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Journal of Geodesy

, Volume 93, Issue 10, pp 1897–1909 | Cite as

On the suitability of ERA5 in hourly GPS precipitable water vapor retrieval over China

  • W. Zhang
  • H. Zhang
  • H. LiangEmail author
  • Y. Lou
  • Y. Cai
  • Y. Cao
  • Y. Zhou
  • W. Liu
Original Article
  • 279 Downloads

Abstract

The latest ECMWF global reanalysis, ERA5, is able to provide hourly surface pressure and water vapor-weighted mean temperature (Tm), which are two key factors in GPS precipitable water vapor (PWV) retrieval. Performance of surface pressure, surface air temperature, and Tm derived from ERA5 and its predecessor ERA-Interim (ERAI) are evaluated by comparing with more than 2000 meteorological stations and 89 radiosonde stations in the year of 2016 over China. Average pressure error RMS is 0.7 hPa for ERA5, compared to 1.0 hPa for ERAI, and ERA5 pressure diurnal variations agree much better than ERAI with in situ measurements. Temperature and Tm differences between ERA5 and ERAI are relatively smaller, with error RMS of 1.8 K and 1.6 K for ERA5-derived temperature and Tm, respectively. PWV error contributed by reanalysis-derived parameters is also estimated. The ERA5-induced PWV error is generally less than 1 mm, with smaller errors (< 0.4 mm) in eastern China but larger errors (can exceed 0.6 mm) in northwestern China and in the southeast of the Tibetan Plateau. Diurnal variations of PWV retrieved using pressure and Tm from meteorological measurements (MET) and reanalysis products are compared. Good agreements are found between ERA5-based PWV and MET-based PWV in diurnal variations, while artificial diurnal signals are introduced in ERAI-based PWV, especially in the Tibetan Plateau. This study indicates that ERA5 can support high-accuracy hourly GPS PWV retrieval over China without contaminating the diurnal cycles, which is of great importance for historical GPS PWV retrieval at stations without collocated meteorological sensors equipped.

Keywords

Precipitable water vapor GPS ERA5 ERA-interim Diurnal variation 

Notes

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2016YFB0501800), the National Natural Science Foundation of China (41774036; 41804023), the China Postdoctoral Science Foundation funded project (2017M622518), and the Natural Science Foundation of Hubei Province of China (2018CFB193).

Author Contributions

H. Liang, W. Zhang and Y. Lou designed the research; W. Zhang, H. Zhang, Y. Zhou and W. Liu analyzed the data; Y. Lou, Y. Cai and Y. Cao performed the research. W. Zhang drafted the paper; all authors discussed and commented on the manuscript.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.GNSS Research CenterWuhan UniversityWuhanChina
  2. 2.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina
  3. 3.Meteorological Observation Centre of China Meteorological AdministrationBeijingChina
  4. 4.China Research & Development Academy of Machinery EquipmentBeijingChina

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