南极长城站与IGS站组网解算的最佳站数探讨

GPS气象学在南极的应用中,南极长城站上空对流层天顶总延迟的解算精度直接影响该站上空的大气水汽含量的估算精度。本文运用麻省理工学院研制的高精度解算软件GAM IT/GLOBK,对引入不同数目的IGS跟踪站与南极长城站的GPS数据分别进行了组网解算,得出了该站上空的天顶总延迟,并解算了该站上空的可降水分,将其与实际降水进行了对比分析,得出了与南极长城站组网解算的最佳IGS跟踪站站数为3个。     

GPS站水汽压与可降水分关系的探讨

利用GPS技术遥感大气可降水分的精度已经达到1-2mm,可以作为检验其他手段获取的可降水分的精度。文中对于南极稀少的GPS站点估计的可降水分,探讨了水汽压与可降水分的关系,得出两者满足的二次曲线拟合模型,使之适合无GPS站点的局部地区,并通过南极应用实例验证了该模型的正确性。     

北斗区域系统解算对流层天顶延迟比对分析

在分析了当前GNSS主要的误差源,比较对流层延迟改正模型的基础上,应用Saastamoinen模型对BDS和GPS原始观测数据解算对流层天顶延迟,并对全球6个站点一个月的解算值进行比对分析,结果发现：北斗区域系统解算的ZTD相比于GPS结果,76%位于2cm之内,只有个别站点个别天的解算结果出现较大偏差,在中国周边站点解算结果优于其他地区站点。表明：北斗区域系统已经具备在中国周边同GPS相当的ZTD解算精度,为下一步北斗全球系统的建设奠定了坚实的基础。     

不同IGS星历产品对地基GPS反演水汽的影响北大核心CSCD

为了研究不同国际GNSS服务(IGS)星历产品对地基GPS反演可降水汽精度的影响,评估超快星历用于实时水汽反演的精度,该文借助Bernese5.2软件获取不同IGS星历产品解算的IGS跟踪站天顶总延迟,结合GPT2模型估算的气象参数反演得到大气可降水,最后与探空站资料计算的大气可降水进行对比分析。结果表明,利用超快速星历预报部分反演大气可降水结果的RMS在±8mm内波动,优于1cm,有助于实时探测大气可降水量的变化,进一步有效促进地基GPS在短临天气预报中的应用。     

提高对流层天顶总延迟解算精度的新方法探讨

对流层天顶总延迟的解算精度,直接影响长基线解算的精度和大气水汽含量的计算精度。文中提出克利金内插法解算天顶总延迟的新方法,并利用南极长城站和周边IGS跟踪站的GPS数据,通过高精度解算软件GAMIT/GLOBK,解算出长城站上空的对流层天顶总延迟,将其与利用内插方法解算的天顶总延迟进行了对比分析,得出:利用该内插方法获取的南极长城站在夏季的天顶总延迟的均方差可达0.2mm,这对今后GPS高精度定位和GPS气象学应用来说,具有重要意义。     

GPS测量中天顶干延迟的计算方法的研究

大气可降水份的估计是地基GPS气象学的一个主要研究方向。本文介绍了大气折射对GPS测量的影响,简介了两种常用的天顶干延迟分量模型——Saastamoinen模型和Hopfield模型和各种模型的特点。通过对北京、乌鲁木齐、拉萨3个IGS站的气象数据对这两个的天顶延迟干分量模型进行了分析总结。     

GPS水汽反演技术在四川地区的应用研究

根据四川网络GPS站点附近的气压、温度计算了天顶静力学延迟量,经过综合分析,得到了最适于四川地区的天顶静力学延迟模型。建立了适于四川地区的加权平均温度计算公式,并说明了此公式的有效性。使用了全球气压和温度模型（GPT）代替实测气象数据进行水汽反演,将GPT可降水量与实测气象可降水量、探空数据可降水量以及实际降水量进行比较分析,得出了一些有益结论。     

GPS数据解算对流层天顶总延迟探讨

运用GAMIT／GLOBK软件,对南极长城站与周边的各IGS跟踪站的GPS观测数据进行组网解算。在解算各站上空总天顶延迟的过程中,利用不同的星历进行解算,并对其解算结果进行了分析和探讨得出：实时预报。星历与精密星历在解算结果上差别不大,最小差值是0mm,最大差值仅为0．5mm。所以在计算各GPS站上空大气水汽含量时,可直接采用实时预报星历,对今后实时探测水汽及实时天气预报具有一定的实用意义。     

GPS水汽反演在成都地区的应用

本文利用成都及周边GPS连续观测站的观测数据及IGS精密星历数据,反演了成都地区2005年7、8、9三个月的大气可降水量,并与探空结果、实际降水量进行对比分析,证实了GPS水汽反演在成都地区的可行性.研究表明,GPS水汽反演结果与探空结果有良好的相关性,但目前还无法将其用于中、短期的降雨预报.     

局部地区对流层大气垂直干延迟的模型改正

干延迟的精确确定对GPS气象中解算可降水分含量有很重要的作用。根据武汉和探空站Kingspark的探空资料,计算了这两地的实际干延迟量。在这些资料的基础上,用回归分析的方法对这两地的干延迟算式进行了建模和分析,发现该算式的精度优于其他模型。     

GPS/PWV在台风"玛莉亚"袭闽期间的变化特征研究

可降水量（PWV）表征大气中的水汽含量,本文利用福建省卫星导航定位基准服务系统（FJCORS）的GPS观测资料反演得到可降水量（GPS/PWV）,通过与实测的高精度探空PWV资料进行对比发现,其相关系数达到0.98,与探空结果具有较好的一致性;平均偏差在1.10 mm以内,表明GPS/PWV资料具有较高的精度。在此基础上分析2018年第8号台风“玛莉亚”登陆福建前后的GPS/PWV变化特征及其与实际降水量的关系,结果表明,GPS/PWV资料能够很好地反映台风期间水汽的时空动态传输过程,并与降水之间具有良好的对应关系。     

基于超快速星历进行实时反演大气水汽总量的可行性研究

从GPS气象学实际应用的角度出发,能够实时获取高时空分辨率的大气水汽场是一个十分关键的问题。基于地基GPS遥感水汽的原理,利用香港地区CORS网的实际测量数据进行试验,根据IGS网站提供的不同精度的轨道信息设计了试验方案,并且比较了方案中最终精密星历、超快速星历以及气象探空站探测得到的大气可降水量序列。实验结果表明,利用超快速星历反演算出的大气水汽总量与最终精密星历一致,其精度可以满足气象预报等实时业务的需求。      

GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica

Three permanent GPS tracking stations in the trans Antarctic mountain deformation (TAMDEF) network were used to estimate precipitable water vapor (PWV) using measurement series covering the period of 2002–2005. TAMDEF is a National Science Foundation funded joint project between The Ohio State University and the United States Geological Survey. The TAMDEF sites with the longest GPS data spans considered in this research are Franklin Island East (FIE0), the International GNSS Service site McMurdo (MCM4), and Cape Roberts (ROB1). For the experiment, PWV was extracted from the ionosphere-free double-difference carrier phase observations, processed using the adjustment of GPS ephemerides (PAGES) software. The GPS data were processed with a 30 s sampling rate, 15-degree cutoff angle, and precise GPS orbits disseminated by IGS. The time-varying part of the zenith wet delay is estimated using the Marini mapping function, while the constant part is evaluated using the corresponding Marini tropospheric model. Previous studies using TAMDEF data for PWV estimation show that the Marini mapping function performs the best among the models offered by PAGES. The data reduction to compute the zenith wet delay follows the step piecewise linear strategy, which is subsequently transformed to PWV. The resulting GPS-based PWV is compared to the radiosonde observations and to values obtained from the Antarctic mesoscale prediction system (AMPS). This comparison revealed a consistent bias of 1.7 mm between the GPS solution and the radiosonde and AMPS reference values.     

成都地区地基GPS观测网遥感大气可降水量的初步试验

利用首个成都地区地基GPS观测网2004年7～9月30s间隔的测量数据，通过Bernese GPS SoftwareV4．2解算出30min间隔的天顶总延迟量，结合自动气象站获得的气象资料计算出30min间隔的GPS遥感的大气可降水量。与根据气象探空站探测资料算出的可降水量进行统计对比，确定出本次GPS遥感可降水量试验的精度为3．09mm，两种可降水量时间序列呈现高度的一致性。同时验证了计算对流层加权平均温度的Bevis经验公式在成都地区的适用性。     

GPT／2模型用于 GPS 大气可降水汽反演的精度分析

气象参数(温度T、气压P)是GPS大气可降水汽(PWV)反演中必不可少的数据,也是PWV反演的重要误差源之一。文中主要对GPT/2(GPT、GPT2)模型用于PWV反演的精度进行验证和分析。基于非差精密单点定位(PPP)技术,选取SuomiNet网9个测站的观测数据,借助研制的PPP软件,分别采用GPT模型、改进的GPT2模型以及测站实测气象数据进行大气可降水汽(PWV)反演。以实测气象数据处理结果为参考,对两种模型解算的PWV进行了对比和精度分析。结果表明:改进的GPT2模型优于GPT模型,尤其是当测站的高程较大时,GPT2模型的稳定性更优、适用性更广;采用GPT2模型解算的PWV偏差均值小于±1.0mm,精度(RMS)优于±1.5mm。在缺少实测气象数据的情况下,利用GPT2模型数据仍然能够取得较为理想的PWV反演结果。     

Experiment on driving precipitable water vapor from ground-based GPS network in Chengdu Plain

The estimates of total zenith delay are derived using Bernese GPS Software V4. 2 based on GPS data every 30 s from the first measurement experiment of a ground-based GPS network in Chengdu Plain of Southwest China during the period from July to September 2004. Then the estimates of 0.5 hourly precipitable water vapor (PWV) derived from global positioning system (GPS) are obtained using meteorological data from automatic weather stations (AWS). The comparison of PWV derived from GPS and those from radiosonde observations is given for the Chengdu station, with RMS (root mean square) differences of 3.09m. The consistency of precipitable water vapor derived from GPS to those from radiosonde is good. It is concluded that Bevis’ empirical formula for estimating the weighted atmospheric mean temperature can be applicable in Chengdu area because the relationship of GPS PWV with Bevis’ formula and GPS PWV with radiosonde method shows a high correlation. The result of this GPS measurement experiment is helpful both for accumulating the study of precipitable water vapor derived from GPS in Chengdu areas located at the eastern side of the Tibetan Plateau and for studying spatial-temporal variations of regional atmospheric water vapor through many disciplines cooperatively.     

Experiment on Driving Precipitable Water Vapor from Ground-Based GPS Network in Chengdu Plain

The estimates of total zenith delay are derived using Bernese GPS Software V4. 2 based on GPS data every 30 s from the first measurement experiment of a ground-based GPS network in Chengdu Plain of Southwest China during the period from July to September 2004. Then the estimates of 0.5 hourly precipitable water vapor (PWV) derived from global positioning system (GPS) are obtained using meteorological data from automatic weather stations (AWS). The comparison of PWV derived from GPS and those from radiosonde observations is given for the Chengdu station, with RMS (root mean square) differences of 3.09m. The consis- tency of precipitable water vapor derived from GPS to those from radiosonde is good. It is concluded that Bevis’ empirical formula for estimating the weighted atmospheric mean temperature can be applicable in Chengdu area because the relationship of GPS PWV with Bevis’ formula and GPS PWV with radiosonde method shows a high correlation. The result of this GPS measurement experiment is helpful both for accumu- lating the study of precipitable water vapor derived from GPS in Chengdu areas located at the eastern side of the Tibetan Plateau and for studying spatial-temporal variations of regional atmospheric water vapor through many disciplines cooperatively.