One-dimensional solar radiative transfer: Perturbation approach and its application to independent-pixel calculations for realistic cloud fields

The radiative transfer perturbation theory (RTPT), which has already been introduced in atmospheric radiative transfer several years ago, is applied to cloud related problems. The RTPT requires the solution of the radiative transfer equation in the forward and the adjoint mode. The basic principles of this technique are presented as well as its extensions to isotropic surface reflection and its conjunction with the Hermite interpolation. This set of methods is applied to different atmospheric conditions including realistic cloud scenes. The results are compared with the usual (forward) independent-pixel calculations with respect to errors of individual pixels and domain-averaged values. The RTPT turns out to be sufficiently accurate in the case the clouds’ internal vertical variations remain moderate. It is also shown that, depending on the specific radiative transfer problem, the RTPT can offer some advantages on computational speed. However, the limitations of the RTPT with regard to realistic clouds are addressed as well.     

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.     

Three-dimensional polarized Monte Carlo atmospheric radiative transfer model (3DMCPOL): 3D effects on polarized visible reflectances of a cirrus cloud

A polarized atmospheric radiative transfer model for the computation of radiative transfer inside three-dimensional inhomogeneous mediums is described. This code is based on Monte Carlo methods and takes into account the polarization state of the light. Specificities introduced by such consideration are presented. After validation of the model by comparisons with adding-doubling computations, examples of reflectances simulated from a synthetic inhomogeneous cirrus cloud are analyzed and compared with reflectances obtained with the classical assumption of a plane parallel homogeneous cloud (1D approximation). As polarized reflectance is known to saturate for optical thickness of about 3, one could think that they should be less sensitive to 3D effects than total reflectances. However, at high spatial resolution (80 m), values of polarized reflectances much higher than the ones predicted by the 1D theory can be reached. The study of the reflectances of a step cloud shows that these large values are the results of illumination and shadowing effects similar to those often observed on total reflectances. In addition, we show that for larger spatial resolution (10 km), the so-called plane-parallel bias leads to a non-negligible overestimation of the polarized reflectances of about 7–8%.     

Retrieval of tropospheric NO2 columns from satellite measurements in presence of cirrus: A theoretical sensitivity study using SCIATRAN and prospect application for the A-Train

A theoretical sensitivity study of the influence of cirrus cloud properties on tropospheric NO₂ columns retrieved from the spaceborne Ozone Monitoring Instrument (OMI) measurements is performed. It is conducted within the framework of the synergetic use of A-Train sensors to derive more representative trace gas products. We aim to study the potential effects of cirrus clouds on tropospheric NO₂ retrievals using a retrieval algorithm that, unlike the OMI Standard and DOMINO algorithms, does not correct for the effects of clouds. The sensitivity study is based on the radiative transfer code SCIATRAN that performs both simulations of top of atmosphere (TOA) reflectances as measured by an OMI-like band and tropospheric NO₂ column retrievals based on the differential optical absorption spectroscopy (DOAS) method. The results of the sensitivity study show that if a correction for cirrus clouds is not included in our simple retrieval that does not account for clouds in the first place, the tropospheric column can be underestimated by 55%. This underestimation depends strongly on cirrus parameters as, in order of importance, cloud fraction, cloud optical depth, asymmetry factor of cirrus cloud phase function and cloud top height. The perspective of the synergy between OMI and cloud information obtained from cloud-derived products of the A-Train is evaluated in two parts by applying a simple cloud correction scheme based on the independent pixel approximation (IPA). Firstly, we evaluated the tropospheric NO₂ column retrievals error caused by uncertainties in cirrus cloud properties. Secondly we studied the influence of subpixel cloud optical depth variability on NO₂ retrievals. From our simulations, it is demonstrated that the error will be reduced significantly if the cloud fraction is lower or equal to 0.5. In this case, the cloud fraction and the cloud optical depth must be known within accuracy less than 0.05% and 50%, respectively. The cloud top height and the asymmetry factor must be known within uncertainty of at least 1 km and less than 0.05, respectively. The latter result shows that the uncertainty of the asymmetry factor is a major source of error in the cloud correction for tropospheric NO₂ retrieval in the presence of cirrus.     

霾光谱特性分析与卫星遥感识别算法

近年来,我国频繁发生的灰霾污染事件和常态性的高细颗粒物浓度(PM_2.5),已经引起了全世界范围的广泛关注。卫星遥感能够对大气污染进行快速准确地监测。然而在大气遥感领域具有代表性的中分辨率成像光谱仪(NASA/MODIS),其云监测和暗像元反演算法通常把灰霾当做薄云、雾或地表亮目标处理,无法反演霾天的气溶胶光学厚度(aerosol optical depth, AOD)。笔者研究了云、雾、霾、地表覆盖等不同像元在可见光、近红外以及红外通道的光谱特性。基于MODIS数据,参考相关的云监测和气溶胶反演算法,选取多个对灰霾敏感的光谱通道,计算表观反射率和亮度温度。针对不同波段,分别探讨了霾与薄云、低层云、雾、浓密植被和地表亮目标等像元之间的光谱差异,统计灰霾分布的阈值区间,并设计基于MODIS卫星遥感数据的灰霾识别自动处理流程。通过对2008年华北平原春夏两个重霾事件进行测试,该算法的霾分布监测结果与卫星真彩图具有较好的一致性。基于北京和香河AERONET站点观测的高AOD数据,验证了本算法的霾识别率接近80%,在一定程度能够弥补MODIS标准气溶胶算法用于灰霾天的不足。最后,分析了灰霾识别过程中的主要误差来源,并提出了基于霾纹理特征,以及其他辅助数据支撑的改进方法。     

Stochastic radiative transfer in multilayer broken clouds. Part II: validation tests

In the second part of our two-part paper, we estimated the accuracy and robustness of the approximated equations for the mean radiance that were derived in Part I. In our analysis we used the three-dimensional (3D) cloud fields provided by (i) the stochastic Boolean model, (ii) large-eddy simulation model and (iii) satellite cloud retrieval. The accuracy of the obtained equations was evaluated by comparing the ensemble-averaged radiative properties that were obtained by the numerical averaging method (reference) and the analytical averaging method (approximation). The robustness of these equations was estimated by comparing the domain-averaged radiative properties obtained by using (i) the full 3D cloud structure (reference) and (ii) the bulk cloud statistics (approximation). It was shown that the approximated equations could provide reasonable accuracy (∼15%) for both the ensemble- and domain-averaged radiative properties.     

Combining the independent pixel and point-spread function approaches to simulate the actinic radiation field in moderately inhomogeneous 3D cloudy media

A fast method is presented for gaining 3D actinic flux density fields, F_act, in clouds employing the Independent Pixel Approximation (IPA) with a parameterized horizontal photon transport to imitate radiative smoothing effects. For 3D clouds the IPA is an efficient method to simulate radiative transfer, but it suffers from the neglect of horizontal photon fluxes leading to significant errors (up to locally 30% in the present study). Consequently, the resulting actinic flux density fields exhibit an unrealistically rough and rugged structure. In this study, the radiative smoothing is approximated by applying a physically based smoothing algorithm to the calculated IPA actinic flux field.     

Cloud 3D effects on broadband heating rate profiles: I. Model simulation

Solar broadband heating directly drives the atmospheric and ocean circulations, and is largely determined by cloud spatial 3-diminesional (3D) structures. To study the cloud 3D effects on radiation, a 3D broadband Monte-Carlo radiative transfer model, along with an Independent Pixel/Column Approximation (IPA) method, is used to simulate radiation and heating rate of three typical cloud fields generated by cloud resolving models (CRM). A quantitative and statistical estimation of cloud 3D effects has been developed to investigate the impact of cloud 3D structures on both heating rate strength, STD_Bias, and vertical distribution, CorrCoef. The cloud 3D structures affect some clouds more in heating rate strength and others more in vertical distribution. It is crucial to use the combination of CorrCoef and STD_Bias for better quantitative evaluation of the 3D effects. Furthermore, there is no simple way to define a critical resolution (or average radius), within which the IPA heating rate profiles closely represent the true 3D heating rate profiles. The critical radius (or resolution) strongly depends on solar incident angle as well as cloud vertical distribution. Also, the critical radii for clear-sky columns are larger than for cloudy columns, although the corresponding STD_Bias for clear-sky columns are smaller than for cloudy columns. Analysis based on two different statistical average methods illustrates that the cloud 3D effects due to the dimensionality difference between the 3D clouds (circle average) and 2D clouds (line average) significantly impact on the heating rate profiles.     

An Improvement of Spatial Carrier Phase-shifting Method

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An Improvement of Spatial Carrier Phase-shifting Method

Spatial-carrier phase-shifting method (SCPM) retrieves the phase distribution from carrier interferograms by assuming that the phases of the processed pixel and its adjacent pixels are uniform,which introduces considerable theoretical error. A new method is presented in this paper to improve the SCPM accuracy: (1) A quadric curve is used to describe the phase distribution of the adjacent pixels; (2) The linear and quadric terms of the phase are considered as phase shifter errors; (3)Suitable phase shifting algorithms insensitive to these errors are selected. Two "5-step" algorithms are used and their properties are analyzed. An example ofphase retrieving by SCPM is given and the result shows that SCPM has high theoretical accuracy. With the potential high accuracy, ability of measuring dynamic phase andcomputational simplicity, SCPM will become a much more useful phase measurement method.     

图样间联想光学神经网络模型存贮分析及两层异联想识别模型的构造

本文详细讨论了图样间联想网络的最大存贮容量,给出了实现图样间异联想的两个充分条件.在此基础上,利用改进的图样间异联想算法构造了两层异联想模型(THA)用于图样识别,网络判辨率与恢复率较图样间自联想识别均有很大提高;且其互连权矩阵更加简单稀疏并可平面化,光学实现更为简便.     

3D shape measurement of a ground surface optical element using band-pass random patterns projection

For manufacturing a fine optical glass lens, it is important to obtain a 3D profile of a semi-finished product with a rough surface. We develop an active binocular 3D scanning setup to measure the 3D profile of a rough surface optical element. Two cameras simultaneously capture the band-pass binary random patterns which are projected on the target object. The highlight of this system is using the temporal correlation technique to determine the stereo correspondence between the pixels of the two cameras. The 3D point cloud can be reconstructed by the triangulation principle. Experiment results confirmed that this method effectively measures the rough surface of an optical element with sufficient accuracy.     

MAX-DOAS仪器观测大气Ring效应及对气溶胶参数的敏感性研究

Ring效应是指大气中O₂和N₂分子对太阳光的转动拉曼散射致使太阳夫琅禾费结构变浅(被填充)的现象。大气气溶胶能够改变光子在大气中的光程和大气散射性质,进而影响到光子发生转动拉曼散射的几率(RSP),最终影响填充效应。通过观测RSP在不同气溶胶状态下的变化,可以反演得到气溶胶参量信息。采用地基多轴差分吸收光谱(multi-axis differential optical absorption spectroscopy, MAX-DOAS)方法在晴朗无云天气下对Ring效应进行了观测,并把测量值和模型值进行了对比,两者一致性较好;选取大气辐射传输模型McArtim研究了在不同大气条件下Ring效应对气溶胶参数等的灵敏度,结果表明在大多数测量情况下,气溶胶光学厚度和边界层高度对RSP影响较大,在90°仰角时,AOD从0.1增加到1,RSP减少了24.6%,边界层高度从1 km增加到3 km,RSP增加了4.4%。研究表明,Ring效应对气溶胶光学厚度和边界层高度较为敏感,这为反演气溶胶的垂直分布提供了一种新方法。     

Complex noise suppression using a sparse representation and 3D filtering of images

A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.     

结合稳健中国余数定理的合成孔径声呐多子带运动补偿算法

针对运动误差过大导致基于相位的时延估计发生模糊的问题,提出了一种多子带处理和稳健中国余数定理结合的合成孔径声呐运动补偿方法。该方法利用前后两帧回波在多个子频带上的相位差获得模糊时延估计,再根据模糊时延之间的关联性,应用稳健中国余数定理估计真实的时延,最后通过所估计的时延对原始回波进行校正。湖试数据处理结果表明该方法能精确补偿运动误差对成像的影响,进行运动补偿后,包裹目标成像结果的方位向虚假目标被有效消除,且目标的轮廓也变得更加清晰;对线缆目标的成像结果进行斜距向剖面分析,剖面图的-3 dB宽度由运动补偿前的9.05个像素点缩小为运动补偿后的2.06个像素点,线缆目标的聚焦程度明显增强。      

用于反演云层高度的记忆式滑动窗口积分算法

 记忆式滑动窗口积分算法选取一定宽度的窗口,从地面开始滑动,对窗口内的信号进行积分,根据积分值和前一时刻的云层信息来反演云层高度。该算法可消除信号中的噪声,叠加放大信号中的云层信息,将云层与气溶胶加以区分。用该算法处理了Vaisala云高仪的数据,并与云高仪的结果进行了对比,结果表明,记忆式滑动窗口积分算法在反演尝云层信息信息时具有较高的准确性和可靠性。     

Estimation of surface snow properties using combined millimeter-wave backscatter and near-infrared reflectance measurements

Knowledge of surficial snow properties such as grain size, surface roughness, and free-water content provides clues to the metamorphic state of snow on the ground, which in turn yields information on weathering processes and climatic activity. Remote sensing techniques using combined concurrent measurements of near-infrared passive reflectance and millimeter-wave radar backscatter show promise in estimating the above snow parameters. Near-infrared reflectance is strongly dependent on snow grain size and free-water content, while millimeter-wave backscatter is primarily dependent on free-water content and, to some extent, on the surface roughness. A neural-network based inversion algorithm has been developed that optimally combines near-infrared and millimeter-wave measurements for accurate estimation of the relevant snow properties. The algorithm uses reflectances at wavelengths of 1160 nm, 1260 nm and 1360 nm, as well as co-polarized and cross-polarized backscatter at a frequency of 95 GHz. The inversion algorithm has been tested using simulated data, and is seen to perform well under noise-free conditions. Under noise-added conditions, a signal-to-noise ratio of 32 dB or greater ensures acceptable errors in snow parameter estimation.     

Determination of the concentration of aerosol particles in a vertical atmospheric column from satellite measurements of the spectral optical depth

We propose a method for fast retrieval of the inhalable particle concentration (PM_2.5 and PM₁₀) in a vertical atmospheric column from satellite measurements of the aerosol optical depth (AOD) without using a priori assumptions concerning the refractive index and the aerosol particle size distribution function. The method is based on a polynomial regression between PM_2.5, PM₁₀, and AOD at the wavelengths 466 nm and 644 nm, established from AERONET data. We have studied the sensitivity of the method to errors in the optical measurements and have estimated the errors in retrieval of PM_2.5 and PM₁₀ for different atmospheric situations. We carry out parametrization of the regressions on the value of the integrated air moisture content.     

Simultaneous compensation for spatial and temporal dispersion of acousto-optical deflectors for two-dimensional scanning with a single prism

The dispersive nature of the acousto-optical deflector (AOD) presents a challenge to applications of two sequential orthogonal AODs (a two-dimensional AOD) as XY scanners in multiphoton microscopy. Introducing a prism before the two-dimensional (2D) AOD allows both temporal and spatial dispersion to be compensated for simultaneously. A 90 fs laser pulse was broadened to 572 fs without compensation, and 143 fs with compensation. The ratio of long axis to short axis of the exiting laser beam spot was 3.50 without compensation and 1.14 with compensation. The insertion loss was 37%. Two-photon fluorescence microscopy used the compensated 2D AOD scanner to image a fluorescent microsphere, which improves signal intensity -15-fold compared with the uncompensated scanner.     

Kmeans聚类与多光谱阈值相结合的MODIS云检测算法

采用Kmeans聚类与多光谱阈值相结合的方法进行云检测.在地物光谱分析的基础上,应用Kmeans聚类算法对聚类特征数据初始分为两类,第一类为云、烟雾和雪,而植被、水体和陆地等其他下垫面为第二类;然后应用光谱阈值判断排除烟雾和雪等的干扰,对MODIS数据中的云体实现检测.还研究了我国典型区域在不同季节、小同时棚的数据.在...