EMI 南极臭氧柱总量反演研究

利用差分吸收光谱技术 (DOAS) 反演了我国首个星载大气痕量气体差分吸收光谱仪 (EMI) 的臭氧斜柱浓度 (SCD), 通过 SCIATRAN 辐射传输模型建立了大气质量因子 (AMF) 的查找表, 最终得到 EMI 的臭氧垂直柱浓度 (即 臭氧柱总量)。将 EMI、 OMI 和 TROPOMI 于 2018 年 11 月 2 日获得的南极区域臭氧柱总量进行了对比分析, 三者 均观测到南极中高纬度 (30◦ S∼70◦ S) 的臭氧高值区域与南极内陆 (75◦ S∼90◦ S) 的臭氧低值区域, 且 EMI 与 OMI、 TROPOMI 的臭氧柱总量相关性 (R2) 分别为 0.977 和 0.979。进一步将 EMI 反演的臭氧柱总量与南极长城站 (62.22 S, 58.96 W) 地基天顶散射光差分吸收光谱仪 (ZSL-DOAS) 反演的臭氧柱总量进行对比, 二者相关性 (R2) 为 0.926。     

星载大气痕量气体差分吸收光谱仪基于太阳的在轨辐射定标

基于整机双向散射分布函数(Bi-directional scattering distribution function, BSDF),星载大气痕量气体差分吸收光 谱仪(Environmental trace gases monitoring instrument, EMI)在轨可完成基于太阳的辐射定标,整机BSDF表征了EMI观测 光路和定标光路辐射特性的关系。观测光路辐射定标已在地面完成,定标光路辐射特性定标在轨基于太阳完成,进而得到了 整机BSDF参数,基于此实现了EMI在轨基于太阳的辐射定标。结果表明在可比光谱范围内, 与TROPOMI(Tropospheric ozone-monitoring instrument) 载荷交叉比对结果的差异在5%~6.5%以内。     

基于EMI遥感NO2技术监测澳洲森林火灾活动

澳大利亚2019-2020年发生了大规模的森林火灾,本次火灾在六个月的时间内烧毁了超过800万公顷的桉树林.利用大气痕量气体差分吸收光谱仪(EMI)对澳大利亚火灾期间的NO2变化情况进行了分析.研究发现,2019年11月,澳大利亚东南区域的NO2浓度及分布相比往年同期,出现明显的增长趋势.同时具体针对澳大利亚两大国家公...     

星载大气痕量气体差分吸收光谱仪0~1数据处理研究

星载大气痕量气体差分吸收光谱仪(Environmental trace gases monitoring instrument, EMI)于2018年5月9日成功发射升空,目前在轨运行状态良好,能够有效获取全球紫外-可见波段地球大气散射光信号(Digital number, DN)值(0级数据)。为对遥感数据定量化应用, EMI输出的DN值需要完成光谱定标、几何定位、辐亮度定标等处理,得到1级数据产品,1级数据用于反演获取全球大气NO$_2$、SO$_2$和O$_3$等2级产品,进而应用于定量监测全球空气质量变化以及污染气体的分布输运过程。     

激光云高仪云量自动反演算法

云是气象预测和航空航海等领域中非常重要的因素之一,所以对云进行观测具有重要的现实意义。而云量作为其中重要的气象参数之一,已成为气象观测的重要内容。目前,对于云量的观测主要还是靠目测,由于各种因素的影响导致误差较大。测量云量是激光云高仪的一个重要应用。提出了一种激光云高仪云量自动反演算法,算法以激光云高仪单点测量数据为基础构造一个关于时间和云层高度的二维图像,按照云层所占用的时间比率进行反演计算云量。对比实验验证表明,算法能较为准确地反演出云量信息,对激光云高仪具有实用价值。     

海岸带混浊水域MODIS图像的大气校正

大气校正的精确度主要取决于气溶胶光学特性和漫射透过率等参数的精度.针对目前混浊水域上空气溶胶光学特性反演方法的缺点,给出了基于MODIS图像混浊水域上空气溶胶光学特性反演的新方法,论证了该方法的可行性,并给出了一组通过了验证的用来计算大气漫射透过率的参数.讨论了该技术用于海岸带混浊水域上空大气校正的可行性,可以为我国海洋和风云系列卫星资料的大气校正研究提供相关的技术基础.     

哥德堡地区基于无线通讯网络的水汽密度监测分析

利用无线通讯网络中的微波链路来监测降雨和水汽等是大气环境监测的新技术之一。这个技术可以测量近地面的降雨强度和水汽密度等气象参数,具有时空分辨率高、成本低等优势。利用瑞典爱立信公司(Ericsson)提供的位于哥德堡地区E频段的微波通讯链路资料、位于链路一端的气象站1资料和由瑞典气象水文研究所(SMHI)气象网站提供的气象站2资料,对2017年06月13日至2017年07月13日近1个月的水汽密度进行反演计算和分析。结果表明:同一区域的不同地点处的气象要素有一定的差异性,同一区域的温度会有一定的浮动(0~4℃),两者之间的相关性为0. 87;微波通讯链路反演的水汽密度结果与研究区域的地面气象站1和气象站2测量结果有很好的一致性,两者之间的相关性分别为0. 89和0. 97,均方根误分别差为0. 75 g m3和0. 79 g m3;利用微波链路,与现有的湿度监测方法相比,可以为现有的天气监测网络提供额外的丰富的数据源。     

基于氧气A 带的高光谱卫星气溶胶层高优化反演

针对气溶胶被动卫星遥感中由于气溶胶模型的不确定性导致的反演误差, 引入了一种基于贝叶斯理论的新型 气溶胶层高反演算法, 并应用于哨兵5 先导(Sentinel-5P) 卫星的TROPOMI (TROPOspheric Monitoring Instrument) 载 荷。该算法基于不同候选气溶胶模型的模型证据(气溶胶模型的条件概率密度) 确定符合当前观测数据条件的气溶胶 模型, 并通过两种模型选择方案分别得到估算最大值解和估算平均值解作为反演结果。以TROPOMI 观测到的一次真 实野火事件为例, 反演结果和官方产品具有很好的空间一致性, 且明显降低了低估现象, 证明在气溶胶先验知识缺乏 的背景下该算法能够高效选择合适的气溶胶模型, 为今后高光谱卫星气溶胶层高反演的业务化数据处理提供了一种 新的解决方案。     

中国近海蒸发波导反演中最佳雷达参数分析

利用雷达海杂波反演大气波导折射率(Refractivity From Clutter,RFC)的技术可以实现海洋低空对流层近实时、区域性、非均匀折射率的探测反演,但其反演性能受雷达参数和折射率区域时空统计特性以及地(海)面的影响,为了使RFC技术在中国海域蒸发波导反演中体现出较好的性能,使用粒子群优化算法和自适应目标函数,利用美国圣地亚哥空海作战系统中心高级折射效应预报系统提供的中国海域蒸发波导高度区域统计数据,依据考虑区域统计特性的均方根误差评判模型,研究了中国不同海域、不同月份,不同雷达频率天线高度组合情况下的蒸发波导RFC反演性能,分析得出适用于中国近海蒸发波导RFC反演的最佳雷达频率和天线架设高度范围,所得结果对我国周边海域监测以及海上无线电系统的设计与应用具有参考价值.     

海洋上空云多角度偏振辐射阈值检测方法研究

云是海洋遥感的一项重要研究内容,云检测精度对于海洋上空云微物理特性的反演和海洋水体观测具有重要意义.以高分五号卫星搭载的大气气溶胶多角度偏振探测仪(Directional polarimetric camera,DPC)在轨成像数据为研究对象,提出了一种基于多角度偏振辐射信息的海洋上空云检测方法.首先用耀光角判别法区分...     

国产卫星多角度偏振传感器的光谱特征云检测方法研究

在卫星遥感研究中, 云检测是基础环节, 其结果影响大气、地表各种参数的定量遥感, 同时也影响云微物理特 性的反演。本研究针对多角度偏振卫星载荷(高分五号DPC 传感器), 建立了一种改进的光谱特征云检测算法。该算 法综合利用云像元和非云像元在可见光反射率光谱、氧A 波段吸收、蓝光偏振反射率以及偏振虹等特性上的差异, 分别提出了陆地、海洋上空的云检测方案, 并进一步建立了多角度云检测融合策略以标记云、晴空和未定像元。在 陆地检测中, 通过增加表观压强检测和偏振虹检测分别改进了高层薄云和低层薄云的识别; 在海洋检测中, 利用表观 压强与云层的退偏特性改进了耀光区云像元的识别。全球云检测结果示例显示该算法整体检测效果较好, 同时典型 区域的检测结果与MODIS 云产品也具有较好的一致性。该研究可为高分五号02 星上的多角度偏振传感器云检测提 供方法基础。     

Beam-filling effect correction with subpixel cloud fraction using a neural network

In this study, the effects of cloud inhomogeneity on microwave rain rate retrievals are investigated. A single-channel (85 GHz) empirically based algorithm using a neural network approach is presented. The objective is to correct the beam-filling error (BFE), that might occur because of the inherent variability within coarse microwave pixels, with subpixel information. To this aim, we used the Tropical Rainfall Measuring Mission passive microwave, thermal infrared and radar data. The integration of spatial information into the retrieval algorithm enables us to partially overcome the BFE. We use two parameters which characterize the horizontal cloud inhomogeneity within the microwave radiometer field of view, and we add them to simulated brightness temperatures as inputs of the neural network algorithm. The first one is the cloud fraction derived from infrared measurement, and the second corresponds to the fraction of the rainy area derived from radar measurements. The output rain rates were validated using the Precipitation Radar data. It was found that adding cloud fraction of microwave pixels, can lead to more accurate retrievals. Instantaneous precipitation estimates demonstrated correlations of /spl sim/0.6-0.7 and /spl sim/0.7-0.8 with radar-derived rain rates, for ocean and land retrievals respectively. In spite of the problem inherent in deriving the cloud (or rain) fraction, the initial validation results presented in this study are reasonably encouraging and show the advantage of utilizing the information from different sensors in order to optimize the retrieval of rainfall.     

The determination of the atmospheric optical thickness over Western Europe using SeaWiFS imagery

The first results obtained from the aerosol-cloud retrieval algorithm (developed at the University of Bremen) are presented. The algorithm enables the observation of the regional characteristics of aerosol and cloud optical thickness both over land and ocean surfaces. The aerosol and cloud optical thickness over Western Europe is derived from the high-resolution SeaWiFS data for October 11, 2001 (11:30 UTC). The most probable value of the aerosol optical thickness was found to be equal approximately 0.25. The frequency distributions of the aerosol and cloud optical thickness are skewed and have long tails for larger optical thickness. It was found that retrieved values of the aerosol optical thickness at wavelengths 0.412 and 0.440 /spl mu/m are close to those measured by five ground-based instruments placed at different locations. The problems related to the retrieval of the atmospheric optical thickness from space are discussed.     

CALIPSO星载激光在全球海洋上空的透性统计

利用CALIPSO卫星2006年6月至2010年5月四年的5 km二级云产品数据对CALIPSO星载激光在全球海洋上空的穿透性进行统计分析,分别讨论了穿透概率随年度变化、季节变化、昼夜变化及地理位置的变动情况,同时分析了产品版本因素对分析结果造成的影响.分析表明,海洋上空的数据中探测到云层的约占72.2％,其中不透明云...     

Retrieval of Ocean Surface And Atmospheric Parameters from Multichannel Microwave Radiometric Measurements

This paper discusses the retrieval from Scanning Multichannel Microwave Radiometer (SMMR) data of ocean surface temperature, surface wind speed, rain rate, cloud height, and the amount of water vapor and nonprecipitating liquid water over the ocean. The sensitivity of the algorithms that retrieve the wind speed and seasurface temperature in the absence of rain to the (undetected) presence of rain, and the accuracy of a more general method that retrieves rain rate along with other meteorological parameters are discussed. These investigations are based on models of the microwave emission from the Earth's atmosphere over the ocean in the presence of rain. The modeling technique and the retrieval methods are also discussed.     

WindSat Passive Microwave Polarimetric Signatures of the Greenland Ice Sheet

WindSat has systematically collected the first global fully polarimetric passive microwave data over both land and ocean. As the first spaceborne polarimetric microwave radiometer, it was designed to measure ocean surface wind speed and direction by including the third and fourth Stokes parameters, which are mostly related to the asymmetric structures of the ocean surface roughness. Although designed for wind vector retrieval, WindSat data are also collected over land and ice, and this new data has revealed, for the first time, significant land signals in the third and fourth Stokes parameter channels, particularly over Greenland and the Antarctic ice sheets. The third and fourth Stokes parameters show well-defined large azimuth modulations that appear to be correlated with geophysical variations, particularly snow structure, melting, and metamorphism, and have distinct seasonal variation. The polarimetric signatures are relatively weak in the summer and are strongest around spring. This corresponds well with the formation and erosion of the sastrugi in the dry snow zone and snowmelt in the soaked zone. In this paper, we present the full polarimetric signatures obtained from WindSat over Greenland, and use a simple empirical observation model to quantify the azimuthal variations of the signatures in space and time.      

AIRS near-real-time products and algorithms in support of operational numerical weather prediction

The assimilation of Atmospheric InfraRed Sounder, Advanced Microwave Sounding Unit-A, and Humidity Sounder for Brazil (AIRS/AMSU/HSB) data by Numerical Weather Prediction (NWP) centers is expected to result in improved forecasts. Specially tailored radiance and retrieval products derived from AIRS/AMSU/HSB data are being prepared for NWP centers. There are two types of products - thinned radiance data and full-resolution retrieval products of atmospheric and surface parameters. The radiances are thinned because of limitations in communication bandwidth and computational resources at NWP centers. There are two types of thinning: (1) spatial and spectral thinning and (2) data compression using principal component analysis (PCA). PCA is also used for quality control and for deriving the retrieval first guess used in the AIRS processing software. Results show that PCA is effective in estimating and filtering instrument noise. The PCA regression retrievals show layer mean temperature (1 km in troposphere, 3 km in stratosphere) accuracies of better than 1 K in most atmospheric regions from simulated AIRS data. Moisture errors are generally less than 15% in 2-km layers, and ozone errors are near 10% over approximately 5-km layers from simulation. The PCA and regression methodologies are described. The radiance products also include clear field-of-view (FOV) indicators. The residual cloud amount, based on simulated data, for FOVs estimated to be clear (free of clouds) is about 0.5% over ocean and 2.5% over land.