• Askne, J., and H. Nordius, 1987: Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci., 22, 379386, https://doi.org/10.1029/RS022i003p00379.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berrada Baby, H. B., P. Golé, and J. Lavergnat, 1988: A model for the tropospheric excess path length of radio waves from surface meteorological measurements. Radio Sci., 23, 10231038, https://doi.org/10.1029/RS023i006p01023.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bevis, M., S. Businger, T. Herring, C. Rocken, R. Anthes, and R. Ware, 1992: GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system. J. Geophys. Res., 97, 15 78715 801, https://doi.org/10.1029/92JD01517.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bevis, M., S. Businger, S. Chiswell, T. A. Herring, R. A. Anthes, C. Rochen, and R. H. Ware, 1994: GPS meteorology: Mapping zenith wet delays onto precipitable water. J. Appl. Meteor., 33, 379386, https://doi.org/10.1175/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bian, J. C., H. B. Chen, V. Holger, Y. J. Duan, Y. J. Xuan, and D. , 2011: Intercomparison of humidity and temperature sensors: GTS1, Vaisala RS80, and CFH. Adv. Atmos. Sci., 28, 139146, https://doi.org/10.1007/s00376-010-9170-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Black, H. D., 1978: An easily implemented algorithm for the tropospheric range correction. J. Geophys. Res., 83, 18251828, https://doi.org/10.1029/JB083iB04p01825.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Böhm, J., and et al. , 2015: Development of an improved empirical model for slant delays in the troposphere (GPT2w). GPS Solutions, 19, 433441, https://doi.org/10.1007/s10291-014-0403-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Born, M., and E. Wolf, 1964: Principles of Optics: Electromagnetic Theory of Propagation, Interference, and Diffraction of Light. Pergamon Press, 836 pp.

    • Search Google Scholar
    • Export Citation
  • Boudouris, G., 1963: On the index of refraction of air, the absorption and dispersion of centimeter waves by gasses. J. Res. Natl. Bur. Stand., 67D, 631684.

    • Search Google Scholar
    • Export Citation
  • Brettle, M. J., and J. F. P. Galvin, 2003: Back to basics: Radiosondes: Part I—The instrument. Weather, 58, 336341, https://doi.org/10.1256/wea.126.02A.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, B., and Z. Liu, 2014: Voxel-optimized regional water vapor tomography and comparison with radiosonde and numerical weather model. J. Geod., 88, 691703, https://doi.org/10.1007/s00190-014-0715-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, B., and Z. Liu, 2015: A comprehensive evaluation and analysis of the performance of multiple tropospheric models in China region. IEEE Trans. Geosci. Remote Sens., 99, 663678, https://doi.org/10.1109/TGRS.2015.2456099.

    • Search Google Scholar
    • Export Citation
  • Davis, J. L., T. A. Herring, I. I. Shapiro, A. Rogers, and G. Elgered, 1985: Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length. Radio Sci., 20, 15931607, https://doi.org/10.1029/RS020i006p01593.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duan, J., and et al. , 1996: GPS meteorology: Direct estimation of the absolute value of precipitable water. J. Appl. Meteor. Climatol., 35, 830838, https://doi.org/10.1175/1520-0450(1996)035<0830:GMDEOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goad, C. C., and L. L. Goodman, 1974: A modified Hopfield tropospheric refraction correction model. Fall Meeting, San Francisco, CA, Amer. Geophys. Union.

  • Hamill, T. M., and A. T. Church, 2000: Conditional probabilities of significant tornadoes from RUC-2 forecasts. Wea. Forecasting, 15, 461475, https://doi.org/10.1175/1520-0434(2000)015<0461:CPOSTF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hasegawa, S., and D. P. Stokesbury, 1975: Automatic digital microwave hygrometer. Rev. Sci. Instrum., 46, 867873, https://doi.org/10.1063/1.1134331.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hopfield, H. S., 1971: Tropospheric effect on electromagnetically measured range prediction from surface weather data. Radio Sci., 6, 357367, https://doi.org/10.1029/RS006i003p00357.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, L. K., S. F. Xie, L. L. Liu, J. Li, J. Chen, and C. Kang, 2020: SSIEGNOS: A new Asian single site tropospheric correction. ISPRS Int. J. Geo-Infor., 6, 20, https://doi.org/10.3390/IJGI6010020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janes, H. W., R. B. Langley, and S. P. Newby, 1991: Analysis of tropospheric delay prediction models: Comparisons with ray-tracing and implications for GPS relative positioning. Bull. Geod., 65, 151161, https://doi.org/10.1007/BF00806344.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, P., S. R. Ye, Y. Y. Liu, J. J. Zhang, and P. F. Xia, 2014: Near real-time water vapor tomography using ground-based GPS and meteorological data: Long-term experiment in Hong Kong. Ann. Geophys., 32, 911923, https://doi.org/10.5194/angeo-32-911-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, S. G., G. P. Feng, and S. Gleason, 2011: Remote sensing using GNSS signals: Current status and future directions. Adv. Space Res., 47, 16451653, https://doi.org/10.1016/j.asr.2011.01.036.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuo, B., C. Rocken, and R. Anthes, 2007: GPS radio occultation missions. Second FORMOSAT-3/COSMIC Data Users Workshop, Boulder, CO, UCAR.

  • Kursinski, E. R., G. A. Hajj, and J. T. Schofield, 1997: Observing Earth’s atmosphere with radio occultation measurements using the global positioning system. J. Geophys. Res., 102, 23 42923 465, https://doi.org/10.1029/97JD01569.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lagler, K., M. Schindelegger, J. Böhm, H. Krásná, and T. Nilsson, 2013: GPT2: Empirical slant delay model for radio space geodetic techniques. Geophys. Res. Lett., 40, 10691073, https://doi.org/10.1002/grl.50288.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, F., 2006: New developments with upper-air sounding in China. WMO Instruments and Observing Methods Rep. 94, 9 pp., https://library.wmo.int/pmb_ged/wmo-td_1354_en/2(1)_Li-Feng_China.pdf.

  • Li, W., F. Li, Z. Zhao, F. Liu, B. Li, and H. Li, 2009b: Technical assessment report of L-band upper air sounding system (in Chinese). China Meteorological Administration Rep., 95 pp.

  • Liang, H., R. Zhang, J. Liu, Z. Sun, and S. Li, 2012: Systematic errors and their calibrations for radiosonde precipitable water vapor on the Tibetan Plateau (in Chinese). Chin. J. Atmos. Sci., 36, 795810.

    • Search Google Scholar
    • Export Citation
  • Liu, Y. X., Hbiz, and Y. Q. Chen, 2000: Precise determination of dry zenith delay for GPS meteorology applications (in Chinese). Acta Geod. Cartography Sin., 29, 172179.

    • Search Google Scholar
    • Export Citation
  • Liu, Z., M. S. Wong, J. Nichol, and P. W. Chan, 2013: A multisensory study of water vapour from radiosonde, MODIS and AERONET: A case study of Hong Kong. Int. J. Climatol., 33, 109120, https://doi.org/10.1002/joc.3412.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mendes, V. B., 1998: Modeling the neutral-atmosphere propagation delay in radiometric space techniques. Ph.D. dissertation, University of New Brunswick, 353 pp.

  • Miloshevich, L. M., H. Vömel, A. Paukkunen, A. J. Heymsfield, and S. J. Oltmas, 2001: Characterization and correction of relative humidity measurements from Vaisala RS80—A radiosondes at cold temperatures. J. Atmos. Oceanic Technol., 18, 135156, https://doi.org/10.1175/1520-0426(2001)018<0135:CACORH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Owens, J. C., 1967: Optical refractive index of air: Dependence on pressure, temperature, and composition. Appl. Opt., 6, 5158, https://doi.org/10.1364/AO.6.000051.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Penna, N., A. Dodson, and W. Chen, 2001: Assessment of EGNOS tropospheric correction model. J. Navig., 54, 3755, https://doi.org/10.1017/S0373463300001107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Posada, R., E. García-Ortega, J. L. Sánchez, and L. López, 2013: Verification of the MM5 model using radiosonde data from Madrid-Barajas Airport. Atmos. Res., 122, 174182, https://doi.org/10.1016/j.atmosres.2012.10.018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rohm, W., 2013: The ground GNSS tomography-unconstrained approach. Adv. Space Res., 51, 501513, https://doi.org/10.1016/j.asr.2012.09.021.

  • Rüeger, J. M., 2002: Refractive index formulae for radio waves. Proc. 22nd FIG Int. Congress, Washington, DC, International Federation of Surveyors, http://www.fig.net/resources/proceedings/fig_proceedings/fig_2002/Js28/JS28_rueger.pdf.

  • Saastamoinen, J., 1972: Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites. The Use of Artificial Satellites for Geodesy, Geophys. Monogr., Vol. 15, Amer. Geophys. Union, 247–251.

    • Crossref
    • Export Citation
  • Schüler, T., 2014: The TropGrid2 standard tropospheric correction model. GPS Solutions, 18, 123131, https://doi.org/10.1007/s10291-013-0316-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, E. K., and S. Weintraub, 1953: The constants in the equation for atmospheric refractive index at radio frequencies. J. Res. Natl. Bur. Stand., 50, 3941, https://doi.org/10.6028/jres.050.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thayer, G. D., 1974: An improved equation for the radio refractive index of air. Radio Sci., 9, 803807, https://doi.org/10.1029/RS009i010p00803.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tuka, A., and A. El-Mowafy, 2013: Performance evaluation of different troposphere delay models and mapping functions. Measurement, 46, 928937, https://doi.org/10.1016/j.measurement.2012.10.015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, J., H. L. Cole, D. J. Carlson, E. R. Miller, K. Beierle, A. Paukkunen, and T. K. Laine, 2002: Corrections of humidity measurement errors from the Vaisala RS80 radiosonde—Application to TOGA COARE data. J. Atmos. Oceanic Technol., 19, 9811002, https://doi.org/10.1175/1520-0426(2002)019<0981:COHMEF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • WMO, 2019: Guide to meteorological instruments and methods of observation. WMO Doc. 8, 573 pp.

  • Xia, P., C. Cai, and Z. Liu, 2013: GNSS troposphere tomography based on two-step reconstructions using GPS observations and COSMIC profiles. Ann. Geophys., 31, 18051815, https://doi.org/10.5194/angeo-31-1805-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xia, P., S. R. Ye, P. Jiang, L. Pan, and M. Guo, 2018: Assessing water vapor tomography in Hong Kong with improved vertical and horizontal constraints. Ann. Geophys., 36, 969978, https://doi.org/10.5194/angeo-36-969-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yao, W., Y. Ma, and W. Xu, 2008: Relative humidity error of L-band electronic radiosonde and its application (in Chinese). Yingyong Qixiang Xuebao, 19, 356361.

    • Search Google Scholar
    • Export Citation
  • Ye, S. R., P. F. Xia, and C. S. Cai, 2016: Optimization of GPS water vapor tomography technique with radiosonde and COSMIC historical data. Ann. Geophys., 34, 789799, https://doi.org/10.5194/angeo-34-789-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W., and et al. , 2019: Corrections of radiosonde-based precipitable water using ground-based GPS and applications on historical radiosonde data over China. J. Geophys. Res. Atmos., 124, 32083222, https://doi.org/10.1029/2018JD029662.

    • Search Google Scholar
    • Export Citation
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Establishing a High-Precision ZHD Model of China Using 8 Years of Radiosonde Data

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  • 1 a GNSS Research Center, Wuhan University, Wuhan, China
  • | 2 b School of Geodesy and Geomatics, Wuhan University, Wuhan, China
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Abstract

Tropospheric hydrostatic delay is one of the major sources of errors in Global Navigation Satellite System (GNSS) navigation and positioning, and an important parameter in GNSS meteorology. This work first proposes a new method of computing zenith hydrostatic delay (ZHD) based on precipitable water vapor (PWV), using radiosonde data. Next, using these calculations as a reference, the performance of three empirical ZHD models and three ZHD integral models in China is assessed using benchmark values obtained from 8 years (2010–17) of radiosonde data recorded at 75 stations across China. Finally, we provide a new revised ZHD model that can be applied to China and validate its performance using radiosonde data collected in China in 2018. The statistical results indicate that the ZHD can be estimated by this new model with an accuracy of several millimeters. Due to its performance and simplicity, this new model is shown to be the optimal ZHD model for use in China.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Pengfei Xia, pfxia130@whu.edu.cn

Abstract

Tropospheric hydrostatic delay is one of the major sources of errors in Global Navigation Satellite System (GNSS) navigation and positioning, and an important parameter in GNSS meteorology. This work first proposes a new method of computing zenith hydrostatic delay (ZHD) based on precipitable water vapor (PWV), using radiosonde data. Next, using these calculations as a reference, the performance of three empirical ZHD models and three ZHD integral models in China is assessed using benchmark values obtained from 8 years (2010–17) of radiosonde data recorded at 75 stations across China. Finally, we provide a new revised ZHD model that can be applied to China and validate its performance using radiosonde data collected in China in 2018. The statistical results indicate that the ZHD can be estimated by this new model with an accuracy of several millimeters. Due to its performance and simplicity, this new model is shown to be the optimal ZHD model for use in China.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Pengfei Xia, pfxia130@whu.edu.cn
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