VMF3/GPT3: refined discrete and empirical troposphere mapping functions

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of \(3^{\circ }\). Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a \(5^{\circ }\times 5^{\circ }\) as well as a \(1^{\circ }\times 1^{\circ }\) global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.     

Testing of global pressure/temperature (GPT) model and global mapping function (GMF) in GPS analyses

Several sources of a priori meteorological data have been compared for their effects on geodetic results from GPS precise point positioning (PPP). The new global pressure and temperature model (GPT), available at the IERS Conventions web site, provides pressure values that have been used to compute a priori hydrostatic (dry) zenith path delay z _h estimates. Both the GPT-derived and a simple height-dependent a priori constant z _h performed well for low- and mid-latitude stations. However, due to the actual variations not accounted for by the seasonal GPT model pressure values or the a priori constant z _h, GPS height solution errors can sometimes exceed 10 mm, particularly in Polar Regions or with elevation cutoff angles less than 10 degrees. Such height errors are nearly perfectly correlated with local pressure variations so that for most stations they partly (and for solutions with 5-degree elevation angle cutoff almost fully) compensate for the atmospheric loading displacements. Consequently, unlike PPP solutions utilizing a numerical weather model (NWM) or locally measured pressure data for a priori z _h, the GPT-based PPP height repeatabilities are better for most stations before rather than after correcting for atmospheric loading. At 5 of the 11 studied stations, for which measured local meteorological data were available, the PPP height errors caused by a priori z _h interpolated from gridded Vienna Mapping Function-1 (VMF1) data (from a NWM) were less than 0.5 mm. Height errors due to the global mapping function (GMF) are even larger than those caused by the GPT a priori pressure errors. The GMF height errors are mainly due to the hydrostatic mapping and for the solutions with 10-degree elevation cutoff they are about 50% larger than the GPT a priori errors.     

Implementation and testing of the gridded Vienna Mapping Function 1 (VMF1)

The new gridded Vienna Mapping Function (VMF1) was implemented and compared to the well-established site-dependent VMF1, directly and by using precise point positioning (PPP) with International GNSS Service (IGS) Final orbits/clocks for a 1.5-year GPS data set of 11 globally distributed IGS stations. The gridded VMF1 data can be interpolated for any location and for any time after 1994, whereas the site-dependent VMF1 data are only available at selected IGS stations and only after 2004. Both gridded and site-dependent VMF1 PPP solutions agree within 1 and 2 mm for the horizontal and vertical position components, respectively, provided that respective VMF1 hydrostatic zenith path delays (ZPD) are used for hydrostatic ZPD mapping to slant delays. The total ZPD of the gridded and site-dependent VMF1 data agree with PPP ZPD solutions with RMS of 1.5 and 1.8 cm, respectively. Such precise total ZPDs could provide useful initial a priori ZPD estimates for kinematic PPP and regional static GPS solutions. The hydrostatic ZPDs of the gridded VMF1 compare with the site-dependent VMF1 ZPDs with RMS of 0.3 cm, subject to some biases and discontinuities of up to 4 cm, which are likely due to different strategies used in the generation of the site-dependent VMF1 data. The precision of gridded hydrostatic ZPD should be sufficient for accurate a priori hydrostatic ZPD mapping in all precise GPS and very long baseline interferometry (VLBI) solutions. Conversely, precise and globally distributed geodetic solutions of total ZPDs, which need to be linked to VLBI to control biases and stability, should also provide a consistent and stable reference frame for long-term and state-of-the-art numerical weather modeling.     

时段选取对大气负荷重力效应的影响分析

针对当前重力观测数据处理中大气负荷效应改正的不确定性问题,该文提出一种分时段改正方法。通过采用不同时段观测数据,基于回归分析方法系统讨论时段选取对大气负荷重力效应改正的影响。利用高精度Wettzell台站超导重力观测数据进行实验分析。实验结果表明:采用不同时段观测数据,大气导纳值差异最大值约为-0.1μGal/hPa;采用不同时段的观测数据进行大气效应改正,其最大差异整体上可以达到2μGal。本文的研究可为精确计算大气负荷重力效应提供一定参考。     

Comparison of length of day with oceanic and atmospheric angular momentum series

This is a companion paper to earlier comparisons and study of operational polar motion series, published recently in the same journal. In this contribution, four operational, publicly available, length-of-day (LOD) time series have been compared to the atmospheric angular momentum (AAM) augmented with recent oceanic angular momentum (OAM) data during September 1997–July 2000, using several intervals ranging from 3 days to almost 3 years. Additionally, the LOD of the International GNSS Service (IGS) historical series and a new LOD combination (CMB) were also analyzed. All the six LOD series showed an overall correlation exceeding 0.99 for the complete interval of almost 3 years. Even for the shortest interval of only 3 days, the correlation was still higher than 0.60. The combined AAM + OAM series with inverted barometer corrections always gave the best correlation. The Rapid Service LOD of the International Earth Rotation and Reference Systems Service (IERS) compared the best at all intervals but the shortest one, where the CMB LOD was the best with a correlation of 0.73, followed by both IGS series with a correlation of about 0.71. Prior to all the correlation analyses, in addition to the removal of all the known (conventional) LOD tidal variations with periods ranging from 5.6 days to 18.6 years and lunar fortnightly and monthly oceanic tides, small corrections of lunar fortnightly and monthly tides, semi-annual, annual periodical signals, drift and scale had to be estimated with respect to the combined AAM + OAM series.     

Assessment of ZTD derived from ECMWF/NCEP data with GPS ZTD over China

The accuracy and feasibility of computing the zenith tropospheric delays (ZTDs) from data of the European Center for Medium-Range Weather Forecasts (ECMWF) and the United States National Centers for Environmental Prediction (NCEP) are studied. The ZTDs are calculated from ECMWF/NCEP pressure-level data by integration and from the surface data with the Saastamoinen model method and then compared with the solutions measured from 28 global positioning system (GPS) stations of the Crustal Movement Observation Network of China (CMONOC) for 1 year. The results are as follows: (1) the error of the integration method is 1–3 cm less than that of the Saastamoinen model method. The agreement between the ECMWF ZTD and GPS ZTD is better than that between NCEP ZTD and GPS ZTD; (2) the bias and root mean square difference (RMSD), especially the latter, have a seasonal variation, and the RMSD decreases with increasing altitude while the variation with latitude is not obvious; and (3) when using the full horizontal resolution of 0.5° × 0.5° of the ECMWF meteorological data in place of a reduced 2.5° × 2.5° grid, the mean RMSD between GPS and ECMWF ZTD decreases by 4.5 mm. These results illuminated the accuracy and feasibility of computing the tropospheric delays and establishing the ZTD prediction model over China for navigation and positioning with ECMWF and NCEP data.     

Comparison of polar motion with oceanic and atmospheric angular momentum time series for 2-day to Chandler periods

During a 4-year period starting in July 1996 and using intervals ranging from 3 days to 4 years, four precise polar motion (PM) series have been compared to excitation by atmospheric angular momentum (AAM) augmented with oceanic angular momentum (OAM) data. The first three series (C03, C04 and Bulletin A) are multi-technique combinations generated by the International Earth Rotation and Reference Systems Service (IERS) and the fourth combined series (IGS00P02) is produced by the International GPS Service (IGS) using only GPS data. The IGS PM compared the best with the combined excitations of atmosphere and oceans (AAM+OAM) at all intervals, showing high overall correlation of 0.8–0.9. Even for the interval of only three days, the IGS PM gave a significant correlation of about 0.6. Moreover, during the interval of February 1999 – July 2000, which should be representative of the current precision of the IGS PM, a significant correlation (>0.4) extended to periods as short as 2.2 days and 2.5 days for the x_p and y_p PM components, respectively. When using the IERS Bulletin B (C04) PM and an interval of almost 6 years, starting in November 1994, the combined OAM+AAM accounted for practically all the annual, semi-annual and Chandler wobble (CW) PM signals. When only AAM was used, either the US National Centers for Environment Prediction reanalysis data, which were used throughout this study, or the Japanese Meteorological Agency data, two large and well-resolved amplitude peaks of about 0.1 mas/day, remained at the retrograde annual and CW periods.     

两种高光谱热红外数据大气校正方法的分析与比较

利用模拟数据对Autonomous Atmospheric Compensation(AAC)和In-scene Atmospheric Compensation(ISAC)这两种高光谱热红外数据大气校正方法进行了对比和分析。结果显示,在满足方法适用条件情况下,AAC方法大气校正精度较高,除湿热的热带大气外,大气透过率的反演误差小于0.02,大气上行辐射的误差小于0.004W.m-2.sr-1.cm;而ISAC方法精度较低,透过率误差在0.05至0.3之间,上行辐射误差在0.003W.m-2.sr-1.cm至0.035W.m-2.sr-1.cm之间变化,误差随大气水汽含量增加而增加。大气非均一性对大气校正精度影响分析表明,AAC方法大气校正精度受大气非均一性影响显著。因此,需从高光谱数据光谱信息出发,发展针对低空间分辨率高光谱热红外数据的大气校正方法,以克服现有方法大气水平均一假设的不足。     

Robust GPS/BDS/INS tightly coupled integration with atmospheric constraints for long-range kinematic positioning

GPS Solutions - The combination of new global navigation satellite system (GNSS) has brought great benefits to reliable positioning and ambiguity resolution (AR), especially in restricted...     

GPT2w模型检验以及对流层模型的参数互融

各种对流层经验模型中,GPT2w模型是目前标称精度最高的对流层经验模型,其在模型化对流层延迟的同时,也提供具体的模型化气象元素。以USNO的ZTD产品检验模型ZTD精度;以IGRA发布的大气廓线数据,对模型加权平均温度T_m、水汽直减率λ的精度进行验证。计算发现,模型加权平均温度T_m具有-2.56K的系统偏差,改正该偏差后,模型ZTD对比USNO偏差从-1.38 mm提升至-0.3 mm;还验证了模型水汽直减率λ的两种获取方式具有很好的一致性。提出以测站气压P、测站温度t、测站相对湿度hr为实测气象元素,以校正后的T_m、高精度的λ为经验气象元素,作为对流层延迟模型输入参数的互融方法。该互融方法计算ZHD、ZWD经验模型分别采用目前最优的Saast静力学延迟模型和Askne & Nordius湿延迟模型。以USNO发布的340个IGS跟踪站的对流层延迟数据作为参考,该互融方法较直接气象元素法、校正后的GPT2w模型均有显著精度提升。在不可获取气象数据的前提下,校正后的GPT2w模型具有很高的先验精度;若可获取近实时气象数据（如自动气象站）,则推荐采用新的参数互融模型。     

Comparison of SARAL and Jason-1/2 altimetry-derived geoids for geophysical exploration over the Indian offshore

Satellite with ARgos and ALtika (SARAL) altimeter includes the ALTIKA payload, a 35.75 GHz Ka band radar altimeter. High pulse repetition frequency of SARAL (4 KHz) satellite provides better along-track information. Jason-1/2 data have been extensively utilized as a follow-up of TOPEX/Poseidon altimeter data for its accurate measurements of the sea surface heights, particularly for geodetic mission of Jason-1. In this study, we have compared SARAL and Jason-1/2 altimetry-derived classical and residual geoids over the Indian offshore using Rapp’s, EGM96 and EGM08 gravity model coefficients, which are of interest for better understanding of geological and structural evolution/interpretation. SARAL and Jason-1/2 data have also been used over the two prominent geological features over the Indian offshore, namely the Bombay High in the western offshore and the 85°E Ridge in the Bay of Bengal. The SARAL altimetry-derived geoids could delineate these major geological/structural features with distinct residual geoidal lows.     

大气环境卫星污染气体和大气颗粒物协同观测综述

空气污染作为一种重要的环境问题,直接影响人们的日常生活和身体健康。随着污染气体和颗粒物观测技术的逐步成熟,基于卫星平台的近地层大气污染物监测得到了快速的发展。本文概括性描述了大气环境关注的污染气体和大气颗粒物的主流遥感方法,对各方法的适用场景及优缺点进行了评述。尽管差分吸收光谱方法对污染气体的监测十分有效,但最优估计算法可进一步从多光谱信息中提取部分污染气体（例如：臭氧O3、一氧化碳CO等）的分层信息,有助于更细致地刻画污染气体在整层大气中的垂直分布。对于大气颗粒物遥感方法,采用不同的技术手段进行地气解耦是算法的核心问题,增加光谱、角度、偏振以及时间序列信息都可有效增加算法的地气解耦能力。基于对污染气体和大气颗粒物反演算法的总结,从污染气体和颗粒物协同观测的角度对卫星平台及传感器的发展历程进行了梳理,论述了紫外、红外以及可见光波段的传感器协同观测的优势,展望了未来静止卫星星座的高时空分辨率大气污染监测能力以及中国卫星的贡献。还探讨了以近地面大气污染物监测卫星探测技术及遥感算法亟待解决的问题以及未来的可能发展方向。     

北京地区HJ-1卫星CCD数据的气溶胶反演及在大气校正中的应用

与现有的大气卫星传感器相比,环境一号卫星(HJ-1)CCD相机具有较高的空间分辨率(30m),使得在城市地区找到光谱纯像元的机率大大增加。本文提出一种基于纯像元提取的城市地区气溶胶光学厚度(AerosolOpticalDepth,AOD)反演算法,利用像元纯净指数来提取CCD影像上的纯像元,并由HJ-1A星和B星的多时相CCD观测数据结合地表双向反射率模型确定纯像元的地表反射特性,在此基础上反演AOD。与AERONET地基测量数据的对比表明,该算法具有较高精度,相关系数为0.83,线性拟合斜率为1.091,截距为0.053。基于该方法的AOD反演结果作为输入,能较大程度提高HJ-1卫星CCD影像大气校正的精度。     

BDS/GPS/GLONASS组合单历元姿态测量性能对比分析

相比于单一卫星导航系统,多卫星导航系统组合具有显著增加可用卫星数目、改善卫星空间几何结构等优点,因而多卫星导航系统组合应用成为近年来关注的热点。在复杂观测条件下,利用BDS/GPS/GLONASS组合进行载体姿态测量具有单系统无法比拟的优势。首先阐述了BDS/GPS/GLONASS组合超短基线解算的双差模型以及姿态测量基本原理;然后分析了BDS/GPS/GLONASS组合多频单历元姿态测量性能。通过实测静态数据设置不同高度截止角进行分析表明:相比于单系统及双系统组合的姿态测量,BDS/GPS/GLONASS组合能够有效地提高姿态测量的精度、稳定性和可用性。当运动载体处于高楼、峡谷等受遮挡严重的复杂环境时,BDS/GPS/GLONASS组合单历元姿态测量更具有应用价值。     

Use of atmospheric angular momentum forecasts for UT1 predictions: analyses over CONT08

Real-time orbit determination and interplanetary navigation require accurate predictions of the orientation of the Earth in the celestial reference frame and in particular that for Universal Time UT1. Much of the UT1 variations over periods ranging from hours to a couple of years are due to the global atmospheric circulation. Therefore, the axial atmospheric angular momentum (AAM) forecast series may be used as a proxy index to predict UT1. Our approach taking advantage of this fact is based on an adaptive procedure. It involves incorporating integrations of AAM estimates into UT1 series. The procedure runs on a routine basis using AAM forecasts that are based on the two meteorological series, from the US National Centers for Environmental Prediction and the Japan Meteorological Agency. It is pertinent to test the prediction method for the period that includes the special CONT08 campaign over which we expect a significant improvement in UT1 accuracy. The studies we carried out were aimed both to compare atmospheric forecasts and analyses, as well as to compare the skills of the UT1 forecasts based on the method with atmospheric forecasts and that using current statistical processes, as applied to the C04 Earth orientation parameters series derived by the International Earth rotation and Reference Systems service (IERS). Here we neglect the oceanic sub-diurnal and diurnal variations, as these signals are expected to be smaller than the UT1-equivalent of 100 μs, when averaged over a few days. The prediction performances for a 2-day forecast are similar, but at a forecast horizon of a week, the AAM-based forecast is roughly twice as skillful as the statistically based one.     

北京城市下垫面大气CO2反演算法

大气温室气体监测仪GMI（Greenhouse gases Monitor Instrument）是高分五号（GF-5）卫星载荷之一,主要用于全球温室气体含量监测和碳循环研究。高精度反演是卫星大气CO₂遥感的基本需求。地表反射率影响卫星遥感辐射量及辐射传输过程中的地气耦合过程,严重制约着CO₂的反演精度,针对GMI开发高精度的大气CO₂反演算法,地表反射是一个需要重点考虑的因素。城市是CO₂重要的发射源,且城市下垫面存在明显的二向反射特性,加上城市大气条件不良,复杂的地气耦合效应存在这都考验反演算法的准确性和鲁棒性。本文针对北京城市地区,利用2011年—2016年共5年的MODIS（MODerate-resolution Imaging Spectroradiometer）地表二向反射分布函数BRDF（Bidirectional Reflectance Distribution Function）数据,构建了适合利用单次观测数据反演的BRDF模型,并提出一种同时反演地表BRDF参数和大气CO₂含量的算法。结果表明在550 nm波长处气溶胶光学厚度AOD（Aerosol Optical Depth）小于0.4时,大部分GMI模拟数据的反演误差控制在0.5%（~2 ppm）内。利用GOSAT （Greenhouse gases Observing SATellite）实测数据的反演结果与修正后的日本国立环境研究所NIES（National Institute for Environmental Studies）反演结果进行对比,其平均误差为1.25 ppm,相关性达到0.85。本算法满足GMI数据在北京城市区域高精度CO₂反演的需求,并使得反演高值气溶胶区域数据成为可能,增加了GMI观测数据的利用率。     

星载大气探测激光雷达发展与展望

从最早的星载激光雷达空间技术实验LITE出发,回顾了已成功发射的多颗星载激光雷达发展历程。详细阐述了LITE、CALIPSO等星载激光雷达在大气遥感领域,特别是气候环境变化和数值预报模式研究上所取得的成就。主要从全球气溶胶垂直结构及其辐射强迫、全球云垂直结构和特征、气溶胶-云-降水相互作用和气溶胶数据在雾-霾和沙尘天气预报中的应用等4个方面进行展开说明,并且深入分析了未来星载激光雷达在大气风场和大气成分探测方面所面临的需求和挑战。在大气风场探测需求方面,结合星载激光雷达探测优势从提高热带地区的天气预报准确率、提高非地转条件下中小尺度短时临近预报水平和填补卫星高/低空急流监测技术空白等3个方面进行详细论述。在大气成分探测需求方面,与传统被动探测仪器相比较,突出激光雷达在信噪比、CO2垂直结构和夜间探测上的明显优势。最后,指出全球风场和大气成分探测将成为未来星载激光雷达的重要发展方向。     

地表反射率产品支持的GF-1 PMS气溶胶光学厚度反演及大气校正

GF-1卫星PMS(GF-1 PMS)数据具有高空间分辨率、短重访周期的特点,可以在地表类型识别、参数提取中发挥重要作用。但由于缺少2.1μm附近的短波红外波段,使得气溶胶反演时地表反射率的精确确定非常困难,从而导致其高精度大气校正难以开展,限制了该数据的应用。本文提出了一种地表反射率数据支持的气溶胶反演方法,用于GF-1PMS数据的大气校正。其基本思想是:使用现有的地表反射率数据集为GF-1PMS数据提供地表反射率,用于确定GF-1PMS图像中浓密植被像元(DDV)的分布,基于确定的浓密植被像元反演气溶胶光学厚度(AOD),并用于大气校正。这里使用的地表反射率数据集为合成的无云MODIS地表反射率产品,对GF-1PMS数据做了空间尺度的转换。为降低两类数据配准误差对地表反射率确定的影响,提出了使用区域NDVI分布百分比匹配的方法,回避了像元的直接匹配,为GF-1PMS数据提供DDV的空间分布。为验证该方法的有效性,利用北京、太湖两个AERONET站点观测的气溶胶光学厚度对气溶胶反演结果进行精度验证,结果表明,气溶胶反演算法精度较高,稳定性较强。AOD反演结果应用于北京和敦煌地区的GF-1PMS数据大气校正,获得的地表反射率与地面实测的地表反射率的误差低于0.015,且大气校正后影像对比度明显提高。     

针对GF-1遥感影像的基于影像与基于辐射传输模型的两种交叉定标方法比较

"高分一号"配置了4台16m分辨率多光谱宽幅(WFV)相机,组合观测幅宽达到800km。为了将其应用于定量遥感,需要对其进行精确的辐射定标。目前针对高分一号卫星有两种交叉定标方法,都在传统方法的基础上进行了改进。一种是基于影像的交叉定标方法(image-based),另一种是基于辐射传输模型和二向反射分布函数的交叉定标方法(RTM-BRDF)。本文采用这两种方法对高分一号(GF-1)的4个相机进行辐射定标,并对这两种方法进行了对比分析,发现对于WFV2和WFV3这两个近似星下点成像相机,image-based方法可以得到精度较高的辐射定标系数,而对于WFV1和WFV4这两个非星下点成像相机来说,RTM-BRDF方法得到的定标系数精度较高。因此,最终将两种方法结合给出GF-1 4个相机最终的定标系数。