- 1University of New Brunswick, Fredericton, Canada (msantos@unb.ca)
- 2e-Geos/ASI/ Centro di Geodesia Spaziale, Matera, Italy
- 3Federal Agency for Cartography and Geodesy (BKG), Frankfurt am Main, Germany
- 4US Naval Observatory, Washington, United States
- 5GFZ German Research Centre for Geosciences, Potsdam, Germany
- 6The Met Office, Exeter, United Kingdom
- 7Tallinn University of Technology, Tallinn, Estonia
- 8Military University of Technology, Warsaw, Poland
- 9Wuhan University, Wuhan, China
- 10Instituto Militar de Engenharia, Rio de Janeiro, Brazil
- 11Université Paris Cité, Paris, France
- 12Natural Resources Canada, Ottawa, Canada
- 13Universidad de O’Higgins, Rancagua, Chile
- 14Universidad de Chile, Santiago, Chile
- 15Univ Gustave Eiffel, Marne-la-Vallée, France
GNSS Zenith Total Delay (ZTD) estimates are quantities of great interest by climate modellers since atmospheric water vapour is the major greenhouse gas. Therefore, the importance of its accurate, long-term monitoring and evaluation of trends and variability, potentially serving as independent benchmarks to climatological models, both on longer trends derived from GNSS, but also shorter trends, which could be used for assimilation and validation of climate models. ZTD estimates are determined on a regular basis by several processing centers as well as by demand. It has also been demonstrated that series of ZTD estimates can be used for quality control purposes. At the same time, GNSS reached the “maturity age” of 30 years when climate normals of ZTD and gradients can be derived. But what would be the best ZTD series to serve the climate community? What series would offer the most realistic trends? This poster discusses an on-going investigation under the auspices of the International Association of Geodesy, through a joint working group nested within the Inter-Commission Committee on Geodesy for Climate Research. In a previous study, we made use of the ZTD series derived by the third reprocessing campaign (REPRO3), based on a variety of processing modes and models. But this study was partial as the ZTD times series estimated by the Analysis Centers were not covering the same periods. This time, ZTD time series are generated using dedicated PPP scientific software suites. The generated trends are to be compared and analysed.
How to cite: C. Santos, M., Pacione, R., Balidakis, K., Byrant, S., Dick, G., Hughes, R., Jones, J., Keernik, H., Klos, A., Lou, Y., Marques, H., Nahmani, S., Nikolaidou, T., Rannat, K., Valenzuela, R., Weixing, Z., Yao, Y., and Yuan, P.: Ground-GNSS ZTD trends for climate models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11277, https://doi.org/10.5194/egusphere-egu25-11277, 2025.