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Monitoring Water Vapor Variability with Ground-based GPS Measurements:

Monitoring Water Vapor Variability with Ground-based GPS Measurements: Diurnal cycle to long-term trend. Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research, Boulder , CO. Collaborators: Liangying (Liz) Zhang (NCAR/EOL ), Aiguo Dai (NCAR/CGD),

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Monitoring Water Vapor Variability with Ground-based GPS Measurements:

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  1. Monitoring Water Vapor Variability with Ground-based GPS Measurements: Diurnal cycle to long-term trend Junhong (June) Wang Earth Observing Laboratory National Center for Atmospheric Research, Boulder, CO Collaborators: Liangying (Liz) Zhang (NCAR/EOL), Aiguo Dai (NCAR/CGD), John Braun & Teresa Van Hove (UCAR/COSMIC), Steve Worley & ZaihuaJi (NCAR/CISL), Tong Ning & Gunnar Elgered (Chalmers University of Technology) UNAVCO Science Workshop 2012

  2. Challenge: Large variability Gaffen et al. (1995) UNAVCO Science Workshop 2012

  3. Comparisons of water vapor measurement techniques • Diurnal variation • Climate extremes Validations of other measurements Climate trends UNAVCO Science Workshop 2012

  4. Jan. 1995 to Dec. 2011 • 2 hourly (0100, 0300, …, 2300 UTC) • 380 IGS, 169 SuomiNet, 1223 GEONET • Accuracy: < 3 mm • Ps, Tm, ZHD and ZWD also available • http://dss.ucar.edu/datasets/ds721.1/ NCAR global, 2-hourly GPS-PW data (1995-present) Wang et al. (2007) UNAVCO Science Workshop 2012

  5. Global PW Diurnal Cycle Globe S. H. N. H. • The diurnal cycle is less than 5% of annual mean PW • Larger magnitude in summer than in winter • Peak around late afternoon to early evening • An order of magnitude smaller than seasonal variation UNAVCO Science Workshop 2012 Wang & Zhang (2009)

  6. Seasonal variations of diurnal anomalies in four regions Europe 30-70S N.H. Mountains Darwin region UNAVCO Science Workshop 2012

  7. Validating radiosonde data Before correction Vaisala RS92 Before correction After correction After correction GPS UNAVCO Science Workshop 2012

  8. Diurnal Signal Feb vs Aug 2009 00 18 06 12 Lin et al. (2010) Braun et al. (2012 MWR)

  9. Water Vapor Extremes (Miami, USA) UNAVCO Science Workshop 2012

  10. Hurricane Ernesto (24 Aug – 1 Sep. 2006) UNAVCO Science Workshop 2012

  11. Foster et al. 2003 Connections between water vapor and precipitation extremes • Ka’ū storm, Big Island of HI, Nov. 1-2 2000; • > 100mm/hr (~4”/hr) maximum hourly rain rate • Most intense, widespread rain event in 20 years • $70 M property damage • Impacts on roads and other infrastructure for weeks afterward • Using GPS PW data to predict rain rate and validate model results UNAVCO Science Workshop 2012

  12. PW Anomaly in 2010 (GPS v.s. Microwave satellite) Mears et al. (2010) Mears et al. (2011) Mears et al. (2011) UNAVCO Science Workshop 2012

  13. PW Anomaly in 2011 (GPS v.s. Radiosonde) UNAVCO Science Workshop 2012

  14. Inter-annual and Long-Term PW Variability Land El Nino Ocean La Nina UNAVCO Science Workshop 2012 Mears et al. (2012)

  15. Review on GPS PW Trend Studies summer winter winter summer UNAVCO Science Workshop 2012

  16. Long-Term PW Trend (1995-2011) UNAVCO Science Workshop 2012

  17. Changes in the IGS ZTD product (1997-2011) UNAVCO Science Workshop 2012

  18. 2-hrly combined to 5-min PPP IGS05 UNAVCO Science Workshop 2012

  19. Long-term trend (before/after reprocessing) Before After UNAVCO Science Workshop 2012

  20. ZTD differences in 2011 between consistently processed and IGS ZTD BRUS 4/17/2011 WSRT UNAVCO Science Workshop 2012

  21. Differences of monthly mean PW anomalies (GPS – Radiosonde) April 2011 4/17/2011 UNAVCO Science Workshop 2012

  22. Challenges for Climate Variability: Incompleteness 2008 Annual PW at 252 stations 2008: 560 total; 308 not enough for annual mean Continuous data for 1997-2010: 70 UNAVCO Science Workshop 2012

  23. The GCOS Reference Upper Air Network • Provide long-term high-quality upper-air climate records • Constrain and calibrate data from more spatially-comprehensive global observing systems • Fully characterize the properties of the atmospheric column • GRUAN GNSS-PW Task Team: • To define GRUAN requirements on GNSS-PW observations, the state-of-art GNSS site, data & meta-data; • To provide guidelines for GNSS-PW uncertainty analysis; • To provide guidelines on how to better manage changes. UNAVCO Science Workshop 2012

  24. Summary The GPS PW data have been approved very useful for studying water vapor diurnal, inter-annual and long-term variations, and extreme events. However, the temporal inhomogeneity of the GPS-PW data is introduced by changes in instruments, data processing algorithms and other factors. This raises concerns on long-term stability of GPS-PW data and its usefulness for water vapor variability. There is a urgent need to consistently reprocess the GPS-PW data for climate studies, and better manage changes in the future, including maintaining complete metadata on changes and always evaluating the impacts of changes before they are implemented. Best efforts should be made to continuously collect data. UNAVCO Science Workshop 2012

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