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https://doi.org/10.5194/egusphere-2024-2716
https://doi.org/10.5194/egusphere-2024-2716
02 Oct 2024
 | 02 Oct 2024

Atmospheric horizontal gradients measured with eight co-located GNSS stations and a microwave radiometer

Ning Tong and Gunnar Elgered

Abstract. We have used eight co-located GNSS stations, with different antenna mounts, to estimate atmospheric signal propagation delays in the zenith direction
and linear horizontal gradients. The gradients are compared with the results from a water vapour radiometer (WVR).  Water drops in the atmosphere has a negative influence on the retrieval accuracy of the WVR. Hence we see a better agreement using WVR data with a liquid water content (LWC) less than 0.05 mm compared to when LWC values of up to 0.7 mm are included. We have used two different constraints when estimating the linear gradients from the GNSS data. Using a weak constraint enhances the GNSS estimates to track large gradients of short duration at the cost of increased formal errors. To mitigate random noise in the GNSS data, we adopted a fusion approach averaging estimates from the GNSS stations. This resulted in significant improvements for the agreement with WVR data, a maximum of 17 % increase in the correlation and an 14 % reduction in the root-mean-square (rms) difference for the east gradients. The corresponding values for the north gradients are both 25 %. Overall, no large differences in terms of quality is  observed for the eight GNSS stations. However, one station shows slightly poorer agreement for  the north gradients compared to the others.  This is attributed to the station's proximity to a radio telescope, which causes data loss of observations at low elevation angles in the south-south-west direction. 

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Journal article(s) based on this preprint

09 May 2025
Atmospheric horizontal gradients measured with eight co-located GNSS stations and a microwave radiometer
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 18, 2069–2082, https://doi.org/10.5194/amt-18-2069-2025,https://doi.org/10.5194/amt-18-2069-2025, 2025
Short summary
Ning Tong and Gunnar Elgered

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2716', Anonymous Referee #1, 07 Nov 2024
  • RC2: 'Comment on egusphere-2024-2716', Anonymous Referee #2, 09 Jan 2025

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2716', Anonymous Referee #1, 07 Nov 2024
  • RC2: 'Comment on egusphere-2024-2716', Anonymous Referee #2, 09 Jan 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Tong Ning on behalf of the Authors (04 Feb 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (06 Feb 2025) by Roeland Van Malderen
RR by Anonymous Referee #2 (19 Feb 2025)
ED: Publish subject to technical corrections (27 Feb 2025) by Roeland Van Malderen
AR by Tong Ning on behalf of the Authors (28 Feb 2025)  Manuscript 

Journal article(s) based on this preprint

09 May 2025
Atmospheric horizontal gradients measured with eight co-located GNSS stations and a microwave radiometer
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 18, 2069–2082, https://doi.org/10.5194/amt-18-2069-2025,https://doi.org/10.5194/amt-18-2069-2025, 2025
Short summary
Ning Tong and Gunnar Elgered
Ning Tong and Gunnar Elgered

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Short summary
The gradients estimated from multi-GNSS data were compared to WVR data. A better agreement is obtained when using WVR data with a smaller value of liquid water content. A weak constraint in GNSS data processing may be desirable for applications with a higher tolerance for formal errors but a greater focus on tracking the variability of water vapour. The averaged GNSS gradients can significantly reduce the random noise which can be used to obtain a more reliable variability of the water vapour.
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