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Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research

Climate applications of a global, 2-hourly atmospheric precipitable water dataset from IGS tropospheric products. Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research.

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Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research

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  1. Climate applications of a global, 2-hourly atmospheric precipitable water dataset from IGS tropospheric products Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research Collaborators: Liangying (Liz) Zhang (EOL), Aiguo Dai (CGD), Teresa Van Hove and Ted Iwabuchi (UCAR/COSMIC), and Joel Van Baelen (CNRS) Thank Support from NOAA Climate Change Data and Detection program

  2. Outline • The analysis technique and GPS PW dataset • Application #1: Quantifying systematic errors in global radiosonde humidity data • Application #2: Diurnal variations • Summary • Future needs

  3. How does GPS estimate precipitable water? Total delay = Ionosphere + dry + wet Noise (geodesy) Signal (meteorology) ZPD = ZHD + ZWD ZWD = ZPD - ZHD PW =  * ZWD  = f (Tm)

  4. Feb. 1997 to Dec. 2007 • 2 hourly (0100, 0300, …, 2300 UTC) • 370 IGS, 169 SuomiNet, 1223 GEONET • Accuracy: < 3 mm • Ps, Tm, ZHD and ZWD also available • Request data: junhong@ucar.edu A global, 11-year, 2-hourly PW dataset from ground-based GPS measurements(Wang et al. 2007, JGR)

  5. Highlight of GPS-PW data

  6. Hurricane Ernesto (24 Aug – 1 Sep. 2006)

  7. Problems: • Errors and biases • Spatial and temporal inhomogeneity • Spatial sampling errors • Diurnal sampling errors Results: The role of radiosonde observations in climate studies is limited. Solutions: To quantify radiosonde errors and correct them.

  8. Matched GPS and radiosonde data (< 50 km in distance, < 100 m in elevation, < 2 hours; 14 types and 136 stations) • Humidity sensors: • Capacitive • Carbon hygristor • Goldbeater’s skin Wang and Zhang (2008a)

  9. Capacitive Carbon hygristor Goldbeater’s skin median -1.67 1.97 0.81 S.D. 1.72 4.15 1.93 Systematic errors – mean biases Wang and Zhang (2008a)

  10. Vaisala RS80-A with cover PW difference (mm radiosonde-GPS) without cover Sensor boom cover with cover Vaisala RS80-H PW difference (mm radiosonde-GPS) without cover Wang et al. (2002) Impacts of the sensor boom cover on Vaisala RS80 dry bias Wang and Zhang (2008a)

  11. Temporal inhomogeneity of radiosonde PW data carbon hygristor capacitive with cover capacitive carbon hygristor Goldbeater’s skin Carbon hygristor Miami, U.S.A Suwon-Shi, Korea Relative PW differences (% Radiosonde-GPS) Beijing, China Wang and Zhang (2008)

  12. Impacts of temporal inhomogeneity Carbon hygristor Capacitive

  13. PW diurnal variations in four regions Europe 30-70S Month Month LST LST mm N.H. Mountains Darwin region Month Month LST LST Wang and Zhang (2008b)

  14. Seasonal variations of diurnal and sub-monthly variability over Europe GPS NCEP/NCAR JRA ERA-40 mm Wang and Zhang (2008c)

  15. Summary • Dataset: A global, 11-year, 2-hourly GPS-PW dataset is created from IGS tropospheric products for various scientific applications. • Climate applications: The dataset is used to quantify systematic errors in global radiosonde PW data, validate global reanalysis products and study diurnal variations. • 3. More information: • Wang, J., and L. Zhang, 2008: Validation of Atmospheric Precipitable Water in Three Reanalysis Products using Ground-based GPS Measurements, extended abstract for Third WCRP International Conference on Reanalysis, Jan. 28 – Feb. 1, 2008, Tokyo, Japan. • Wang, J., and L. Zhang, 2008: Climate applications of a global, 2-hourly atmospheric precipitable water dataset from IGS ground-based GPS measurements, J. of Geodesy, accepted. • Wang, J., and L. Zhang, 2008: Systematic errors in global radiosonde precipitable water data from comparisons with ground-based GPS measurements. J. Climate, in press. • Wang, J., L. Zhang, A. Dai, T. Van Hove and J. Van Baelen, 2007: A near-global, 8-year, 2-hourly atmospheric precipitable water dataset from ground-based GPS measurements, J. Geophys. Res., 112, D11107. doi;10.1029/2006JD007529. . • Wang, J., L. Zhang, and A. Dai, Global estimates of water-vapor-weighted mean temperature of the atmosphere for GPS applications. J. Geophys. Res., 110, D21101, doi:10.1029/2005JD006215, 2005.

  16. Future Needs Recommendations on improving future IGS products • To continuously produce the ZTD product and maintain its long-term stability and high quality • To reduce diurnal biases in the ZTD product • To improve and increase sfc-met data • To co-locate with radiosonde stations • To increase the spatial and temporal coverage

  17. 1. To maintain long-term stability and high quality of the ZTD product

  18. 4. To co-locate with radiosonde stations • Provide long-term, high-quality climate records • Constrain/calibrate data from more spatially-comprehensive global observing systems • Measure large suite of co-related climate variables

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