GPS遥感气象要素的理论与应用研究
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摘要
GPS气象学是一门新兴的学科,随着全球导航卫星系统和低轨卫星计划的发展,GPS气象学也得到了迅速地发展,同时也为我们提供了更多的研究课题,对其进行深入的研究将有助于GPS气象学的发展和应用。
本文详细介绍了GPS气象学的发展现状和已经取得的研究成果,分析了国内外的研究动态。综合论述了GPS、GLONASS和Galileo系统的构成、特点和发展情况以及GPS现代化进程。全面介绍了未来的低轨卫星计划—我国台湾和美国联合开发的COSMIC计划和欧洲空间局开发的ACE+计划的组成、研究领域、目标和任务,并分析了各自的技术特点。通过与传统的大气探测手段的比较,从地基和空基两个方面讨论了GPS气象遥感技术的特点。对地基和空基GPS遥感气象要素的理论和实现方法进行了深入的研究,并通过大量的实际观测数据的处理和分析对理论模型和方法进行了充分地研究。本文的主要研究成果包括:
(1) 修正了Hopfield模型,提高了其计算结果的可靠性:Hopfield、Saastamoinen和Black等三种模型是利用GPS数据推算大气综合水汽含量(integrated water vapor(IWV))时,计算天顶静水力学延迟(zenith hydrostatic delay(ZHD))的主要模型,它们的精度将直接影响到水汽含量的精度,为此,本文采用我国地理位置不同的三个IGS跟踪站(北京、武汉和拉萨)上的天顶中性层延迟(zenith neutral delay(ZND))和气象数据,使用上述三种模型分别计算了水汽含量,并对计算结果进行了比较和分析。发现在拉萨站,Hopfield模型与其它两种模型计算的IWV出现了系统性的偏移现象,通过与拉萨站上的探空数据的比较证实Saastamoinen和Black模型计算的IWV比较合理。随后通过对不同地理位置、不同海拔高程跟踪站和不同日期的计算结果的比较,证明了Hopfield模型计算的IWV出现系统性偏差与地理经纬度和日期无关,只与测站的海拔高程有关。本文通过对23个IGS站(海拔高程较均匀的分布在0km-3.622km之间)的IWV偏差的数据拟合,首次给出了Hopfield模型的改正项。通过实际观测数据的验算证明Hopfield模型的修正项能很好地消除由于测站高程的变化所引起的天顶静水力学延迟的系统误差,大大提高Hopfield模型推算结果的可靠性。
(2) 首次提出了利用天顶中性层延迟直接推算水汽含量新方法:通过对北京、武汉和拉萨站上的天顶中性层延迟和相应的水汽含量的比较,笔者发现ZND的变化趋势与IWV的变化趋势是一致的,通过数值上的进一步分析和研究,本文首次提出了利用天顶中性层延迟直接推算水汽含量新方法,经过实测数据的计算,证明了它的可行性。
GPS meteorology is a rising subject. With the development of Global Navigation Satellite System and LEO Satellite Project, GPS meteorology is rapidly developing. More research projects are provided for us. Research on the projects will help development and application of GPS meteorology.The development status and research achievements of GPS meteorology are introduced in detail, and the research trends are analysed in this dissertation. The composition, characteristics, development status of GPS, GLONASS and Galileo and the course of GPS modernization are discussed. COSMIC, a joint U.S.-Taiwan project and ACE+ which is a project managed by ESA are introduced, including their composition, research fields, objectives, and missions, and their technical characteristics are analysed. The characteristics of ground-based and space-based GPS meteorological remote sensing technique are discussed by comparing with traditional atmosphere sounding means. The theory and realization method of remotely sensing meteorological parameters using ground-based and space-based GPS data are studied. The models and methods are researched by processing and analysing measurement data. The main research achievements in this dissertation is shown as the following:(1) Hopfield model is modified and the reliability of calculating result of using the model is enhanced.Hopfield, Saastamoinen and Black models are main models of calculating zenith hydrostatic delay (ZHD) in estimating integrated water vapor (IWV) using GPS data. Their accuracy will directly affect the IWV accuracy. Therefore, integrated water vapor is calculated respectively by above 3 models using zenith neutral delay (ZND ) and meteorological data in BJFS, LHAS and WUHN stations which have different geographical positions. The calculating results are compared and analysed. The analysing result shows that the IWV of calculating with Hopfield model appears systemic deviation compared with the IWV of calculating with other models in LHAS station. The IWVs that are calculated using Saastamoinen model and Black model are validated by comparing with radiosonde data. Following study proves that the systematic deviation is not influenced by geographical latitude, longitude and date, it is only dependent on the station elevation. The modified term
of Hopfield model is first given by fiting the IWV deviation in 23 stations. The checking computation proves that the modified term of Hopfield model can well cancel the deviation due to station elevation, and improve the reliability of calculating result with Hopfield model.(2) The new method of directly estimating IWV using ZND is first advanced. Author finds that the change trends of ZND and IWV are consistent by comparing ZNDwith IWV in BJFS, LHAS and WUHN stations. The new method of directly estimating IWV using ZND is first advanced in further study and analysis for numerical value. The feasibility of the method is testified by calculation of measurement data. If the calculating IWV using former method is taken as true value, root mean square (rms) error is about ±1.0 kg/m2 in not eliminating gross error. The new method of directly estimating IWV using ZND is very useful for estimating IWV in the stations or period that have not meteorological data.(3) The new method of making dynamic modification for transformation coefficient is proposed. The error caused by using different transformation coefficient model and mean temperature formula is analysed.In calculating IWV using ZWD, the key variable is a transformation coefficient. There are two models of calculating transformation coefficient: one is a function of mean temperature, which is widely used, another is a function of station latitude and date. The transformation coefficient is calcualted using two models in BJFS, LHAS and WUHN stations. The IWV bias due to the difference between transformation coefficients calcualted using two models is analysed. The result shows that the bias is relate to station geographical position and date. Sometimes the bias can reach lkg/m2. The mean bias of IWV in LHAS station approachs lkg/m2. The bias is due to model error. So the selection and optimization of the models of calculating transformation coefficient are very important.For analysing the influence of mean temperature, the linear regress formula which is given by Bevis et al. (1992) and the linear regress formula which is proposed by Li Jianguo et al. (1999) are compared. The result shows that the mean temperature calculated by the two formulas is different, and the difference is relate to temperature and humidity. As a rule, IWV bias because of the difference is smaller than 0.3 kg/m2, but it will become large in winter and humid area. IWV bias can reach 0.76 kg/m2 in -20 °C and IWV of 60 kg/m2.For eleminating the influence of model error, improving accuracy of transformation coefficient, a new method of making dynamic modification for transformation coefficient
using rediosonde data is proposed. The method is not validated because of the lack of rediosonde data.(4) The method of assessing the accuracy of IWV calculated with ZWD model by IWV computed using GPS data is first used in this dissertation.The meteorological data in stations includes temperature, pressure, and humidity. The humidity is not used in estimating IWV using GPS data. It is key data to directly estimate IWV by ZWD model. The meteorological data and elevation are used to calculate IWV by Hopfield and Saastamoinen ZWD model, and the result is compared with corresponding IWV calculated using GPS data. The result shows that the accuracy of IWV calculated by Hopfield and Saastamoinen ZWD model is about 20%~30%. IWV calculated by Hopfield ZWD model and IWV calculated by Saastamoinen ZWD model are different, the difference is affected by elevation.(5) How to determine initialization height of the Abel integral inversion using retrieval temperature profile is discussed. The temperature profile change before and after statistical optimization for GPS/MET and CHAMP is analysed.The choice of initialization height will influence retrieval of temperature profile. By analysing the relationship between the boundary condition of temperature and retrieval temperature profile, it can be known that the retrieval result is most reasonable when the upper boundary condition of temperature is most close to the change trend of retrieval temperature profile.By comparing and analysing retrieval temperature profile without statistical optimization and with statistical optimization, it can be found that temperature profile change before and after statistical optimization is obvious for GPS/MET data, and temperature profile change is not obvious for CHAMP data.(6) The effect of gravity value on retrieval result is analysed.When the pressure is calculated, the two methods can be selected: the gravity is integrated in one method, and the gravity is taken as a constant in another method. The temperatures and pressures which are calculated using the two methods are different, the difference of temperature is smaller than 0.6 K, the difference of pressure is smaller than 2 hPa.
(7) Exploiting and developing two kinds of software: IWV processing and analysing system and GPS occultation retrieval system.For processing, comparing and analysing large numbers of data, author develops two kinds of software: IWV processing and analysing system and GPS occultation retrieval system.IWV processing and analysing system takes ZND and meteorological data as original data, and uses Hopfield, Saastamoinen and Black models (including ZHD and ZWD models) and two transformation coefficient models. The software can extract the required raw data from many files in format of ZND data and meteorological data provided by IGS besides the function of batch data processing and graph display. It can give more than 30 kinds of data, such as IWV, ZHD, ZWD, transformation coefficient etc for study and analysis.GPS occultation retrieval system takes Level2 data of CHAMP and GPS/MET as original data, and Abel integral inversion is used in refractivity retrieval. The coordinate transformation, ionospheric correction, earth's flattening correction, upper boundary condition statistical optimization etc are used in retrieval process. The software can fulfill retrieval from extra phase delay to bending angle, refractivity, pressure and temperature.
本文详细介绍了GPS气象学的发展现状和已经取得的研究成果,分析了国内外的研究动态。综合论述了GPS、GLONASS和Galileo系统的构成、特点和发展情况以及GPS现代化进程。全面介绍了未来的低轨卫星计划—我国台湾和美国联合开发的COSMIC计划和欧洲空间局开发的ACE+计划的组成、研究领域、目标和任务,并分析了各自的技术特点。通过与传统的大气探测手段的比较,从地基和空基两个方面讨论了GPS气象遥感技术的特点。对地基和空基GPS遥感气象要素的理论和实现方法进行了深入的研究,并通过大量的实际观测数据的处理和分析对理论模型和方法进行了充分地研究。本文的主要研究成果包括:
(1) 修正了Hopfield模型,提高了其计算结果的可靠性:Hopfield、Saastamoinen和Black等三种模型是利用GPS数据推算大气综合水汽含量(integrated water vapor(IWV))时,计算天顶静水力学延迟(zenith hydrostatic delay(ZHD))的主要模型,它们的精度将直接影响到水汽含量的精度,为此,本文采用我国地理位置不同的三个IGS跟踪站(北京、武汉和拉萨)上的天顶中性层延迟(zenith neutral delay(ZND))和气象数据,使用上述三种模型分别计算了水汽含量,并对计算结果进行了比较和分析。发现在拉萨站,Hopfield模型与其它两种模型计算的IWV出现了系统性的偏移现象,通过与拉萨站上的探空数据的比较证实Saastamoinen和Black模型计算的IWV比较合理。随后通过对不同地理位置、不同海拔高程跟踪站和不同日期的计算结果的比较,证明了Hopfield模型计算的IWV出现系统性偏差与地理经纬度和日期无关,只与测站的海拔高程有关。本文通过对23个IGS站(海拔高程较均匀的分布在0km-3.622km之间)的IWV偏差的数据拟合,首次给出了Hopfield模型的改正项。通过实际观测数据的验算证明Hopfield模型的修正项能很好地消除由于测站高程的变化所引起的天顶静水力学延迟的系统误差,大大提高Hopfield模型推算结果的可靠性。
(2) 首次提出了利用天顶中性层延迟直接推算水汽含量新方法:通过对北京、武汉和拉萨站上的天顶中性层延迟和相应的水汽含量的比较,笔者发现ZND的变化趋势与IWV的变化趋势是一致的,通过数值上的进一步分析和研究,本文首次提出了利用天顶中性层延迟直接推算水汽含量新方法,经过实测数据的计算,证明了它的可行性。
GPS meteorology is a rising subject. With the development of Global Navigation Satellite System and LEO Satellite Project, GPS meteorology is rapidly developing. More research projects are provided for us. Research on the projects will help development and application of GPS meteorology.The development status and research achievements of GPS meteorology are introduced in detail, and the research trends are analysed in this dissertation. The composition, characteristics, development status of GPS, GLONASS and Galileo and the course of GPS modernization are discussed. COSMIC, a joint U.S.-Taiwan project and ACE+ which is a project managed by ESA are introduced, including their composition, research fields, objectives, and missions, and their technical characteristics are analysed. The characteristics of ground-based and space-based GPS meteorological remote sensing technique are discussed by comparing with traditional atmosphere sounding means. The theory and realization method of remotely sensing meteorological parameters using ground-based and space-based GPS data are studied. The models and methods are researched by processing and analysing measurement data. The main research achievements in this dissertation is shown as the following:(1) Hopfield model is modified and the reliability of calculating result of using the model is enhanced.Hopfield, Saastamoinen and Black models are main models of calculating zenith hydrostatic delay (ZHD) in estimating integrated water vapor (IWV) using GPS data. Their accuracy will directly affect the IWV accuracy. Therefore, integrated water vapor is calculated respectively by above 3 models using zenith neutral delay (ZND ) and meteorological data in BJFS, LHAS and WUHN stations which have different geographical positions. The calculating results are compared and analysed. The analysing result shows that the IWV of calculating with Hopfield model appears systemic deviation compared with the IWV of calculating with other models in LHAS station. The IWVs that are calculated using Saastamoinen model and Black model are validated by comparing with radiosonde data. Following study proves that the systematic deviation is not influenced by geographical latitude, longitude and date, it is only dependent on the station elevation. The modified term
of Hopfield model is first given by fiting the IWV deviation in 23 stations. The checking computation proves that the modified term of Hopfield model can well cancel the deviation due to station elevation, and improve the reliability of calculating result with Hopfield model.(2) The new method of directly estimating IWV using ZND is first advanced. Author finds that the change trends of ZND and IWV are consistent by comparing ZNDwith IWV in BJFS, LHAS and WUHN stations. The new method of directly estimating IWV using ZND is first advanced in further study and analysis for numerical value. The feasibility of the method is testified by calculation of measurement data. If the calculating IWV using former method is taken as true value, root mean square (rms) error is about ±1.0 kg/m2 in not eliminating gross error. The new method of directly estimating IWV using ZND is very useful for estimating IWV in the stations or period that have not meteorological data.(3) The new method of making dynamic modification for transformation coefficient is proposed. The error caused by using different transformation coefficient model and mean temperature formula is analysed.In calculating IWV using ZWD, the key variable is a transformation coefficient. There are two models of calculating transformation coefficient: one is a function of mean temperature, which is widely used, another is a function of station latitude and date. The transformation coefficient is calcualted using two models in BJFS, LHAS and WUHN stations. The IWV bias due to the difference between transformation coefficients calcualted using two models is analysed. The result shows that the bias is relate to station geographical position and date. Sometimes the bias can reach lkg/m2. The mean bias of IWV in LHAS station approachs lkg/m2. The bias is due to model error. So the selection and optimization of the models of calculating transformation coefficient are very important.For analysing the influence of mean temperature, the linear regress formula which is given by Bevis et al. (1992) and the linear regress formula which is proposed by Li Jianguo et al. (1999) are compared. The result shows that the mean temperature calculated by the two formulas is different, and the difference is relate to temperature and humidity. As a rule, IWV bias because of the difference is smaller than 0.3 kg/m2, but it will become large in winter and humid area. IWV bias can reach 0.76 kg/m2 in -20 °C and IWV of 60 kg/m2.For eleminating the influence of model error, improving accuracy of transformation coefficient, a new method of making dynamic modification for transformation coefficient
using rediosonde data is proposed. The method is not validated because of the lack of rediosonde data.(4) The method of assessing the accuracy of IWV calculated with ZWD model by IWV computed using GPS data is first used in this dissertation.The meteorological data in stations includes temperature, pressure, and humidity. The humidity is not used in estimating IWV using GPS data. It is key data to directly estimate IWV by ZWD model. The meteorological data and elevation are used to calculate IWV by Hopfield and Saastamoinen ZWD model, and the result is compared with corresponding IWV calculated using GPS data. The result shows that the accuracy of IWV calculated by Hopfield and Saastamoinen ZWD model is about 20%~30%. IWV calculated by Hopfield ZWD model and IWV calculated by Saastamoinen ZWD model are different, the difference is affected by elevation.(5) How to determine initialization height of the Abel integral inversion using retrieval temperature profile is discussed. The temperature profile change before and after statistical optimization for GPS/MET and CHAMP is analysed.The choice of initialization height will influence retrieval of temperature profile. By analysing the relationship between the boundary condition of temperature and retrieval temperature profile, it can be known that the retrieval result is most reasonable when the upper boundary condition of temperature is most close to the change trend of retrieval temperature profile.By comparing and analysing retrieval temperature profile without statistical optimization and with statistical optimization, it can be found that temperature profile change before and after statistical optimization is obvious for GPS/MET data, and temperature profile change is not obvious for CHAMP data.(6) The effect of gravity value on retrieval result is analysed.When the pressure is calculated, the two methods can be selected: the gravity is integrated in one method, and the gravity is taken as a constant in another method. The temperatures and pressures which are calculated using the two methods are different, the difference of temperature is smaller than 0.6 K, the difference of pressure is smaller than 2 hPa.
(7) Exploiting and developing two kinds of software: IWV processing and analysing system and GPS occultation retrieval system.For processing, comparing and analysing large numbers of data, author develops two kinds of software: IWV processing and analysing system and GPS occultation retrieval system.IWV processing and analysing system takes ZND and meteorological data as original data, and uses Hopfield, Saastamoinen and Black models (including ZHD and ZWD models) and two transformation coefficient models. The software can extract the required raw data from many files in format of ZND data and meteorological data provided by IGS besides the function of batch data processing and graph display. It can give more than 30 kinds of data, such as IWV, ZHD, ZWD, transformation coefficient etc for study and analysis.GPS occultation retrieval system takes Level2 data of CHAMP and GPS/MET as original data, and Abel integral inversion is used in refractivity retrieval. The coordinate transformation, ionospheric correction, earth's flattening correction, upper boundary condition statistical optimization etc are used in retrieval process. The software can fulfill retrieval from extra phase delay to bending angle, refractivity, pressure and temperature.
引文
[1] 曲建光,魏旭东等.在高海拔地区Saastamoinen模型和Hopfield模型推算水汽含量差异的研究.武汉大学学报(信息科学版),2003,28(4):397～399
[2] 曲建光,刘基余,韩中元.利用天顶对流层延迟数据直接推算水汽含量方法的研究.武汉大学学报(信息科学版),已录用.
[3] 曲建光,刘基余.利用GPS数据推算水汽含量动态模型的研究.测绘通报,2004(2):5～7
[4] 曲建光,刘基余.用于气象研究的低轨卫星计划发展动态的分析.测绘工程,2004,13(1):44～46
[5] 曲建光等.从GPS推算大气水汽的误差分析.测绘工程,2001,10(4):24～26
[6] 曲建光.推算大气综合水汽转换系数K值的计算与分析.黑龙江工程学院学报,2002,16(3):35～37
[7] QU Jian-guang, YANG Ze-yun, LIU Ji-yu. Influence of geographical position on accuracy in calculating integrated water vapor using GPS data. Proceedings of ⅩⅡ international society for mine surveying, 2004
[8] 曲建光,杨泽运.GPS空间定位技术及其应用.哈尔滨:哈尔滨地图出版社,2004
[9] 刘基余,李征航等.全球定位系统原理及其应用.北京:测绘出版社,1993
[10] 刘基余.GPS卫星导航定位原理与方法.北京:科学出版社,2003
[11] 陈俊勇.GPS气象遥感技术.测绘通报,1997(9):2～4
[12] 陈俊勇.地基GPS遥感大气水汽含量的误差分析.测绘学报,1998,27(2):113～118
[13] 陈洪滨,吕达仁等.微波高度计测高的大气订正新算式.大气科学,1995(3)
[14] 程晓,徐冠华,周春霞,王清华,鄂栋臣.应用GPS资料反演南极大气可降水量的试验分析.极地研究,2002,14(2):136～144
[16] 郭际明.GPS与GLONASS最新发展.测绘信息与工程,2002:28～30
[17] 郭鹏,洪振杰,严豪健,黄珹.反演地球大气模拟软件(SHAOOS)介绍.中国科学院上海天文台年刊,2003,24:150～156
[18] 郭鹏,洪振杰,张大海,COSMIC计划.天文学进展,2002,20(4):324～336
[19] 何平,徐宝祥,周秀骥,王红艳.地基GPS反演大气水汽总量的初步试验.应用气象学报,2002,13(2):179～183
[20] 胡雄,曾桢,张训械,熊建刚,张冬娅,黄泽荣,艾勇.无线电掩星技术及其应用.电波科学学报,2002,17(5):549～556
[21] 黄栋,严豪健,黄碱.GPS无线电掩星监测地球大气技术中的一种长时间序列地面测点方法.天文学报,2000,41(1):51～57
[22] 蒋虎.LEONE星轨道设计中的主要摄动源影响评估.云南天文台台刊,2002,2:29～34
[23] 蒋虎等.MSISE90大气密度模型及其在GPS掩星技术中的应用.云南天文台台刊,2001,2:27～30
[24] 蒋虎等.针对实际气象需要的地球低轨道卫星的轨道计算.云南天文台台刊,2001,2:31～34
[25] 蒋虎,黄珹.低轨卫星轨道误差对中性层延迟量影响的模拟研究.地球物理学报,2003,46(2):167～179
[26] 蒋虎,黄珹,严豪健.空间GPS无线电掩星反演大气参数方法及其应用.地球科学进展,2000,15(5):565～570
[27] 蒋虎,黄珹,张运刚.GPS无线电掩星反演大气参数中的算法研究.地球物理学进展,2002,17(3):451～455
[28] 蒋虎.空基GPS遥感地球大气参数方法研究.测绘学报,2001,30(3):238～241
[29] 蒋虎等.掩星观测中电离层延迟对LEO卫星轨道误差的响应.电波科学学报,2002,17(6):646～649
[30] 金双根,朱文耀.GPS气象学应用进展及其监测实例分析.自然杂志,24(2):99～103
[31] 李建国,毛节泰,李成才,夏青.使用全球定位系统遥感水汽分布原理和中国东部地区加权“平均温度”的回归分析.气象学报,1999,57(3):283～292
[32] 李延兴,徐宝祥,胡新康,何平.应用地基GPS技术遥感大气柱水汽量的试验研究.应用气象学报,2001,12(1):61～69
[33] 刘焱雄,H B IZ,陈永奇.GPS气象学垂直干分量延迟的精确确定.测绘学报,2000,29(2):172～180
[34] 刘焱雄,陈永奇,刘经南.利用地面气象观测资料确定对流层加权平均温度.武汉测绘科技大学学报,2000,25(5):400～404
[35] 陆忠汉,王婉馨.简明气象词典.长沙:湖南科学技术出版社,1983
[36] 欧吉坤.GPS测量的中性大气折射改正的研究.测绘学报,1998,27(1):31～36
[37] 漆炙荣,周绍祥等.理科最新常用数据手册.西安:陕西人民出版社,1983
[38] 邵占英.GPS定位中对流层折射率随机模型的研究.地壳形变与地震,1996,16(2):1～7
[39] 邵占英,刘经南,姜卫平,李延兴,邵占英.GPS精密相对定位中用分段线性法估算对流层折射偏差的影响.地壳形变与地震,1998,18(3):13～18
[40] 宋淑丽,朱文耀,丁金才,程宗颐.上海GPS综合应用网及2002年长江三角洲地区入梅过程的监测.天文学进展,2003,21(2):180～184
[41] 宋淑丽,朱文耀,廖新浩.地基GPS气象学研究的主要问题及最新进展.地球科学进展,2004,19(2):250～259
[42] 宋淑丽,朱文耀.区域GPS网实时计算可降水量的若干问题.中国科学院上海天文台年刊,2003,24:20～27
[43] 王柏春,彭洪淼,顾大权,许屏.cosmic及其在气象领域的应用.气象科学,2002,22(2):247～252
[44] 王小亚,朱文耀,严豪健,程宗颐,丁金才.地面GPS探测大气可降水量的初步结果.大气科学,1999,23(5):605～612
[45] 王小亚,朱文耀,严豪健,丁金才.地面GPS探测大气的最新进展.地球科学进展,1997,6:519～527
[46] 吴必军.我国中性大气折射对GPS测量影响特点及其修正新模式的初步研究.导航,1997(2)
[47] 徐晓华等.利用GPS掩星资料反演地球中性大气参数折射角方法研究.武汉大学学报,2003,28(5):589～592
[48] 徐晓华.利用GNSS无线电掩星技术探测地球大气的研究.武汉:武汉大学博士学位论文,2003
[49] 严豪健,郭鹏,张贵霞,黄珹.上海天文台GPS掩星技术研究现状.中国科学院上海天文台年刊,2003,24:39～47
[50] 严豪健,朱文耀,黄碱.上海天文台GPS气象学的研究现状.中国科学院上海天文台年刊,2000,21:24～34
[51] 袁招洪,丁金才,陈敏.GPS观测资料应用于中尺度数值预报模式的初步研究.气象学报,2004,62(2):200～212
[52] 曾桢,胡雄,张训械.无线电掩星与微波雷达观测结果的比较.空间科学学报,2001,21(2):165～171
[53] 张大海,郭鹏,张贵霞,严豪健,黄珹.GPS掩星技术低轨卫星计划的现状与进展.天文学进展,2002,20(2):114～121
[54] 张庆阳,张沅,李莉,田静.大气探测技术发展概述.气象科技,2003,31(2):119～123
[55] 赵世军,孙学金,朱有成,廖仿玉.LEO卫星轨道参数对GPS掩星数量和分布的影响.解放军理工大学学报,2002,3(2):85～89
[56] 郑作亚等.利用多参数估计法解算对流层延迟.山东科技大学学报,2001,20(4):82～84
[57] 周忠谟,易杰军.卫星测量原理与应用.北京:测绘出版社,1992
[58] 周其焕.欧洲Galileo系统的信号结构和服务性能.全球定位系统,2002,27(1):19～23
[59] Aparicio, J. M., A. Rius, A ray tracing inversion procedure for the extraction of the atmospheric refractivity from GNSS travel-time data. Phys. Chem. Earth, 2004, 29:213～224
[60] Baltink, H. K, et al, Integrated Atmospheric water estimates from a regional GPS nework. J. Geophys. Res., 2002, 107(D3): ACL 3-1～3-8
[61] Basili, P., S. Bonafoni, et al, Atmospheric water vapor retrieval by means of both a GPS network and a microwave radiometer during an experimental campaign in Cagliari, Italy, in 1999. IEEE Transactions On Geoscience and Remote Sensing, 2001, 39(11): 2436～2443
[62] Behrend, D., L. Cucurull, J. Vila, and R. Haas, An inter-comparison study to estimate zenith wet delays using VLBI GPS and NWP models. Earth Planets Space, 2000, 52:691～694
[63] Bevis, M., S. Businger, et al, Remote sensing of atmospheric water vapor using the GPS. J. Geophys. Res., 1992, 970314): 15878～15881
[64] Bevis, M., S. Businger, GPS Meteorology and the International GPS Service, The Preceedings of lGS 95 Workshop, 1995:6～16
[65] Bock, H., U. Hugentobler, T. A. Springer, and G. Beutler, Efficient precise orbit determination of LEO satellites using GPS. Adv. Space Res., 2002, 30(2): 295～300
[66] Bock, O., and E. Doerflinger, Atmospheric modeling in GPS data analysis for high accuracy positioning. Phys. Chem. Earth (A), 2001, 26(6-8): 373～383
[67] Bock, O., E. Doerflinger, F. Masson, A. Walpersdorf, J. Van-Baelen, J. Tarniewicz, M. Troller, A. Somieski, A. Geiger, B. Burki, GPS water vapor project associated to the ESCOMPTE programme: description and first results of the field experiment. Phys. Chem. Earth, 2004, 29:149～157
[68] Bouma, H. R., and B. Stoew, GPS observations of daily variations in the atmospheric water vapor content. Phys. Chem. Earth (A), 2001, 26(6-8): 389～392
[69] Cucurull, L., P. Sed6, D. Behrend, E. Cardellach, A. Rius, Integrating NWP products into the analysis of GPS observables. Phys. Chem. Earth, 2002, 27:377～383
[70] Davis, J. L., Atmospheric water-vapor signals in GPS data: synergies, correlations, signals and errors. Phys. Chem. Earth (A), 2001, 26(6-8): 513～522
[71] Davis, J. L., G. Elgered, The Spatio-temporal structure of GPS water-vaper determination. Phys. Chem. Earth, 1998, 23(1): 91-96
[72] Dick, G., Gerd Gendt, Christoph Reigber, First experience with near real-time water vapor estimation in a German GPS network. J. Atmos. Sol. Terr. Phys., 2001, 63:1295～1304
[73] Dodson, A. H., and H. C. Baker, Accuracy of orbit for GPS atmospheric water vapor estimation. Phys. Chem. Earth, 1998, 23(1): 119～124
[74] Dou_sa, J., Evaluation of tropospheric parameters estimated in various routine GPS analysis. Phys. Chem. Earth, 2004, 29:167～175
[75] Elgered., G., An overview of COST action 716 exploitation of ground-based GPS for climate and numerical weather prediction applications. Phys. Chem. Earth (A), 2001,26(6-8): 399-404
[76] E1osegui, P., J. L. Davis, L. P. Gradinarsky, G. Elgered, J. M. Johansson, D. A. Tahmoush, and A. Rius, Sensing atmospheric structure using small-scale space of geodetic networks. Geophys Res. Lett., 1999,26(16): 2445-2448
[77] Emardson, T. R., G. Elgered, et al, Three months of continuous monitoring of atmospheric water vapor with a network of GPS receivers. J.Geophys.Res., 1998,103(D2): 1807-1820
[78] Engeln, A., S. Buhler, et al, Temperature profile retrieval from surface to mesopause by combining GNSS radio occultation and passive microwave limb sounder data. J. Geophys. Res., 2001, 28(5): 775-778
[79] Feng, D., B. Herman, et al, Preliminary results from the GPS/MET atmospheric remote sensing experiment, The Preceedings of IGS 95 Workshop, 1995:139-143
[80] Fjedbo, G., A. R. Kliore, and V.R.Eshelman, The neutral atmosphere of Venus as studied with the Mariner V radio occultation experiments. Astron. J., 1971,76:123-140
[81] Flores, A., L. P. Gradinarsky, P. Elosegui, G. Elgered, J. L. Davis, and A. Rius, Sensing atmospheric structure:Tropospheric tomographic results of the small-scale GPS campaign at the Onsala Space Observatory. Earth Planets Space, 2000,52:941-945
[82] Foelsche, U., and G. Kirchengast, A new "geometric" mapping function for the hydrostatic delay at GPS frequencies. Phys. Chem. Earth (A), 2001,26(3): 153-157
[83] Foelsche, U., G Kirchengast, Sensitivity of GNSS radio occultation data to horizontal variability in the troposphere. Phys. Chem. Earth, 2004,29: 225-240
[84] Foster, J., M. Bevis, et al, El Nino, water vapor, and the Global Positioning System. Geophys Res. Lett., 2000,27(17): 2697-2700
[85] Galas, R., J. Wiekert and W. Burghardt, High rate low latency gps ground tracking network for CHAMP. Phys. Chem. Earth (A), 2001,26(6-8): 649-652
[86] Gao, B.C., Ed R. Westwater, et al, Comparison of column water vapor measurements using downward-looking near-infrared and infrared imaging systems and upward-looking microwave radiometers, J. Appl. Meteor., 1992:1193-1201
[87] Gavrilov, N. M., N. V. Karpova, Ch. Jacobi, Global distributions of the refraction index variances at different altitudes in the atmosphere from GPS/MET satellite occultation data. Phys. Chem. Earth, 2004, 29: 241-249
[88] Ge, M., E. Calais and J. Haase, Automatic orbit quality control for near real-time GPS zenith
tropospheric delay estimation. Phys. Chem. Earth (A), 2001, 26(3): 177-181
[89] Ge, M., E. Calais, et al, Sensitivity of zenith total delay accuracy to GPS orbit errors and implications for near-real-time GPS meteorology. J. Geophys. Res., 2002,107(D16): ACL 12-1-12-15
[90] Ge, M., E. Calais, J. Haase, Reducing satellite orbit error effects in near real-time GPS zenith tropospheric delay estimation for meteorology. Geophys Res. Lett., 2000,27(13): 1915-1918
[91] Gendt, G., G. Dick, A. Rlus and P. Sedo, Comparision of software and techniques for water vapor estimation using german near real-time GPS data. Phys. Chem. Earth (A), 2001,26(6-8): 417-420
[92] Gorbunov, M. E., An asymptotic method of modeling radio occultations. J. Atmos. Sol. Terr. Phys., 2003,65:1361-1367
[93] Gorbunov, M. E., L. Kornblueh, Analysis and validation of GPS/MET radio occultation data. J. Geophys. Res., 2001,106 (D15): 17161-17169
[94] Guerova, G., J. M. Bettems, E. Brockmann, Ch. Matzler, Assimilation of the GPS-derived integrated water vapour (IWV) in the MeteoSwiss numerical weather prediction model-a first experiment. Phys. Chem. Earth, 2004, 29:177-186
[95] Guldner, J., Validation of integrated water vapor using independent measurement techniques. Phys. Chem. Earth (A), 2001,26(6-8): 427-431
[96] Guo P., F. J. Cai, Z. J. Hong, H. J. Yan, M. Liu, An algorithm for the retrieval of the earth's atmospheric parameters from occultation data of GPS/LEO satellites with non-circular orbits. Chinese Astronomy and Astrophysics, 2004,28: 338- 347
[97] Haase, J. E., Calais, J. Talaya, A. Rius, et al, The contributions of the MAGIC project to the COST 716 objectives of assessing the operational potential of ground-based GPS meteorology on an international scale. Phys. Chem. Earth (A), 2001, 26(6-8): 433-437
[98] Hajj, G A., E. R. Kursinski, L. J. Romans, W. I. Bertiger, S. S. Leroy, A technical description of atmospheric sounding by GPS occultation. J. Atmos. Sol. Terr. Phys., 2002,64: 451-469
[99] Hajj, GA., E. R. Kursinski, et al, Initial results of gps-leo occultation measurements of earth's atmosphere obtained with GPS-MET experiment. The Preceedings of IGS 95 Workshop, 1995: 144-153
[100] Stoew, B., P. Jarlemark, J. Johansson, and G. Elgered, Atmospheric delay estimates from a ground -based real -time GPS Network. ION GPS, 2001,11-14:1079-1083
[101] Hay, C, J. Wong, Enhancing GPS tropospheric delay prediction at the Master Control Station. GPS World, 2000,11(1)
[102] Healy, S. B., Smoothing radio occultation bending angles above 40 km. Annals of Geophysics, 2001b, 19(4): 459-468
[103] Hernandez-Pajares, M., J. M. Juam, J. Sanz, D. Bilitza, Combining GPS measurements and in model values for space weather specification. Adv. Space Res., 2002,29(6): 949~958
[104] Hernandez-Pajares, M., J. M. Juan, J. Sanz, et al, A new strategy for real-time integrated water vapor determination in WADGPS networks. Geophys. Res. Lett., 2001,28(17): 3267-3270
[105] Higgins, M., Progress in 3D-variational assimilation of total zenith delay at the met office. Phys. Chem. Earth (A), 2001,26(6-8): 445-449
[106] Hochegger, G., and R. Leitinger, Model assisted inversion of gnss occultation data. Phys. Chem. Earth (C), 2001,26(5): 325-330
[107] Hocke, K., A. G. Pavelyev, O. I. Yakovlev, L. Barthes, N. Jakowski, Radio occultation data analysis by the radioholographic method.J. Atmos. Sol. Terr. Phys., 1999,61(15): 1169-1177
[108] Hocke, K., and A. G. Pavelyev, General aspect of GPS data use for atmospheric science. Adv. Space Res., 2001,27(6-7): 1313-1320
[109] Hocke, K., and T. Tsuda, Gravity waves and ionospheric irregularities over tropical convection zones observed by GPS/MET radio occultation. Geophys Res. Lett., 2001,28(14): 2815-2818
[110] Hocke, K., and T. Tsuda, Using GPS satellites to study plasma irregularities. GPS World, 2001,12(7): 34-36
[111] Hocke, K., Inversion of GPS meteorology data. Annales Geophysicae, 1997,15:443 -450
[112] Hocke, K., K. Igarashi,M. Nakamura, P. Wilkinson, J. Wu, A. Pavelyev, J. Wickert, Global sounding of sporadic E layers by the GPS/MET radio occultation experiment. J. Atmos. Sol. Terr. Phys., 2001, 63:1973-1980
[113] Huang, C, F. P. Zhang, H. J. Yan, Controls of the sounding points in space-based GPSLEO meteorology.J. Atmos. Sol. Terr. Phys., 2001, 63:1601-1607
[114] Ioltukhovski, A. A., M. Ya. Marov, Spectral remote sensing of the atmosphere by the occultation of stars: Retrieval of the constituents and evaluation of the refraction effect. J. Atmos. Sol. Terr. Phys., 1998,60:1555-1571
[115] Iwabuchi, T., and Isao Naito, Nobutaka Mannoji, A Comparison of Global Positioning System retrieved precipitable water vapor with the numerical weather prediction analysis data over the Japanese islands. J. Geophys. Res., 2000,105(D4): 4573-4585
[116] Iwabuchi, T., Shin'ichi Miyazaki, et al, An impact of estimating tropospheric delay gradients on
tropospheric delay estimations in the summer using the Japanese nationwide GPS array. J. Geophys. Res., 2003,108(D10): ACL 10-1-10-14
[117] Johasson, J. ML, T. R. Emardson, P. O. J. Jarlemark, L. P. Gradinarsky and G. Elgered, The atmospheric influence on the results from the Swedish GPS network. Phys. Chan. Earth, 2001, 23(1): 107-112
[118] Johnsen, K. P., and B. Rockel, Validation of a regional weather forecast model with GPS data. Phys. Chem. Earth (B), 2001, 26(5-6): 415-419
[119] Johnsen, K. P., and B. Rockel, Validation of the NWP model HRM with ground-based GPS data. Phys. Chem. Earth (A), 2001, 26(6-8): 463-466
[120] Johnsen, K. P., J. Miao, S.Q. Kidder, Comparison of atmospheric water vapor over Antarctica derived from CHAMP GPS and AMSU-B data. Phys. Chem. Earth, 2004,29: 251-255
[121] Kunitsyn, V., V. Zakharov, K. Dethloff, A. Weisheimer, M. Gerding, R. Neuber, A. Rinke, I. Hebestadt, Improved radio occultation sounding of the Arctic atmosphere using simulations with a high resolution atmospheric model. Phys. Chem. Earth, 2004, 29:277-286
[122] Kursinski, E. R., and G A. Hajj, A Comparison of water vapor derived from GPS occultations and global weather analyses. 7. Geophys. Res., 2001,106(D1): 1113-1138
[123] Kursinski, E. R., G A. Hajj, K. R. Hardy, J. T. Schofield, R. Linfield, Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System. J. Geophys. Res., 1997, 102(D19): 23429-23465
[124] Lesne, O., J. Haase, G. Kirchengast, J. Ramsauer, W. Poetzi, Sensitivity analysis for airborne sounding of the troposphere by GNSS radio occultation. Phys. Chem. Earth, 2002,27: 291-299
[125] Liu, H., X. Zou, H. Shao, R. A. Anthes, J. C. Chang, J. H. Tseng, and B. Wang, Impact of 837 GPS/MET bending angle profiles on assimilation and forecasts for the period June 20-30,1995. J. Geophys. Res., 2001,106(D23): 31771- 31786
[126] Liu, Y, and Y. Chen, H. Baki lz, Precision of precipitable water vapor from radiosonde data for GPS solutions. Geomatica, 2000,54(2): 171-175
[127] Liu, Y. A., C. Y. Huang, and Y. T. Teng, Precipitable water observed by ground-based GPS receivers and microwave radiometry. Earth Planets Space, 2000,52: 445-450
[128] MacMillan D. S., Atmospheric gradients from very long baseline interferometry observations, Geophys.Res.Lett., 1995, 22(9): 1041-1044,
[129] Marel, H. The COST-716 Team,COST-716 demonstration project for the near real-time estimation of integrated water vapour from GPS. Phys. Chem. Earth, 2004, 29:187-199
[130] Marquardt, C, K. Labitzke, Ch. Reigber, T. Schmidt and J. Wickert, An assessment of the quality of GPS/MET radio limb soundings during February 1997. Phys. Chem. Earth (A), 2001,26(3): 125-130
[131] Mendes, V. B., R .B. Langley, Tropospheric zenith delay prediction accuracy for high-precesion GPS positioning and navigation. Navigation, 1999,46(1): 25-33.
[132] Montenbruck, O., An epoch state filter for use with analytical orbit models of low earth satellites. Aerosp. Sci. Technol, 2000,4: 277-287
[133] Nicholas, A. C, J. M. Picone, S. E. Thonnard, R. R. Meier, K. F. Dymond, D. P. Drob, A methodology for using optimal MSIS parameters retrieved from SSULI data to compute satellite drag on LEO objects. J. Atmos. Sol. Terr. Phys., 2000,62:1317-1326
[134] Ohtani, R., Detection of water vapor variations driven by thermally induced local circulations using the Japanese continuous GPS network. Geophys Res. Lett., 2001,28(1): 151-154
[135] Owens, J. F., Optical infractive index of air: Dependence on pressure, temperature and composition. Appl. Opt., 1967,6:51-52
[136] Pacione, R., C. Sciarretta, F. Vespe, C. Faccani: R. Ferretti, E. Fionda, C. Ferraro and A. Nardi, GPS Meteorology: validation and comparisons with ground-based microwave radiometer and mesoscale model for the Italian GPS permanent stations. Phys. Chem. Earth (A), 2001,26(3): 139-145
[137] Pacione, R., E. Fionda, R. Ferrara, R. Lanotte, C. Sciarretta, F. Vespe, Comparison of atmospheric parameters derived from GPS, VLBI and a ground-based microwave radiometer in Italy. Phys. Chem. Earth, 2002,27:309-316
[138] Palmer, P. I., and J. J. Barnett, J. R. Eyre and S. B. Healy. A nonlinear optimal estimation inverse method for radio occultation measurements of temperature, humidity, and surface pressure. J. Geophys. Res., 2000,150(D13): 17153-17526
[139] Palmer, P. I., and J. J. Barnett, Application of an optimal estimation inverse method to GPS/MET bending angle observations. J. Geophys. Res., 2001,106(D15): 17147-17160
[140] Pany, T., Measuring and modeling the slant wet delay with GPS and the ECMWF NWP model. Phys. Chem. Earth, 2002,27: 347-354
[141] Pany, T., P. Pesec and G. Stangl, Atmospheric GPS slant path delays and ray tracing through numerical weather model. Phys. Chem. Earth (A), 2001, 26(3): 183-188
[142] Pany, T., P. Pesec and G. Stangl, Elimination of tropospheric path delays in GPS observations with the ECMWF numerical weather model. Phys. Chem. Earth (A), 2001, 26(6-8): 487-492
[143] Elosegui, P., A. Ruis, J. L Davis, G. Ruffini, S. J. Keihm, B. Burki and L. P. Kruse, An experiment for estimation of the spatial and temporal variation of water vapor using GPS data. Phys. Chem. Earth, 1998, 23(1): 125～130
[144] Pugnaghi, S., M. Boccolari, S. Fazlagic, R. Pacione, R. Santangelo, H. Vedel, F. Vespe, Comparison of independent integrated water vapour estimates from GPS and sun photometer measurements and a meteorological model. Phys. Chem. Earth, 2002, 27:355～362
[145] Reigber, C., G. Gendt, et al, Near-real-time water vapor monitoring for weather forecasts. GPS World, 2002, 13(1): 18～27
[146] Rhoden, E. A., J. M. Forbes, F. A. Marcos, The infuence of geomagnetic and solar variabilities on lower thermosphere density. J. Atraos. Sol. Terr. Phys., 2000, 62:999～1013
[147] Rocken, C., F. S. Solheim, et al, Application of IGS data to GPS sensing of the atmosphere for weather and climate research, The Preceedings oflGS 95 Workshop, 1995:93～104
[148] Rocken, C., R. Ware, et al, Sensing atmospheric water vapor with GPS, Geophys. Res. Lett., 1993, 20(23): 2631～2634,
[149] Schenewerk, M. S., G. L. Mader, et al, A review of the NOAA Geosciences Lab's automated water vapor project. The Preceedings of IGS 95 Workshop, 1995:104～111
[150] Schmidt, T., J. Wickert, C. Marquardt, G. Beyede, C. Reigber, R. Galas, R. Konig, GPS radio occultation with CHAMP: an innovative remote sensing method of the atmosphere. Advances in Space Research, 2004, 33:1036～1040
[151] Sierk, B., B. Burki, L. P. Kruse, S. Florek, H. Becker-Ross, H. G. Kahle and R. Neubert, A new instrumental approach to water vapor determination based on solar spectroscopy. Phys. Chem. Earth, 1998, 23(1): 113～117
[152] Steiner, A. K, G. Kirchengast, H. P. Ladreiter, Inversion, error analysis, and validation of GPSMET occultation data. Annales Geophysicae, 1999, 17:122～138
[153] Steiner, A. K, G. Kirchengast, U. Foelsche, L. Kornblueh, E. Manzini and L Bengtsson, GNSS occultation sounding for climate monitoring. Phys. Chem. Earth (A), 2001, 26(3): 113～124
[154] Sun, D.Z., R. S. Lindzen, Distribution of tropical tropospheric water vapor, J. Atmos. Sci., 1993: 1643～1659
[155] Tomassini, M., G. Gendt, G. Dick, M. Ramatschi, C. Schraff, Monitoring of Integrated Water Vapour from ground-based GPS observations and their assimilation in a limited-area NWP model. Phys. Chem. Earth, 2002, 27:341～346
[156] Tsuda, T., K. Heki, S. Miyazaki, K. Aonashi, K. Hirahara, H. Nakamura, M. Tobita, F. Kimata, T. Tabei, T. Matsushima, F. Kimura, M. Satomura, T. Kato, and I. Naito, GPS meteorology project of Japan - Exploring frontiers of geodesy. Earth Planets Space, 1998,50(10): i~v
[157] Vespe , F., C. Benedetto, R. Pacione, The use of refractivity retrieved by radio occultation technique for the derivation of atmospheric water vapor content. Phys. Chem. Earth, 2004,29:257~265
[158] Vorob'ev, V.V., and T.G. Krasil'nikova, Estimation of the accuracy of the atmospheric refractive index recovery from Doppler shift measurements at frequencies used in the NAVSTAR system. Phys. Atmos. Ocean, 1994,29: 602-609.
[159] Walpersdorf, A., E. Calais, J. Haase, L. Eymard, M. Desbois and H. Vedel. Atmospheric gradients estimated by GPS compared to a high resolution Numerical Weather Prediction (NWP) model. Phys. Chem. Earth (A), 2001,26(3): 147-152
[160] Ware, R., C. Alber, C. Rocken, F. Solheim, Sensing integrated water vapor along GPS ray paths. Geophys Res. Lett., 1997,24: 417-420
[161] Ware, R., C. Rocken, et al, Pointed water vapor radiometer corrections for accurate global positioning system surveying. Geophys Res. Lett., 1993,20(23): 2635-2638,
[162] Ware, R., D. W. Fulker, S. A. Stein, D. N. Anderson, S. K. Avery, R. D. Clark, K. K. Droegemeier, J. P. Kuettner, J. B. Minster, S. Sorooshian, Real-time national GPS networks for atmospheric sensing. J. Atmos. Sol. Terr. Phys., 2001, 63:1315-1330
[163] Webley, P. W., R. M. Bingley, A. H. Dodson, G. Wadge, S. J. Waugh, I. N. James, Atmospheric water vapour correction to InSAR surface motion measurements on mountains: results from a dense GPS network on Mount Etna. Phys. Chem. Earth, 2002, 27:363-370
[164] Wickert, J., C. Reigber, et al, Atmosphere sounding by GPS radio occultation: First results from CHAMP. Geophys Res. Lett., 2001,28(17): 3263-3266
[165] Wickert, J., R. Galas, G. Beyerle, R. Konig and C. Reigber, GPS Ground station data for CHAMP radio occultation measurements. Phys. Chem. Earth (A), 2001, 26(6-8): 503-511
[166] Wickert, J., R. Galas, T. Schmidt, G. Beyerle, C. Reigber, C. Forste, M. Ramatschi, Atmospheric sounding with CHAMP: GPS ground station data for occultation processing. Phys. Chem. Earth, 2004, 29: 267-275
[167] Yuan, L. L., R. A. Anthes, et al, Sensing climate change using the GPS. J. Geophys. Res., 1993, 98(D8): 14925-14937
[168] Yunck, T. P., G. A. Hajj, E. R. Kursinski, J. A. LaBrecque, S. T. Lowe, M. M. Watkins, C. M.
Cormick, AMORE: An autotonomous constellation concept for atmospheric and ocean observation. Acta Astronautica, 2000,46(2-6): 355 -364
[169] Zou, X., F. Vandenberghe, B. Wang, M. E. Gorbunov, Y. H. Kuo, S. Sokolovskiy, J. C. Chang, J. G. Sela, R. A. Anthes, A ray tracing operator and its adjomt for the use of GPS/MET refraction angle measurements.J. Geophys. Res., 1999,104(D18): 22301-22318
[170] Zou, X., B.Wang, H. Liu, R. A. Anthes, T. Matsumura, Y. J. Zhu, Use of GPS/MET refraction angles in three-dimensional variational analysis. QJ.R.Meteorol.Soc, 2000,126: 3013-3040
[2] 曲建光,刘基余,韩中元.利用天顶对流层延迟数据直接推算水汽含量方法的研究.武汉大学学报(信息科学版),已录用.
[3] 曲建光,刘基余.利用GPS数据推算水汽含量动态模型的研究.测绘通报,2004(2):5～7
[4] 曲建光,刘基余.用于气象研究的低轨卫星计划发展动态的分析.测绘工程,2004,13(1):44～46
[5] 曲建光等.从GPS推算大气水汽的误差分析.测绘工程,2001,10(4):24～26
[6] 曲建光.推算大气综合水汽转换系数K值的计算与分析.黑龙江工程学院学报,2002,16(3):35～37
[7] QU Jian-guang, YANG Ze-yun, LIU Ji-yu. Influence of geographical position on accuracy in calculating integrated water vapor using GPS data. Proceedings of ⅩⅡ international society for mine surveying, 2004
[8] 曲建光,杨泽运.GPS空间定位技术及其应用.哈尔滨:哈尔滨地图出版社,2004
[9] 刘基余,李征航等.全球定位系统原理及其应用.北京:测绘出版社,1993
[10] 刘基余.GPS卫星导航定位原理与方法.北京:科学出版社,2003
[11] 陈俊勇.GPS气象遥感技术.测绘通报,1997(9):2～4
[12] 陈俊勇.地基GPS遥感大气水汽含量的误差分析.测绘学报,1998,27(2):113～118
[13] 陈洪滨,吕达仁等.微波高度计测高的大气订正新算式.大气科学,1995(3)
[14] 程晓,徐冠华,周春霞,王清华,鄂栋臣.应用GPS资料反演南极大气可降水量的试验分析.极地研究,2002,14(2):136～144
[16] 郭际明.GPS与GLONASS最新发展.测绘信息与工程,2002:28～30
[17] 郭鹏,洪振杰,严豪健,黄珹.反演地球大气模拟软件(SHAOOS)介绍.中国科学院上海天文台年刊,2003,24:150～156
[18] 郭鹏,洪振杰,张大海,COSMIC计划.天文学进展,2002,20(4):324～336
[19] 何平,徐宝祥,周秀骥,王红艳.地基GPS反演大气水汽总量的初步试验.应用气象学报,2002,13(2):179～183
[20] 胡雄,曾桢,张训械,熊建刚,张冬娅,黄泽荣,艾勇.无线电掩星技术及其应用.电波科学学报,2002,17(5):549～556
[21] 黄栋,严豪健,黄碱.GPS无线电掩星监测地球大气技术中的一种长时间序列地面测点方法.天文学报,2000,41(1):51～57
[22] 蒋虎.LEONE星轨道设计中的主要摄动源影响评估.云南天文台台刊,2002,2:29～34
[23] 蒋虎等.MSISE90大气密度模型及其在GPS掩星技术中的应用.云南天文台台刊,2001,2:27～30
[24] 蒋虎等.针对实际气象需要的地球低轨道卫星的轨道计算.云南天文台台刊,2001,2:31～34
[25] 蒋虎,黄珹.低轨卫星轨道误差对中性层延迟量影响的模拟研究.地球物理学报,2003,46(2):167～179
[26] 蒋虎,黄珹,严豪健.空间GPS无线电掩星反演大气参数方法及其应用.地球科学进展,2000,15(5):565～570
[27] 蒋虎,黄珹,张运刚.GPS无线电掩星反演大气参数中的算法研究.地球物理学进展,2002,17(3):451～455
[28] 蒋虎.空基GPS遥感地球大气参数方法研究.测绘学报,2001,30(3):238～241
[29] 蒋虎等.掩星观测中电离层延迟对LEO卫星轨道误差的响应.电波科学学报,2002,17(6):646～649
[30] 金双根,朱文耀.GPS气象学应用进展及其监测实例分析.自然杂志,24(2):99～103
[31] 李建国,毛节泰,李成才,夏青.使用全球定位系统遥感水汽分布原理和中国东部地区加权“平均温度”的回归分析.气象学报,1999,57(3):283～292
[32] 李延兴,徐宝祥,胡新康,何平.应用地基GPS技术遥感大气柱水汽量的试验研究.应用气象学报,2001,12(1):61～69
[33] 刘焱雄,H B IZ,陈永奇.GPS气象学垂直干分量延迟的精确确定.测绘学报,2000,29(2):172～180
[34] 刘焱雄,陈永奇,刘经南.利用地面气象观测资料确定对流层加权平均温度.武汉测绘科技大学学报,2000,25(5):400～404
[35] 陆忠汉,王婉馨.简明气象词典.长沙:湖南科学技术出版社,1983
[36] 欧吉坤.GPS测量的中性大气折射改正的研究.测绘学报,1998,27(1):31～36
[37] 漆炙荣,周绍祥等.理科最新常用数据手册.西安:陕西人民出版社,1983
[38] 邵占英.GPS定位中对流层折射率随机模型的研究.地壳形变与地震,1996,16(2):1～7
[39] 邵占英,刘经南,姜卫平,李延兴,邵占英.GPS精密相对定位中用分段线性法估算对流层折射偏差的影响.地壳形变与地震,1998,18(3):13～18
[40] 宋淑丽,朱文耀,丁金才,程宗颐.上海GPS综合应用网及2002年长江三角洲地区入梅过程的监测.天文学进展,2003,21(2):180～184
[41] 宋淑丽,朱文耀,廖新浩.地基GPS气象学研究的主要问题及最新进展.地球科学进展,2004,19(2):250～259
[42] 宋淑丽,朱文耀.区域GPS网实时计算可降水量的若干问题.中国科学院上海天文台年刊,2003,24:20～27
[43] 王柏春,彭洪淼,顾大权,许屏.cosmic及其在气象领域的应用.气象科学,2002,22(2):247～252
[44] 王小亚,朱文耀,严豪健,程宗颐,丁金才.地面GPS探测大气可降水量的初步结果.大气科学,1999,23(5):605～612
[45] 王小亚,朱文耀,严豪健,丁金才.地面GPS探测大气的最新进展.地球科学进展,1997,6:519～527
[46] 吴必军.我国中性大气折射对GPS测量影响特点及其修正新模式的初步研究.导航,1997(2)
[47] 徐晓华等.利用GPS掩星资料反演地球中性大气参数折射角方法研究.武汉大学学报,2003,28(5):589～592
[48] 徐晓华.利用GNSS无线电掩星技术探测地球大气的研究.武汉:武汉大学博士学位论文,2003
[49] 严豪健,郭鹏,张贵霞,黄珹.上海天文台GPS掩星技术研究现状.中国科学院上海天文台年刊,2003,24:39～47
[50] 严豪健,朱文耀,黄碱.上海天文台GPS气象学的研究现状.中国科学院上海天文台年刊,2000,21:24～34
[51] 袁招洪,丁金才,陈敏.GPS观测资料应用于中尺度数值预报模式的初步研究.气象学报,2004,62(2):200～212
[52] 曾桢,胡雄,张训械.无线电掩星与微波雷达观测结果的比较.空间科学学报,2001,21(2):165～171
[53] 张大海,郭鹏,张贵霞,严豪健,黄珹.GPS掩星技术低轨卫星计划的现状与进展.天文学进展,2002,20(2):114～121
[54] 张庆阳,张沅,李莉,田静.大气探测技术发展概述.气象科技,2003,31(2):119～123
[55] 赵世军,孙学金,朱有成,廖仿玉.LEO卫星轨道参数对GPS掩星数量和分布的影响.解放军理工大学学报,2002,3(2):85～89
[56] 郑作亚等.利用多参数估计法解算对流层延迟.山东科技大学学报,2001,20(4):82～84
[57] 周忠谟,易杰军.卫星测量原理与应用.北京:测绘出版社,1992
[58] 周其焕.欧洲Galileo系统的信号结构和服务性能.全球定位系统,2002,27(1):19～23
[59] Aparicio, J. M., A. Rius, A ray tracing inversion procedure for the extraction of the atmospheric refractivity from GNSS travel-time data. Phys. Chem. Earth, 2004, 29:213～224
[60] Baltink, H. K, et al, Integrated Atmospheric water estimates from a regional GPS nework. J. Geophys. Res., 2002, 107(D3): ACL 3-1～3-8
[61] Basili, P., S. Bonafoni, et al, Atmospheric water vapor retrieval by means of both a GPS network and a microwave radiometer during an experimental campaign in Cagliari, Italy, in 1999. IEEE Transactions On Geoscience and Remote Sensing, 2001, 39(11): 2436～2443
[62] Behrend, D., L. Cucurull, J. Vila, and R. Haas, An inter-comparison study to estimate zenith wet delays using VLBI GPS and NWP models. Earth Planets Space, 2000, 52:691～694
[63] Bevis, M., S. Businger, et al, Remote sensing of atmospheric water vapor using the GPS. J. Geophys. Res., 1992, 970314): 15878～15881
[64] Bevis, M., S. Businger, GPS Meteorology and the International GPS Service, The Preceedings of lGS 95 Workshop, 1995:6～16
[65] Bock, H., U. Hugentobler, T. A. Springer, and G. Beutler, Efficient precise orbit determination of LEO satellites using GPS. Adv. Space Res., 2002, 30(2): 295～300
[66] Bock, O., and E. Doerflinger, Atmospheric modeling in GPS data analysis for high accuracy positioning. Phys. Chem. Earth (A), 2001, 26(6-8): 373～383
[67] Bock, O., E. Doerflinger, F. Masson, A. Walpersdorf, J. Van-Baelen, J. Tarniewicz, M. Troller, A. Somieski, A. Geiger, B. Burki, GPS water vapor project associated to the ESCOMPTE programme: description and first results of the field experiment. Phys. Chem. Earth, 2004, 29:149～157
[68] Bouma, H. R., and B. Stoew, GPS observations of daily variations in the atmospheric water vapor content. Phys. Chem. Earth (A), 2001, 26(6-8): 389～392
[69] Cucurull, L., P. Sed6, D. Behrend, E. Cardellach, A. Rius, Integrating NWP products into the analysis of GPS observables. Phys. Chem. Earth, 2002, 27:377～383
[70] Davis, J. L., Atmospheric water-vapor signals in GPS data: synergies, correlations, signals and errors. Phys. Chem. Earth (A), 2001, 26(6-8): 513～522
[71] Davis, J. L., G. Elgered, The Spatio-temporal structure of GPS water-vaper determination. Phys. Chem. Earth, 1998, 23(1): 91-96
[72] Dick, G., Gerd Gendt, Christoph Reigber, First experience with near real-time water vapor estimation in a German GPS network. J. Atmos. Sol. Terr. Phys., 2001, 63:1295～1304
[73] Dodson, A. H., and H. C. Baker, Accuracy of orbit for GPS atmospheric water vapor estimation. Phys. Chem. Earth, 1998, 23(1): 119～124
[74] Dou_sa, J., Evaluation of tropospheric parameters estimated in various routine GPS analysis. Phys. Chem. Earth, 2004, 29:167～175
[75] Elgered., G., An overview of COST action 716 exploitation of ground-based GPS for climate and numerical weather prediction applications. Phys. Chem. Earth (A), 2001,26(6-8): 399-404
[76] E1osegui, P., J. L. Davis, L. P. Gradinarsky, G. Elgered, J. M. Johansson, D. A. Tahmoush, and A. Rius, Sensing atmospheric structure using small-scale space of geodetic networks. Geophys Res. Lett., 1999,26(16): 2445-2448
[77] Emardson, T. R., G. Elgered, et al, Three months of continuous monitoring of atmospheric water vapor with a network of GPS receivers. J.Geophys.Res., 1998,103(D2): 1807-1820
[78] Engeln, A., S. Buhler, et al, Temperature profile retrieval from surface to mesopause by combining GNSS radio occultation and passive microwave limb sounder data. J. Geophys. Res., 2001, 28(5): 775-778
[79] Feng, D., B. Herman, et al, Preliminary results from the GPS/MET atmospheric remote sensing experiment, The Preceedings of IGS 95 Workshop, 1995:139-143
[80] Fjedbo, G., A. R. Kliore, and V.R.Eshelman, The neutral atmosphere of Venus as studied with the Mariner V radio occultation experiments. Astron. J., 1971,76:123-140
[81] Flores, A., L. P. Gradinarsky, P. Elosegui, G. Elgered, J. L. Davis, and A. Rius, Sensing atmospheric structure:Tropospheric tomographic results of the small-scale GPS campaign at the Onsala Space Observatory. Earth Planets Space, 2000,52:941-945
[82] Foelsche, U., and G. Kirchengast, A new "geometric" mapping function for the hydrostatic delay at GPS frequencies. Phys. Chem. Earth (A), 2001,26(3): 153-157
[83] Foelsche, U., G Kirchengast, Sensitivity of GNSS radio occultation data to horizontal variability in the troposphere. Phys. Chem. Earth, 2004,29: 225-240
[84] Foster, J., M. Bevis, et al, El Nino, water vapor, and the Global Positioning System. Geophys Res. Lett., 2000,27(17): 2697-2700
[85] Galas, R., J. Wiekert and W. Burghardt, High rate low latency gps ground tracking network for CHAMP. Phys. Chem. Earth (A), 2001,26(6-8): 649-652
[86] Gao, B.C., Ed R. Westwater, et al, Comparison of column water vapor measurements using downward-looking near-infrared and infrared imaging systems and upward-looking microwave radiometers, J. Appl. Meteor., 1992:1193-1201
[87] Gavrilov, N. M., N. V. Karpova, Ch. Jacobi, Global distributions of the refraction index variances at different altitudes in the atmosphere from GPS/MET satellite occultation data. Phys. Chem. Earth, 2004, 29: 241-249
[88] Ge, M., E. Calais and J. Haase, Automatic orbit quality control for near real-time GPS zenith
tropospheric delay estimation. Phys. Chem. Earth (A), 2001, 26(3): 177-181
[89] Ge, M., E. Calais, et al, Sensitivity of zenith total delay accuracy to GPS orbit errors and implications for near-real-time GPS meteorology. J. Geophys. Res., 2002,107(D16): ACL 12-1-12-15
[90] Ge, M., E. Calais, J. Haase, Reducing satellite orbit error effects in near real-time GPS zenith tropospheric delay estimation for meteorology. Geophys Res. Lett., 2000,27(13): 1915-1918
[91] Gendt, G., G. Dick, A. Rlus and P. Sedo, Comparision of software and techniques for water vapor estimation using german near real-time GPS data. Phys. Chem. Earth (A), 2001,26(6-8): 417-420
[92] Gorbunov, M. E., An asymptotic method of modeling radio occultations. J. Atmos. Sol. Terr. Phys., 2003,65:1361-1367
[93] Gorbunov, M. E., L. Kornblueh, Analysis and validation of GPS/MET radio occultation data. J. Geophys. Res., 2001,106 (D15): 17161-17169
[94] Guerova, G., J. M. Bettems, E. Brockmann, Ch. Matzler, Assimilation of the GPS-derived integrated water vapour (IWV) in the MeteoSwiss numerical weather prediction model-a first experiment. Phys. Chem. Earth, 2004, 29:177-186
[95] Guldner, J., Validation of integrated water vapor using independent measurement techniques. Phys. Chem. Earth (A), 2001,26(6-8): 427-431
[96] Guo P., F. J. Cai, Z. J. Hong, H. J. Yan, M. Liu, An algorithm for the retrieval of the earth's atmospheric parameters from occultation data of GPS/LEO satellites with non-circular orbits. Chinese Astronomy and Astrophysics, 2004,28: 338- 347
[97] Haase, J. E., Calais, J. Talaya, A. Rius, et al, The contributions of the MAGIC project to the COST 716 objectives of assessing the operational potential of ground-based GPS meteorology on an international scale. Phys. Chem. Earth (A), 2001, 26(6-8): 433-437
[98] Hajj, G A., E. R. Kursinski, L. J. Romans, W. I. Bertiger, S. S. Leroy, A technical description of atmospheric sounding by GPS occultation. J. Atmos. Sol. Terr. Phys., 2002,64: 451-469
[99] Hajj, GA., E. R. Kursinski, et al, Initial results of gps-leo occultation measurements of earth's atmosphere obtained with GPS-MET experiment. The Preceedings of IGS 95 Workshop, 1995: 144-153
[100] Stoew, B., P. Jarlemark, J. Johansson, and G. Elgered, Atmospheric delay estimates from a ground -based real -time GPS Network. ION GPS, 2001,11-14:1079-1083
[101] Hay, C, J. Wong, Enhancing GPS tropospheric delay prediction at the Master Control Station. GPS World, 2000,11(1)
[102] Healy, S. B., Smoothing radio occultation bending angles above 40 km. Annals of Geophysics, 2001b, 19(4): 459-468
[103] Hernandez-Pajares, M., J. M. Juam, J. Sanz, D. Bilitza, Combining GPS measurements and in model values for space weather specification. Adv. Space Res., 2002,29(6): 949~958
[104] Hernandez-Pajares, M., J. M. Juan, J. Sanz, et al, A new strategy for real-time integrated water vapor determination in WADGPS networks. Geophys. Res. Lett., 2001,28(17): 3267-3270
[105] Higgins, M., Progress in 3D-variational assimilation of total zenith delay at the met office. Phys. Chem. Earth (A), 2001,26(6-8): 445-449
[106] Hochegger, G., and R. Leitinger, Model assisted inversion of gnss occultation data. Phys. Chem. Earth (C), 2001,26(5): 325-330
[107] Hocke, K., A. G. Pavelyev, O. I. Yakovlev, L. Barthes, N. Jakowski, Radio occultation data analysis by the radioholographic method.J. Atmos. Sol. Terr. Phys., 1999,61(15): 1169-1177
[108] Hocke, K., and A. G. Pavelyev, General aspect of GPS data use for atmospheric science. Adv. Space Res., 2001,27(6-7): 1313-1320
[109] Hocke, K., and T. Tsuda, Gravity waves and ionospheric irregularities over tropical convection zones observed by GPS/MET radio occultation. Geophys Res. Lett., 2001,28(14): 2815-2818
[110] Hocke, K., and T. Tsuda, Using GPS satellites to study plasma irregularities. GPS World, 2001,12(7): 34-36
[111] Hocke, K., Inversion of GPS meteorology data. Annales Geophysicae, 1997,15:443 -450
[112] Hocke, K., K. Igarashi,M. Nakamura, P. Wilkinson, J. Wu, A. Pavelyev, J. Wickert, Global sounding of sporadic E layers by the GPS/MET radio occultation experiment. J. Atmos. Sol. Terr. Phys., 2001, 63:1973-1980
[113] Huang, C, F. P. Zhang, H. J. Yan, Controls of the sounding points in space-based GPSLEO meteorology.J. Atmos. Sol. Terr. Phys., 2001, 63:1601-1607
[114] Ioltukhovski, A. A., M. Ya. Marov, Spectral remote sensing of the atmosphere by the occultation of stars: Retrieval of the constituents and evaluation of the refraction effect. J. Atmos. Sol. Terr. Phys., 1998,60:1555-1571
[115] Iwabuchi, T., and Isao Naito, Nobutaka Mannoji, A Comparison of Global Positioning System retrieved precipitable water vapor with the numerical weather prediction analysis data over the Japanese islands. J. Geophys. Res., 2000,105(D4): 4573-4585
[116] Iwabuchi, T., Shin'ichi Miyazaki, et al, An impact of estimating tropospheric delay gradients on
tropospheric delay estimations in the summer using the Japanese nationwide GPS array. J. Geophys. Res., 2003,108(D10): ACL 10-1-10-14
[117] Johasson, J. ML, T. R. Emardson, P. O. J. Jarlemark, L. P. Gradinarsky and G. Elgered, The atmospheric influence on the results from the Swedish GPS network. Phys. Chan. Earth, 2001, 23(1): 107-112
[118] Johnsen, K. P., and B. Rockel, Validation of a regional weather forecast model with GPS data. Phys. Chem. Earth (B), 2001, 26(5-6): 415-419
[119] Johnsen, K. P., and B. Rockel, Validation of the NWP model HRM with ground-based GPS data. Phys. Chem. Earth (A), 2001, 26(6-8): 463-466
[120] Johnsen, K. P., J. Miao, S.Q. Kidder, Comparison of atmospheric water vapor over Antarctica derived from CHAMP GPS and AMSU-B data. Phys. Chem. Earth, 2004,29: 251-255
[121] Kunitsyn, V., V. Zakharov, K. Dethloff, A. Weisheimer, M. Gerding, R. Neuber, A. Rinke, I. Hebestadt, Improved radio occultation sounding of the Arctic atmosphere using simulations with a high resolution atmospheric model. Phys. Chem. Earth, 2004, 29:277-286
[122] Kursinski, E. R., and G A. Hajj, A Comparison of water vapor derived from GPS occultations and global weather analyses. 7. Geophys. Res., 2001,106(D1): 1113-1138
[123] Kursinski, E. R., G A. Hajj, K. R. Hardy, J. T. Schofield, R. Linfield, Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System. J. Geophys. Res., 1997, 102(D19): 23429-23465
[124] Lesne, O., J. Haase, G. Kirchengast, J. Ramsauer, W. Poetzi, Sensitivity analysis for airborne sounding of the troposphere by GNSS radio occultation. Phys. Chem. Earth, 2002,27: 291-299
[125] Liu, H., X. Zou, H. Shao, R. A. Anthes, J. C. Chang, J. H. Tseng, and B. Wang, Impact of 837 GPS/MET bending angle profiles on assimilation and forecasts for the period June 20-30,1995. J. Geophys. Res., 2001,106(D23): 31771- 31786
[126] Liu, Y, and Y. Chen, H. Baki lz, Precision of precipitable water vapor from radiosonde data for GPS solutions. Geomatica, 2000,54(2): 171-175
[127] Liu, Y. A., C. Y. Huang, and Y. T. Teng, Precipitable water observed by ground-based GPS receivers and microwave radiometry. Earth Planets Space, 2000,52: 445-450
[128] MacMillan D. S., Atmospheric gradients from very long baseline interferometry observations, Geophys.Res.Lett., 1995, 22(9): 1041-1044,
[129] Marel, H. The COST-716 Team,COST-716 demonstration project for the near real-time estimation of integrated water vapour from GPS. Phys. Chem. Earth, 2004, 29:187-199
[130] Marquardt, C, K. Labitzke, Ch. Reigber, T. Schmidt and J. Wickert, An assessment of the quality of GPS/MET radio limb soundings during February 1997. Phys. Chem. Earth (A), 2001,26(3): 125-130
[131] Mendes, V. B., R .B. Langley, Tropospheric zenith delay prediction accuracy for high-precesion GPS positioning and navigation. Navigation, 1999,46(1): 25-33.
[132] Montenbruck, O., An epoch state filter for use with analytical orbit models of low earth satellites. Aerosp. Sci. Technol, 2000,4: 277-287
[133] Nicholas, A. C, J. M. Picone, S. E. Thonnard, R. R. Meier, K. F. Dymond, D. P. Drob, A methodology for using optimal MSIS parameters retrieved from SSULI data to compute satellite drag on LEO objects. J. Atmos. Sol. Terr. Phys., 2000,62:1317-1326
[134] Ohtani, R., Detection of water vapor variations driven by thermally induced local circulations using the Japanese continuous GPS network. Geophys Res. Lett., 2001,28(1): 151-154
[135] Owens, J. F., Optical infractive index of air: Dependence on pressure, temperature and composition. Appl. Opt., 1967,6:51-52
[136] Pacione, R., C. Sciarretta, F. Vespe, C. Faccani: R. Ferretti, E. Fionda, C. Ferraro and A. Nardi, GPS Meteorology: validation and comparisons with ground-based microwave radiometer and mesoscale model for the Italian GPS permanent stations. Phys. Chem. Earth (A), 2001,26(3): 139-145
[137] Pacione, R., E. Fionda, R. Ferrara, R. Lanotte, C. Sciarretta, F. Vespe, Comparison of atmospheric parameters derived from GPS, VLBI and a ground-based microwave radiometer in Italy. Phys. Chem. Earth, 2002,27:309-316
[138] Palmer, P. I., and J. J. Barnett, J. R. Eyre and S. B. Healy. A nonlinear optimal estimation inverse method for radio occultation measurements of temperature, humidity, and surface pressure. J. Geophys. Res., 2000,150(D13): 17153-17526
[139] Palmer, P. I., and J. J. Barnett, Application of an optimal estimation inverse method to GPS/MET bending angle observations. J. Geophys. Res., 2001,106(D15): 17147-17160
[140] Pany, T., Measuring and modeling the slant wet delay with GPS and the ECMWF NWP model. Phys. Chem. Earth, 2002,27: 347-354
[141] Pany, T., P. Pesec and G. Stangl, Atmospheric GPS slant path delays and ray tracing through numerical weather model. Phys. Chem. Earth (A), 2001, 26(3): 183-188
[142] Pany, T., P. Pesec and G. Stangl, Elimination of tropospheric path delays in GPS observations with the ECMWF numerical weather model. Phys. Chem. Earth (A), 2001, 26(6-8): 487-492
[143] Elosegui, P., A. Ruis, J. L Davis, G. Ruffini, S. J. Keihm, B. Burki and L. P. Kruse, An experiment for estimation of the spatial and temporal variation of water vapor using GPS data. Phys. Chem. Earth, 1998, 23(1): 125～130
[144] Pugnaghi, S., M. Boccolari, S. Fazlagic, R. Pacione, R. Santangelo, H. Vedel, F. Vespe, Comparison of independent integrated water vapour estimates from GPS and sun photometer measurements and a meteorological model. Phys. Chem. Earth, 2002, 27:355～362
[145] Reigber, C., G. Gendt, et al, Near-real-time water vapor monitoring for weather forecasts. GPS World, 2002, 13(1): 18～27
[146] Rhoden, E. A., J. M. Forbes, F. A. Marcos, The infuence of geomagnetic and solar variabilities on lower thermosphere density. J. Atraos. Sol. Terr. Phys., 2000, 62:999～1013
[147] Rocken, C., F. S. Solheim, et al, Application of IGS data to GPS sensing of the atmosphere for weather and climate research, The Preceedings oflGS 95 Workshop, 1995:93～104
[148] Rocken, C., R. Ware, et al, Sensing atmospheric water vapor with GPS, Geophys. Res. Lett., 1993, 20(23): 2631～2634,
[149] Schenewerk, M. S., G. L. Mader, et al, A review of the NOAA Geosciences Lab's automated water vapor project. The Preceedings of IGS 95 Workshop, 1995:104～111
[150] Schmidt, T., J. Wickert, C. Marquardt, G. Beyede, C. Reigber, R. Galas, R. Konig, GPS radio occultation with CHAMP: an innovative remote sensing method of the atmosphere. Advances in Space Research, 2004, 33:1036～1040
[151] Sierk, B., B. Burki, L. P. Kruse, S. Florek, H. Becker-Ross, H. G. Kahle and R. Neubert, A new instrumental approach to water vapor determination based on solar spectroscopy. Phys. Chem. Earth, 1998, 23(1): 113～117
[152] Steiner, A. K, G. Kirchengast, H. P. Ladreiter, Inversion, error analysis, and validation of GPSMET occultation data. Annales Geophysicae, 1999, 17:122～138
[153] Steiner, A. K, G. Kirchengast, U. Foelsche, L. Kornblueh, E. Manzini and L Bengtsson, GNSS occultation sounding for climate monitoring. Phys. Chem. Earth (A), 2001, 26(3): 113～124
[154] Sun, D.Z., R. S. Lindzen, Distribution of tropical tropospheric water vapor, J. Atmos. Sci., 1993: 1643～1659
[155] Tomassini, M., G. Gendt, G. Dick, M. Ramatschi, C. Schraff, Monitoring of Integrated Water Vapour from ground-based GPS observations and their assimilation in a limited-area NWP model. Phys. Chem. Earth, 2002, 27:341～346
[156] Tsuda, T., K. Heki, S. Miyazaki, K. Aonashi, K. Hirahara, H. Nakamura, M. Tobita, F. Kimata, T. Tabei, T. Matsushima, F. Kimura, M. Satomura, T. Kato, and I. Naito, GPS meteorology project of Japan - Exploring frontiers of geodesy. Earth Planets Space, 1998,50(10): i~v
[157] Vespe , F., C. Benedetto, R. Pacione, The use of refractivity retrieved by radio occultation technique for the derivation of atmospheric water vapor content. Phys. Chem. Earth, 2004,29:257~265
[158] Vorob'ev, V.V., and T.G. Krasil'nikova, Estimation of the accuracy of the atmospheric refractive index recovery from Doppler shift measurements at frequencies used in the NAVSTAR system. Phys. Atmos. Ocean, 1994,29: 602-609.
[159] Walpersdorf, A., E. Calais, J. Haase, L. Eymard, M. Desbois and H. Vedel. Atmospheric gradients estimated by GPS compared to a high resolution Numerical Weather Prediction (NWP) model. Phys. Chem. Earth (A), 2001,26(3): 147-152
[160] Ware, R., C. Alber, C. Rocken, F. Solheim, Sensing integrated water vapor along GPS ray paths. Geophys Res. Lett., 1997,24: 417-420
[161] Ware, R., C. Rocken, et al, Pointed water vapor radiometer corrections for accurate global positioning system surveying. Geophys Res. Lett., 1993,20(23): 2635-2638,
[162] Ware, R., D. W. Fulker, S. A. Stein, D. N. Anderson, S. K. Avery, R. D. Clark, K. K. Droegemeier, J. P. Kuettner, J. B. Minster, S. Sorooshian, Real-time national GPS networks for atmospheric sensing. J. Atmos. Sol. Terr. Phys., 2001, 63:1315-1330
[163] Webley, P. W., R. M. Bingley, A. H. Dodson, G. Wadge, S. J. Waugh, I. N. James, Atmospheric water vapour correction to InSAR surface motion measurements on mountains: results from a dense GPS network on Mount Etna. Phys. Chem. Earth, 2002, 27:363-370
[164] Wickert, J., C. Reigber, et al, Atmosphere sounding by GPS radio occultation: First results from CHAMP. Geophys Res. Lett., 2001,28(17): 3263-3266
[165] Wickert, J., R. Galas, G. Beyerle, R. Konig and C. Reigber, GPS Ground station data for CHAMP radio occultation measurements. Phys. Chem. Earth (A), 2001, 26(6-8): 503-511
[166] Wickert, J., R. Galas, T. Schmidt, G. Beyerle, C. Reigber, C. Forste, M. Ramatschi, Atmospheric sounding with CHAMP: GPS ground station data for occultation processing. Phys. Chem. Earth, 2004, 29: 267-275
[167] Yuan, L. L., R. A. Anthes, et al, Sensing climate change using the GPS. J. Geophys. Res., 1993, 98(D8): 14925-14937
[168] Yunck, T. P., G. A. Hajj, E. R. Kursinski, J. A. LaBrecque, S. T. Lowe, M. M. Watkins, C. M.
Cormick, AMORE: An autotonomous constellation concept for atmospheric and ocean observation. Acta Astronautica, 2000,46(2-6): 355 -364
[169] Zou, X., F. Vandenberghe, B. Wang, M. E. Gorbunov, Y. H. Kuo, S. Sokolovskiy, J. C. Chang, J. G. Sela, R. A. Anthes, A ray tracing operator and its adjomt for the use of GPS/MET refraction angle measurements.J. Geophys. Res., 1999,104(D18): 22301-22318
[170] Zou, X., B.Wang, H. Liu, R. A. Anthes, T. Matsumura, Y. J. Zhu, Use of GPS/MET refraction angles in three-dimensional variational analysis. QJ.R.Meteorol.Soc, 2000,126: 3013-3040