Estimation and evaluation of hourly updated global GPS Zenith Total Delays over ten months

The EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) is responsible for the coordination of near real time GPS Zenith Total Delay (ZTD) production in Europe and for aiding the development of ZTD assimilation into Numerical Weather Prediction (NWP) models. Since 2000, the Geodetic Observatory Pecný (GOP) has been routinely estimating regional ZTDs in near real time. In 2010, GOP developed a modified processing system in order to provide the first optimal and robust ZTD solution with a global scope and hourly upgrade, fulfilling the requirements for assimilation into operational NWP models. Since July 2010, the GOP global tropospheric product has consisted of about 90 sites and has contributed routinely in a testing mode into the E-GVAP database. Global near real time ZTDs generated over ten months have been evaluated with respect to IGS and EUREF routine post-processed ZTD products, ZTDs integrated from radiosonde profiles, and ZTDs calculated from the Met Office global NWP model. Comparison with the GNSS post-processed solutions gives standard deviations of 3–6 mm in ZTD and biases of 1–2 mm, which is comparable to GOP regional near real time solution, however, for some isolated or low data quality stations up to 20 % quality decrease can be found. Comparison with NWP shows a latitudinal trend in the standard deviation with values as low as 4 mm at high latitudes, increasing to almost 20 mm in the tropics, and a lack of variability in the model background ZTD in the tropics. The evaluation with global radiosondes gives ZTD standard deviation of 5–16 mm, which is comparable with previous studies in European scope. Since the 10-month comparison gave satisfactory results, GOP was asked by UK Met Office to disseminate the global product to the end users via the Global Telecommunications System. Since 10 October 2011, the GOP global ZTD product configuration has been extended to about 164 global stations and still processed within 10 min. However, in GOP routine contribution to E-GVAP, about 124 stations are available in general due to hourly data latency above 30 min or data gaps.     

Comparative analysis of real-time precise point positioning zenith total delay estimates

The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction (NWP) models, which assimilate GNSS-derived zenith total delay (ZTD) estimates. The development of NWP models with faster assimilation cycles, e.g., 1-h assimilation cycle in the rapid update cycle NWP model, has increased the interest of the meteorological community toward sub-hour ZTD estimates. The suitability of real-time ZTD estimates obtained from three different precise point positioning software packages has been assessed by comparing them with the state-of-the-art IGS final troposphere product as well as collocated radiosonde (RS) observations. The ZTD estimates obtained by BNC2.7 show a mean bias of 0.21 cm, and those obtained by the G-Nut/Tefnut software library show a mean bias of 1.09 cm to the IGS final troposphere product. In comparison with the RS-based ZTD, the BNC2.7 solutions show mean biases between 1 and 2 cm, whereas the G-Nut/Tefnut solutions show mean biases between 2 and 3 cm with the RS-based ZTD, and the ambiguity float and ambiguity fixed solutions obtained by PPP-Wizard have mean biases between 6 and 7 cm with the references. The large biases in the time series from PPP-Wizard are due to the fact that this software has been developed for kinematic applications and hence does not apply receiver antenna eccentricity and phase center offset (PCO) corrections on the observations. Application of the eccentricity and PCO corrections to the a priori coordinates has resulted in a 66 % reduction of bias in the PPP-Wizard solutions. The biases are found to be stable over the whole period of the comparison, which are criteria (rather than the magnitude of the bias) for the suitability of ZTD estimates for use in NWP nowcasting. A millimeter-level impact on the ZTD estimates has also been observed in relation to ambiguity resolution. As a result of a comparison with the established user requirements for NWP nowcasting, it was found that both the G-Nut/Tefnut solutions and one of the BNC2.7 solutions meet the threshold requirements, whereas one of the BNC2.7 solution and both the PPP-Wizard solutions currently exceed this threshold.     

单站地基GPS天顶延迟反演大气剖面研究

基于一定的大气折射率剖面模型和搜索方法,可以由GPS天顶延迟反演大气折射率剖面。利用上海气象站的探空数据和上海IGS站的GPS数据,对基于单站地基GPS天顶延迟的大气折射率剖面反演方法进行了验证。结果表明,根据目前处理得到的天顶延迟,反演剖面与实际剖面吻合较好。     

地基GPS反演水汽影响因素分析

地基GPS(Global Position System)技术日益成熟,气象观测应用此技术逐渐增多,但对此影响因素的分析不是太多。本文首先阐述了地基GPS遥感水汽原理,然后结合雾灵山GPS气象观测试验数据,利用GAMIT软件解算此期间数据的对流层延迟量,主要分析了影响地基GPS遥感水汽的几项因素,得出测站精度与ZTD精度变化趋势图、星历精度与ZTD(Troposphere Zenith Delay)精度变化趋势图和不同参考站对ZTD的影响。其结果对GPS遥感大气水汽有一定的参考价值。     

基于GNSS基准站网的对流层延迟建模

针对在卫星导航定位中,通常采用对流层模型进行,对流层延迟误差修正的现状,该文研究了一种基于GNSS基准站网的对流层延迟建模方法,并基于此方法利用日本地区GENET参考网约737个站5a的GNSS-ZTD序列建立了区域对流层模型ZTDM-JPN,并将ZTDM-JPN模型应用于GPS及北斗定位实验,分析了其在GPS及北斗定位中的实际应用性能。通过与国际上常用的对流层模型EGNOS、UNB3m作比较,结果表明,ZTDM-JPN模型的模拟精度较相同条件下的EGNOS与UNB3m模型分别提升约26%和21%,从而验证了该建模方法的可行性与优越性。     

Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS

The revitalized Russian GLONASS system provides new potential for real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV) in order to support time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a method of real-time ZTD/PWV retrieval based on GLONASS and/or GPS observations. The performance of ZTD and PWV derived from GLONASS data using real-time precise point positioning (PPP) technique is carefully investigated and evaluated. The potential of combining GLONASS and GPS data for ZTD/PWV retrieving is assessed as well. The GLONASS and GPS observations of about half a year for 80 globally distributed stations from the IGS (International GNSS Service) network are processed. The results show that the real-time GLONASS ZTD series agree quite well with the GPS ZTD series in general: the RMS of ZTD differences is about 8 mm (about 1.2 mm in PWV). Furthermore, for an inter-technique validation, the real-time ZTD estimated from GLONASS-only, GPS-only, and the GPS/GLONASS combined solutions are compared with those derived from very long baseline interferometry (VLBI) at colocated GNSS/VLBI stations. The comparison shows that GLONASS can contribute to real-time meteorological applications, with almost the same accuracy as GPS. More accurate and reliable water vapor values, about 1.5–2.3 mm in PWV, can be achieved when GLONASS observations are combined with the GPS ones in the real-time PPP data processing. The comparison with radiosonde data further confirms the performance of GLONASS-derived real-time PWV and the benefit of adding GLONASS to stand-alone GPS processing.     

京津冀地区GNSS对流层延迟空间插值研究

对流层延迟差异影响合成孔径雷达干涉测量技术(InSAR)形变测量精度;水汽的变化影响天气变化．对流层延迟与水汽具有较好的对应,因此有必要开展全球导航卫星系统(GNSS)对流层延迟的插值研究．以京津冀地区为例,针对GNSS对流层延迟,开展对流层延迟的空间插值研究．首先开展了GNSS对流层延迟与水汽的比较分析,两者存在显著正相关特性,相关性超过91.7％,论证了对流层延迟取代水汽的可行性．然后利用反距离权重法对京津冀地区2016年9月至2017年8月的12组GNSS测站对流层延迟进行空间插值,通过提取插值点对流层延迟与GNSS站点对流层延迟比较验证空间插值精度．全年数据平均偏差最大为1.12 cm,均方根误差最大为0.89 cm;未发生降水过程平均偏差最大为1.25 cm,均方根误差最大为0.82 cm;发生降水过程平均偏差最大为1.08 cm,均方根误差最大为1.38 cm．京津冀平原区域的GNSS对流层延迟空间插值结果精度满足气象等应用要求,可为气象预报和InSAR大气校正提供参考.      

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.     

Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns

Continuous, very long baseline interferometry (VLBI) campaigns over 2 weeks have been carried out repeatedly, i.e., CONT02 in October 2002, CONT05 in September 2005, CONT08 in August 2008, and CONT11 in September 2011, to demonstrate the highest accuracy the current VLBI was capable at that time. In this study, we have compared zenith total delays (ZTD) and troposphere gradients as consistently estimated from the observations of VLBI, Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) at VLBI sites participating in the CONT campaigns. We analyzed the CONT campaigns using the state-of-the-art software following common processing strategies as closely as possible. In parallel, ZTD and gradients were derived from numerical weather models, i.e., from the global European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields, the High Resolution Limited Area Model (European sites), the Japan Meteorological Agency-Operational Meso-Analysis Field (MANAL, over Japan), and the Cloud Resolving Storm Simulator (Tsukuba, Japan). Finally, zenith wet delays were estimated from the observations of water vapor radiometers (WVR) at sites where the WVR observables are available during the CONT sessions. The best ZTD agreement, interpreted as the smallest standard deviation, was found between GNSS and VLBI techniques to be about 5–6 mm at most of the co-located sites and CONT campaigns. We did not detect any significant improvement in the ZTD agreement between various techniques over time, except for DORIS and MANAL. On the other hand, the agreement and thus the accuracy of the troposphere parameters mainly depend on the amount of humidity in the atmosphere.     

Using external tropospheric corrections to improve GNSS positioning of hot-air balloon

High accurate global navigation satellite systems (GNSS) require to correct a signal delay caused by the troposphere. The delay can be estimated along with other unknowns or introduced from external models. We assess the impact of the recently developed augmentation tropospheric model on real-time kinematic precise point positioning (PPP). The model is based on numerical weather forecast and thus reflects the actual state of weather conditions. Using the G-Nut/Geb software, we processed GNSS and meteorological data collected during the experiment using a hot-air balloon flying up to an altitude of 2000 m. We studied the impacts of random walk noise setting of zenith total delay (ZTD) on estimated parameters and the mutual correlations, the use of external tropospheric corrections, the use of data from a single or dual GNSS constellation and the use of Kalman filter and backward smoothing processing methods. We observed a significant negative correlation of the estimated rover height and ZTD which depends on constraining ZTD estimates. Such correlation caused a degraded performance of both parameters when estimated simultaneously, in particular for a single GNSS constellation. The impact of ZTD constraining reached up to 50-cm differences in the rover height. Introducing external tropospheric corrections improved the PPP solution regarding: (1) shortened convergence, (2) better overall robustness, particularly, in case of degraded satellite geometry, (3) less adjusted parameters with lower correlations. The numerical weather model-driven PPP resulted in 9–12- and 5–6-cm uncertainties in the rover altitude using the Kalman filter and the backward smoothing, respectively. Compared to standard PPP, it indicates better performance by a factor of 1–2 depending on the availability of GNSS constellations, the troposphere constraining and the processing strategy.     

耦合PSO与扩展RBF神经网络估计NWM模型ZTD计算精度EI北大核心CSCD

针对基于数值气象模型获取的对流层天顶延迟精度估计依赖外部基准的问题,本文构建耦合了粒子群算法与扩展径向基函数神经网络的ZTD精度估计模型,模型样本特征集利用NWM自身气象数据和地形特征数据构建,目标集以GNSS ZTD产品为参考值构建,模型规模结构通过层次聚类和模糊C均值聚类确定,模型参数通过粒子群算法优化。以欧洲中期天气预报中心提供的ERA5气压分层产品为NWM特例进行了模型训练和结果验证。结果表明,模型估计精度和泛化能力较好,平均估计精度优于4 mm,可在任意位置实现不依赖于外部参考基准的ZTD精度估计。     

Comparison of individual and combined zenith tropospheric delay estimations during CONT08 campaign

CONT campaigns are 2-week campaigns of continuous VLBI observations. The IERS working group on combination at the observation level uses these campaigns to study such combinations. In this work, combinations of DORIS, GPS, SLR, and VLBI technique measurements are studied during CONT08. We present different results concerning the use of common zenith tropospheric delay (ZTD) during the combination. We compare the ZTD obtained separately using each individual technique data processing, the combined ZTD, and the ZTD derived from a meteorological model. This resulted in a high level of consistency between each of these ZTD at a sub-centimeter level, a consistency which especially depends on the number of observations per estimated ZTD and the humidity level in the troposphere. We noted that GPS provides the main information about the combined ZTD, the other techniques providing complementary information when a lack of GPS observations occurs.     

A grid-based tropospheric product for China using a GNSS network

Tropospheric delay accounts for one source of error in global navigation satellite systems (GNSS). To better characterize the tropospheric delays in the temporal and spatial domain and facilitate the safety-critical use of GNSS across China, a method is proposed to generate a grid-based tropospheric product (GTP) using the GNSS network with an empirical tropospheric model, known as IGGtrop. The prototype system generates the GTPs in post-processing and real-time modes and is based on the undifferenced and uncombined precise point positioning (UU-PPP) technique. GTPs are constructed for a grid form (\(2.0{^{\circ }}\times 2.5{^{\circ }}\) latitude–longitude) over China with a time resolution of 5 min. The real-time GTP messages are encoded in a self-defined RTCM3 format and broadcast to users using NTRIP (networked transport of RTCM via internet protocol), which enables efficient and safe transmission to real-time users. Our approach for GTP generation consists of three sequential steps. In the first step, GNSS-derived zenith tropospheric delays (ZTDs) for a network of GNSS stations are estimated using UU-PPP. In the second step, vertical adjustments for the GNSS-derived ZTDs are applied to address the height differences between the GNSS stations and grid points. The ZTD height corrections are provided by the IGGtrop model. Finally, an inverse distance weighting method is used to interpolate the GNSS-derived ZTDs from the surrounding GNSS stations to the location of the grid point. A total of 210 global positioning system (GPS) stations from the crustal movement observation network of China are used to generate the GTPs in both post-processing and real-time modes. The accuracies of the GTPs are assessed against with ERA-Interim-derived ZTDs and the GPS-derived ZTDs at 12 test GPS stations, respectively. The results show that the post-processing and real-time GTPs can provide the ZTDs with accuracies of 1.4 and 1.8 cm, respectively. We also apply the GTPs in real-time kinematic GPS PPP, and the results show that the convergence time of the PPP solutions is shortened. These results confirm that the GTPs can act as an efficient information source to augment GNSS positioning over China.     

一种基于SARIMA的经验对流层延迟模型

为了减弱对流层延迟的影响,提高GNSS定位精度,探讨了在无气象参数的条件下,利用预测模型计算对流层延迟的可能性,并提出了一种经验对流层延迟预测模型,即基于季节性自回归移动平均模型（SARIMA）的对流层延迟预报方法。结合中国长春和上海两个地区的ZTD数据进行预测分析,预测结果表明：基于SARIMA的ZTD预报模型能够满足不同地区不同时段下的ZTD估计需求,是一种较高精度的ZTD预报方法。     

一种优化的基于神经网络的经验ZTD模型

目前,经验对流层天顶延迟（ZTD）模型已经有了飞速的发展,因为它们在使用时无需任何测量的实时地面气象数据,这给GNSS用户提供了极大方便。神经网络技术在实测参数型的ZTD建模中已经取得了一定的成果。与此同时,国内虽然有学者构建了神经外网络的经验ZTD模型,其最大的缺点是忽略了ZTD时间变化且只能单独预报ZTD。本文针对这些缺点构建了优化的神经网络经验ZTD模型。试验结果表明,本文提出的神经网络模型可以分别预报天顶干延迟ZHD和天顶湿延迟ZWD,且具有良好的精度：ZHD的Bias和RMSE分别为-3.7和19.8 mm;ZWD的Bias和RMSE分别为-0.6和34.2 mm。本文的神经网络模型预报的ZHD和ZWD的精度均与目前世界著名的GPT2w格网模型相当。另外,与GPT2w模型相比较,神经网络模型最大的优点就是无需庞大的预存格网数据作为输入,在使用时仅需要知道一个训练好的神经网络即可,该特点为GNSS用户提供了极大的方便。     

利用中国区域MERRA-2资料计算ZTD和ZWD的精度分析

对流层延迟是影响高精度定位与导航的主要误差之一,也是全球导航卫星系统（global navigation satellite system,GNSS）水汽探测的关键参数。美国航空航天局发布了最新一代的大气再分析资料（MERRA-2资料）,其可用于计算高时空分辨率的对流层延迟产品,但是目前尚无文献对利用MERRA-2资料计算天顶对流层延迟（zenith tropospheric delay,ZTD）和天顶湿延迟（zenith wet delay,ZWD）的精度进行分析。因此,联合2015年中国陆态网214个GNSS站ZTD产品和分布于中国区域的87个探空站资料,对利用MERRA-2资料在中国区域计算ZTD/ZWD的精度进行评估。结果表明：（1）以陆态网ZTD为参考值,利用MERRA-2资料积分计算ZTD的年均偏差和均方根误差（root mean square error,RMSE）分别为0.32 cm和1.21 cm,且偏差和RMSE均表现出一定的季节变化,总体上呈现为夏季精度低、冬季精度高;在空间分布上,偏差随纬度和高程的变化趋势并不明显,但RMSE随纬度和高程的增加总体上呈现递减的趋...     

GGOS对流层延迟产品精度分析及在PPP中的应用

对流层延迟是卫星导航定位的主要误差源,GNSS广域增强需要高精度的对流层延迟产品进行误差修正。对流层延迟可通过GNSS进行实时估计,也可通过融合多源数据的数值气象预报模型获取。IGS发布的全球对流层天顶延迟产品由GNSS解算,其精度可达4mm,时间分辨率为5min,但其分布不均匀,在广袤的海洋区域无数据覆盖。GGOS Atmosphere基于ECMWF 40年再分析资料,可提供1979年以来时间分辨率为6h、空间分辨率为2.5°×2°的全球天顶对流层总延迟格网数据。本文通过2015年全球IGS测站的ZTD资料对GGOS的ZTD产品进行了评估,研究了GGOS Atmosphere对流层延迟产品与IGS发布ZTD资料之间的系统差,通过线性拟合估计出每个测站GGOS-ZTD与IGSZTD系统差系数(包括比例误差a和固定误差b),然后对比例误差a、固定误差b进行球谐展开,建立了两种ZTD数据源之间的系统差模型。选取IGS测站和陆态网测站,对附加系统偏差改正后的GGOSZTD产品对PPP的收敛速度的影响进行研究。本文研究结果表明:GGOS-ZTD与IGS-ZTD间存在系统偏差,其bias平均为-0.54cm;两者之间较差的RMS平均为1.31cm,说明GGOS-ZTD产品足以满足广大GNSS导航定位用户对对流层延迟改正的需要。将改正了系统差后的GGOS-ZTD产品用于ALBH、DEAR、ISPA测站、PALM测站、ADIS测站、YNMH测站、WUHN测站进行PPP试验,发现可明显提高定位收敛速度,尤其是在U方向上,收敛速度分别提高10.58%、31.68%、15.96%、43.89%、51.46%、14.69%、18.40%。     

一种优化的对流层天顶延迟融合模型FZTD

对流层延迟是影响全球卫星导航系统(GNSS)定位精度的主要误差源之一,模型修正法是目前削弱对流层延迟影响的主要方法. 以简单易用的角度为切入点,综合UNB3模型的简易性和GPT2w模型的高精度特点,构建一种简易且精度较高的对流层天顶延迟融合模型(FZTD). 并利用多年的国际GNSS服务(IGS) 对流层天顶延迟(ZTD)数据对该模型精度进行了验证. 结果表明FZTD模型的均方根(RMS)与平均偏差(bias)值分别为4.4 cm和?0.3 cm,均小于传统模型UNB3m(RMS:5.1 cm,bias:1.1 cm)和EGNOS(RMS:5.1 cm,bias:0.3 cm),定位精度提高了14%,而且在南半球提高尤为明显,特别在南极地区,精度提高了近3倍,弥补了传统模型在南北半球精度差异大的不足. 新模型总气象参数仅为120个比GPT2w模型急剧减少,与传统模型相当,为GNSS实时导航定位终端的预定义对流层延迟改正提供了更优的选择.      

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

Impact of tropospheric modelling on GNSS vertical precision: an empirical analysis based on a local active network

The troposphere affects Global Navigation Satellite System (GNSS) signals due to the variability of the refractive index. Tropospheric delay is a function of the satellite elevation angle and the altitude of the GNSS receiver and depends on the atmospheric parameters. If the residual tropospheric delay is not modelled carefully a bias error will occur in the vertical component. In order to analyse the precise altimetric positioning based on a local active network, four scenarios in Southern Spain with different topographical, environmental, and meteorological conditions are presented, considering both favourable and non-favourable conditions. The use of surface meteorological observations allows us to take into account the tropospheric conditions instead of a standard atmosphere, but introduces a residual tropospheric bias which reduces the accuracy of precise GNSS positioning. Thus, with short observation times it is recommended not to estimate troposphere parameters, but to use an a priori model together with the standard atmosphere. The results confirm that it is possible to achieve centimetre-scale vertical accuracy and precision with real time kinematic positioning even with large elevation differences with respect to the nearest reference stations. These numerical results may be taken into consideration for improving the altimetric configuration of the local active network.