毫米波/亚毫米波冰云探测辐射计模型仿真

冰云对全球气候的显著影响,使得利用毫米波/亚毫米波辐射计探测冰云分布持续受到关注。为从辐射计亮温测量值中反演出冰云粒子参数,完善的辐射传输正演模型起到非常关键的作用。针对即将发射的冰云成像仪毫米波/亚毫米波星载辐射计,建立起了包含粒子散射在内的完整的辐射传输模型。传输模型读取大气廓线及云层粒子微观参数,仿真计算得到辐射计各通道的辐射亮温。给出了辐射传输模型的详细配置,并分析了不同通道对云层粒子的敏感性。结果表明：冰云成像仪各通道对冰云粒子、雪粒子均有很强的敏感性,但只有低频率通道能探测到水云粒子、雨粒子的变化。辐射计通道中,不同的中心频率对冰晶粒子敏感度不同,从而可使辐射计探测不同高度、不同特性的粒子。对于同一中心频率,不同频偏对应不同的大气透明度,使得辐射计可进一步探测到不同高度的云层信息。仿真工作将会为后续的毫米波/亚毫米波辐射计设计、反演算法研究等打下良好的基础。     

改进的浓密植被法反演Landsat-8 OLI气溶胶光学厚度

针对利用传统浓密植被法难以准确确定地表反射率的不足,分析了Landsat-8 OLI影像红蓝波段的地表反射率与归一化植被指数、散射角对短波红外波段(2.1μm)地表反射率的关系。分析表明,红、蓝波段与短波红外波段(2.1μm)地表反射率之间的比例关系随归一化植被指数和散射角的改变而不同,据此提出构建用于确定红、蓝波段地表反射率的关系模型,用于实现气溶胶光学厚度的反演。选取美国中东部云覆盖较小的地区进行气溶胶反演,使用AERONET站点数据进行反演结果的验证。结果表明,使用该模型得到反演结果与AERONET站点的实测值具有很好的一致性,拟合结果较好;大约70%的数据位于误差线内,反演结果满足精度要求。     

卫星微波遥感受水成物影响及其敏感度分析研究

对卫星微波遥感水成物辐射效应的理解在云参数反演以及数值预报中使用受云和降水影响卫星资料等诸多应用中都是十分重要的。使用快速辐射传输模式CRTM,通过中尺度数值模式WRF预报输出的水成物信息,分析了云水、雨水、冰、雪和霰5类水成物对卫星微波遥感的影响及水成物辐射效应给卫星微波观测计算带来的误差特征,设计敏感性试验研究了卫星微波遥感对水成物含量、有效粒子半径和垂直分布层次的敏感度。结果表明:卫星微波遥感在多个探测频率上受水成物的影响较大,云水和雨水的影响主要以增温为主,雨水的影响幅度要大于云水,在影响最大的AMSUA 2通道,云水和雨水的增温分别可达到8 K和17 K左右。冰、雪和霰散射效应对卫星微波遥感的影响则主要以降温为主;相比之下,霰的影响量级最大,雪次之,两种水成物对微波遥感影响最大的通道为AMUSB的2通道,可达到-18 K和-9 K左右,冰的作用微乎其微。卫星微波遥感探测通道对水成物含量的敏感与受水成物辐射效应影响对应一致。卫星微波遥感不受云水和冰水粒子有效半径变化的影响,对雨、雪和霰大降水粒子的有效粒子半径较为敏感。同时,敏感性和影响程度随探测频率的不同呈现出影响的复杂性。此外,卫星微波探测对水成物垂直分布层次的敏感性表现为对水成物敏感探测通道的变化,其中AMSUB 3~5通道对高层水物质,包括冰、雪和霰垂直廓线的变化最为敏感。     

基于多角度微波辐射亮温数据反演冬小麦光学厚度

基于高级积分方程模型(Advanced Integrated Emission Model,AIEM),构建了包含宽范围土壤参数的C波段(6.925GHz)多角度裸露土壤发射率模拟数据库,利用该模拟数据分析了不同观测角度的裸露土壤发射率极化差之间的关系。在此基础上,结合ω-τ零阶辐射传输模型发展了C波段低矮植被光学厚度反演算法,并利用地基微波辐射计观测数据开展了冬小麦的光学厚度反演。结果显示,冬小麦光学厚度反演结果与实测冬小麦LAI在变化趋势上具有较好的一致性,反演算法具有一定的可行性。     

利用MODIS数据计算中国地表短波净辐射通量的研究

地表短波净辐射是辐射能量的重要收入部分,对研究地表辐射平衡、地气能量交换以及各种天气气候的形成都具有决定性的意义.目前国际上利用卫星数据计算地表短波净辐射大多采用空间分辨率较低的宽通道反照率数据(如ERBE卫星数据,空间分辨率为35km),这难以满足局部尺度的能量平衡和蒸散等研究的需要.本文利用空间分辨率达1km的窄通道多光谱MODIS卫星数据,通过相关处理计算,无需气象数据和地面测量数据的参与,就获得了中国的地表短波净辐射通量分布图.经与禹城地区地面实测数据对比可知,晴空时均方根误差小于20 W/m2,有云时均方根误差小于35 W/m2,表明本文使用的地表短波净辐射反演方法适合中国范围地表短波净辐射的计算.     

双通道算法与MODIS算法反演中国近海气溶胶光学特性的对比研究

利用双通道和IMAPP气溶胶反演算法处理TERRA/MODIS L1B数据得出中国近海气溶胶的光学厚度,与AERONET太阳光度计的反演结果作对比分析,验证了反演方法的可行性。同时,对各海域的反演结果及表征粒子谱宽度的Angstrom指数(α)的变化情况进行了分析,结果表明：在东海和日本以南等广阔海域,两种反演算法的结果同AERONET太阳光度计的观测结果基本一致,相关性较好;在渤海和黄海近海岸一带两者气溶胶光学厚度的反演值均偏高,其原因主要是由这些海域的二类水体的影响导致的。探讨分析了这些海域的水域特征及光学特性,为研究发展适合中国近海气溶胶特性的反演算法提供了依据。     

暗目标法从风云三号数据反演陆地气溶胶

针对2013年发射升空的FY-3C星的中分辨率光谱成像仪(MERSI)应用气溶胶反演较少的不足,开展了暗目标法反演陆地气溶胶的应用研究,为研究气候变化、大气环境监测等提供数据支撑。在MODIS暗目标法基础上,针对FY-3C/MERSI数据反演陆地气溶胶,使用6SV完成辐射传输计算建立大气参数查找表,采用IDL的HDF5读写接口完成数据提取与辐射定标,利用蓝光波段(470nm)与短波红外波段(2 130nm)的线性关系分离出大气信息,插值大气参数查找表得到气溶胶光学厚度(aerosol optical depth,AOD)。2014年5月15日华北地区的算法应用表明,该算法能较好地监测空气污染的分布。2014年5月的MERSI数据反演结果与同期AERONET香河站的气溶胶产品比对表明,该算法与地面观测结果有着较好的一致性,相关系数优于0.8。     

红外亮温和云参数信息对降水识别能力的研究

利用卫星可见光/红外资料遥感降水有其独特的优势,依据该资料反演获得的云光学厚度和云滴有效半径被证明能够对降水判别产生明显效应。以现有两种降水云识别方案为基础,进一步考察云顶红外亮温信息的价值,探索了红外亮温、云光学厚度及云滴有效半径综合信息对降水事件的指示能力。选取2006和2007年夏季热带测雨卫星(TRMM)可见光/红外辐射计(VIRS)和测雨雷达(PR)的融合观测资料,以PR探测为真值,采用3种二元预报评价因子对识别结果进行了评估,并与现有降水云识别方案进行了比较。研究表明:由于引入了云顶红外亮温信息,降水云识别能力比仅采用光学厚度和有效半径的方案明显提高。无论陆地还是海洋区域,新增红外亮温信息之后,能够更有效地识别弱降水,出现降水误判和漏判的区域面积比现有方案更小。特别是在洋面上,降水云识别比率达79%,而同时对非降水云的误判率仅为8%,相应其CSI、ETS和HSS因子值明显提升。以此为基础建立的IPCTC方案适用于常见星载多通道可见光/红外探测仪,可应用于卫星实时降水监测。     

月球表面微波主被动遥感的建模模拟与反演

探测月球和其它外星球是我国空间遥感与深空探测的又一轮新课题。研究地球遥感中星载被动遥感辐射计、主动遥感高分辨率合成孔径雷达等如何应用于月球和其它外星球的探测是一项十分有意义的工作。了解月球表层的月壤与月岩的物质状态及其分布,对于月球资源的科学认识、以及未来月球探测、登月与月球开发,以及其它外星球探测均具有十分重要的意义。先讨论微波被动遥感月球表面辐射的模拟和由微波辐射反演月壤厚度。由月球表面数字高程和月壤厚度实测点数据建立月球表面高度与月壤厚度的一种对应关系,构造整个月球表面月壤厚度的试验性分布。根据克莱门汀的紫外可见光光学数据,计算整个月球表面月壤中FeO+TiO2含量分布,给出整个月球表面月壤介电常数分布。由月球表层温度的观测结果以及月壤的导热特性,给出月尘层与月壤层温度随纬度分布的经验公式。在这些条件基础上,建立月尘、月壤、月岩3层微波热辐射模型。由起伏逸散定理,模拟计算月壤低耗散介质层多通道辐射亮度温度。以此辐射亮度温度模拟加随机噪声为理论观测值,按3层模型提出月壤层厚度反演方法。由于高频通道穿透深度小,由高频通道的辐射亮度温度按照两层尘-月壤微波热辐射模型反演月尘层与月壤层的物理温度。并以此为已知参数,由穿透深度较大的低频通道的辐射亮度温度反演月壤层厚度,对于反演的相对误差也进行了讨论。在研究微波主动遥感方面,提出低空飞行全极化L波段雷达窄脉冲探测月壤层厚与层结构的建议。此时采用一层具有上下随机粗糙界面的有耗 介质层月壤层模型,在下垫月岩粗糙界面上有一层随机分布的碎石散射体。推导了包含面散射、体散射,以及面体相互作用7种散射机制的全极化脉冲波Mueller矩阵解。以月壤特征参数(月壤层厚、FeO+TiO2金属含量、介电常数,界面粗糙度、碎石分布等)为函数,用时域Mueller矩阵解数值模拟来验证方法可行性。L波段窄脉冲极化回波波形能用于反演或估算月壤厚度与分层结构。     

短波红外CO_2反演辐射传输模式综述

高精度的辐射传输计算是保证短波红外卫星遥感反演CO2精度的重要因素之一。地球大气散射辐射一般是偏振的,传统的标量辐射传输模式计算精度无法满足需求;特别是针对美国OCO-2(Orbiting Carbon Observatory-2)、中国TanSat(全球二氧化碳监测科学实验卫星)等跟踪主平面仪器,矢量的辐射传输模式更为必要。在二氧化碳监测卫星的目标模式下,卫星观测角度变化较大,平行平面大气假设不再适用,需要采用伪球面近似以提高精度。本文对适用短波红外CO2反演的辐射传输模式进行总结。首先介绍了基于不同辐射传输方程数值解法的多种辐射传输模式发展概况。针对CO2反演对权重函数的需求,线性化模式可以提供解析权重函数和更为稳定高效的计算方案。接着,简要总结各种线性化矢量辐射传输模式,并进一步分析比较几种CO2反演中常用矢量模式的异同。最后,讨论CO2高精度反演对模式速度的需求和加速优化计算的必要性,对辐射传输加速算法研究现状进行总结。     

利用MODIS云产品对安徽不同地区云特性的研究

针对不同区域云特性的差异,利用2006—2015年MODIS云产品MYD06_L2,对安徽淮北和江淮地区云相态、云粒子有效半径、云光学厚度和云顶高度发生概率进行统计分析,并对两地区云特性进行对比研究。研究表明,两地区夏季水云发生概率>冰云>晴空>混合相云,秋冬季则水云>晴空>冰云>混合相云。夏季两地区水云粒子有效半径相当,在14μm左右。淮北地区四季冰云粒子有效半径略高,夏季年际变化小,两地区逐年在24μm左右。春冬季江淮地区云光学厚度相对淮北地区较高。夏季冰云和混合相云云顶高度相对较高。研究结果为安徽省不同地区合理科学的规划和开展人工增雨作业提供了一定的理论依据。     

Retrieval of warm cloud optical properties using simple approximations

A new technique relying on SimpLe Approximations for cLOudy Media (SLALOM) for the retrieval of cloud optical and microphysical parameters from optical satellite data during daytime is introduced. The technique is based on simple yet highly accurate approximations of the asymptotic solutions of the radiative transfer theory which have already been implemented in the forward radiative transfer model CLOUD. These approximations enable a solution of the equations of the corresponding backward model during runtime leading to a very fast computation speed. Since these asymptotic solutions are generally applicable to weakly absorbing media only, pre-calculated look-up tables for the reflection function of a semi-infinite cloud (and also the escape function) are used to overcome this restriction within this new retrieval. SLALOM is capable of retrieving the cloud optical thickness, the effective cloud droplet radius, the liquid and ice water paths, the particle absorption length as well as some other properties of water and ice clouds. The comparison of SLALOM with both exact radiative transfer computations and the NASA MODIS cloud property product shows a very good agreement. A Fortran implementation of both CLOUD and SLALOM is available for download under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 license (see http://creativecommons.org/licenses/by-nc-sa/3.0) at http://www.klimatologie.uni-bayreuth.de.     

山区可见光—近红外遥感影像浓密植被暗像元自动识别方法研究

暗目标法是目前气溶胶光学厚度遥感反演中应用最为广泛的方法,浓密植被暗像元的识别是暗目标法的基础。针对可见光—近红外影像缺少中红外波段难以有效识别浓密植被暗像元的问题,引入红波段直方图阈值法识别山区可见光—近红外影像的浓密植被暗像元。该方法利用浓密森林像元在可见光波段反射率低的特点,通过搜索红波段直方图的最小峰值自动识别浓密植被暗像元。试验中选取Landsat TM影像前4个波段利用红波段直方图阈值法识别可见光—近红外影像的浓密植被暗像元,并与在中红外波段影像和可见光—近红外影像中广泛应用的两种暗像元识别方法进行对比分析,探讨红波段直方图阈值法的有效性,最后将该方法应用于环境减灾卫星(HJ-1)CCD影像的暗像元识别和气溶胶反演。实验结果表明:红波段直方图阈值法明显优于常用的可见光—近红外影像暗像元识别方法,识别精度接近传统的中红外波段影像识别方法,相似度指数小于2和小于3的暗像元分别为83.12%和93.48%。该方法为山区可见光—近红外影像浓密植被暗像元自动识别提供了一种新的适用方法,识别结果能够满足暗目标法反演气溶胶光学厚度的要求。     

Simulation of atmospheric profile retrieval from hyperspectral infrared data under cloudy conditions

In this paper, simulated space-based high spectral resolution AIRS (Atmospheric Infrared Sounder) infrared radiances with different cloud top heights and effective cloud fractions are used to demonstrate measurement sensitivity and atmospheric profile retrieval performance. Simulated cloudy retrievals of atmospheric temperature and moisture derived from the statistical eigenvector regression algorithm are analysed with different effective cloud fractions and different cloud heights. The results show that knowledge of cloud height is critical to sounding retrieval performance and the root mean square error of retrieved temperature and the mixed ratio of water vapour below the cloud top increases with effective cloud fraction. When there is 50 hPa error in the cloud height the retrieval accuracy of temperature and humidity decrease, compared with when the cloud height is known perfectly; the temperature retrieval is more sensitive to cloud height error than humidity retrieval. Collocated cloudy AIRS and the associated clear MODIS (Moderate Resolution Imaging Spectroradiometer) infrared observations within the AIRS field of view (FOV) are also used to demonstrate profile retrieval improvement below the cloud layer. It is demonstrated that using collocated clear MODIS multispectral imager data along with AIRS high spectral resolution infrared radiances can greatly improve the single FOV cloudy retrieval even under opaque cloudy conditions.     

A multi-spectral non-local method for retrieval of boundary layer cloud properties from optical remote sensing data

A multi-spectral non-local (MSN) method is developed for advanced retrieval of boundary layer cloud properties from remote sensing data, as an alternative to the independent pixel approximation (IPA) method. The non-local method uses data at both the target pixel and neighboring pixels to retrieve cloud properties such as pixel-averaged cloud optical thickness and effective droplet radius. Radiance data to be observed from space were simulated by a three-dimensional (3D) radiation model and a stochastic boundary layer cloud model with two-dimensional (horizontal and vertical) variability in cloud liquid water and effective radius. An adiabatic assumption is used for each cloud column to model the geometrical thickness and vertical profiles of cloud liquid water content and effective droplet radius, neglecting drizzle and cloud brokenness for simplicity. The dependence of radiative smoothing and roughening on horizontal scale, optical thickness and single scattering albedo are investigated. Then, retrieval methods using 250-m horizontal resolution data onboard new generation satellites are discussed. The regression model for the MSN method was trained based on datasets from numerical simulations. The training was performed with respect to various domain averages of optical thickness and effective radius, because smoothing and roughening effects are strongly dependent on the two variables. Retrieval accuracy is discussed here with datasets independent of those used in the training, towards assessing the generality of the technique. It is demonstrated that retrieval accuracy of cloud optical thickness, which is often retrieved from single-spectral visible-wavelength data, is improved the most using neighboring pixel data and secondly using multi-spectral data, and ideally with both. When the IPA retrieval method is applied to optical thickness and effective radius, the root-mean-square relative errors can be 15-90%, depending on solar and view directions. In contrast, the MSN method has errors of 4-10%, which is smaller than IPA by a factor of 2-10. It is also suggested that the accuracy of the MSN method is insensitive to some assumptions in the inhomogeneous cloud input data used to train the regression model.     

INSAT-3D cloud microphysical product: retrieval and validation

The 6-channel Imager onboard the Indian geostationary satellite Indian National Satellite-3D (INSAT-3D) provides half-hourly multispectral images over the Indian monsoon region. The availability of shortwave infrared (SWIR) (1.6 μm) channel along with visible (0.6 μm) channel observations provide an opportunity to estimate cloud microphysical parameters (CMP) over the India and surrounding regions with high temporal frequency. In this paper, we describe the retrieval and validation of two important CMPs, i.e. cloud optical thickness (COT) and cloud effective radius (CER) over the ocean from INSAT-3D. This is the first time; a CMP product has been made available for INSAT-3D. We describe here the development of the forward model, based on a look-up-table (LUT) approach using Radiative transfer simulations. The inversion is carried out by selecting the vector (CMP) which provides the best match between the observed and simulated radiances. The present retrieval is limited to water clouds over ocean only. The retrieved INSAT-3D CMP were then compared with MODerate Resolution Imaging Spectroradiometer (MODIS) product for the months of January and July 2016. For cloudy month (July), the mean correlation between INSAT-3D and MODIS was 0.73 and 0.47 for COT and CER, respectively. Similarly, for the month of January with less cloud cover, the mean correlation was 0.60 and 0.40 for COT and CER, respectively. INSAT-3D products are available every half hourly in real time through web portal www.mosdac.gov.in and will be valuable for studying short-term variation in cloud-microphysics over the equatorial Indian Ocean.     

A three-channel algorithm for retrieving night-time land surface temperature from MODIS data under thin cirrus clouds

Thin cirrus clouds are dominated by non-spherical ice crystals with an effective emissivity of less than 0.5. Until now, the influences of clouds were not commonly considered in the development of algorithms for retrieving land-surface temperature (LST). However, numerical simulations showed that the influence of thin cirrus clouds could lead to a maximum LST retrieval error of more than 14 K at night if the cirrus optical depth (COD) at 12 μm was equal to 0.7 (cirrus emissivity equivalent to 0.5). To obtain an accurate estimate of the LST under thin cirrus using satellite infrared data, a nonlinear three-channel LST retrieval algorithm was proposed based on a widely used two-channel algorithm for clear-sky conditions. The variations in the cloud top height, COD, and effective radius of cirrus clouds were considered in this three-channel LST retrieval algorithm. Using Moderate Resolution Imaging Spectroradiometer (MODIS) channels 20, 31, and 32 (centred at 3.8, 11.0, and 12.0 μm, respectively) and the corresponding land surface emissivities (LSEs), the simulated data showed that this algorithm could obtain LSTs with root mean square errors (RMSEs) of less than 2.8 K when the COD at 12 μm is less than 0.7 and the viewing zenith angle (VZA) is less than 60°. In addition, a sensitivity analysis of the proposed algorithm showed that the total LST errors, including errors from the uncertainties in input parameters and algorithm error, were nearly the same as the algorithm error itself. Some lake surface water temperatures measured in Lake Superior and Lake Erie were used to test the performance of the proposed LST retrieval algorithm. The results showed that the proposed nonlinear three-channel algorithm could be used for estimating LST under thin cirrus with an RMSE of less than 2.8 K.     

Synergetic use of POLDER and MODIS for multilayered cloud identification

The purpose of this study is to investigate the possibility of identifying overlapping clouds that contain thin cirrus overlying a lower-level water cloud by synergetic use of POLDER-3 (Polarization and Directionality of the Earth Reflectance) and MODIS (MODerate resolution Imaging Spectroradiometer) data. When thin cirrus clouds overlap the liquid cloud layer, the liquid information may be obtained by POLDER observations and the presence of the cirrus may be inferred from the MODIS CO₂-slicing technique. An initial comparison of the POLDER cloud phase and the MODIS cloud-top pressure for one scene over East Asia also shows that a large portion of clouds declared as liquid water clouds by POLDER-3 correspond to the lower cloud-top pressures derived from MODIS. As a result, an overlapped cloud identification method is proposed under the assumption that the multilayered cloud would be present if the POLDER cloud phase is liquid water and the MODIS cloud-top pressure is less than 500 hPa. For the studied scene, the comparison of the multilayered cloud identification results with CloudSat and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations illustrates that the proposed method could detect multilayered clouds when the upper cirrus has a visible optical thickness of less than 2.0. Then the identification results are compared with the MODIS Cloud_Multi_Layer_Flag. It is indicated that the consistency between the multilayered clouds from the proposed synergy and MODIS-operational algorithm increases gradually from over 40% to nearly 100% with the increase of the confidence level of the MODIS multilayered clouds from the lowest to the highest. Further analysis suggests that the majority of multilayered clouds falsely classified as single-layered clouds by the proposed method may correspond to relatively thick cirrus covering lower-level water clouds. Additionally, an index by using the multilayered cloud detection differences from the two methods is proposed to provide some information on the optical thickness of the cirrus covering lower-level water cloud. Finally, quantitative comparisons are extended to four other scenes at different locations by using active measurements. The results also show that the mean visible optical thickness of the high-level clouds of the multilayered clouds detected by both methods (1.57) is remarkably less than that by only MODIS-operational method (2.84), which means that the differences between the results from the two methods are mainly caused by the different sensitivities to the visible optical thickness of the high-level cloud and could be used to indicate the range of the visible optical thickness of the cirrus clouds covering the lower-level water clouds.     

Transect method for Antarctic cloud property retrieval using AVHRR data

For studies of Antarctic climate change, the Advanced Very High Resolution Radiometer (AVHRR) offers a time series spanning more than two decades, with numerous overpasses per day from converging polar orbits, and with radiometrically calibrated thermal infrared channels. However, over the Antarctic Plateau, standard multispectral application of AVHRR data for cloud optical property retrieval with individual pixels is problematic due to poor scene contrasts and measurement uncertainties. We present a method that takes advantage of rapid changes in radiances at well-defined cloud boundaries. We examine a transect of AVHRR-measured radiances in the three thermal infrared channels across a boundary between cloudy and cloud-free parts of the image. Using scatter diagrams, made from the data along this transect, of the brightness temperature differences between channels 3 and 4, and channels 4 and 5, it is possible to fit families of radiative transfer solutions to the data to estimate cloud effective temperature, thermodynamic phase, and effective particle radius. The major approximation with this method is that along such a transect, cloud water path has considerable spatial variability, while effective radius, phase, and cloud temperature have much less variability. To illustrate this method, two AVHRR images centred about the South Pole are analysed. The two images are chosen based on their differing contrasts in brightness temperature between clear and cloud-filled pixels, to demonstrate that our method can work with varying cloud top heights. In one image the data are consistent with radiative transfer simulations using ice cloud. In the other, the data are inconsistent with ice cloud and are well simulated with supercooled liquid water cloud at 241.5 K. This method therefore has potential for climatological investigation of the radiatively important phase transition in the extremely cold and pristine Antarctic environment.