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Wang, Xiaoming; Zhang, Kefei; Wu, Suqin; Fan, Shijie; Cheng, Yingyan (2016): Long-term global GPS-derived precipitable water vapor data set [dataset publication series]. RMIT University, Melbourne, PANGAEA, https://doi.org/10.1594/PANGAEA.862525, Supplement to: Wang, X et al. (2016): Water vapor-weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend. Journal of Geophysical Research: Atmospheres, 121(2), 833-852, https://doi.org/10.1002/2015JD024181

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Abstract:
Water vapor-weighted mean temperature, Tm, is a vital parameter for retrieving precipitable water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems (GNSS) signal propagation. In this study, the Tm at 368 GNSS stations for 2000-2012 were calculated using three methods: (1) temperature and humidity profiles from ERA-Interim, (2) the Bevis Tm-Ts relationship, and (3) the Global Pressure and Temperature 2 wet model. Tm derived from the first method was used as a reference to assess the errors of the other two methods. Comparisons show that the relative errors of the Tm derived from these two methods are in the range of 1-3% across more than 95% of all the stations. The PWVs were calculated using the aforementioned three types of Tm and the GNSS-derived ZWD at 107 stations. Again, the PWVs calculated using Tm from the first method were used as the reference of the other two PWVs. The root-mean-square errors of these two PWVs are both in the range of 0.1-0.7 mm. The second method is recommended in real-time applications, since its performance is slightly better than the third method. In addition, the linear trends of the PWV time series from the first method were also used as the reference to evaluate the trends from the other two methods. Results show that 13% and 23% of the PWV trends from the respective second and third methods have a relative error of larger than 10%. For climate change studies, the first method, if available, is always recommended.
Other version:
GPS-derived precipitable water vapor data sets in original format (zipped, 33 MB)
Coverage:
Median Latitude: 17.843183 * Median Longitude: 9.950370 * South-bound Latitude: -77.848000 * West-bound Longitude: -176.617100 * North-bound Latitude: 82.494300 * East-bound Longitude: 174.834400
Date/Time Start: 1994-01-02T00:00:00 * Date/Time End: 2013-12-29T00:00:00
License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Size:
372 datasets

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Datasets listed in this publication series

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  1. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station THU3. https://doi.org/10.1594/PANGAEA.862452
  2. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TID1. https://doi.org/10.1594/PANGAEA.862453
  3. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TIDB. https://doi.org/10.1594/PANGAEA.862454
  4. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TITZ. https://doi.org/10.1594/PANGAEA.862455
  5. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TIXG. https://doi.org/10.1594/PANGAEA.862456
  6. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TIXI. https://doi.org/10.1594/PANGAEA.862457
  7. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TIXJ. https://doi.org/10.1594/PANGAEA.862458
  8. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TLSE. https://doi.org/10.1594/PANGAEA.862459
  9. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TN22. https://doi.org/10.1594/PANGAEA.862460
  10. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TNML. https://doi.org/10.1594/PANGAEA.862461
  11. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TOUL. https://doi.org/10.1594/PANGAEA.862462
  12. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TOW2. https://doi.org/10.1594/PANGAEA.862463
  13. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TRAB. https://doi.org/10.1594/PANGAEA.862464
  14. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TRO1. https://doi.org/10.1594/PANGAEA.862465
  15. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TROM. https://doi.org/10.1594/PANGAEA.862466
  16. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TSEA. https://doi.org/10.1594/PANGAEA.862467
  17. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TSKB. https://doi.org/10.1594/PANGAEA.862468
  18. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TWTF. https://doi.org/10.1594/PANGAEA.862469
  19. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station TXES. https://doi.org/10.1594/PANGAEA.862470
  20. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station UFPR. https://doi.org/10.1594/PANGAEA.862471
  21. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ULAB. https://doi.org/10.1594/PANGAEA.862472
  22. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station UNBJ. https://doi.org/10.1594/PANGAEA.862473
  23. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station UNSA. https://doi.org/10.1594/PANGAEA.862474
  24. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station URUM. https://doi.org/10.1594/PANGAEA.862475
  25. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station USN3. https://doi.org/10.1594/PANGAEA.862476
  26. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station USNA. https://doi.org/10.1594/PANGAEA.862477
  27. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station USNO. https://doi.org/10.1594/PANGAEA.862478
  28. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station USUD. https://doi.org/10.1594/PANGAEA.862479
  29. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VACO. https://doi.org/10.1594/PANGAEA.862480
  30. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VALD. https://doi.org/10.1594/PANGAEA.862481
  31. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VENE. https://doi.org/10.1594/PANGAEA.862482
  32. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VESL. https://doi.org/10.1594/PANGAEA.862483
  33. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VIL0. https://doi.org/10.1594/PANGAEA.862484
  34. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VILL. https://doi.org/10.1594/PANGAEA.862485
  35. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VIS0. https://doi.org/10.1594/PANGAEA.862486
  36. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station VTSP. https://doi.org/10.1594/PANGAEA.862487
  37. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WDC1. https://doi.org/10.1594/PANGAEA.862488
  38. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WDC3. https://doi.org/10.1594/PANGAEA.862489
  39. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WEL1. https://doi.org/10.1594/PANGAEA.862490
  40. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WES2. https://doi.org/10.1594/PANGAEA.862491
  41. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WETT. https://doi.org/10.1594/PANGAEA.862492
  42. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WGTN. https://doi.org/10.1594/PANGAEA.862493
  43. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WHIT. https://doi.org/10.1594/PANGAEA.862494
  44. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WILL. https://doi.org/10.1594/PANGAEA.862495
  45. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WIND. https://doi.org/10.1594/PANGAEA.862496
  46. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WROC. https://doi.org/10.1594/PANGAEA.862497
  47. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WSRT. https://doi.org/10.1594/PANGAEA.862498
  48. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WTZA. https://doi.org/10.1594/PANGAEA.862499
  49. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WTZR. https://doi.org/10.1594/PANGAEA.862500
  50. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WTZZ. https://doi.org/10.1594/PANGAEA.862501
  51. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station WUHN. https://doi.org/10.1594/PANGAEA.862502
  52. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station XIAN. https://doi.org/10.1594/PANGAEA.862503
  53. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station XMIS. https://doi.org/10.1594/PANGAEA.862504
  54. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YAKT. https://doi.org/10.1594/PANGAEA.862505
  55. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YAKZ. https://doi.org/10.1594/PANGAEA.862506
  56. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YAR1. https://doi.org/10.1594/PANGAEA.862507
  57. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YAR2. https://doi.org/10.1594/PANGAEA.862508
  58. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YAR3. https://doi.org/10.1594/PANGAEA.862509
  59. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YARR. https://doi.org/10.1594/PANGAEA.862510
  60. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YCBA. https://doi.org/10.1594/PANGAEA.862511
  61. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YEBE. https://doi.org/10.1594/PANGAEA.862512
  62. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YELL. https://doi.org/10.1594/PANGAEA.862513
  63. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YIBL. https://doi.org/10.1594/PANGAEA.862514
  64. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YKRO. https://doi.org/10.1594/PANGAEA.862515
  65. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station YSSK. https://doi.org/10.1594/PANGAEA.862516
  66. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZAMB. https://doi.org/10.1594/PANGAEA.862517
  67. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZECK. https://doi.org/10.1594/PANGAEA.862518
  68. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZIM2. https://doi.org/10.1594/PANGAEA.862519
  69. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZIMJ. https://doi.org/10.1594/PANGAEA.862520
  70. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZIMM. https://doi.org/10.1594/PANGAEA.862521
  71. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZWE2. https://doi.org/10.1594/PANGAEA.862522
  72. Wang, X (2016): GPS-derived precipitable water vapor content calculated for station ZWEN. https://doi.org/10.1594/PANGAEA.862523

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