An enhanced integrated water vapour dataset from more than 10&thinsp;000 global ground-based GPS stations in 2020

Yuan, Peng; Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Argus, Donald; Yin, Xungang; Van Malderen, Roeland; Mayer, Michael; Jiang, Weiping; Awange, Joseph; Kutterer, Hansjörg

doi:https://doi.org/10.5194/essd-15-723-2023

Articles | Volume 15, issue 2

https://doi.org/10.5194/essd-15-723-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Analysis of atmospheric water vapour observations and their...

https://doi.org/10.5194/essd-15-723-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 2

Data description paper

|

10 Feb 2023

Data description paper |

| 10 Feb 2023

An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020

Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer

Supplement

https://doi.org/10.5194/essd-15-723-2023-supplement

Data sets

An enhanced integrated water vapour dataset from more than 10,000 global ground-based GPS stations in 2020 P. Yuan, G. Blewitt, C. Kreemer, W. C. Hammond, D. Argus, X. Yin, R. Van Malderen, M. Mayer, W. Jiang, J. Awange, and H. Kutterer https://doi.org/10.5281/zenodo.6973528

Integrated Global Radiosonde Archive (IGRA) Version 2 NCEI https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00975

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Short summary

We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.