Systematic Errors in Global Radiosonde Precipitable Water Data from Comparisons with Ground-Based GPS Measurements

Junhong Wang Earth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

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Liangying Zhang Earth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

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Abstract

A global, 10-yr (February 1997–April 2006), 2-hourly dataset of atmospheric precipitable water (PW) was produced from ground-based global positioning system (GPS) measurements of zenith tropospheric delay (ZTD) at approximately 350 International Global Navigation Satellite Systems (GNSS) Service (IGS) ground stations. A total of 130 pairs of radiosonde and GPS stations are found within a 50-km distance and 100-m elevation of each other. At these stations, 14 types of radiosondes are launched and the following 3 types of humidity sensors are used: capacitive polymer, carbon hygristor, and goldbeater’s skin. The PW comparison between radiosonde and GPS data reveals three types of systematic errors in the global radiosonde PW data: measurement biases of the 14 radiosonde types along with their characteristics, long-term temporal inhomogeneity, and diurnal sampling errors of once- and twice-daily radiosonde data. The capacitive polymer generally shows mean dry bias of −1.19 mm (−6.8%). However, the carbon hygristor and goldbeater’s skin hygrometers have mean moist biases of 1.01 mm (3.4%) and 0.76 mm (5.4%), respectively. The protective shield over the humidity sensor boom introduced in late 2000 reduces the PW dry bias from 6.1% and 2.6% in 2000 to 3.9% and −1.14% (wet bias) in 2001 for the Vaisala RS80A and RS80H, respectively. The dry bias in Vaisala radiosondes has larger magnitudes during the day than at night, especially for RS90 and RS92, with a day–night difference of 5%–7%. The time series of monthly mean PW differences between the radiosonde and GPS are able to detect significant changes associated with known radiosonde type changes. Such changes would have a significant impact on the long-term trend estimate. Diurnal sampling errors of twice-daily radiosonde data are generally within 2%, but can be as much as 10%–15% for the once-daily soundings. In conclusion, this study demonstrates that the global GPS PW data are useful for identifying and quantifying several kinds of systematic errors in global radiosonde PW data. Several recommendations are made for future needs of global radiosonde and GPS networks and data.

Corresponding author address: Junhong Wang, NCAR/EOL, P.O. Box 3000, Boulder, CO 80307. Email: junhong@ucar.edu

Abstract

A global, 10-yr (February 1997–April 2006), 2-hourly dataset of atmospheric precipitable water (PW) was produced from ground-based global positioning system (GPS) measurements of zenith tropospheric delay (ZTD) at approximately 350 International Global Navigation Satellite Systems (GNSS) Service (IGS) ground stations. A total of 130 pairs of radiosonde and GPS stations are found within a 50-km distance and 100-m elevation of each other. At these stations, 14 types of radiosondes are launched and the following 3 types of humidity sensors are used: capacitive polymer, carbon hygristor, and goldbeater’s skin. The PW comparison between radiosonde and GPS data reveals three types of systematic errors in the global radiosonde PW data: measurement biases of the 14 radiosonde types along with their characteristics, long-term temporal inhomogeneity, and diurnal sampling errors of once- and twice-daily radiosonde data. The capacitive polymer generally shows mean dry bias of −1.19 mm (−6.8%). However, the carbon hygristor and goldbeater’s skin hygrometers have mean moist biases of 1.01 mm (3.4%) and 0.76 mm (5.4%), respectively. The protective shield over the humidity sensor boom introduced in late 2000 reduces the PW dry bias from 6.1% and 2.6% in 2000 to 3.9% and −1.14% (wet bias) in 2001 for the Vaisala RS80A and RS80H, respectively. The dry bias in Vaisala radiosondes has larger magnitudes during the day than at night, especially for RS90 and RS92, with a day–night difference of 5%–7%. The time series of monthly mean PW differences between the radiosonde and GPS are able to detect significant changes associated with known radiosonde type changes. Such changes would have a significant impact on the long-term trend estimate. Diurnal sampling errors of twice-daily radiosonde data are generally within 2%, but can be as much as 10%–15% for the once-daily soundings. In conclusion, this study demonstrates that the global GPS PW data are useful for identifying and quantifying several kinds of systematic errors in global radiosonde PW data. Several recommendations are made for future needs of global radiosonde and GPS networks and data.

Corresponding author address: Junhong Wang, NCAR/EOL, P.O. Box 3000, Boulder, CO 80307. Email: junhong@ucar.edu

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  • Angell, J. K., W. P. Elliott, and M. E. Smith, 1984: Tropospheric humidity variations at Brownsville, Texas and Great Falls, Montana, 1958–80. J. Climate Appl. Meteor., 23 , 12861295.

    • Search Google Scholar
    • Export Citation
  • Bevis, M., S. Businger, T. A. Herring, C. Rocken, R. A. Anthes, and R. H. Ware, 1992: GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system. J. Geophys. Res., 97 , 1578715801.

    • Search Google Scholar
    • Export Citation
  • Bevis, M., S. Businger, S. Chiswell, T. A. Herring, R. A. Anthes, C. Rocken, and R. H. Ware, 1994: GPS meteorology: Mapping zenith wet delays onto precipitable water. J. Appl. Meteor., 33 , 379386.

    • Search Google Scholar
    • Export Citation
  • Bokoye, A. I., A. Royer, N. T. O’Neill, P. Cliche, L. J. B. McArthur, P. M. Teillet, G. Fedosejevs, and J-M. Thériault, 2003: Multisensor analysis of integrated atmospheric water vapor over Canada and Alaska. J. Geophys. Res., 108 .4480, doi:10.1029/2002JD002721.

    • Search Google Scholar
    • Export Citation
  • Bolton, D., 1980: The computation of equivalent potential temperature. Mon. Wea. Rev., 108 , 10461053.

  • Ciesielski, P. E., R. H. Johnson, P. T. Haertel, and J. Wang, 2003: Corrected TOGA COARE sounding humidity data: Impact on diagnosed properties of convection and climate over the warm pool. J. Climate, 16 , 23702384.

    • Search Google Scholar
    • Export Citation
  • Crutcher, H. L., and R. E. Eskridge, 1993: Development of a method to modify solar-induced humidity biases in the US radiosonde data from the period 1961–1973. Preprints, Eighth Symp. on Meteorological Observations and Instrumentation, Anaheim, CA, Amer. Meteor. Soc., 143–147.

  • Dai, A., J. Wang, R. H. Ware, and T. Van Hove, 2002: Diurnal variation in water vapor over North America and its implications for sampling errors in radiosonde humidity. J. Geophys. Res., 107 .4090, doi:10.1029/2001JD000642.

    • Search Google Scholar
    • Export Citation
  • Deblonde, G., S. Macpherson, Y. Mireault, and P. Héroux, 2005: Evaluation of GPS precipitable water over Canada and the IGS network. J. Appl. Meteor., 44 , 153166.

    • Search Google Scholar
    • Export Citation
  • Durre, I., R. S. Vose, and D. B. Wuertz, 2006: Overview of the Integrated Global Radiosonde Archive. J. Climate, 19 , 5368.

  • Elliott, W. P., and D. J. Gaffen, 1991: On the utility of radiosonde humidity archives for climate studies. Bull. Amer. Meteor. Soc., 72 , 15071520.

    • Search Google Scholar
    • Export Citation
  • Elliott, W. P., R. J. Ross, and B. Schwartz, 1998: Effects on climate records of changes in National Weather Service humidity processing procedures. J. Climate, 11 , 24242436.

    • Search Google Scholar
    • Export Citation
  • Elliott, W. P., R. J. Ross, and W. H. Blackmore, 2002: Recent changes in NWS upper-air observations with emphasis on changes from VIZ to Vaisala radiosondes. Bull. Amer. Meteor. Soc., 83 , 10031017.

    • Search Google Scholar
    • Export Citation
  • Elms, J., 2003: Compatibility of radiosonde geopotential measurements for period from 1998 to 2001. WMO Tech. Doc. 1197, 55 pp.

  • Emardson, T. R., G. Elgered, and J. M. Johansson, 1998: Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers. J. Geophys. Res., 103 , 18071820.

    • Search Google Scholar
    • Export Citation
  • Fujiwara, M., M. Shiotani, F. Hasebe, H. Vomel, S. J. Oltmans, P. Ruppert, T. Horinouchi, and T. Tsuda, 2003: Performance of the Meteolabor “Snow White” chilled-mirror hygrometer in the tropical troposphere: Comparison with the Vaisala RS80 A/H-Humicap sensors. J. Atmos. Oceanic Technol., 20 , 15341542.

    • Search Google Scholar
    • Export Citation
  • Gaffen, D. J., 1993: Historical changes in radiosonde instruments and practices. WMO Tech. Doc. 541, Instruments and Observing Methods Rep. 50, 123 pp.

  • Gaffen, D. J., 1996: A digitized metadata set of global upper-air station histories. NOAA Tech. Memo. ERL ARL-211, 37 pp.

  • Gendt, G., 1998: IGS combination of tropospheric estimates—The pilot experiment. 1997 Technical Reports, I. Mueller, K. Gowey, and R. Neilan, Eds., International GPS Services for Geodynamics, 265–269. [Available online at http://igscb.jpl.nasa.gov/overview/pubs/97techr.html.].

    • Search Google Scholar
    • Export Citation
  • Guerova, G., E. Brockmann, J. Quiby, F. Schubiger, and C. Matzler, 2003: Validation of NWP mesoscale models with Swiss GPS network AGNES. J. Appl. Meteor., 42 , 141150.

    • Search Google Scholar
    • Export Citation
  • Gutman, S. I., S. Sahm, S. Benjamin, and T. L. Smith, 2004: GPS water vapor observation errors. Preprints, Eighth Symp. on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, Seattle, WA, Amer. Meteor. Soc., 8.3. [Available online at http://ams.confex.com/ams/pdfpapers/72508.pdf.].

  • Häberli, C., 2006: Assessment, correction and impact of the dry bias in radiosonde humidity data during the MAP SOP. Quart. J. Roy. Meteor. Soc., 132 , 28272852.

    • Search Google Scholar
    • Export Citation
  • Hagemann, S., L. Bengtsson, and G. Gendt, 2003: On the determination of atmospheric water vapor from GPS measurements. J. Geophys. Res., 108 .4678, doi:10.1029/2002JD003235.

    • Search Google Scholar
    • Export Citation
  • Kuo, Y-H., W. S. Schreiner, J. Wang, D. L. Rossiter, and Y. Zhang, 2005: Comparison of GPS radio occultation soundings with radiosondes. Geophys. Res. Lett., 32 .L05817, doi:10.1029/2004GL021443.

    • Search Google Scholar
    • Export Citation
  • Leiterer, U., H. Dier, and T. Naebert, 1997: Improvements in radiosonde humidity profiles using RS80/RS90 radiosondes of Vaisala. Beitr. Phys. Atmos., 70 , 319336.

    • Search Google Scholar
    • Export Citation
  • Li, Z., J-P. Muller, and P. Cross, 2003: Comparison of precipitable water vapor derived from radiosonde, GPS, and moderate-resolution imaging spectroradiometer measurements. J. Geophys. Res., 108 .4651, doi:10.1029/2003JD003372.

    • Search Google Scholar
    • Export Citation
  • Liou, Y-A., Y-T. Teng, T. Van Hove, and J. C. Liljegren, 2001: Comparison of precipitable water observations in the near tropics by GPS, microwave radiometer, and radiosondes. J. Appl. Meteor., 40 , 515.

    • Search Google Scholar
    • Export Citation
  • Lucas, C., and E. J. Zipser, 2000: Environmental variability during TOGA COARE. J. Atmos. Sci., 57 , 23332350.

  • Miloshevich, L. M., H. Vömel, A. Paukkunen, A. J. Heymsfield, and S. J. Oltmans, 2001: Characterization and correction of relative humidity measurements from Vaisala RS80-A radiosondes at cold temperatures. J. Atmos. Oceanic Technol., 18 , 135155.

    • Search Google Scholar
    • Export Citation
  • Nakamura, H., H. Seko, and Y. Shoji, 2004: Dry biases of humidity measurements from the Vaisala RS80-A and Meisei RS2-91 radiosondes and from ground-based GPS. J. Meteor. Soc. Japan, 82 , 277299.

    • Search Google Scholar
    • Export Citation
  • Nash, J., R. Smout, T. Oakley, B. Pathack, and S. Kurnosenko, 2005: WMO intercomparison of high quality radiosonde systems: Final report. WMO Rep., 118 pp. [Available online at http://www.wmo.int/pages/prog/www/IMOP/intercomparisons/RSO-2005/RSO-IC-2005_Final_Report.pdf.].

  • Niell, A. E., 1996: Global mapping functions for the atmosphere delay at radio wavelengths. J. Geophys. Res., 101 , 32273246.

  • Niell, A. E., A. J. Coster, F. S. Solheim, V. B. Mendes, P. C. Toor, R. B. Langley, and C. A. Upham, 2001: Comparison of measurements of atmospheric wet delay by radiosonde, water vapor radiometer, GPS, and VLBI. J. Atmos. Oceanic Technol., 18 , 830850.

    • Search Google Scholar
    • Export Citation
  • Ohtani, R., and I. Naito, 2000: Comparisons of GPS-derived precipitable water vapors with radiosonde observations in Japan. J. Geophys. Res., 105 , 2691726929.

    • Search Google Scholar
    • Export Citation
  • Ray, J., D. Crump, and M. Chin, 2006: New GPS reference station in Brazil. Geophysical Research Abstracts, Vol. 8, Abstract 04919. [Available online at http://www.cosis.net/abstracts/EGU06/04919/EGU06-J-04919-1.pdf.].

    • Search Google Scholar
    • Export Citation
  • Rocken, C., R. H. Ware, T. Van Hove, F. Solheim, C. Alber, J. Johnson, M. Bevis, and S. Businger, 1993: Sensing atmospheric water vapor with the global positioning system. Geophys. Res. Lett., 20 , 26312634.

    • Search Google Scholar
    • Export Citation
  • Rocken, C., T. Van Hove, and R. H. Ware, 1997: Near real-time GPS sensing of atmospheric water vapor. Geophys. Res. Lett., 24 , 32213224.

    • Search Google Scholar
    • Export Citation
  • Ross, R. J., and D. J. Gaffen, 1998: Comment on “Widespread tropical atmospheric drying from 1979 to 1995” by Schroeder and McGuirk. Geophys. Res. Lett., 25 , 43574358.

    • Search Google Scholar
    • Export Citation
  • Schroeder, S. R., 2007: Using sensitive variables to validate and complete global historical radiosonde metadata—Toward computing atmospheric climate trends adjusted for instrument changes. Preprints, 14th Symp. on Meteorological Observation and Instrumentation, San Antonio, TX, Amer. Meteor. Soc., JP1.2. [Available online at http://ams.confex.com/ams/pdfpapers/119792.pdf.].

  • Sharpe, M. C., and B. Macpherson, 2001: Developments in the correction of radiosonde relative humidity biases at the Met Office. Preprints. 14th Conf. on Numerical Weather Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc., 250–253. [Available online at http://ams.confex.com/ams/pdfpapers/22640.pdf.].

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., and J. R. Lanzante, 1996: An assessment of satellite and radiosonde climatologies of upper-tropospheric water vapor. J. Climate, 9 , 12351250.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., and S. R. Schroeder, 2000: Decadal variations in tropical water vapor: A comparison of observations and a model simulation. J. Climate, 13 , 33373341.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., D. D. Turner, B. M. Lesht, and L. M. Miloshevich, 2004: An analysis of satellite, radiosonde, and lidar observations of upper tropospheric water vapor from the Atmospheric Radiation Measurement Program. J. Geophys. Res., 109 .D04105, doi:10.1029/2003JD003828.

    • Search Google Scholar
    • Export Citation
  • Thorne, P. W., D. E. Parker, S. F. B. Tett, P. D. Jones, M. McCarthy, H. Coleman, and P. Brohan, 2005: Revisiting radiosonde upper air temperatures from 1958 to 2002. J. Geophys. Res., 110 .D18105, doi:10.1029/2004JD005753.

    • Search Google Scholar
    • Export Citation
  • Tregoning, P., R. Boers, D. O’Brien, and M. Hendy, 1998: Accuracy of absolute precipitable water vapor estimates from GPS observations. J. Geophys. Res., 103 , 2870128710.

    • Search Google Scholar
    • Export Citation
  • Turner, D. D., B. M. Lesht, S. A. Clough, J. C. Liljegren, H. E. Revercomb, and D. C. Tobin, 2003: Dry bias and variability in Vaisala RS80-H radiosondes: The ARM experience. J. Atmos. Oceanic Technol., 20 , 117132.

    • Search Google Scholar
    • Export Citation
  • Van Baelen, J., J-P. Aubagnac, and A. Dabas, 2005: Comparison of near–real time estimates of integrated water vapor derived with GPS, radiosondes, and microwave radiometer. J. Atmos. Oceanic Technol., 22 , 201210.

    • Search Google Scholar
    • Export Citation
  • Vömel, H., and Coauthors, 2007: Radiation dry bias of the Vaisala RS92 humidity sensor. J. Atmos. Oceanic Technol., 24 , 953963.

  • Wade, C. G., 1994: An evaluation of problems affecting the measurement of low relative humidity on the United States radiosonde. J. Atmos. Oceanic Technol., 11 , 687700.

    • Search Google Scholar
    • Export Citation
  • Wade, C. G., and B. Schwartz, 1993: Radiosonde humidity observations near saturation. Preprints. Eighth Symp. on Meteorological Observations and Instrumentation, Anaheim, CA, Amer. Meteor. Soc., 44–49.

    • Search Google Scholar
    • Export Citation
  • Wang, J., 2002: Understanding and correcting humidity measurement errors from Vaisala RS80 and VIZ radiosondes. Proc. Radiosonde Workshop, Hampton University, VA, 7 pp. [Available online at http://www.eol.ucar.edu/homes/junhong/paper/RadiosondeWS02.pdf.].

    • Search Google Scholar
    • Export Citation
  • Wang, J., and K. Young, 2005: Comparisons of 7-year radiosonde data from two neighboring stations and estimation of random error variances for four types of radiosondes. Preprints, 13th Symp. on Meteorological Observations and Instrumentation, Savannah, GA, Amer. Meteor. Soc., 3.5. [Available online at http://ams.confex.com/ams/pdfpapers/94104.pdf.].

  • Wang, J., H. L. Cole, and D. J. Carlson, 2001: Water vapor variability in the tropical western Pacific from a 20-year radiosonde data. Adv. Atmos. Sci., 18 , 752766.

    • Search Google Scholar
    • Export Citation
  • Wang, J., H. L. Cole, D. J. Carlson, E. R. Miller, K. Beierle, A. Paukkunen, and T. K. Laine, 2002a: Corrections of humidity measurement errors from the Vaisala RS80 radiosonde—Application to TOGA COARE data. J. Atmos. Oceanic Technol., 19 , 9811002.

    • Search Google Scholar
    • Export Citation
  • Wang, J., A. Dai, D. J. Carlson, R. H. Ware, and J. C. Liljegren, 2002b: Diurnal variation in water vapor and liquid water profiles from a new microwave radiometer profiler. Preprints, Sixth Symp. on Integrated Observing Systems, Orlando, FL, Amer. Meteor. Soc., 198–201.

  • Wang, J., D. J. Carlson, D. B. Parsons, T. F. Hock, D. Lauritsen, H. L. Cole, K. Beierle, and N. Chamberlain, 2003: Performance of operational radiosonde humidity sensors in direct comparison with a chilled mirror dew-point hygrometer and its climate implication. Geophys. Res. Lett., 30 .1860, doi:10.1029/2003GL016985.

    • Search Google Scholar
    • Export Citation
  • Wang, J., L. Zhang, and A. Dai, 2006: A global, 2-hourly atmospheric precipitable water dataset from IGS ground-based GPS measurements: Scientific applications and future needs. Proc. Int. GNSS Service (IGS) Workshop 2006, Darmstadt, Germany, European Space Agency, 1–12.

    • Search Google Scholar
    • Export Citation
  • Wang, J., L. Zhang, A. Dai, T. Van Hove, and J. Van Baelen, 2007: A near-global, 8-year, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J. Geophys. Res., 112 .D11107, doi:10.1029/2006JD007529.

    • Search Google Scholar
    • Export Citation
  • WMO, 2006: Observing stations and WMO catalogue of radiosondes. WMO Publ. 9, Vol. A. [Available online at http://www.wmo.ch/pages/prog/www/ois/volume-a/vola-home.htm.].

  • WMO, 2007: GCOS Reference Upper Air Network (GRUAN): Justification, requirements, siting, and instrumentation options. WMO Tech. Doc. 1379, 42 pp. [Available online at http://www.wmo.ch/pages/prog/gcos/Publications/gcos-112.pdf.].

  • Zipser, E. J., and R. H. Johnson, 1998: Systematic errors in radiosonde humidities: A global problem? Preprints, 10th Symp. on Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 72–73.

  • Zurbenko, I., P. S. Porter, S. T. Rao, J. Y. Ku, R. Gui, and R. E. Eskridge, 1996: Detecting discontinuities in time series of upper-air data: Development and demonstration of an adaptive filter technique. J. Climate, 9 , 35483560.

    • Search Google Scholar
    • Export Citation
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