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table1
table1
Table 1: Average IPW bias and RMSD between IGS data and co-located techniques.

Comparison

No. of co-located sites

Avg. points per site

Bias

RMSD

Avg. [mm]

Range [mm]

Avg. [mm]

Range [mm]

ERA5–IGS daily

18

46 894

0.15

-0.9 to 0.93

1.46

0.93 to 2.6

GRUAN RS–IGS  daily

2

704

0.23

0.11 to 0.36

0.91

0.6 to 1.23

IGRA–IGS daily

15

2 054

0.43

-0.9 to 1.84

1.64

0.73 to 2.27

MWR–IGS daily

1

3 120

0.64

1.21

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figure5
figure5


Figure 5: IPW differences in IGRA−IGS daily, ERA5−IGS daily, MWR−IGS daily, and GRUAN RS−IGS daily co-location datasets.

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 IGS and EPN dataset tabular description

Table 2. Metadata table

standard name

description

report_id

This parameter starts from 1 for the first data report provided in the data file, and is incremented for each new report.

report_timestampObservation date time UTC
station_nameGNSS station identifier
cityCity name
latitudeLatitude deg. North
longitudeLongitude deg. East
height_of_station_above_sea_levelAltitude above mean sea level

Table 3. Data table 

standard name

description

zenith_total_delayIt is one of the final products from geodetic GNSS data processing software, characterizing a delay of the GNSS signal on the path from a satellite to the receiver due to atmospheric refraction and bending, mapped into zenith direction. The numerical value of the zenith total delay correlates with the amount of total column water vapour (i.e., not including liquid water and/or ice) overhead the GNSS receiver antenna.
uncertainty_value1Rough estimate of standard uncertainty equivalent to 1-sigma uncertainty of zenith total delay
total_column_water_vapourTotal column water vapour derived from ZTD and ancillary meteorological data
uncertainty_value5Total uncertainty of GNSS total column water vapour
total_column_water_vapour_era5Total column water vapour retrieved from ERA5 at the station coordinates and altitude

Product Availability and data licenses

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Jupyter notebook(s) at the following location provide examples on how to read, plot, and reorganize the data:

Jupyter ViewernotebookUrlhttps://github.com/ecmwf-projects/dss-notebooks/blob/main/datasets/insitu-observations-gnss/In-situ observations GNSS: download-and-explore.ipynb

References

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ref1
ref1
[1]     Thorne, P. W., Madonna, F., Schulz, J., Oakley, T., Ingleby, B., Rosoldi, M., Tramutola, E., Arola, A., Buschmann, M., Mikalsen, A. C., Davy, R., Voces, C., Kreher, K., De Maziere, M., and Pappalardo, G.: Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment, Geosci. Instrum. Method. Data Syst., 6, 453–472, 2017, https://doi.org/10.5194/gi-6-453-2017.

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