基于垂直剖面函数式的全球对流层天顶延迟模型的建立

对流层延迟是无线电导航定位的主要误差源之一,其值对目标高程的变化敏感.在动态导航定位中,由于目标高程变化随机性强,延迟改正实时性需求高,已有的对流层延迟模型难以满足应用需求.本文利用2005到2006年ERA-Interim再分析气象资料积分方法计算的对流层天顶总延迟(ZTD)、天顶静力学延迟(ZHD)以及天顶非静力学延迟(ZWD)的垂直剖面研究了ZTD随高程变化的最佳拟合形式,并以此为基础建立了全球ZTD改正模型SHAO-H.该模型以大气中水汽的垂直分布规律为依据,将ZTD表示为高程的分段函数,进而再模制每段函数中各参数随时间的变化.精度评估显示:与积分ZTD相比,SHAO-H模型计算的ZTD在不同等压层上的平均bias大部分在±1 mm以内,随着高度的上升,平均RMS由39 mm减小至不足1 mm;与IGS (International GNSS Service)实测ZTD相比,SHAO-H模型的精度(bias为7.02 mm,RMS为38.50 mm)优于UNB3m模型(bias为14.67 mm, RMS为51.95 mm).SHAO-H模型具有精度稳定、计算简便等优点,适宜任意高度的用户使用.     

一种新的高精度全球对流层天顶延迟模型

对流层延迟是影响高精度卫星导航定位的关键因素,也是大气科学研究的重要数据.针对已有全球对流层延迟模型的模型方程未同时顾及高程、纬度和季节变化以及模型构建时仅使用单一格网点数据等问题,本文提出了一种对流层天顶延迟(ZTD)全球模型构建的新方法,即引入滑动窗口算法将全球剖分为大小一致的规则窗口,利用2008—2015年全球大地观测系统(GGOS)大气格网产品构建每个窗口同时顾及高程、纬度和季节因子的全球ZTD新模型(GGZTD模型).联合未参与建模的2016年全球GGOS格网产品和2016年全球316个IGS站精密ZTD产品,检验了GGZTD模型的精度和适用性.结果表明:以GGOS大气格网ZTD产品和IGS站ZTD产品为参考值,GGZTD模型在全球的精度分别为3.58 cm和3.62 cm,相对于UNB3m模型和目前标称精度最优的GPT2w模型计算的ZTD信息,GGZTD模型在全球表现出了最优的精度和稳定性,其精度相对于UNB3m模型具有显著的提升(精度提高了30%以上),相对于GPT2w模型仍具有一定的改善;在ZTD计算时GGZTD模型相对于GPT2w模型显著地减少了模型参数,尤其相对于GPT2w-1(减少了99%).GGZTD模型只需输入位置与时间和依赖相对较少的模型参数则能在全球获得高精度和稳定的ZTD信息,极大地提升了模型的计算效率.     

两种精化的对流层延迟改正模型

对流层延迟是全球导航卫星系统(Global Navigation Satellite System,GNSS)导航定位中的重要误差源,其量值主要受气象条件影响.采用传统对流层建模思路,利用GPT2模型来提供相对准确的气温、气压和相对湿度,然后利用Saastamoinen模型来计算天顶对流层延迟,由此构建了GPT2+Saas模型;采用新的对流层建模思路,直接针对天顶对流层延迟的时空特性建模,构建了与GPT2+Saas模型相匹配的GZTDS格网模型.以GGOS Atmosphere格网数据为参考,GPT2+Saas模型(Bias:0.2cm;RMS:4.2cm)和GZTDS模型(Bias:0.2cm;RMS:3.7cm)较UNB3m模型精度分别提升34%和43%.以IGS(International GNSS Service)数据为参考,GPT2+Saas(Bias:0.5cm;RMS:4.7cm)和GZTDS(Bias:-0.3cm;RMS:3.8cm)相对UNB3m模型精度分别提升10%和27%.针对GPT2+Saas模型在少数测站出现精度异常的情况进行了研究,探讨了可能的原因.在两种不同思路构建的精化对流层模型中,GZTDS模型不仅表现出更高的精度,而且在时间稳定性和地理稳定性上也表现出优越性.     

亚洲地区ECMWF/NCEP资料计算 ZTD的精度分析

对流层延迟是卫星导航定位的主要误差源,气象观测的数值预报资料可用来计算对流层延迟改正量.本文通过分布于亚洲地区的49个GPS台站一年的实测ZTD资料,对利用欧洲中尺度天气预报中心(ECMWF)分析资料、美国国家环境预报中心(NCEP)再分析资料和NCEP预报资料,计算对流层天顶延迟(ZTD)改正的有效性和可能达到的精度进行了评估,分析了ECMWF和NCEP在亚洲地区的适用程度和其分辨率对计算ZTD精度的影响.研究结果表明:(1)相对于 GPS实测ZTD,用ECMWF资料计算ZTD的bias和rms分别为-1.0 cm 和2.7 cm,优于NCEP再分析资料,可用于高精度ZTD研究和应用;NCEP预报数据计算ZTD的bias和rms分别为2.4 cm 和 6.8 cm,足以满足广大GNSS实时导航定位用户对流层延迟改正的需要.(2)bias和rms呈现明显的季节性变化,总体上夏季大,冬季小;在空间分布上随着纬度的变化不明显,但随高度的增加rms总体上有递减趋势.另外还发现,亚洲东部地区夏季日平均bias和rms和南部热带地区冬季的日平均bias和rms变化相对较大.(3)ECMWF2.5°和0.5°的资料进行了对比分析,发现0.5°分辨率资料的rms比2.5°减小1~5 mm.这些结果,为在亚洲地区的空间大地测量、导航定位和INSAR等工作中,应用ECMWF/NCEP的资料进行对流层大气延迟改正的有效性和可能达到的精度提供了重要参考.     

对流层天顶延迟模型研究进展及其在中国区域的精度分析

对流层延迟是空间大地测量技术的主要误差源之一,数据处理中对流层延迟的修正需要借助对流层延迟模型.本文首先从物理原理出发,梳理了对流层天顶延迟模型的研究历程和最新进展.按照时间顺序,对流层延迟模型先后经历了依赖实测气象资料的经典模型、不依赖实测参数的经验模型和以数值模型气象资料为基础的高分辨经验模型三个发展阶段.其次,本文利用中国区域内219个GPS测站2014—2015年两年实测的天顶延迟,对后两类经验模型中国际最新通用的代表模型UNB3m和GPT2w在中国境内的实际精度进行评估.精度评估结果显示:UNB3m模型在中国地区的平均Bias为-0.85 cm,平均RMSE为5.14 cm,其精度不随计算时间分辨率的变化而显著变化;模型参数的空间分辨率对GPT2w模型在中国地区的精度的影响不大,但GPT2w模型精度随计算时间分辨率的提高显著下降,2 h分辨率时GPT2w模型的平均RMSE分别为8.07 cm(1°参数文件)和7.97 cm(5°参数文件),1天分辨率时GPT2w模型的平均RMSE分别为3.49 cm(1°参数文件)和3.59 cm(5°参数文件);受水汽分布的影响,时间上,两个模型在冬季的精度相对最高,在夏季的精度相对最差,空间上,两个模型在高纬度和高海拔地区的精度相对较高.以上分析可为中国区域用户对流层延迟模型的选择提供参考.     

基于GNSS的再分析资料对流层延迟精度评估

对流层延迟对导航定位精度有着重要的影响,而再分析资料提供的高精度气象参数计算的对流层延迟可应用于定位过程中以提升定位精度.本文针对三种再分析资料计算的对流层延迟进行精度评估,并将其应用在精密单点定位中,分析其对定位精度的影响.首先,利用2020年全球范围内125个IGS(International GNSS Service)站的对流层天顶总延迟(Zenith Total Delay, ZTD)作为真值对三种再分析资料(ERA5、MERRA2、CRA40)计算的ZTD进行了精度评估,并分析其时空分布特性.研究结果表明：ERA5-ZTD的均方根误差(RMS)最小(12.1 mm),其次为CRA40-ZTD(15.8 mm)和MERRA2-ZTD(16.9 mm),整体上ERA5-ZTD的精度最高;据所选的IGS站点的比较结果发现赤道平均偏差(BIAS)呈现负值,在中高纬度地区CRA40的精度优于MERRA2,在低纬度地区则相反,而ERA5在各纬度平均精度均为最优;当考虑季节因素时,三者计算的ZTD-RMS在夏秋季较大,其中ERA5的RMS季节变化最稳定.之后还利用180个探空站点对三者计算...     

区域实时对流层网格模型构建及在精密单点定位中的应用

受制于对流层延迟建模方法和建模背景场精度及时空分辨率的影响,目前实时对流层延迟模型的精度和稳定性都有待进一步改善.本文利用甘肃及周围地基共计184个GNSS (Global Navigation Satellite System)站估算的ZTD (Zenith Troposphere Delay),构建了空间分辨率为0.25°×0.25°的甘肃地区实时ZTD网格模型.针对传统的高程归化模型及水平内插模型精度低的问题,本文提出了利用高斯指数函数模型将不同高程的GNSS/ZTD归化到统一的高度,再基于BP神经网络模型从网格顶点周围统一高度后的GNSS/ZTD中内插出网格顶点处的ZTD.为了验证甘肃ZTD网格模型的精度,选取2022年甘肃地区8个未参与建模的陆态网GNSS测站的数据进行了实验.统计结果显示：与事后PPP (Precise Point Positioning)处理GNSS估算的ZTD相比,甘肃ZTD网格模型与真值偏差的RMS优于1.52 cm.此外,将构建的实时ZTD格网模型用于约束PPP处理,对于PPP浮点解施加ZTD约束后U方向精度提升22.9%,U方向收敛时间缩短26.4...     

基于全球气象再分析资料的InSAR对流层延迟改正研究

气压、温度和水汽含量等大气物理参数的时空变化导致的对流层延迟是制约合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)高精度应用的重要因素之一.最新研究显示气象再分析资料在补偿对流层延迟影响方面具有巨大的应用潜力,这促使我们对其有效性和鲁棒性做进一步的研究和探索.本文首先推导了利用气象再分析资料对InSAR进行对流层延迟校正的算法;然后以美国南加州地区的ENVISAT ASAR数据为例,分析了基于两种气象再分析资料(ERA-Interim和North American Regional Reanalysis,NARR)校正InSAR对流层延迟改正的效果;通过与MERIS水汽延迟改正结果比较,验证了该方法的有效性.实验结果表明:(1)不能简单忽略干延迟,可通过气象再分析资料进行有效估计;(2)通过与MERIS水汽产品获得的对流层延迟比较发现,气象再分析资料能够取得接近于MERIS的改善效果;(3)对ERA-Interim和NARR两种气象再分析资料而言,虽然后者具有更高的时间和空间分辨率,但在改正InSAR对流层延迟方面并没有表现出比前者更明显的优势;(4)气象再分析资料可以很好地估计与地形强相关的垂直分层延迟,但对于小尺度的湍流混合延迟的捕捉能力有限.综合分析认为,气象再分析资料的优势在于其数据可随时获得、免费和全球覆盖,它可以显著减弱大尺度的垂直分层延迟对干涉图相位的影响,从而有助于InSAR获取更真实可靠的地形高程和地表形变信息.     

基于改进的BP神经网络构建区域精密对流层延迟模型

利用神经网络算法挖掘海量数据的规律已成为科技发展的一种趋势,本文针对卫星信号的天顶对流层延迟进行建模.对流层延迟是影响卫星定位精度的重要因素之一,建立精密区域对流层模型对高精度定位有着重要的意义.对区域测站对流层延迟数据的分析,考虑到实时建模中传统BP（Back Propagation）神经网络计算量大,易出现"过拟合"现象、不稳定等因素,通过改进的BP神经网络建立了区域精密对流层模型.详细介绍了新模型的建立过程,并与常用的对流层区域实时模型进行了对比.还讨论了建模测站数目对预报精度的影响.相比现有的其他对流层延迟模型,基于改进的BP神经网络构建的区域精密对流层延迟模型无论在拟合和预报方面都有较好的精度,且随着测站数目的增加模型精度趋于平稳.改进的模型参数较少,可以进行实时的区域精密对流层延迟改正;需要播发的信息量小,适用于连续运行参考站系统（Continuously Operating Reference Stations,CORS）的应用.研究表明：改进的BP神经网络模型能够更好的充分利用大规模历史数据描述卫星信号对流层延迟的空间分布情况,适用于实时大区域精密对流层建模.基于日本地区2005年近1000多个测站的NCAR（National Center Atmospheric Research）对流层数据进行区域对流层延迟建模,结果表明改进的BP神经网络模型在拟合和预报精度上都有较大提升,RMSE（Root Mean Square Error）分别为：7.83 mm和8.52 mm,而四参数模型拟合、预报RMSE分别18.03 mm和16.60 mm.     

一种能实现单频PPP-RTK的GNSS局域参考网数据处理算法

全球范围内大量布设的GNSS(Global Navigation Satellite System)参考网为精密定位、导航和授时等应用提供了丰富的数据资源.基于局域参考网,先后发展了若干侧重实现双频精密定位的技术,如NRTK(Network Real Time Kinematic),PPP(Precise Point Positioning)和PPP-RTK等.其中,PPP-RTK融合了NRTK和PPP的技术优势,是目前相关研究的热点.本文改进了利用局域参考网提取各类改正信息的算法,以便于实现单频PPP-RTK,具体步骤包括:1)逐参考站实施非组合PPP,并固定已知站星距和卫星钟差,预估电离层延迟、浮点模糊度等参数;2)联合所有参考站的PPP模糊度预估值,通过重新参数化,形成一组双差整周模糊度和接收机、卫星相位偏差;3)固定双差整周模糊度,精化求解卫星相位偏差和各参考站PPP电离层延迟.基于网解中用到的卫星轨道和钟差,以及网解所提供的卫星相位偏差和(内插的)电离层延迟,参考网内的单频流动站即可实施PPP-RTK.基于澳大利亚某连续运行参考站网和流动站的实测数据,考察了:1)参考网数据处理中,双差模糊度的固定成功率(98.89%)和卫星相位偏差估值的时间稳定性(各连续弧段优于0.2周);2)流动站处电离层延迟的内插精度(优于10cm);3)单天内任一历元起算,固定静态(动态)单频PPP整周模糊度所需时长(均不超过10min);4)模糊度固定前后,单频动态PPP的定位精度(模糊度固定后,平面和天顶RMS分别优于5cm和10cm;模糊度固定前,相应RMS仅为28~53cm).     

A global empirical model for estimating zenith tropospheric delay

Tropospheric delay acts as a systematic error source in the Global Navigation Satellite Systems (GNSS) positioning. Empirical models UNB3, UNB3m, UNB4 and EGNOS have been developed for use in Satellite-Based Augmentation Systems (SBAS). Model performance, however, is limited due to the low spatial resolution of the look-up tables for meteorological parameters. A new design has been established in this study for improving performance of the tropospheric delay model by more effectively eliminating the error produced by tropospheric delay. The spatiotemporal characteristics of the Zenith Tropospheric Delay (ZTD) were analyzed with findings that ZTD exhibits different annual variations at different locations and decreases exponentially with height increasing. Spherical harmonics are utilized based on the findings to fit the annual mean and amplitude of the ZTD on a global scale and the exponential function is utilized for height corrections, yielding the ZTrop model. On a global scale, the ZTrop features an average deviation of -1.0 cm and Root Mean Square (RMS) of 4.7 cm compared with the International GNSS Service (IGS) ZTD products, an average deviation of 0.0 cm and RMS of 4.5 cm compared with the Global Geodetic Observing System (GGOS) ZTD data, and an average deviation of -1.3 cm and RMS of 5.2 cm compared with the ZTD data from the Constellation Observing System of Meteorology, Ionosphere, and Climate (COSMIC). The RMS of the ZTrop model is 14.5% smaller than that of UNB3, 6.0% smaller than that of UNB3m, 16% smaller than that of UNB4, 14.5% smaller than that of EGNOS and equivalent to the sophisticated GPT2+Saas model in comparison with the IGS ZTD products. The ZTrop, UNB3m and GPT2+Saas models are finally evaluated in GPS-based Precise Point Positioning (PPP), as the models act to aid in obtaining PPP position error less than 1.5 cm in north and east components and relative large error (>5 cm) in up component with respect to the random walk approach.     

Testing Stokes-Helmert geoid model computation on a synthetic gravity field: experiences and shortcomings

We report on testing the UNB (University of New Brunswick) software suite for accurate regional geoid model determination by use of Stokes-Helmert’s method against an Australian Synthetic Field (ASF) as “ground truth”. This testing has taken several years and has led to discoveries of several significant errors (larger than 5mm in the resulting geoid models) both in the UNB software as well as the ASF. It was our hope that, after correcting the errors in UNB software, we would be able to come up with some definite numbers as far as the achievable accuracy for a geoid model computed by the UNB software. Unfortunately, it turned out that the ASF contained errors, some of as yet unknown origin, that will have to be removed before that ultimate goal can be reached. Regardless, the testing has taught us some valuable lessons, which we describe in this paper. As matters stand now, it seems that given errorless gravity data on 1′ by 1′ grid, a digital elevation model of a reasonable accuracy and no topographical density variations, the Stokes-Helmert approach as realised in the UNB software suite is capable of delivering an accuracy of the geoid model of no constant bias, standard deviation of about 25 mm and a maximum range of about 200 mm. We note that the UNB software suite does not use any corrective measures, such as biases and tilts or surface fitting, so the resulting errors reflect only the errors in modelling the geoid.     

APOD mission status and preliminary results

On September 20 th, 2015, twenty satellites were successfully deployed into a near-polar circular orbit at 520 km altitude by the Chinese CZ-6 test rocket, which was launched from the Tai Yuan Satellite Launch Center. Among these satellites, a set of 4 Cube Sats conform the atmospheric density detection and precise orbit determination(APOD) mission, which is projected for atmospheric density estimation from in-situ detection and precise orbit products. The APOD satellites are manufactured by China Spacesat Co. Ltd. and the payload instruments include an atmospheric density detector(ADD), a dual-frequency dualmode global navigation satellite system(GNSS) receiver(GPS and Beidou), a satellite laser ranging(SLR) reflector, and an S/Xband very long baseline interferometry(VLBI) beacon. In this paper, we compare the GNSS precise orbit products with colocated SLR observations, and the 3 D orbit accuracy shows better than 10 cm RMS. These results reveal the great potential of the onboard micro-electro-mechanical system(MEMS) GNSS receiver. After calibrating ADD density estimates with precise orbit products, the accuracy of our density products can reach about 10% with respect to the background density. Density estimates from APOD are of a great importance for scientific studies on upper atmosphere variations and useful for model data assimilation.     

Assessing Amur Water Regime Variations in the XXI Century with Two Methods Used to Specify Climate Projections in River Runoff Formation Model

A regional numerical physico-mathematical model of river runoff formation is used to study the possibility to assess long-term variations of water regime characteristics in the Amur R. in the XXI century. Two methods were used to specify climate projections as boundary conditions in the hydrological model: (1) based on the results of calculations with an ensemble of global climate models of CMI5 project, (2) based on data obtained by linear transformation of series of actual meteorological observations with the use of normal annual climate parameters calculated by climate models. The results of numerical experiments were used to analyze the sensitivity of the anomaly of Amur normal annual runoff to changes in the climate normals of air temperature and precipitation. The anomalies of normal annual runoff were shown to respond similarly (within the accuracy of sensitivity coefficient estimates) to changes in the appropriate climate normals, whatever the way of specifying climate projections.     

Evaluation of dynamically downscaled reanalysis precipitation data for hydrological application

Skilful and reliable precipitation data are essential for seasonal hydrologic forecasting and generation of hydrological data. Although output from dynamic downscaling methods is used for hydrological application, the existence of systematic errors in dynamically downscaled data adversely affects the skill of hydrologic forecasting. This study evaluates the precipitation data derived by dynamically downscaling the global atmospheric reanalysis data by propagating them through three hydrological models. Hydrological models are calibrated for 28 watersheds located across the southeastern United States that is minimally affected by human intervention. Calibrated hydrological models are forced with five different types of datasets: global atmospheric reanalysis (National Centers for Environmental Prediction/Department of Energy Global Reanalysis and European Centre for Medium‐Range Weather Forecasts 40‐year Reanalysis) at their native resolution; dynamically downscaled global atmospheric reanalysis at 10‐km grid resolution; stochastically generated data from weather generator; bias‐corrected dynamically downscaled; and bias‐corrected global reanalysis. The reanalysis products are considered as surrogates for large‐scale observations. Our study indicates that over the 28 watersheds in the southeastern United States, the simulated hydrological response to the bias‐corrected dynamically downscaled data is superior to the other four meteorological datasets. In comparison with synthetically generated meteorological forcing (from weather generator), the dynamically downscaled data from global atmospheric reanalysis result in more realistic hydrological simulations. Therefore, we conclude that dynamical downscaling of global reanalysis, which offers data for sufficient number of years (in this case 22 years), although resource intensive, is relatively more useful than other sources of meteorological data with comparable period in simulating realistic hydrological response at watershed scales. Copyright © 2013 John Wiley & Sons, Ltd.     

Validation of recent geopotential models in Tierra Del Fuego

This work presents a validation study of global geopotential models (GGM) in the region of Fagnano Lake, located in the southern Andes. This is an excellent area for this type of validation because it is surrounded by the Andes Mountains, and there is no terrestrial gravity or GNSS/levelling data. However, there are mean lake level (MLL) observations, and its surface is assumed to be almost equipotential. Furthermore, in this article, we propose improved geoid solutions through the Residual Terrain Modelling (RTM) approach. Using a global geopotential model, the results achieved allow us to conclude that it is possible to use this technique to extend an existing geoid model to those regions that lack any information (neither gravimetric nor GNSS/levelling observations). As GGMs have evolved, our results have improved progressively. While the validation of EGM2008 with MLL data shows a standard deviation of 35 cm, GOCO05C shows a deviation of 13 cm, similar to the results obtained on land.