect on lidar returns. Contrary to the body of literature on the theory of multiple scattering, very few experimental works were conducted under controlled and well-defined conditions. This is especially true for the scattering properties at a given scattering angle as a function of the wavelength. In this work, scattering calculations developed by the group and theoretical laboratory measurements of the multiple scattering as a function of wavelength for two values of optical depth are presented.     

云和气溶胶探测星载激光雷达及其应用

介绍了在轨飞行的云和气溶胶探测星载激光雷达系统的原理和结构,该激光雷达能够探测全球范围内30km以下的云和气溶胶的消光系数和退偏比。利用CAUPSO实测数据,对发生在华北的一次沙尘天气进行分析,得到了河北省内沙尘消光系数和退偏比分布。结果表明,由沙尘气溶胶导致的消光系数最大可以达到0．22／kin;该次沙尘具有典型的层状结构,最可几层数为2,沙尘层的最大退偏比可以达到0．23。     

Estimates of radiation over clouds and dust aerosols: Optimized number of terms in phase function expansion

The bulk-scattering properties of dust aerosols and clouds are computed for the community radiative transfer model (CRTM) that is a flagship effort of the Joint Center for Satellite Data Assimilation (JCSDA). The delta-fit method is employed to truncate the forward peaks of the scattering phase functions and to compute the Legendre expansion coefficients for re-constructing the truncated phase function. Use of more terms in the expansion gives more accurate re-construction of the phase function, but the issue remains as to how many terms are necessary for different applications. To explore this issue further, the bidirectional reflectances associated with dust aerosols, water clouds, and ice clouds are simulated with various numbers of Legendre expansion terms. To have relative numerical errors smaller than 5%, the present analyses indicate that, in the visible spectrum, 16 Legendre polynomials should be used for dust aerosols, while 32 Legendre expansion terms should be used for both water and ice clouds. In the infrared spectrum, the brightness temperatures at the top of the atmosphere are computed by using the scattering properties of dust aerosols, water clouds and ice clouds. Although small differences of brightness temperatures compared with the counterparts computed with 4, 8, 128 expansion terms are observed at large viewing angles for each layer, it is shown that 4 terms of Legendre polynomials are sufficient in the radiative transfer computation at infrared wavelengths for practical applications.     

On the retrieval of ice cloud particle shapes from POLDER measurements

Shapes of ice crystals can significantly affect the radiative transfer in ice clouds. The angular distribution of the polarized reflectance over ice clouds strongly depends on ice crystal shapes. Although the angular-distribution features of the total or polarized reflectance over ice clouds imply a possibility of retrieving ice cloud particle shapes by use of remote sensing data, the accuracy of the retrieval must be evaluated. In this study, a technique that applies single ice crystal habit and multidirectional polarized radiance to retrieve ice cloud particle shapes is assessed. Our sensitivity studies show that the retrieved particle shapes from this algorithm can be considered good approximations to those in actual clouds in calculation of the phase matrix elements. However, this algorithm can only work well under the following conditions: (1) the retrievable must be overcast and thick ice cloud pixels, (2) the particles in the cloud must be randomly oriented, (3) the particle shapes and size distributions used in the lookup tables must be representative, and (4) the multi-angle polarized measurements must be accurate and sufficient to identify ice cloud pixels of randomly oriented particles. In practice, these conditions will exclude most of the measured cloud pixels. Additionally, because the polarized measurements are only sensitive to the upper cloud part not deeper than an optical thickness of 4, the retrieved particle shapes with the polarized radiance may only approximate those in the upper parts of the clouds. In other words, for thicker clouds with vertical inhomogeneity in particle shapes, these retrieved particle shapes cannot represent those of whole clouds. More robust algorithm is needed in accurate retrieval of ice cloud particle shapes.