GPS资料在中尺度数值预报模式中的应用研究
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摘要
利用建立在长江三角洲地区GPS观测网中GPS资料，针对2002年梅雨期间影响长江三角洲地区的降水过程进行了GPS资料在MM5中尺度数值预报模式中的应用研究。研究表明：
1、GPS是一种连续监测大气水汽的有效手段。与常规探空观测相比，GPS测量的可降水量有很好的代表性。在相距2km时，两种测量手段测量可降水量和总延迟量的平均绝对偏差分别为2.13mm和1.28cm。总延迟的变化主要是由湿延迟的变化而引起，其中静力延迟变化呈现了明显的周期性，而湿延迟的变化与天气过程相关联。通过可降水量、总延迟和湿延迟的时、空变化可以分析天气系统演变。应用MM5模式预报结果计算大气平均温度可提高GPS可降水量的反演精度。
2、MM5模式初始场对静力延迟有较好的描述能力，但对湿延迟和可降水量的描述还存在比静力延迟更大的描述误差。MM5模式连续滚动预报(12h)基本能反映总延迟、静力延迟、湿延迟和可降水量的日际变化趋势，但对这些量逐时预报还存在误差。MM5模式对湿延迟的预报能力明显低于对静力延迟的预报能力，并且模式对总延迟的预报误差主要是由湿延迟预报误差产生的。MM5模式分辨率的提高有利于改善模式对静力延迟、湿延迟和可降水量的描述和预报。
MM5模式对可降水量的预报能力与积云参数化方案的选用有关。在MM5模式24h积分的前10～11h，选用KF、BM和Grell三种积云参数化方案模式对可降水量的预报偏差基本接近，对可降水量具有较好的预报能力，其后三种积云参数化方案对可降水量的预报偏差差异增大，模式积分至20～21h后对可降水量的预报能力明显减小。对模式粗网格，Grell方案总体上表现了最高的可降水量预报能力。对模式细网格，Grell和KF方案比BM方案表现了较高的可降水量预报能力。
3、用GPS测量的可降水量资料调整MM5模式湿度初始场可明显增强模式初始场描述水汽分布的能力，使其对可降水量的描述误差明显减小，有利于模式初始场更好地反映出水汽分布的局地特征，从而有效地控制模式积分初期对可降水量的预报误差。GPS可降水量资料的Nudging同化对可降水量预报改善较小，
并且Nudging系数的增加对可降水量预报效果的改善程度影响不大。用GPs资
料调整模式湿度初始场对预报6h累积降水量的改善主要是通过改善模式网格尺
度降水预报来实现的，GPS可降水量资料Nudging同化主要通过改善次网格尺度
降水预报来实现6h累计降水预报能力提高的。总体上，应用GPS可降水量资料
调整模式湿度初始场对6h累积降水预报效果的改善优于连续Nudg ing同化对6h
累积降水预报效果的改善。
4、背景误差对三维变分同化效果起着关键作用，使用NMC方法重新构建
的背景误差更接近实际背景误差。模式变量(。、、、T、p和q)对应的误差水平
尺度与NMC方法中预报误差的平均时间长度和模式提供1 Zh和24h预报所选用
的积云参数化方案有直接的关系。不同模式变量的误差水平尺度存在差异，并且
同一模式变量的误差水平尺度在模式不同的高度层也存在差异。
5、用三维变分技术能有效地同化GPS可降水量资料。GPS可降水量资料的
同化不仅能调整MMS模式湿度初始场，而且使模式初始气压、温度和风场也能
得到相应的调整.在模式积分的前6小时，Cressman客观分析试验对累计降水
量预报优于GPs可降水量资料三维变分同化试验对累积降水量预报，但在模式
积分的6一18小时GPS可降水量三维变分同化试验对累计降水的预报却优于
cressman客观分析试验。总体上，GPs可降水量资料的同化有利于模式降水预
报能力的提高。
6、GPS湿延迟量资料的三维变分同化比GPs可降水量资料同化更容易将GPS
对大气的监测信息传递给MMS模式初始场，使得对模式初始湿度、温度、气压
和风场的调整程度大于GPs可降水量资料同化对模式初始要素场的调整.尽管湿
延迟量资料同化对6h累计降水预报的改善在不同的降水等级表现了不同效果，
但总体上湿延迟量资料同化对6h累计降水预报的改善程度要高于可降水量资料
变分同化。
The GPS data from GPS networks in Yangtze delta is explored to investigate the improvement of MM5 simulation on rainfall event occurred over Meiyu period in 2002 with the aid of initial humidity fields reanalysis and assimulation. The results show:
1, GPS is a valuable tool of observing water vapor in atmosphere consecutively. GPS observation which is about 2km far away from radiosonde site is comparable to radiosonde with a absolute bias of 2.13mm on precipitable water (PW) observation and 1.28cm on zenith total delay (ZTD). The variation of ZTD is mainly caused by the zenith wet delay (ZWD). zenith hydrostatic delay (ZHD) and ZWD from different GPS sites exhibit individual features that ZHD has a obvious periodic change and ZWD is related to weather. Accuracy of PW retrieved from GPS observation can be improved by using the average vertical temperature calculated from MM5 outputs.
2. The reanalysis fields of MM5 can reveal the distribution of ZHD as a whole and has larger bias on ZWD and PW than ZTD. 12h-simulation of MM5 can show the daily change tendency of ZTD, ZHD, ZWD and PW with a bias in depicting their hourly change. MM5 has a ability of simulating ZWD on the whole with a bias larger than ZHD's, which manipulates the bias of ZTD simulation. The increase of MM5 resolution can improve the ability of simulating and depicting ZHD, ZWD and PW distribution.
KF, BM and Grell parametric schemes have a close ability of simulating PW at the beginning of 10-11h integration of MM5 model, and then the prediction bias of PW increases obviously after 20-21h integration. Grell scheme can simulate PW more accurate than others for coarse grid of MM5 and PW simulation of BM scheme is less accurate than others for fine grid of MM5.
3, The initial humidity fields reanalyzed by using GPS PW can obviously improve its capability in revealing the water vapor distribution, which can result in restraining PW prediction bias during the earlier period of model integration so as to improve PW prediction. Nudging assimulation of PW can improve prediction slightly, and increasing nudging gain coefficient play a little role in improving prediction. It's
also found that the reanalysis influences the results of 6h accumulated precipitation through changing the non-convective precipitation prediction mainly, while results improved by the nudging assimulation are substantially associated with convective precipitation change. On the whole, better results are obtained by the reanalysis than by the nudging assimulation.
4, Background errors (BE) play a key role in three dimensional variation assimulation (3dvar). The BE calculated by NMC technique reach the true BE more closely than that provided by MM5-3dvar system. The horizontal scalelength of model variables (u. v. T, p and q) is closely related to the average time of NMC technique and convective parameteric scheme of MM5 which affect the 12h and 24h outputs of MM5 integration. The scalelength of model variables is different for each other, which value is associated with the vertical height of the variable on the MM5 level.
5, GPS PW data can be assimulated into MM5 by using 3dvar technique. After GPS PW data assimulation, the initial humidity field can be reanalyzed while the initial temperature, pressure and wind fields also being modified. Although MM5 with the Cressman objective analysis predicts the first 6h accumulated precipitation more accurately than 3dvar of GPS PW data, vice versa for 6-18 h accumulated precipitation. On the whole, GPS PW data assimulation will improve precipitation prediction.
6, GPS ZWD assimulation ingests atmospheric information observed by GPS into MM5 initial fields more easily than GPS PW assimulation so that the initial fields of humidity, temperature, pressure and wind can be modified in a greater degree. In general, 6h accumulated rainfall prediction of MM5 is improved by 3dvar of GPS ZWD data more significantly than GPS PW data although the former improvement is related to the rainfall amount.
1、GPS是一种连续监测大气水汽的有效手段。与常规探空观测相比，GPS测量的可降水量有很好的代表性。在相距2km时，两种测量手段测量可降水量和总延迟量的平均绝对偏差分别为2.13mm和1.28cm。总延迟的变化主要是由湿延迟的变化而引起，其中静力延迟变化呈现了明显的周期性，而湿延迟的变化与天气过程相关联。通过可降水量、总延迟和湿延迟的时、空变化可以分析天气系统演变。应用MM5模式预报结果计算大气平均温度可提高GPS可降水量的反演精度。
2、MM5模式初始场对静力延迟有较好的描述能力，但对湿延迟和可降水量的描述还存在比静力延迟更大的描述误差。MM5模式连续滚动预报(12h)基本能反映总延迟、静力延迟、湿延迟和可降水量的日际变化趋势，但对这些量逐时预报还存在误差。MM5模式对湿延迟的预报能力明显低于对静力延迟的预报能力，并且模式对总延迟的预报误差主要是由湿延迟预报误差产生的。MM5模式分辨率的提高有利于改善模式对静力延迟、湿延迟和可降水量的描述和预报。
MM5模式对可降水量的预报能力与积云参数化方案的选用有关。在MM5模式24h积分的前10～11h，选用KF、BM和Grell三种积云参数化方案模式对可降水量的预报偏差基本接近，对可降水量具有较好的预报能力，其后三种积云参数化方案对可降水量的预报偏差差异增大，模式积分至20～21h后对可降水量的预报能力明显减小。对模式粗网格，Grell方案总体上表现了最高的可降水量预报能力。对模式细网格，Grell和KF方案比BM方案表现了较高的可降水量预报能力。
3、用GPS测量的可降水量资料调整MM5模式湿度初始场可明显增强模式初始场描述水汽分布的能力，使其对可降水量的描述误差明显减小，有利于模式初始场更好地反映出水汽分布的局地特征，从而有效地控制模式积分初期对可降水量的预报误差。GPS可降水量资料的Nudging同化对可降水量预报改善较小，
并且Nudging系数的增加对可降水量预报效果的改善程度影响不大。用GPs资
料调整模式湿度初始场对预报6h累积降水量的改善主要是通过改善模式网格尺
度降水预报来实现的，GPS可降水量资料Nudging同化主要通过改善次网格尺度
降水预报来实现6h累计降水预报能力提高的。总体上，应用GPS可降水量资料
调整模式湿度初始场对6h累积降水预报效果的改善优于连续Nudg ing同化对6h
累积降水预报效果的改善。
4、背景误差对三维变分同化效果起着关键作用，使用NMC方法重新构建
的背景误差更接近实际背景误差。模式变量(。、、、T、p和q)对应的误差水平
尺度与NMC方法中预报误差的平均时间长度和模式提供1 Zh和24h预报所选用
的积云参数化方案有直接的关系。不同模式变量的误差水平尺度存在差异，并且
同一模式变量的误差水平尺度在模式不同的高度层也存在差异。
5、用三维变分技术能有效地同化GPS可降水量资料。GPS可降水量资料的
同化不仅能调整MMS模式湿度初始场，而且使模式初始气压、温度和风场也能
得到相应的调整.在模式积分的前6小时，Cressman客观分析试验对累计降水
量预报优于GPs可降水量资料三维变分同化试验对累积降水量预报，但在模式
积分的6一18小时GPS可降水量三维变分同化试验对累计降水的预报却优于
cressman客观分析试验。总体上，GPs可降水量资料的同化有利于模式降水预
报能力的提高。
6、GPS湿延迟量资料的三维变分同化比GPs可降水量资料同化更容易将GPS
对大气的监测信息传递给MMS模式初始场，使得对模式初始湿度、温度、气压
和风场的调整程度大于GPs可降水量资料同化对模式初始要素场的调整.尽管湿
延迟量资料同化对6h累计降水预报的改善在不同的降水等级表现了不同效果，
但总体上湿延迟量资料同化对6h累计降水预报的改善程度要高于可降水量资料
变分同化。
The GPS data from GPS networks in Yangtze delta is explored to investigate the improvement of MM5 simulation on rainfall event occurred over Meiyu period in 2002 with the aid of initial humidity fields reanalysis and assimulation. The results show:
1, GPS is a valuable tool of observing water vapor in atmosphere consecutively. GPS observation which is about 2km far away from radiosonde site is comparable to radiosonde with a absolute bias of 2.13mm on precipitable water (PW) observation and 1.28cm on zenith total delay (ZTD). The variation of ZTD is mainly caused by the zenith wet delay (ZWD). zenith hydrostatic delay (ZHD) and ZWD from different GPS sites exhibit individual features that ZHD has a obvious periodic change and ZWD is related to weather. Accuracy of PW retrieved from GPS observation can be improved by using the average vertical temperature calculated from MM5 outputs.
2. The reanalysis fields of MM5 can reveal the distribution of ZHD as a whole and has larger bias on ZWD and PW than ZTD. 12h-simulation of MM5 can show the daily change tendency of ZTD, ZHD, ZWD and PW with a bias in depicting their hourly change. MM5 has a ability of simulating ZWD on the whole with a bias larger than ZHD's, which manipulates the bias of ZTD simulation. The increase of MM5 resolution can improve the ability of simulating and depicting ZHD, ZWD and PW distribution.
KF, BM and Grell parametric schemes have a close ability of simulating PW at the beginning of 10-11h integration of MM5 model, and then the prediction bias of PW increases obviously after 20-21h integration. Grell scheme can simulate PW more accurate than others for coarse grid of MM5 and PW simulation of BM scheme is less accurate than others for fine grid of MM5.
3, The initial humidity fields reanalyzed by using GPS PW can obviously improve its capability in revealing the water vapor distribution, which can result in restraining PW prediction bias during the earlier period of model integration so as to improve PW prediction. Nudging assimulation of PW can improve prediction slightly, and increasing nudging gain coefficient play a little role in improving prediction. It's
also found that the reanalysis influences the results of 6h accumulated precipitation through changing the non-convective precipitation prediction mainly, while results improved by the nudging assimulation are substantially associated with convective precipitation change. On the whole, better results are obtained by the reanalysis than by the nudging assimulation.
4, Background errors (BE) play a key role in three dimensional variation assimulation (3dvar). The BE calculated by NMC technique reach the true BE more closely than that provided by MM5-3dvar system. The horizontal scalelength of model variables (u. v. T, p and q) is closely related to the average time of NMC technique and convective parameteric scheme of MM5 which affect the 12h and 24h outputs of MM5 integration. The scalelength of model variables is different for each other, which value is associated with the vertical height of the variable on the MM5 level.
5, GPS PW data can be assimulated into MM5 by using 3dvar technique. After GPS PW data assimulation, the initial humidity field can be reanalyzed while the initial temperature, pressure and wind fields also being modified. Although MM5 with the Cressman objective analysis predicts the first 6h accumulated precipitation more accurately than 3dvar of GPS PW data, vice versa for 6-18 h accumulated precipitation. On the whole, GPS PW data assimulation will improve precipitation prediction.
6, GPS ZWD assimulation ingests atmospheric information observed by GPS into MM5 initial fields more easily than GPS PW assimulation so that the initial fields of humidity, temperature, pressure and wind can be modified in a greater degree. In general, 6h accumulated rainfall prediction of MM5 is improved by 3dvar of GPS ZWD data more significantly than GPS PW data although the former improvement is related to the rainfall amount.
引文
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李延兴、徐宝祥、胡新康、何平、黄永详，用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果，中国科学(A辑)，2000，30，107～110．
李延兴、徐宝祥、胡新康、何平，应用地基GPS技术遥感大气拄水汽量的试验研究，应用气象学报，2001，12，61～69．
李延兴、徐宝祥、胡新康、何平、黄永祥，用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果，中国科学(A辑)，2002，30，107～110．
刘志赵、刘经南、刘征航，GPS技术在气象学中的应用，测绘通报，2000，(2)，7～8。
刘志权、方宗义、徐建平、夏青，探测大气参数的GPS／MET方法，气象科技，1996，(2)，1～9．
刘焱雄、H B Iz、陈永奇，地基GPS技术遥感香港地区大气水汽含量，武汉测绘科技大学学报，1999，24，245～248．
金双根、朱文耀，GPS气象学应用进展及其监测分析实例，自然杂志，2002，24，99～103．
Kopken, C., Validation of Integrated Water Vapor from Numerical Models Using Ground-Based GPS, SSM/I, and Water Vapor Radiometer Measurements, J. Appl. Meteor., 2001, 40, 1105～1117.
Kuo, Y.-H., Y.-R. Guo, and E. R. Westwater, Assimilation of precipitable water vapor into mesoscale numerical model, Mon. Wea. Rev., 1993, 121, 1215～1238.
Kuo, Y.-H., X. Zou, and Y.-R. Guo, Variational assimilation of precipitable water using a nonhydrostatic mesoscale adjoint model, Mon. Wea. Rev., 1996, 124, 122～147.
MacDonald, A. and Y., Xie, Diagnosis of Three-Dimension Water Vapor Using a GPS Network, Mon. Wea. Rev., 2002, 130, 386～397.
MacDonald, A. E., Y. Xie, and R. H. Ware, Diagnosis of Three-Dimensional Water Vapor Using a GPS Network, Mon. Wea. Rev., 2002, 130, 386～397.
Mazany, R. A., S. Businger, A. I. Gutman, and W. Roeder, A Lighting Prediction Index that Utilizes GPS Integerated Precipitable Water Vapor, Weather and
Forecasting, 2002, 17, 1034～1047.
Niell, A. E., Improved atmospheric mapping functions for VLBI and GPS, Earth Planets Space, 2001, 52, 699～702.
Niell, A. E., A. J. Coster, F. S. Solheim, V. B. Mendes, P. C. Toor, P. B. Langley, and C. A. Upham, Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water vapor Radiometer, GPS and VLBI, J. Atmos. And Oceanic Technol., 2001, 18, 830～850.
Park, S., and K. Droegemeier, Sensitivity of 3-D convective storm evolution to water vapor and implications for variational data assimilation. Preprints, 11~(th) Conf. On Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 1996, 137～139.
曲建光、吴壮，从GPS推算大气水汽的误差分析，测绘工程，2002，10，24～26．
Rocken, C., J. Johnson, R. Neilan, M. Cerezo, J. Jordan, M. Falls, L. Nelson, R. Ware, and M. Hayes, The Measurement of Atmospheric Water Vapor: Radiometer Comprison and Spatial Variations, IEEE Trans. Geosci. & Remote Sensing, 1991a, 29, 3～8.
Rocken, C., R. Ware, T. Van Hove, F. Solheim, C. Alber, and J. Johnson, Sensing atmospheric water vapor with the global positioning system, Geophys. Res. Lett., 1993, 20, 468～478.
Rocken, C., T. Van Hove, J. Johnson, F. Johnson, F. Solheim, R. Ware, M. Bevis, S. Chiswell, and S. Businger, GPS/STORM—GPS sensing of atmospheric water vapor for meteorology, J. Atmos. Ocean. Technol., 1995, 12, 468～478.
Rocken, C., S. Sokolovskiy, J. M. Johnson, and D. Hunt, lmproved Mapping of Tropospheric Delays, J, Atmos. And Oceanic Technol., 2001, 18, 1205～1213.
Smith, T., S. G Benjamin, S. I. Gulman, and B. E. Schwartz, Impact of GPS Water Vapor Data on RUC severe Weather Forecasts, 2002, Preprints. 21~(st) Conf on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., J43～J46.
Solheim, F. S., J. Vivekanandan, R. H. Ware, and C. Rocken, Propagation Delays Induced in GPS signals by Dry Air, Water Vapor, Hydrometeors and Other
Particulates, J. Geophys. Res., 1999, 104, 9663～9670.
Spilker, J. T., 1980: Signal structure and performance characteristics. Global Positioning System, 1980, Vol. 1, The Institute of Navigation, 246.
Stevens, M., Optimal climate signal detection in four dimensions, J. Geophys. Res., 1999, 104, 4089～4099.
Thayer, D., An improved equation for the radio refractive index of air, Radio Sci., 1974, 9, 803～807.
Tomassini, M., G Gendt, G. Dick, M. Ramatschi, and C. Schraff, Monitoring of Integrated water vapor from ground-based GPS observations and their assimilation in a limited-area NWP model, Phy. Chem. Earth(A), 2002, 27, 341～346.
Tralli, D. M., T. H. Dixon, and S. A. Stephens, Effect of wet tropospheric path delays on estimation of geodetic baselines in the Gulf of California using the global positioning system, J. Geophys Res., 1988, 93, 6545～6557.
Tralli, D. M., and S. M. Lichten, Stochastic estimation of tropospheric path delays in global positioning system geodetic measurements, Bull. Geod., 1990, 64, 127～159.
Tregoning, P. R. Boers, D. O'Brien, and M. Hendy, Accuracy of absolute precipitable water vapor estimates from GPS observartions, J. Geophys. Res., 1998, 103, 28701～28710.
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，1997，12，519～527．
王小亚、朱文耀、严豪健、陈宗颐、丁金才，地面GPS探测大气可降水量的初步结果，大气科学，1999，23，605～612．
Ware, R., C. Alber, C. Rocken, and F. Solheim, Sensing integrated water vapor along GPS ray paths, Geophys. Res. Lett., 1997, 24, 417～420.
Ware, R., F. David and S. Seth, SuomiNet: A Real-Time National GPS Network for Atmospheric Research and Education, Mon. Wea. Rev., 2000, 81,677～694.
徐晓华、李征航，GPS 气象学研究的最新进展，黑龙江工程学院学报，2002，
16，14～18．
许华冠，GPS资料分析中大气折射水平梯度的估计，中国科学院上海天文台年刊，1999，(20)，84～90．
熊永清，利用地面 GPS 技术绝对测定湿大气含量的可能性，气象学报，1999，57，632～639．
杨红梅、徐宝祥、周秀骥，GPS 资料在天气分析中的应用，气象科技，2000，4，32～37．
杨红梅、何平、徐宝祥．利用 GPS 资料分析华南暴雨的水汽特征，气象，2002，28(5)，17～21．
杨光林、刘晶淼、毛节泰，西藏地区水汽GPS遥感分析，气象科技，2002，30，266～272．
Yang, X-H., B. H. Sass, G. Elgered, J. M. Johansson, and T. R. Emardson, A Comparison of Precipitable Water Vapor Estimates by an NWP Simulation and GPS Observations, J. Appl. Meteor., 1999, 38, 941～956.
Yuan, L., R. A. Anthes, R. H. Ware, C. Rocken, W. D. Bonner, M. Bevis, and S. Businger, Sensing climate change using the Global Positioning System, J. Geophys. Res., 1993, 98, 14925～14937.
Yuan, X., B. H. Sass, G. Elgered, J. M. Johansson, and T. R. Emardson, A Comparison of Precipitatable Water Vapor Estimates by an NWP Simulation and GPS Observation, J. Appl. Meteor., 1999, 38, 941～956.
张晋、张阿丽，GPS 观测在气象中的应用，新疆气象，2002，25，21～23．
Bevis, M., S. Businger, S.R. Chiswell, T.A.Herring, R.A. Anthes, C. Rocken, and R.H. Ware, GPS meteorology: Mapping zenith wet delays onto precipitable water, J. Appl. Meteor., 1994, 33, 379～386.
Businger, S., S. R. Chiswell, M. Bevis, J.-P. Duan, R. A. Anthes, C. Rocken, R. H. Ware, M. Exner, T. Vanhove, and F. S. Solheim, The Promise of GPS in Atmospheric Monitoring, Bull. Amer. Meteor. Soc., 1996, 77, 5～18.
陈洪滨、吕达仁，GPS测量中的大气路径延迟订正，测绘学报，1996，25(2)，127～132．
陈世范，GPS气象观测应用的研究进展与展望，气象学报，1999，57，242～252．
陈俊勇，地基GPS遥感大气水汽含量的误差分析，测绘学报，1998，27，113～118．
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，2002，14，136～144．
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丁继新、成英燕、王权、党亚民，利用GPs技术遥感大气对流层水汽含量的研究，测绘科学，2002，27，16～19．
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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实验，应用气象学报，2002，13(2)，179～183．
Iwabuchi, T., I. Natio, and N. Mannoji, A comparison of global positioning system retrieved precipitable water vapor with numeric weather prediction analysis data over Japanese Island, J. Geophys. Res., 2000, 105, 4573～4585.
Liou, Y.-A., and C.-Y. Huang, GPS observations of PW during the passage of a typhoon, Earth Planets Space, 2000, 52, 709～712.
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李成才、毛节泰，GPS 地基遥感大气水汽分析，应用气象学报，1998，9(4)，
470～477．
李延兴、徐宝祥、胡新康、何平、黄永详，用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果，中国科学(A辑)，2000，30，107～110．
李延兴、徐宝祥、胡新康、何平，应用地基GPS技术遥感大气拄水汽量的试验研究，应用气象学报，2001，12，61～69．
李延兴、徐宝祥、胡新康、何平、黄永祥，用地基GPS观测站遥测大气含水量和可降雨量的理论基础与试验结果，中国科学(A辑)，2002，30，107～110．
刘志赵、刘经南、刘征航，GPS技术在气象学中的应用，测绘通报，2000，(2)，7～8。
刘志权、方宗义、徐建平、夏青，探测大气参数的GPS／MET方法，气象科技，1996，(2)，1～9．
刘焱雄、H B Iz、陈永奇，地基GPS技术遥感香港地区大气水汽含量，武汉测绘科技大学学报，1999，24，245～248．
金双根、朱文耀，GPS气象学应用进展及其监测分析实例，自然杂志，2002，24，99～103．
Kopken, C., Validation of Integrated Water Vapor from Numerical Models Using Ground-Based GPS, SSM/I, and Water Vapor Radiometer Measurements, J. Appl. Meteor., 2001, 40, 1105～1117.
Kuo, Y.-H., Y.-R. Guo, and E. R. Westwater, Assimilation of precipitable water vapor into mesoscale numerical model, Mon. Wea. Rev., 1993, 121, 1215～1238.
Kuo, Y.-H., X. Zou, and Y.-R. Guo, Variational assimilation of precipitable water using a nonhydrostatic mesoscale adjoint model, Mon. Wea. Rev., 1996, 124, 122～147.
MacDonald, A. and Y., Xie, Diagnosis of Three-Dimension Water Vapor Using a GPS Network, Mon. Wea. Rev., 2002, 130, 386～397.
MacDonald, A. E., Y. Xie, and R. H. Ware, Diagnosis of Three-Dimensional Water Vapor Using a GPS Network, Mon. Wea. Rev., 2002, 130, 386～397.
Mazany, R. A., S. Businger, A. I. Gutman, and W. Roeder, A Lighting Prediction Index that Utilizes GPS Integerated Precipitable Water Vapor, Weather and
Forecasting, 2002, 17, 1034～1047.
Niell, A. E., Improved atmospheric mapping functions for VLBI and GPS, Earth Planets Space, 2001, 52, 699～702.
Niell, A. E., A. J. Coster, F. S. Solheim, V. B. Mendes, P. C. Toor, P. B. Langley, and C. A. Upham, Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water vapor Radiometer, GPS and VLBI, J. Atmos. And Oceanic Technol., 2001, 18, 830～850.
Park, S., and K. Droegemeier, Sensitivity of 3-D convective storm evolution to water vapor and implications for variational data assimilation. Preprints, 11~(th) Conf. On Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 1996, 137～139.
曲建光、吴壮，从GPS推算大气水汽的误差分析，测绘工程，2002，10，24～26．
Rocken, C., J. Johnson, R. Neilan, M. Cerezo, J. Jordan, M. Falls, L. Nelson, R. Ware, and M. Hayes, The Measurement of Atmospheric Water Vapor: Radiometer Comprison and Spatial Variations, IEEE Trans. Geosci. & Remote Sensing, 1991a, 29, 3～8.
Rocken, C., R. Ware, T. Van Hove, F. Solheim, C. Alber, and J. Johnson, Sensing atmospheric water vapor with the global positioning system, Geophys. Res. Lett., 1993, 20, 468～478.
Rocken, C., T. Van Hove, J. Johnson, F. Johnson, F. Solheim, R. Ware, M. Bevis, S. Chiswell, and S. Businger, GPS/STORM—GPS sensing of atmospheric water vapor for meteorology, J. Atmos. Ocean. Technol., 1995, 12, 468～478.
Rocken, C., S. Sokolovskiy, J. M. Johnson, and D. Hunt, lmproved Mapping of Tropospheric Delays, J, Atmos. And Oceanic Technol., 2001, 18, 1205～1213.
Smith, T., S. G Benjamin, S. I. Gulman, and B. E. Schwartz, Impact of GPS Water Vapor Data on RUC severe Weather Forecasts, 2002, Preprints. 21~(st) Conf on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., J43～J46.
Solheim, F. S., J. Vivekanandan, R. H. Ware, and C. Rocken, Propagation Delays Induced in GPS signals by Dry Air, Water Vapor, Hydrometeors and Other
Particulates, J. Geophys. Res., 1999, 104, 9663～9670.
Spilker, J. T., 1980: Signal structure and performance characteristics. Global Positioning System, 1980, Vol. 1, The Institute of Navigation, 246.
Stevens, M., Optimal climate signal detection in four dimensions, J. Geophys. Res., 1999, 104, 4089～4099.
Thayer, D., An improved equation for the radio refractive index of air, Radio Sci., 1974, 9, 803～807.
Tomassini, M., G Gendt, G. Dick, M. Ramatschi, and C. Schraff, Monitoring of Integrated water vapor from ground-based GPS observations and their assimilation in a limited-area NWP model, Phy. Chem. Earth(A), 2002, 27, 341～346.
Tralli, D. M., T. H. Dixon, and S. A. Stephens, Effect of wet tropospheric path delays on estimation of geodetic baselines in the Gulf of California using the global positioning system, J. Geophys Res., 1988, 93, 6545～6557.
Tralli, D. M., and S. M. Lichten, Stochastic estimation of tropospheric path delays in global positioning system geodetic measurements, Bull. Geod., 1990, 64, 127～159.
Tregoning, P. R. Boers, D. O'Brien, and M. Hendy, Accuracy of absolute precipitable water vapor estimates from GPS observartions, J. Geophys. Res., 1998, 103, 28701～28710.
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，1997，12，519～527．
王小亚、朱文耀、严豪健、陈宗颐、丁金才，地面GPS探测大气可降水量的初步结果，大气科学，1999，23，605～612．
Ware, R., C. Alber, C. Rocken, and F. Solheim, Sensing integrated water vapor along GPS ray paths, Geophys. Res. Lett., 1997, 24, 417～420.
Ware, R., F. David and S. Seth, SuomiNet: A Real-Time National GPS Network for Atmospheric Research and Education, Mon. Wea. Rev., 2000, 81,677～694.
徐晓华、李征航，GPS 气象学研究的最新进展，黑龙江工程学院学报，2002，
16，14～18．
许华冠，GPS资料分析中大气折射水平梯度的估计，中国科学院上海天文台年刊，1999，(20)，84～90．
熊永清，利用地面 GPS 技术绝对测定湿大气含量的可能性，气象学报，1999，57，632～639．
杨红梅、徐宝祥、周秀骥，GPS 资料在天气分析中的应用，气象科技，2000，4，32～37．
杨红梅、何平、徐宝祥．利用 GPS 资料分析华南暴雨的水汽特征，气象，2002，28(5)，17～21．
杨光林、刘晶淼、毛节泰，西藏地区水汽GPS遥感分析，气象科技，2002，30，266～272．
Yang, X-H., B. H. Sass, G. Elgered, J. M. Johansson, and T. R. Emardson, A Comparison of Precipitable Water Vapor Estimates by an NWP Simulation and GPS Observations, J. Appl. Meteor., 1999, 38, 941～956.
Yuan, L., R. A. Anthes, R. H. Ware, C. Rocken, W. D. Bonner, M. Bevis, and S. Businger, Sensing climate change using the Global Positioning System, J. Geophys. Res., 1993, 98, 14925～14937.
Yuan, X., B. H. Sass, G. Elgered, J. M. Johansson, and T. R. Emardson, A Comparison of Precipitatable Water Vapor Estimates by an NWP Simulation and GPS Observation, J. Appl. Meteor., 1999, 38, 941～956.
张晋、张阿丽，GPS 观测在气象中的应用，新疆气象，2002，25，21～23．