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Dataset . 2022
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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An enhanced integrated water vapour dataset from more than 10,000 global ground-based GPS stations in 2020

Authors: Yuan, Peng; Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Argus, Donald; Yin, Xungang; Van Malderen, Roeland; +4 Authors

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

Abstract

This is a 5-min Integrated Water Vapor (IWV) product from 12,552 ground-based GPS stations worldwide in 2020. It contains 1,093,591,492 IWV estimates in total. The dataset is an enhanced version of the existing operational GPS IWV dataset from 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. DESCRIPTION Geodetic Institute, Karlsruhe Institute of Technology, Germany OUTPUT 5-min enhanced GPS Integrated Water Vapour product CONTACT Peng Yuan, pyuan@gfz-potsdam.de; Geoffrey Blewitt, gblewitt@unr.edu INPUT NGL: GPS ZTD; ERA5 pressure level product: pressure and Tm NGL: Nevada Geodetic Laboratory, University of Nevada, http://geodesy.unr.edu ERA5: the fifth generation ECMWF reanalysis, https://www.ecmwf.int Authors: Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, Hansjoerg Kutterer Detailed descriptions and quality evaluations of the dataset have been published in Earth System Science Data (see below). If you would like to use the dataset, please cite the dataset and the associated paper as follows: [1] Yuan, P., Blewitt, G., Kreemer, C., Hammond, W. C., Argus, D., Yin, X., Van Malderen, R., Mayer, M., Jiang, W., Awange, J., and Kutterer, H.: An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020, Earth System Science Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, 2023. [2] Yuan, Peng, Blewitt, Geoffrey, Kreemer, Corné, Hammond, William C., Argus, Donald, Yin, Xungang, Van Malderen, Roeland, Mayer, Michael, Jiang, Weiping, Awange, Joseph, & Kutterer, Hansjörg. (2022). An enhanced integrated water vapour dataset from more than 10,000 global ground-based GPS stations in 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6973528 >>File: NGL2020_12552_blgph.txtDescription: coordinates of the 12552 GPS stations worldwideFormat: column #1: Site name column #2: Latitude (degree) column #3: Longitude (degree) column #4: Geopotential altitude (geopotential meter) >>ZIP files: data saved according to the first letter of the station namesDescription: enhanced GPS IWV data product at 12552 stations worldwideStructure: saved as each day for each station, and then all the daily files of each station were saved as respective ZIP file which named as "site"_2020.trop.zipFormat: IGS TROP format

We are grateful to NGL for providing the GPS ZTD products and many institutions for sharing the continuous GPS observations. We also thank ECMWF, TUW, and NCEI for providing the ERA5, TUW, IGRA radiosonde, and ISD synoptic data. This work was funded at KIT with the German Research Foundation (DFG, project number: 321886779). This work was funded at NGL with NASA grants 80NSSC19K1044 and 80NSSC22K0463. If you would like to use the dataset, please cite the dataset and the associated paper with the information provided in the dataset description.

Keywords

Water Vapor, GPS, IWV

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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