遥感GPS倾斜路径信号构筑水汽时空分布图

一般情况下, 一台GPS接收机可接收5~7颗GPS卫星的信号, 通过倾斜路径水汽测量的技术, 可以反演这些不同路径方向的水汽总量SWV(slant-path water vapor). 由SWV可以推导出两个新参数: 绝对VSWV(vertical SWV)和相对VSWV(vertical SWV), 利用它们的时空分布图可反映水汽非均匀分布及其变化情况. 上述方法被应用于2004年7月北京地区的天气分析中, 结果表明绝对VSWV时空分布图和相对VSWV时空分布图有助于监测水汽的演变过程和加深对降水过程的了解.     

地基GPS低高度角观测反演大气折射率廓线的模拟仿真

用价值函数的最优估计方法,发展了地基GPS弯曲角和相位观测联合反演大气折射率廓线的算法. 在价值函数中提出了一个比较合理的权系统;通过四参数形式的折射率模型,采用变分同化技术,反演出大气折射率廓线. 模拟结果显示,地基GPS观测反演得到的低层大气折射率廓线与真值吻合较好,并可以应用到大气波导的探测.     

基于GPS和MODIS的ENVISAT ASAR数据干涉测量中大气改正方法研究

GPS数据用于改正InSAR中大气延迟误差的方法受GPS站点密度的限制,只利用有限的几个站点所观测到的大气数据来生成干涉图的大气改正图,往往达不到很好的效果.本文研究利用GPS与MODIS数据的联合使用来生成大气改正图,首先用GPS数据对MODIS水汽产品进行分块校准,并且对MODIS水汽数据进行了空间结构函数分析,得到研究区域内水汽场的空间分布规律.然后把这种区域水汽场的空间分布信息结合到Kriging内插法中生成更为合理的水汽图.通过上海地区ENVISAT ASAR数据的实验发现,这种加以改正的GPS和MODIS数据联合改正法不仅可以对长波大气信号有明显的消弱,还能消弱一些短波的大气信号,特别是一些幅度较强的短波信号;经过GPS+MODIS算法改正后,短波信号占优和长波信号占优的两幅差分大气延迟图的整体RMS分别降低了32.74%和38.82%,去除幅度较大.与GPS+ATM(大气传输模型)算法比较,我们发现,在上海地区有限的数据条件下（即研究区域内只有6个GPS点）,GPS+MODIS法在大气去除效果或者说大气信号重现能力方面优于GPS+ATM算法.GPS+MODIS算法在捕获短波大气信号方面要比GPS+ATM更有优势,因此也可以改正短波大气误差.     

利用GPS观测资料反演水汽含量及地震异常初步探讨

利用GPS观测数据反演大气水汽技术是20世纪90年代发展起来的一种全新的大气探测手段。根据中国大陆构造环境监测网络(简称陆态网)和广东省地震局建设的广东省地壳运动观测网络提供的GPS数据反演大气水汽含量,用ECMWF水汽含量数据进行对比和补充,并试图把它们应用于地震研究,探讨广东地区地震前后的水汽含量变化特征。结果表明:GPS反演结果是可靠的;广东地区水汽含量具有夏高冬低的年变规律和南高北低的分布特征;广东地区2000年以来3个MS4.8级地震前1个月以内震中区都出现了显著的水汽含量增加的现象,异常幅度超过平均值30 mm,高值区沿构造带展布,并在水汽含量出现异常的同时,伴随着地表气温的异常,说明水汽含量增加与震中区热作用增强、水汽蒸发加速有关,可能是地震前的异常反应。     

基于星载高精度GPS观测数据的大气密度反演

星载高精度GPS观测数据可提供卫星速度和位置信息,而卫星的运行轨迹又与所处位置的大气密度紧密相关,因此可通过求解大气阻力微分方程,由高精度GPS观测数据反演出卫星运行轨迹上的热层大气密度.本文从星载高精度GPS观测数据出发,给出大气密度的反演方法,以及平均平动参数nM、反弹道系数B两个重要参数的解算过程,并以天宫一号为例,给出反演结果与天宫一号观测数据的比对.结果表明,反演结果与观测值符合很好,两者的均方差在2012年1月1日、2月24日分别为8.6%和8.4%,说明利用星载GPS观测数据反演大气密度是有效、可行的,可成为今后获取高精度大气密度的一种方法.     

大气掩星反演误差特性初步分析

GPS大气掩星探测技术可以获得全球大气折射率、气压、密度、温度和水汽压等气象参数，该技术基本原理是基于几何光学近似的Abel积分反演.地球扁率、电离层传播时间延迟、大气大尺度水平梯度、多路径传播现象等因素在某些高度范围影响大气反演的精度.本文采用模拟的方法，分析其中地球扁率及电离层对反演结果的影响，并讨论局部圆弧修正及电离层修正的效果.利用CHAMP掩星实测轨道数据和有关电离层和大气经验模式、采用三维射线追踪方法模拟计算几种情形下的GPS掩星观测附加相位数据，对模拟数据进行反演，将反演气象参量剖面与模拟时给定模式剖面进行比较，得到了0～60 km高度范围内的反演误差.误差统计分析结果表明，局部圆弧中心的修正以及电离层修正，对于高精度的GPS掩星反演是非常重要的；电离层修正残差仍是制约30～60 km高度范围内反演精度的重要因素，进一步完善和优化大气掩星反演需要发展新的电离层修正算法.     

基于多源遥感数据陆面大气水汽反演的物理统计算法研究

大气水汽对全球以及区域气候变化有着极其重要的影响,因而精确的获取水汽数据一直是非常重要的研究课题.单一传感器的遥感水汽反演算法有一定的局限,本文致力于发展一个基于多源遥感数据的水汽反演物理统计算法,该算法还能有效解决有云情况下的水汽反演.通过将晴空条件下近红外水汽反演结果与基于微波23.8 GHz的水汽敏感波段的组合指数进行回归,再将有云覆盖区域的微波指数代入到回归反演模型,从而获得有云覆盖条件下的水汽结果,实现有云条件下的水汽反演,对基于光学波段的水汽反演结果进行补充.不同的地表覆盖会对裸土表面的微波辐射有不同的影响作用,本文的算法还利用地表覆盖数据有效消除了这一影响,针对不同的地表覆盖,分别进行回归模型的建立.最后将该算法反演的结果与地基GPS的水汽监测数据进行对比,有云条件下的均方根误差为8 mm,且利用本算法可以较好的对光学数据进行补充,具有良好的空间一致性.     

高光谱遥感数据的改正暗目标大气校正方法研究

高光谱遥感数据常用的大气校正方法均侧重于去除水汽及其他吸收气体的影响, 主要研究了从高光谱影像同时去除气溶胶与水汽影响的方法. 由于高光谱遥感数据波段众多, 常规暗目标方法一直难以适用于高光谱遥感数据的大气校正. 通过选取小麦作为新的暗目标对象, 着重讨论了使用多波段线性回归与插值的方法对常规暗目标方法进行改正使之充分利用高光谱的众多波段特性, 从而把改进的暗目标方法扩展应用于高光谱遥感数据的大气校正. 为了同时去除大气中水汽的影响, 大气校正全过程采用了循环迭代的算法. 以山东济宁地区EO-1卫星搭载的Hyperion高光谱数据为应用实例, 通过使用MODTRAN建立的查找表直接从影像估算出气溶胶与水汽含量, 实现了对该数据的大气校正. 大气校正的结果表明, 改正暗目标大气校正算法可以有效地对高光谱遥感数据进行大气校正.     

BRD和DOAS SO_2总量遥感反演算法的比对

大气中SO_2是一种对城市大气环境变化和全球辐射能量平衡有着重要影响的痕量气体.BRD(Band Residual Difference Algorithm)和DOAS(Differential Optical Absorption Spectroscopy)算法是两种主要的SO_2总量遥感反演算法,分别被用于美国和欧洲不同卫星载荷数据的SO_2反演.然而,目前缺少两种算法在相同观测条件下SO_2反演的精度比较及不确定性分析、在物理数学反演机制上的差异追因.因此,本文基于相同的仿真模拟数据和卫星紫外辐射观测数据,反演获得不同大气状况下的BRD和DOAS SO_2总量并进行精度比较验证.从算法反演通道、O_3吸收、气溶胶、地表反射率和观测角度影响等方面,讨论分析BRD和DOAS反演结果差异及反演误差的原因.结果表明,在低浓度SO_2情况下,BRD反演SO_2总量更接近于正演输入SO_2总量,DOAS反演结果存在高估,但相对于BRD算法,DOAS算法长时间序列卫星反演结果更能表现出SO_2的季节变化特征;在高浓度SO_2情况下,BRD(310.8~314.4nm)和DOAS(315~327nm)反演结果的绝对值差异明显且存在低估,BRD(310.8~314.4nm)SO_2反演值及反演精度都低于DOAS(315~327nm)反演结果.基于高光谱分辨率大气辐射传输模型SCIATRAN的反演不确定性分析结果显示,反演通道选择、紫外O_3吸收、气溶胶、地表反射率和观测角度对SO_2总量反演精度的影响较大.本研究对于SO_2卫星遥感反演算法的改进及SO_2反演产品的应用具有重要的科学意义,也可促进中国未来大气成分SO_2卫星遥感产品的研发.     

大气GPS掩星观测反演方法

大气GPS掩星观测可获得全球的大气气象参量剖面信息.本文阐述了地球大气GPS掩星观测反演原理,详细介绍了其几何光学近似反演方法和全谱反演方法,提出了将几何光学反演方法和全谱反演方法结合以形成可以处理多路径掩星数据的反演新方案.该方案和几何光学反演方法应用于GPS/MET和CHAMP大气掩星数据反演,成功地获得了大气参量剖面.结果表明,新反演方案是可行的、有效的GPS大气掩星反演方案.     

Physical statistical algorithm for precipitable water vapor inversion on land surface based on multi-source remotely sensed data

Water vapor plays a crucial role in atmospheric processes that act over a wide range of temporal and spatial scales, from global climate to micrometeorology. The determination of water vapor distribution in the atmosphere and its changing pattern is very important. Although atmospheric scientists have developed a variety of means to measure precipitable water vapor(PWV) using remote sensing data that have been widely used, there are some limitations in using one kind satellite measurements for PWV retrieval over land. In this paper, a new algorithm is proposed for retrieving PWV over land by combining different kinds of remote sensing data and it would work well under the cloud weather conditions. The PWV retrieval algorithm based on near infrared data is more suitable to clear sky conditions with high precision. The 23.5 GHz microwave remote sensing data is sensitive to water vapor and powerful in cloud-covered areas because of its longer wavelengths that permit viewing into and through the atmosphere. Therefore, the PWV retrieval results from near infrared data and the indices combined by microwave bands remote sensing data which are sensitive to water vapor will be regressed to generate the equation for PWV retrieval under cloud covered areas. The algorithm developed in this paper has the potential to detect PWV under all weather conditions and makes an excellent complement to PWV retrieved by near infrared data. Different types of surface exert different depolarization effects on surface emissions, which would increase the complexity of the algorithm. In this paper, MODIS surface classification data was used to consider this influence. Compared with the GPS results, the root mean square error of our algorithm is 8 mm for cloud covered area. Regional consistency was found between the results from MODIS and our algorithm. Our algorithm can yield reasonable results on the surfaces covered by cloud where MODIS cannot be used to retrieve PWV.     

Constructing temporal and spatial water vapor figures by GPS remote sensing along slant rays

A Global Positioning System (GPS) receiver can generally track 5-7 rays from GPS satellites at any moment, and water vapor along these ray paths (slant-path water vapor, SWV) may be retrieved using the methods developed in recent years. This paper suggests two new parameters-absolute vertical SWV (VSWV) and relative VSWV derived from SWV, and their temporal and spatial figures can reflect the heterogeneous distribution and variation of water vapor field. This approach has been applied to the weather diagnoses in a severe storm event in Beijing during July 2004, and it is concluded that the temporal and spatial figures of absolute VSWV and relative VSWV can be useful in monitoring the evolution of water vapor field and be potential in better understanding the precipitation process.     

Emerging Technologies and Synergies for Airborne and Space-Based Measurements of Water Vapor Profiles

A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity.     

Meteorological fields from remote infrared sensing

Modern numerical weather prediction techniques require global observations of the atmospheric state and structure parameters. The current meteorological observing system, which is based on radiosonde balloon observations, has extensive gaps. Remote sensing of the Earth atmosphere emission spectrum from satellites can fill these gaps. The physical basis for extracting information on meteorological fields from such remote observations is explained. The problem reduces to that of solving a linear Fredholm equation of the first kind in the presence of noisy data. There is no unique solution to such a problem. The mathematical techniques-inversion techniques-that are currently used to solve the problem are reviewed. Examples are given of meteorological fields obtained from remote infrared sensing from satellites. Results indicate that meteorological parameters such as temperature and geopotential height of constant pressure surfaces can be measured-in conditions of clear skies-to accuracies approaching that of the radiosonde system. Other meterological variables, e.g., water vapor and ozone, can be determined to a lesser degree of accuracy. Applications of the remotely sensed fields are described. Problem areas and suggested solutions are discussed.     

电离层垂直TEC映射函数的实验观测与统计特性

利用GPS信标测量获得的电离层电子浓度总含量（TEC）是沿电波路径的斜向TEC.理论研究和实际应用中,常常需要通过映射函数将斜向TEC转换为垂直方向的TEC,这在当前主要采用对电子浓度分布模型的数值积分得到模型映射函数来实现.本文在考察现有不同模型映射函数的基础上,又提出了一种源于实际观测的实验映射函数的概念与估算方法.我们利用IGS的全球GPS观测站的斜向TEC和JPL提供的垂直TEC数据获得了2006年期间的实验映射函数,并对所得结果进行了初步统计分析.在卫星天顶角较小时,上述实验映射函数和模型映射函数之间相差甚微,均可很好描述垂直TEC与斜TEC之间关系;但卫星天顶角较大时,实验映射函数和常用的模型映射函数之间存在明显差异.本文认为,这种差异主要是因为现有模型映射函数中没有考虑到等离子体层的贡献.我们认为采用基于实验映射函数的模式,或者通过考虑等离子体层的贡献对现有模型映射函数进行改进,可以有效提高电离层TEC的估算精度.     

GPS接收机仪器偏差的短期时变特征提取与建模

卫星和接收机仪器偏差(Differential Code Biases,DCB)是利用GPS(Global Positioning System)研究电离层的两类主要误差源.由于所处的空间环境恒定,且可被全球跟踪站连续观测,GPS卫星的DCB具备长期稳定性和较高的估计精度.但针对各类型接收机而言,受测站环境、硬件设施等影响,其DCB可能会呈现明显的短期变化.精确地模型化接收机DCB的短期变化特征,将有助于提高GPS电离层产品的可靠性,以及基于这些产品反演空间和地球科学现象的准确性.采用零/短基线GPS数据,本文改进了提取和分析接收机DCB变化的现有方案.随后,本文推导了一种能直接估计接收机DCB的函数模型.当检验出接收机DCB的短期变化服从随机游走时,通过对比接收机DCB的直接估值与间接提取值之间的符合程度,可"试探出"过程噪声标准差的最优经验值.实验分析选用4台双频接收机(共形成1条零基线和2条短基线,间距最大为15m)多天的观测数据,主要结论包括:1)改进的接收机DCB提取方案能较好地克服低频伪距噪声和多路径效应的影响;2)针对零基线,其接收机DCB在各天内的变化量级小于1TECu,变化趋势则可采用过程噪声标准差为1.0~1.5mm的随机游走加以描述;3)对应于某短基线的接收机DCB在某天内的变化可达12TECu,当采用随机游走描述其趋势时,过程噪声标准差的经验值超过2mm.     

区域网GPS观测得到的汶川大地震前后的地壳垂直运动

中国地壳运动观测网络1000个观测站的GPS非连续观测区域网分别在1999年、 2001年、 2004年、 2007年和2009年作了5次观测。 2008年5月12日汶川8.0 级地震震中(31.0°N, 103.4°E)恰好在区域网GPS观测站密集的地区。 区域网长期、 多期GPS观测可降低年周期变化影响, 有利于获取此次地震前后的垂直位移趋势变化。 简要讨论了GPS垂直位移观测的精度。 分析了垂直位移观测的主要干扰地面沉降, 特别是华北地区因大量抽取地下水产生的严重地面沉降。 为获取汶川地震前垂直运动信息, 首先剔除因大量抽取地下水产生的大幅度沉降干扰结果, 通过趋势面分析中国大陆垂直位移空间分布, 显示了3个垂直位移沉降最显著区域。 对比分析表明, 临近汶川震区的沉降区, 未见大量抽取地下水干扰影响。 汶川地震前1999—2007年区域网GPS观测站得到的垂直位移表明, 汶川地震紧临显著沉降区的西北侧, 龙门山断层北段垂直运动闭锁。 该沉降区与另两个沉降区的时空变化明显不同, 也与区域网水平应变异常区的空间分布不同, 但该沉降区与区域网水平应变异常区同时出现。 大幅度同震垂直位移集中在龙门山断层北段震前垂直位移闭锁区。 这些事实表明, 汶川地震前GPS观测到的紧临震中的沉降区及垂直运动闭锁区与汶川地震的发生存在密切关系。     

Measurement of ice flow velocities from GPS positions logged by short-period seismographs in East Antarctica

The ice flow velocity is a basic feature of glaciers and ice sheets. Measuring ice flow velocities is very important for estimating the mass balance of ice sheets in the Arctic and Antarctic. Traditional methods for measuring ice flow velocity include the use of stakes, snow pits and on-site geodetic GPS and remote sensing measurement methods. Geodetic GPS measurements have high accuracy, but geodetic GPS monitoring points only sparsely cover the Antarctic ice sheets. Moreover, the resolution and accuracy of ice flow velocities based on remote sensing measurements are low. Although the accuracy of the location data recorded by the navigation-grade GPS receivers embedded in short-period seismographs is not as good as that of geodetic GPS,the ice flow velocity can be accurately measured by these navigation-grade GPS data collected over a sufficiently long period. In this paper, navigation-grade GPS location data obtained by passive seismic observations during the 36 th Chinese National Antarctic Research Expedition were used to accurately track the movement characteristics of the ice sheet in the Larsemann Hills of East Antarctica and the Taishan Station area. The results showed that the ice sheet in the two study areas is basically moving northwestward with an average ice flow velocity of approximately 1 m mon-1. The results in the Taishan Station area are basically consistent with the geodetic GPS results, indicating that it is feasible to use the embedded GPS location data from shortperiod seismographs to track the movement characteristics of ice sheets. The ice flow characteristics in the Larsemann Hills are more complex. The measured ice flow velocities in the Larsemann Hills with a resolution of 200 m help to understand its characteristics. In summary, the ice flow velocities derived from GPS location data are of great significance for studying ice sheet dynamics and glacier mass balance and for evaluating the systematic errors caused by ice sheet movements in seismic imaging.     

Reconstructing Regional Ionospheric Electron Density: A Combined Spherical Slepian Function and Empirical Orthogonal Function Approach

The computerized ionospheric tomography is a method for imaging the Earth’s ionosphere using a sounding technique and computing the slant total electron content (STEC) values from data of the global positioning system (GPS). The most common approach for ionospheric tomography is the voxel-based model, in which (1) the ionosphere is divided into voxels, (2) the STEC is then measured along (many) satellite signal paths, and finally (3) an inversion procedure is applied to reconstruct the electron density distribution of the ionosphere. In this study, a computationally efficient approach is introduced, which improves the inversion procedure of step 3. Our proposed method combines the empirical orthogonal function and the spherical Slepian base functions to describe the vertical and horizontal distribution of electron density, respectively. Thus, it can be applied on regional and global case studies. Numerical application is demonstrated using the ground-based GPS data over South America. Our results are validated against ionospheric tomography obtained from the constellation observing system for meteorology, ionosphere, and climate (COSMIC) observations and the global ionosphere map estimated by international centers, as well as by comparison with STEC derived from independent GPS stations. Using the proposed approach, we find that while using 30 GPS measurements in South America, one can achieve comparable accuracy with those from COSMIC data within the reported accuracy (1 × 10¹¹ el/cm³) of the product. Comparisons with real observations of two GPS stations indicate an absolute difference is less than 2 TECU (where 1 total electron content unit, TECU, is 10¹⁶ electrons/m²).