Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 19
Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-6987-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-6987-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 19
Development and technical paper
 | 
10 Oct 2025
Development and technical paper |  | 10 Oct 2025

A hybrid-grid global model for the estimation of atmospheric weighted mean temperature considering time-varying vertical adjustment rate in GNSS precipitable water vapour retrieval

Shaofeng Xie, Jihong Zhang, Liangke Huang, Fade Chen, Yongfeng Wu, Yijie Wang, and Lilong Liu

Viewed

Total article views: 3,681 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,335 1,064 282 3,681 250 319
  • HTML: 2,335
  • PDF: 1,064
  • XML: 282
  • Total: 3,681
  • BibTeX: 250
  • EndNote: 319
Views and downloads (calculated since 11 Apr 2024)
Cumulative views and downloads (calculated since 11 Apr 2024)

Viewed (geographical distribution)

Total article views: 3,681 (including HTML, PDF, and XML) Thereof 3,635 with geography defined and 46 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 06 Nov 2026
Download
Short summary
We developed a new global atmospheric weighted mean temperature (Tm) model considering time-varying vertical adjustment rate. Firstly, a global Tm vertical adjustment rate model (NGGTm-H) was developed using the sliding-window algorithm. Secondly, the daily variation characteristics of Tm and its relationships with geographical situations were investigated. Finally, a hybrid-grid global Tm model considering the time-varying vertical adjustment rate (NGGTm) was developed.
Read more
Share
Altmetrics
Final-revised paper
Preprint