Remote sensing of cirrus optical and microphysical properties from ground-based infrared radiometric Measurements-part II: retrievals from CRYSTAL-FACE measurements

The ground-based infrared radiance measurements acquired on July 14, 20, and 28, 2002 during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida Area Cirrus Experiment (CRYSTAL-FACE) campaign have been used for simultaneously retrieving the optical thickness and effective particle size on the basis of the retrieval algorithm reported in the preceding counterpart of this paper. The corresponding ice water path is derived from the retrieved optical thickness and effective particle size. Specifically, the data used for the retrieval include: 1) the infrared radiance spectrum observed by an atmospheric emitted radiance interferometer at the surface; 2) the sky condition and cloud height determined from a sky imager and a micropulse lidar; and 3) the sounding data for the profiles of temperature, pressure, and relative humidity. For these three case studies, the retrieved cirrus optical thickness, effective particle size, and ice water path are in the range of 0.2-1.5, 18-42 /spl mu/m, and 2-15 g /spl middot/ m/sup -2/, respectively. Furthermore, error analyses show that the retrieval uncertainties of the optical thickness and effective particle size are less than 15% if the uncertainty of water vapor vertical profile is within 5%. The retrieval errors are within 10% if the uncertainty of cloud temperature is within 7 K.     

Remote sensing of cirrus optical and microphysical properties from ground-based infrared radiometric Measurements-part I: a new retrieval method based on microwindow spectral signature

The surface radiance spectrum within the terrestrial infrared window (i.e., wavelengths between 8-12 /spl mu/m or wavenumbers between 833-1250 cm/sup -1/) is sensitive to the optical and microphysical properties of cirrus clouds. Numerous microwindows where atmospheric absorption is minimum exist in the spectral regions of 820-960 cm/sup -1/ and 1100-1240 cm/sup -1/. The minimum radiances at the microwindows in these two spectral regions can be fitted by using two linear lines. The slope of the fitting line for the spectral region of 820-960 cm/sup -1/ is sensitive to the effective size of ice crystals within cirrus clouds, whereas the intercept of the fitting line for the spectral region of 1100-1240 cm/sup -1/ is sensitive to the optical thickness of the clouds. Based on this spectral feature, a new retrieval method has been developed for simultaneously retrieving cirrus optical thickness and the effective particle size of ice crystals. Furthermore, the ice water path of cirrus clouds can be estimated from the retrieved values of cloud optical thickness and effective particle size.     

Spectroradiometric requirements for the reflective module of the airborne spectrometer ARES

The Airborne Reflective/Emissive Spectrometer is specified as a whisk-broom imaging spectrometer for remote sensing of land surfaces covering the wavelength regions 0.47-2.45 /spl mu/m and 8-12 /spl mu/m with 160 spectral bands. The instrument is being built by Integrated Spectronics, financed by the German Aerospace Agency (DLR) and the GeoResearch Centre Potsdam (GFZ) and will be available to the scientific community from end 2005 on. The spectroradiometric design is based on scientific requirements derived from three main application scenarios comprising vegetation, soil, and mineral sciences. Two of these are described in this letter. Measured or modeled reflectance spectra are input to a simulation model that calculates at-sensor radiance spectra, resamples them with the channel-specific response functions, adds different amounts of noise in the radiance domain, and performs a retrieval to get the corresponding noisy surface reflectance spectra. The retrieval results as a function of the sensor noise level are compared with the accuracy requirements imposed by the different application fields taking into account the technical boundary conditions. The final specifications account for the most demanding requirements of the three application fields: a spectral sampling distance of 13-14 nm in the 470-1800 nm region, and 12 nm in the 2000-2450-nm region. The required noise-equivalent radiances are 5, 3, and 2 nW/spl middot/cm/sup -2//spl middot/sr/sup -1//spl middot/nm/sup -1/ for the spectral regions 470-1000, 1000-1800, and 2000-2450 nm, respectively.     

The cloud phase discrimination from a satellite

A new technique to identify mixed-phase clouds but also clouds with supercooled water droplets using satellite measurements is proposed. The technique is based on measurements of the backscattered solar light at wavelengths 1.55 and 1.67 /spl mu/m in combination with cloud brightness temperature measurements at 12 /spl mu/m. For the first time, the concept of the phase index-temperature correlation plot (the P-T diagram) is introduced in the cloud remote sensing. Retrievals of cloud temperature and cloud phase index are performed using data from the Advanced Along Track Scanning Radiometer (AATSR) and Scaning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) both onboard the Envisat platform.     

Intercomparison of deep convective cloud fractions from passive infrared and microwave radiance measurements

The common method to detect deep convective clouds is from satellite infrared (IR) measurements, which is based on thresholds of cloud-top temperatures. However, thick cirrus clouds with high cloud tops are difficult to screen out using IR methods, resulting in an overestimation of deep convective cloud fractions. Two aircraft cases with simultaneous Millimeter-wave Imaging Radiometer, Multispectral Atmospheric Mapping Sensor, and ER-2 Doppler radar measurements during the Convection and Moisture Experiment 3 in August 1998 are analyzed to investigate the influence of high thick cirrus clouds on two previously developed IR methods. In contrast, a microwave method based on the brightness temperature differences between the three water vapor channels around 183.3 GHz of the Advanced Microwave Sounding Unit-B (AMSU-B) (183.3/spl plusmn/1,183.3/spl plusmn/3, and 183.3/spl plusmn/7 GHz) can screen out high thick cirrus clouds efficiently. The tropical deep convective cloud fractions (30/spl deg/S-30/spl deg/N) estimated by the IR methods and the AMSU-B method are compared. Although their geographical distributions are in well agreement with each other, the total fractions detected by the IR methods are about 2-3.5 times greater than that detected by the AMSU-B method. Moreover, the overestimation of deep convective cloud fractions by the IR method (11-/spl mu/m brightness temperature less than 215 K) can result in a displacement in the detected location of the deep convective clouds. The average thick cirrus clouds cover 2.5 times the area of the deep convective clouds that generates them.     

Snow and ice mask for the MODIS aerosol products

Atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua spacecraft. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-infrared channels centered near 0.86 and 1.24 /spl mu/m and a thermal emission channel near 11 /spl mu/m to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.     

中低云云底高的地基红外遥感的初步分析

在辐射传输模拟结果分析的基础上,提出利用云底高与下行红外辐射之间的单调关系进行云底高遥感反演的算法,并结合激光测云仪云底高实测数据对算法进行了初步验证。结果表明,该算法对中低云云底高反演的平均误差为107 m,具有较高的准确性。     

A stochastic model for active fire detection using the thermal bands of MODIS data

Active fire detection using satellite thermal sensors usually involves thresholding the detected brightness temperature in several bands. Most frequently used features for fire detection are the brightness temperature in the 4-/spl mu/m wavelength band (T/sub 4/) and the brightness temperature difference between 4- and 11-/spl mu/m bands (/spl Delta/T=T/sub 4/-T/sub 11/). In this letter, the task of active fire detection is examined in the context of a stochastic model for target detection. The proposed fire detection method consists of applying a decorrelation transform in the (T/sub 4/,/spl Delta/T) space. Probability density functions for the fire and background pixels are then computed in the transformed variable space using simulated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal data under different atmospheric humidity conditions and for cases of flaming and smoldering fires. The Pareto curve for each detection case is constructed. Optimal thresholds are derived by minimizing a cost function, which is a weighted sum of the omission and commission errors. The method has also been tested on a MODIS reference dataset validated using high-resolution SPOT images. The results show that the detection errors are comparable with the expected values, and the proposed method performs slightly better than the standard MODIS absolute detection method in terms of the lower cost function.     

Potential to estimate the canting angle of tilted structures in clouds from microwave radiances around 183 GHz

The effects of cloud structures on microwave radiances at frequencies from 89-190 GHz are investigated by simulations using the Goddard cumulus ensemble model data as input for a radiative transfer model. It was found that the brightness temperatures at these frequencies have different sensitivities to clouds with a tilted structure. The different sensitivities to altitude and amount of hydrometeors allow the estimation of the canting angle and tilt direction of tilted clouds using brightness temperatures at the water vapor channels at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. The estimated canting angle and tilt direction are in agreement with the model situation. This method provides a potential to estimate tilted convective structures from microwave radiometric observations at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. It is applied to a tilted storm observed from the National Aeronautics and Space Administration's ER-2 aircraft flying at about 20 km on August 26, 1998 during the third Convection and Moisture Experiment using the observed downlooking brightness temperatures at the water vapor channels of a Millimeter-wave Imaging Radiometer. The estimated results are in good agreement with the realistic storm situation obtained from the simultaneous observations of the ER-2 Doppler radar. This method also provides information about the vertical displacement of cloud structure and thereby to estimate the accurate location of surface rainfall. This is important when validating precipitation retrieval based on observations of the ice scattering above surface rainfall against surface rain observations using the microwave frequencies sensitive to high altitudes.     

Soil moisture retrievals from biangular L-band passive microwave observations

A simple approach for correcting the effect of vegetation in the estimation of soil moisture (w/sub S/) from L-band passive microwave observations is presented in this study. The approach is based on statistical relationships, calibrated from simulated datasets, which requires only two observations made at distinct incidence angles (/spl theta//sub 1/,/spl theta//sub 2/). A sensitivity study was carried out, and best retrieval remote sensing configurations, in terms of polarization and couple of incidence angles (/spl theta//sub 1/,/spl theta//sub 2/), were investigated. Best estimations of w/sub S/ could be made at H polarization, for /spl theta//sub 1/ varying between 15/spl deg/ and 30/spl deg/, and with a difference (/spl theta//sub 2/-/spl theta//sub 1/) larger than 30/spl deg/. The method was tested against two experimental datasets acquired over crop fields (soybean and wheat). The average accuracy in the soil moisture retrievals during the whole crop cycle was found to be about 0.05 m/sup 3//m/sup 3/ for both crops.     

A new method for retrieving band 6 of aqua MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key research instrument for the NASA Earth Observing System (EOS) mission. It was successfully launched onboard the Terra satellite in December 1999 and Aqua satellite in May 2002. Both MODIS instruments have been working well except that 15 of the 20 detectors in Aqua MODIS band 6 (1.628-1.652 /spl mu/m) are either nonfunctional or noisy. The striping in Aqua MODIS band 6 caused by its nonfunctional or noisy detectors has been a serious problem for MODIS snow products, which use band 6 primarily for snow detection. MODIS scientists have been using Aqua MODIS band 7 (2.105-2.155 /spl mu/m) instead of band 6 for computing the normalized difference snow index to continue detecting global snow coverage. The main objective of this letter is to retrieve Aqua MODIS band 6 using other bands based on their relationships in Terra MODIS. The band retrieval approach proposed in this letter is also very useful for the next generation of MODIS sensor-the Visible/Infrared Imager/Radiometer Suite (VIIRS) band M10 proxy data generation. Such proxy data can support the VIIRS prelaunch end-to-end testing, postlaunch calibration/validation, and data quality checking.     

联合统计信息与散射模型的GF-5 AHSI可见光影像薄云校正

针对高分五号可见短波红外高光谱相机AHSI (visible-shortwave infrared Advanced HyperSpectral Imager)可见光波段存在的薄云干扰,本文提出了一种联合统计信息与散射模型的校正方法。利用AHSI影像邻近波段间地表与云雾辐射的统计差异,实现对不同场景下相对薄云辐射RCR (Relative Cloud Radiance)的准确估计。基于此,根据不同波段的散射特性,分别利用分级暗目标统计和散射模型约束策略,获取可见光波段的绝对云辐射强度,最终实现影像校正。通过设置模拟与真实实验对方法的有效性和鲁棒性进行目视和定量检验。模拟实验中,可见光波段内的薄云干扰均可被有效地去除,校正结果与真实地表十分一致;此外,RMSE (RootMean-Square Error),MAE (Mean Absolute Error)和SA (Spectral Angle) 3个评价指标的值分别为1.9891,1.6822和0.4901,远小于对比方法。真实实验中,不同场景内的薄云可被有效抑制,在较为准确恢复降质地表信息的同时保持晴空区光谱特征;Q指数,SSIM (Structural Similarity Index)和UQI (Universal Quality Index)的计算结果优于对比方法。综上,本文提出方法可用于不同场景下高分五号AHSI影像可见光波段的薄云校正,可得到目视效果良好且光谱保真度高的校正结果。     

High-resolution airborne infrared measurements of ocean skin temperature

Airborne measurements of ocean skin temperature T/sub s/ are presented from the Coupled Boundary Layers, Air-Sea Transfer in Low Winds (CBLAST-Low) Pilot Experiment in August 2001 off Martha's Vineyard, MA. We used an infrared (IR) camera with a spatial resolution of 1 m or less and temperature resolution of roughly 0.02/spl deg/C. Using subframe sampling of the IR imagery, we achieve lower noise and higher spatial resolution than reported by previous investigators using IR radiometers. Fine-scale maps of T/sub s/ exhibit horizontal variability over spatial scales ranging from O(10 km) down to O(1 m) that are related to atmospheric and subsurface phenomena under low to moderate wind conditions. Based on supporting measurements of wind and waves, we identify coherent ramp-like structures in T/sub s/ with stratification breakdown and meandering streaky features with internal waves. Regional maps of T/sub s/ show the standard deviation for the region is /spl plusmn/1.04/spl deg/C, while the meridional and zonal variability is 0.23/spl deg/C /spl middot/ km/sup -1/ and 0.27/spl deg/C /spl middot/ km/sup -1/, respectively. This temperature variability results in meridional and zonal scalar heat flux variability of 7.0 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/ and 7.6 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/, respectively. Our results demonstrate the potential for airborne IR imagery accompanied by high-quality ocean data to identify T/sub s/ features produced by subsurface circulation.     

A bundle adjustment approach with inner constraints for the scaled orthographic projection

Bundle adjustment is a method for simultaneously calculating both the interior and exterior orientation parameters of a set of images, and the object-space coordinates of the observed points. In the case of long focal length lenses and narrow field-of-view (FOV) imaging situations, collinearity based (perspective projection) algorithms may result in linear dependencies between parameters that cause solution instability. The use of a scaled orthographic projection model based on linear algebraic formulations was therefore adopted to reduce this risk. Using quaternions, a new mathematical model is derived that includes the partial derivatives as well as the inner constraint equations for a scaled orthographic bundle adjustment. The model was then tested using two image sets of a single, small vessel (about 6 m length) with a cube target of known dimensions at two distinct ranges; perspective solutions were also calculated for comparison. RMS residual errors of 0.74-0.78 pixels associated with the new method compare favorably to a residual error range of 0.59-0.74 pixels using a perspective bundle adjustment of the same target points. Relative precisions (as a ratio of target size) of between 1:1650 and 1:750 have been achieved at ranges of 375 m and 850 m, respectively, given comparisons with the known cube dimensions. A third image dataset consisting of a network of 16 images was solved with a 1:2200 relative precision showing the new method can successfully handle high redundancy. For the experiments that were conducted, the new method was found to produce less precise results than the perspective bundle solution for a FOV of 0.50-0.65° where the object fills 5-8% of the image. However, it was found to match the precision of the perspective model (with an uncalibrated camera) for a FOV of 0.20-0.30° where the object of interest fills only 1-2% of the full image.     

基于地面观测资料的MODIS云量产品订正

通过对MODIS云量数字产品与气象站云量观测资料的对比分析,发现两者间存在较大偏差。本文以气象站观测云量资料为基准,提出了差值订正、比值订正、差值混合订正、比值混合订正和归一化混合订正5种MODIS云量数字产品的订正方法。结果表明:5种订正方法均有效,其中比值订正法最简单易行,且效果最好,是基于地面观测资料MODIS云量数字产品的最优订正方法。订正后的MODIS云量与气象站观测云量在空间分布特征和数值上都非常吻合。加密站验证结果表明:各月绝对误差平均值均小于5%。本研究为利用地面观测资料订正相关卫星数字产品提供了借鉴方法,有效发挥了卫星空间连续观测的优势,对高原、荒漠和山地等地面测站稀缺地区的相关研究具有重要意义。     

利用云下阴影实现陆地上空气溶胶和地表反射率的同时反演—理论方法和模拟

卫星探测信号包含大气中分子和粒子的散射贡献以及地表反射的贡献,在陆地上空二者的贡献相当,并且陆地地表反射率在时间和空间上极度不均一,因此,很难区分二者的各自贡献从而定量提取大气气溶胶和地表反射率,陆地上空气溶胶的反演也一直是一个极具挑战性的课题.而高分辨率卫星资料如TM5的可见光通道能够很好地区分云和云下阴影,如果云是不透光的,在阴影上空,卫星信号仅包含大气散射贡献和地表漫反射贡献,而在邻近的非阴影区上空,卫星探测信号还包含地表直接反射的贡献,根据这个原理,利用辐射传输模式分析了阴影区和非阴影区上空卫星探测的辐射量差别与地表反射率和大气气溶胶的关系,提出一种利用云下阴影来同时提取阴影上空大气气溶胶和地表反射率的单波长反演方案,并对气溶胶单次散射反照率,散射相函数,测量精度以及地表反射率的不均一性进行了敏感性分析.     

The influence of thermodynamic phase on the retrieval of mixed-phase cloud microphysical and optical properties in the visible and near-infrared region

Cloud microphysical and optical properties are inferred from the bidirectional reflectances simulated for a single-layered cloud consisting of an external mixture of ice particles and liquid droplets. The reflectances are calculated with a rigorous discrete ordinates radiative transfer model and are functions of the cloud effective particle size, the cloud optical thickness, and the values of the ice fraction in the cloud (i.e., the ratio of ice water content to total water content). In the present light scattering and radiative transfer simulations, the ice fraction is assumed to be vertically homogeneous; the habit (shape) percentage as a function of ice particle size is consistent with that used for the Moderate Resolution Imaging Spectroradiometer (MODIS) operational (Collection 4 and earlier) cloud products; and the surface is assumed to be Lambertian with an albedo of 0.03. Furthermore, error analyses are performed that pertain to the inference of the mixed-phase cloud effective particle size and optical thickness. Errors are calculated with respect to the assumption of a cloud containing solely liquid or ice phase particles. The analyses suggest that the effective particle size inferred for a mixed-phase cloud can be underestimated (or overestimated) if pure liquid phase (or pure ice phase) is assumed for the cloud, whereas the corresponding cloud optical thickness can be overestimated (or underestimated).     

遥感地面辐射观测中的视场效应问题研究

以典型的垄行作物玉米为研究对象，提出了一种新的视场效应分析方法：网格模型法。该方法将目标空间和测量空间网格化，然后在网格空间计算观测视场内的组分比例，进而确定组合信号值。本文采用网格模型法分析了垄行作物亮叶、暗叶、亮土、暗土四分量在传感器视场中面积权重变化、空隙率的变化、方向亮温的变化、红波段反射率的变化、红外波段反射率的变化以及植被指数NDVI的变化率，研究了不同观测角度情况下视场效应的变化。     

垄行作物玉米方向亮温野外测量中视场角影响的简单分析

基于透视原理、地面试验中对于较高目标的观测存在着一定的偏差。这种偏差随传感器高度、观测角度、视场角大小、观测位置等多个因素改变。由于垄行作物空间结构和温度分布的复杂性 ,在采用较大视场角测量方向亮温的地面实验中 ,将不可避免地存在着误差。采用一个简化的三分量二维结构模型对这种误差进行初步的分析与估算。亮温三分量分别为植被、被阳光照到的亮土和植被阴影下的暗土。作物的结构简化为剖面为矩形的无限长平行体。通过对这三个分量在传感器视场中面积权重的计算来模拟目标结构、传感器高度、位置、视场角大小、观测角度等因素对测量结果产生的影响。模拟结果表明 ,在垂直观测中 ,视场中的植被权重往往被高估 ,偏差随传感器高度的降低急剧增加。在倾斜观测中 ,由于一种互补效应的产生 ,偏差被限制在一个较低的范围内。经过分析 ,减小误差的最有效办法是提高传感器高度。最后 ,实验数据与模拟结果进行了比较。恰当地选取模型输入 ,两种数据能非常好的吻合。     

Diffusion Source Detection of Volcanic Ash Cloud Using MODIS Satellite Data

The massive volcanic ash cloud not only causes obvious global climate and environmental changes, but also threatens aviation safety under the background of globalization. The diffusion source detection is a key factor in the volcanic ash cloud monitoring and the diffusion research. Taking the Eyjafjallajokull’s volcanic ash cloud on April 19, 2010 in Iceland as an example, based on the analysis of the absorption spectrum characteristics in the thermal infrared spectral range, in this paper, a new diffusion source detection algorithm of volcanic ash cloud combining split window algorithm with SO₂ concentration distribution is proposed from the moderate resolution imaging spectroradiometer (MODIS) satellite remote sensing images; subsequently the ash radiance index (ARI) and absorbing aerosol index (AAI) are applied as contrast to the detection results. The results show that the proposed algorithm can effectively detect the diffusion source of volcanic ash cloud, and has high consistency with the ARI and AAI distributions, and has certain potential applications in improving the detection effect of volcanic ash cloud and prediction accuracy of diffusion model.