A predictive model for regional zenith tropospheric delay correction

The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.

A zenith tropospheric delay correction model based on the regional CORS network

Tropospheric delay is a primary error source in earth observations and a variety of radio navigation technologies. In this paper, the relationship between zenith tropospheric delays and the elevation and longitude of stations is analyzed using the zenith tropospheric delay final products of International GNSS Service （IGS） stations from 2011. Two new models are proposed for estimating zenith tropospheric delays from regional CORS data without meteorological data. The proposed models are compared with the direct interpolation method and the remove-restore method using data from Guangxi CORS. The results show that the new models significantly improve the calculated precision. Finally, the root mean square （RMS） errors of the new models were used to estimate the surface precipitable water vapor （PWV） value at CORS station, which was determined to be less than 2 mm.

Monitoring Zenithal Total Delays over the three different climatic zones from IGS GPS final products:A comparison between the use of the VMF1 and GMF mapping functions

The International GNSS Service(IGS) final products(ephemeris and clocks-correction) have made the GNSS an indispensable low-cost tool for scientific research, for example sub-daily atmospheric water vapor monitoring. In this study, we investigate if there is a systematic difference coming from the choice between the Vienna Mapping Function 1(VMF1) and the Global Mapping Function(GMF) for the modeling of Zenith Total Delay(ZTD) estimates, as well as the Integrated Precipitable Water Vapor(IPWV) estimates that are deduced from them. As ZTD estimates cannot be fully separated from coordinate estimates, we also investigated the coordinate repeatability between subsequent measurements.For this purpose, we monitored twelve GNSS stations on a global scale, for each of the three climatic zones(polar, mid-latitudes and tropical), with four stations on each zone. We used an automated processing based on the Bernese GNSS Software Version 5.2 by applying the Precise Point Positioning(PPP)approach, L3 Ionosphere-free linear combination, 7 cutoff elevation angle and 2 h sampling. We noticed an excellent agreement with the ZTD estimates and coordinate repeatability for all the stations w.r.t to CODE(the Center for Orbit Determination in Europe) and USNO(US Naval Observatory) products, except for the Antarctic station(Davis) which shows systematic biases for the GMF related results. As a final step, we investigated the effect of using two mapping functions(VMF1 and GMF) to estimate the IPWV,w.r.t the IPWV estimates provided by the Integrated Global Radiosonde Archive(IGRA). The GPS-derived IPWV estimates are very close to the radiosonde-derived IPWV estimates, except for one station in the tropics(Tahiti).

Assessment of GNSS zenith tropospheric delay responses to atmospheric variables derived from ERA5 data over Nigeria

Tropospheric delay is a major error caused by atmospheric refraction in Global Navigation Satellite System(GNSS)positioning.The study evaluates the potential of the European Centre for Medium-range Weather Forecast(ECMWF)Reanalysis 5(ERA5)atmospheric variables in estimating the Zenith Tropospheric Delay(ZTD).Linear regression models(LRM)are applied to estimate ZTD with the ERA5 atmospheric variables.The ZTD are also estimated using standard ZTD models based on ERA5 and Global Pressure and Temperature 3(GPT3)atmospheric variables.These ZTD estimates are evaluated using the data collected from the permanent GNSS continuously operating reference stations in the Nigerian region.The results reveal that the Zenith Hydrostatic Delay(ZHD)from the LRM and the Saastamoinien model using ERA5 surface pressure are of identical accuracy,having a Root Mean Square(RMS)error of 2.3 mm while the GPT3-ZHD has an RMS of 3.4 mm.For the Zenith Wet Delay(ZWD)component,the best estimates are derived using ERA5 Precipitable Water Vapour(PWV).These include the ZWD derived by the LRM having an average RMS of 20.9 mm and Bevis equation having RMS of 21.1 mm and 21.0 mm for global and local weighted mean temperatures,respectively.The evaluation of GPT3-ZWD estimates gives RMS of 45.8 mm.This study has provided a valuable insight into the application of ERA5 data for ZTD estimation.In line with the fndings of the study,the ERA5 atmospheric variables are recommended for improving the accuracy in ZTD estimation,required for GNSS positioning.

Development and evaluation of the refined zenith tropospheric delay(ZTD)models

The tropospheric delay is a significant error source in Global Navigation Satellite System(GNSS)positioning and navigation.It is usually projected into zenith direction by using a mapping function.It is particularly important to establish a model that can provide stable and accurate Zenith Tropospheric Delay(ZTD).Because of the regional accuracy difference and poor stability of the traditional ZTD models,this paper proposed two methods to refine the Hopfield and Saastamoinen ZTD models.One is by adding annual and semi-annual periodic terms and the other is based on Back-Propagation Artificial Neutral Network(BP-ANN).Using 5-year data from 2011 to 2015 collected at 67 GNSS reference stations in China and its surrounding regions,the four refined models were constructed.The tropospheric products at these GNSS stations were derived from the site-wise Vienna Mapping Function 1(VMP1).The spatial analysis,temporal analysis,and residual distribution analysis for all the six models were conducted using the data from 2016 to 2017.The results show that the refined models can effectively improve the accuracy compared with the traditional models.For the Hopfield model,the improvement for the Root Mean Square Error(RMSE)and bias reached 24.5/49.7 and 34.0/52.8 mm,respectively.These values became 8.8/26.7 and 14.7/28.8 mm when the Saastamoinen model was refined using the two methods.This exploration is conducive to GNSS navigation and positioning and GNSS meteorology by providing more accurate tropospheric prior information.

利用动态PPP技术监测ZTD高频变化

基于动态PPP技术,用IGS参考站的静态数据进行动态PPP模拟计算,对静态得到的PPP-ZTD、动态计算得到的PPP-ZTD与IGS公布的ZTD参考值的比较发现,使用动态PPP技术和较高采样间隔的卫星钟差(30 s)也可以获得精度较高的对流层延迟(<6 mm)。

基于GPT3模型的ZTD及PWV反演精度分析

使用亚洲区域18个IGS测站和中国区域内16个探空站2016~2018年的数据,研究GPT3模型反演天顶对流层延迟(ZTD)和大气可降水量(PWV)的精度,并与其他GPT系列模型进行对比。结果表明,GPT3-1模型估计的ZTD的bias均值和最大值均最小,分别为1.34 mm和14.06 mm;GPT3模型整体精度略优于GPT2w模型,优于GPT2模型。探空站处GPT3模型反演的PWV的bias和RMSE均表现出较强的季节性特征;由GPT3模型反演的PWV的月均值可知,GPT3-1模型比GPT3-5模型具有更高的精度和稳定性。

一种新的多因子约束下的NWP反演ZTD残差改正模型

对流层延迟是GNSS定位的主要误差源之一,利用NWP模型的气象数据积分反演ZTD是当前研究热点.然而,采用两大气象预报中心(ECMWF和NCEP)的再分析资料反演ZTD的残差一般在±60mm之间浮动,预报资料反演的ZTD的精度更差,都不能直接用于精密定位.一般是先将此反演的ZTD作为初值,设定先验方差,将残差作为未知参数求解.NWP反演的ZTD的精度,将直接影响对流层和模糊度参数在滤波过程中收敛速度.前人的研究表明.NWP反演ZTD的残差大小与测站所在纬度相关.利用纬度与残差的相关函数可提高NWP反演ZTD的精度.但效果并不明显.针对以上问题,比较ECMWF和NCEP再分析资料反演ZTD的精度,然后分析精度较高的ECMWF资料反演的ZTD的残差随温度、湿度、纬度、季节等因子变化的规律,并结合基于最小绝对残差法的多项式拟合方法拟合残差,提出一种新的多因子约束下的NWP反演ZTD的残差改正模型,从而提高NWP反演ZTD的精度.为验证模型的性能.以133个IGS站高精度ZTD为参考.拟合2015年ECMWF反演ZTD的残差.构建残差改正模型.并利用此模型改正2016年ECMWF反演的ZTD.实验结果表明:在纬度高于15°的地区.NWP反演的ZTD的平均残差和均方根误差比使用模型前分别减小了86.9%和36.3%.另外,对于较低纬度地区.此残差改正模型的效果不明显.

A new global zenith tropospheric delay model IGGtrop for GNSS applications

Tropospheric delay is one of the main sources of measurement error in global navigation satellite systems.It is usually compensated by using an empirical correction model.In this paper,temporal and spatial variations of the global zenith tropospheric delay(ZTD) are further analyzed by ZTD time series from global International GNSS Service stations and annual ZTDs derived from global National Centers for Environmental Prediction reanalysis data,respectively.A new ZTD correction model,named IGGtrop,is developed based on the characteristics of ZTD.Experimental results show that this new 3D-grid-based model that accommodates longitudinal as well as latitudinal variations of ZTD performs better than latitude-only based models(such as UNB3,EGNOS,and UNB3m).The global average bias and RMS for IGGtrop are about-0.8 cm and 4.0 cm,respectively.Bias values for UNB3,EGNOS,and UNB3m are 2.0,2.0,and 0.7 cm,respectively,and respective RMS values 5.4,5.4,and 5.0 cm.IGGtrop shows much more consistent prediction errors for different areas than EGNOS and UNB3m,In China,the performance of IGGtrop(bias values from-2.0 to 0.4 cm and RMS from 2.1 to 6.4 cm) is clearly superior to those of EGNOS and UNB3m.It is also demonstrated that IGGtrop biases vary little with height,and its RMS values tend to decrease with increasing height.In addition,IGGtrop generally estimates ZTD with greater accuracy than EGNOS and UNB3m in the Southern Hemisphere.

融合GNSS ZTD和气象要素的内蒙古土壤水含量模型

土壤水含量是农牧业衡量干旱的重要指标,对气候生态具有重要影响,土壤水的变化趋势对于区域的水土流失和气候变化研究等工作具有重要意义,而我国对于土壤水含量的监测起步较晚,因此有必要利用其他已有数据开展土壤水含量模型研究.利用内蒙古已有全球导航卫星系统(GNSS)天顶对流层延迟(ZTD)数据和湿度、日照以及蒸发量数据进行土壤水含量反演模型研究.首先将各要素与土壤水含量进行相关性分析,因土壤水含量与GNSS ZTD数据均存在观测噪声,所以应对数据进行去噪处理.利用小波变换方法剔除噪声,去噪后土壤水含量数据与各要素相关性均有所提高,土壤水含量与湿度相关性最好,两者各实验点的平均相关性为0.645;土壤水含量与日照和蒸发量呈负相关,其平均相关性分别为−0.561、−0.547;而土壤水含量与GNSS ZTD数据相关性最小,其平均相关性为0.271.根据各要素与土壤水含量的相关性,进行土壤水含量模型构建并进行可靠性验证.经验证误差统计发现:实验区域NMWJ站模型精度最高,其精度为90.1%;HLAR站点模型精度最低,其精度为69.1%;各站点的平均精度为81.35%.基于多变量要素的土壤水含量模型可为土壤水含量的趋势变化研究提供参考,通过研究土壤水含量的变化趋势,对区域进行水资源的合理分配利用从而达到节约水资源目的.

京津冀地区GNSS ZTD时序分析及对厄尔尼诺事件的响应

京津冀地区夏季暴雨频发,水汽是影响暴雨形成的关键要素之一.本文利用中国大陆构造环境监测网络(CMONOC)京津冀地区GNSS(全球导航卫星系统)观测资料,开展GNSS天顶对流层总延迟(ZTD)时序分析及对厄尔尼诺事件的响应研究.利用快速傅里叶变换与小波变换方法从频域和时域开展GNSS ZTD时序分析,并对GNSS ZTD不同周期时序与东部型指数(I_(EP))、中部型指数(I_(CP))进行比较,分析I_(EP)、I_(CP)对GNSS ZTD周期变化的影响.研究发现:GNSS ZTD异常时段与厄尔尼诺事件存在对应关系.东部型指数(I_(EP))与GNSS ZTD呈正相关;中部型指数(I_(CP))与GNSS ZTD呈显著负相关.在东部型厄尔尼诺事件的影响下,GNSS ZTD的季节性周期增大,月周期和半月周期减小;在中部型厄尔尼诺事件的影响下,GNSS ZTD的季节性周期、月周期、半月周期都减小.研究结果可为掌握区域GNSS ZTD预测变化规律提供参考,并为利用水汽感知厄尔尼诺事件提供可行性基础.

Refining the ERA5-based global model for vertical adjustment of zenith tropospheric delay

Tropospheric delay is an important factor affecting high precision Global Navigation Satellite System(GNSS)positioning and also the basic data for GNSS atmospheric research.However,the existing tropospheric delay models have some problems,such as only a single function used for the entire atmosphere.In this paper,an ERA5-based(the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis)global model for vertical adjustment of Zenith Tropospheric Delay(ZTD)using a piecewise function is developed.The ZTD data at 611 radiosonde stations and the MERRA-2(second Modern-Era Retrospective analysis for Research and Applications)atmospheric reanalysis data were used to validate the model reliability.The Global Zenith Tropospheric Delay Piecewise(GZTD-P)model has excellent performance compared with the Global Pressure and Temperature(GPT3)model.Validated at radiosonde stations,the performance of the GZTD-P model was improved by 0.96 cm(23%)relative to the GPT3 model.Validated with MERRA-2 data,the quality of the GZTD-P model is improved by 1.8 cm(50%)compared to the GPT3 model,showing better accuracy and stability.The ZTD vertical adjustment model with different resolutions was established to enrich the model's applicability and speed up the process of tropospheric delay calculation.By providing model parameters with different resolutions,users can choose the appropriate model according to their applications.

基于实时精密单点定位技术的暴雨短临预报

提出了一种将实时精密单点定位(Precise Point Positioning,PPP)技术用于暴雨短临预报的新方法.该方法首先基于GPS连续运行参考站网(Continuously Operating Reference Stations,CORS)实时估计的精密卫星钟差完成PPP解算,再以实时获取的对流层延迟(Zenith Tropospheric Delay,ZTD)及其增量变化为依据进行暴雨短临预报.研究结果表明:一般雷暴天气来临之前的2～6h,ZTD增量表现为先后突破±5mm/5min,且后续记录到的实际降水量大小与ZTD维持在高水平阶段的时间长短有较好的对应关系;就热带气旋而言,在强风作用下,ZTD增量变化表现的异常活跃和复杂,规律性较弱,但对短临预报强降雨仍有一定的指示作用.

亚洲地区EGNOS天顶对流层延迟模型的精度评估

基于亚洲地区48个IGS站2009—2011年实测的天顶对流层延迟(ZTD)数据,对利用EGNOS模型计算的ZTD的精度进行评估,结果表明:1)在亚洲地区,相对于IGS站实测的ZTD,EGNOS模型计算的ZTD的偏差和均方根分别为-0.18 cm和5.98 cm,在中国地区分别为0.81 cm和6.13 cm;2)偏差和均方根差呈现明显的季节变化,偏差表现为夏季最大,秋季最小,而均方根夏季最大,冬季最小;3)在空间分布上,偏差与纬度和高程变化无明显规律,但均方根随着高程或者纬度的增加总体上呈递减趋势,西部和北部高纬度地区,年均偏差和均方根变化相对较小;4:)亚洲南部低纬度地区和东部地区夏季日平均偏差和均方根差变化相对较大。

基于区域CORS网精密天顶对流层延迟建模方法研究

利用区域CORS网参考站已知天顶对流层信息,提出一种不需要气象数据的天顶对流层新模型。利用广西CORS网实测数据,分析了新模型与反距离加权法和移去恢复法的精度,结果表明新模型精度有显著提高。

精密单点定位中4种函数模型解算性能分析

文章针对PPP中4种不同的函数模型，分析了相应模型的特性，并采用IGS连续运行参考站179个测站数据对这4种模型进行解算，从定位精度、收敛速度、ZTD估计精度、解算时间等方面进行统计分析。实验结果表明，UofC、无电离层组合模型、非组合模型及无模糊度模型在30 min内达到厘米级的站点比例分别为75％、48.9％、51.7％、20.7％，平均收敛时间分别为22.6、36.1、40.9、126.3 min。在参数估计精度方面，无模糊度模型精度较低，其他3种模型单天解在N、E方向误差均值在1～9 mm左右，在U方向误差均值约为2 cm ，ZTD误差均值为10 mm左右，整体上参数估计精度具有一致性。

一种用于中国地区的对流层天顶延迟实时修正模型

针对目前对流层延迟修正受限于探空数据不足导致修正效率低的问题,该文结合Saastamoinen和GPT2w模型构建形成组合模型Sa+GPT2w模型,通过利用GPT2w模型提供的高精度气象数据,实现中国地区对流层天顶延迟(ZTD)的实时修正,克服对探空数据的依赖,并用实测数据对计算结果进行验证。以IGS提供的中国地区2015至2017年ZTD时间序列为评估标准时,Sa+GPT2w模型(bias:1.661 cm, RMS:4.711 cm)的精度较同等条件下的Sa+EGNOS, Sa+UNB3m和Hop+GPT2w模型分别提升50.5%, 41.9%和37.1%;以GGOS Atmo-sphere 2017年ZTD数据为标准时,Sa+GPT2w模型(bias:1.551 cm, RMS:4.859 cm)的精度相对同等条件下的另3种模型分别提升49.5%, 38.5%和46.8%;最后对Sa+EGNOS, Sa+UNB3m和Sa+GPT2w模型在ZTD修正中误差结果的时空分布特征进行分析。研究结果可为在中国地区的导航定位、大气折射研究中,应用不同气象参数模型进行ZTD修正的有效性和可能达到的精度提供参考。

区域天顶对流层延迟时空变化特性及其建模研究

介绍几种常用的全球对流层延迟改正模型和几种区域对流层延迟模型的建立方法,再利用美国密歇根州的8个测站天顶对流层延迟数据对天顶对流层延迟进行研究,得出天顶对流层延迟在时间尺度及空间尺度上的变化规律,与经度和纬度相关性一般,与高程强相关。通过美国密歇根州的4个测站数据分别计算3种区域对流层延迟模型,得出各个模型的精度,并比较它们的优劣,结论是一次线性插值模型是三者中精度最高的模型。

雾霾天气对GPS天顶对流层延迟与可降水量影响研究

以北京市GPS连续观测网数据,研究雾霾天气对GPS天顶对流层延迟和可降水量的影响。研究表明,雾霾发生日,天顶对流层延迟和可降水量上升;雾霾持续过程中,天顶对流层延迟和可降水量在序列的峰值徘徊;雾霾结束日,天顶对流层延迟和可降水量下降。

基于不同地形的GPS对流层延迟插值方法研究

通过利用北京、武汉两地的GPS数据,采用反距离加权法、克里金法研究不同地形下GPS对流层延迟插值效果。经比较,反距离加权法与克里金法的插值效果基本一致,在对武汉地区进行GPS对流层延迟插值时插值效果均在毫米级,在北京地区的插值效果则有不同:平坦地区插值效果达到毫米级;山区插值效果为厘米级,无法满足应用需求。