Atmospheric water vapor plays a prominent role in climate change and atmospheric, meteorological, and hydrological processes. Because of its high spatiotemporal variability, precise quantification of water vapor is challenging. This study investigates Integrated Water Vapor (IWV) variability for the period 1995–2010 at 118 globally distributed Global Positioning System (GPS) sites, using additional UV/VIS satellite retrievals by GOME, SCIAMACHY, and GOME-2 (denoted as GOMESCIA below), plus ERA-Interim reanalysis output. Apart from spatial representativeness differences, particularly at coastal and island sites, all three IWV datasets correlate well with the lowest mean correlation coefficient of 0.878 (averaged over all the sites) between GPS and GOMESCIA. We confirm the dominance of standard lognormal distribution of the IWV time series, which can be explained by the combination of a lower mode (dry season characterized by a standard lognormal distribution with a low median value) and an upper mode (wet season characterized by a reverse lognormal distribution with high median value) in European, Western American, and subtropical sites. Despite the relatively short length of the time series, we found a good consistency in the sign of the continental IWV trends, not only between the different datasets, but also compared to temperature and precipitation trends.

In climate research, the role of water vapour can hardly be overestimated. Water vapour is the most important natural greenhouse gas and is responsible for the largest known feedback mechanism for amplifying climate change. It also strongly influences atmospheric dynamics and the hydrologic cycle through surface evaporation, latent heat transport and diabatic heating, and is, in particular, a source of clouds and precipitation.Atmospheric water vapour is highly variable, both in space and in time. Therefore, measuring it remains a demanding and challenging task. The Zenith Total Delay (ZTD) estimated from GNSS observations, provided at a temporal resolution of minutes and under all weather conditions, can be converted to Integrated Water Vapour (IWV), if additional meteorological variables are available. Inconsistencies introduced into long-term time series from improved GNSS processing algorithms, instrumental, and environmental changes at GNSS stations make climate trend analyses challenging. Ongoing re-processing efforts using state-of-the-art models aim at providing consistent time series of tropospheric data, using 24+ years of GNSS observations from global and regional networks. GNSS is reaching the “maturity age” of 30 years when climate normal of ZTD/IWV (and horizontal gradients) can be derived. Being not assimilated in numerical weather prediction model reanalyses, GNSS products can also be used as independent datasets to validate climate model outputs (ZTD/IWV). However, what is the actual use of GNSS ZTDs in climate monitoring? What are the advantages of using GNSS ZTDs for climate monitoring? In addition, what would be the best ZTD time series to serve the climate community?The presentation will provide a review of the progress made in and the status of using GNSS tropospheric datasets for climate research, highlighting the challenges and pitfalls, and outlining the major remaining steps ahead. We will show examples demonstrating the benefits for climate monitoring brought by using GNSS ZTD and/or IWV datasets in complement to other observations.This contribution is related to the activities of JWG C.2: Quality control methods for climate applications of geodetic tropospheric parameters, https://iccc.iag-aig.org/joint-work-groups/216, of the IAG Inter-Commission Committee on "Geodesy for Climate Research" (ICCC).

The Global Climate Observing System (GCOS), supported by a number of international partners and the World Meteorological Organization (WMO), is establishing a reference climate observation network, the GCOS Reference Upper Air Network (GRUAN). Currently, this network comprises 30 reference sites worldwide, designed to detect long-term trends of key climate variables such as temperature and humidity in the upper atmosphere, thus providing a cornerstone to more reliable monitoring of signals of global and regional climate change. GRUAN observations are required to be of reference quality, with known biases removed and with an associated uncertainty value, based on thorough characterization of all sources of measurement.In support of these goals, GNSS precipitable water (GNSS-PW) measurement has been included as a priority one measurement of the essential climate variable water vapor. In addition, a minimum of twice daily measurements (ideally hourly measurement) of PW are required as entrance to the GRUAN program. GNSS-PW is the primary means to accomplish this entrance requirement. The GNSS-PW program produces a nearly continuous reference measurement of PW and is therefore a substantial part of GRUAN. GFZ contributes to GRUAN with its expertise in processing of ground-based GNSS network data to generate precise PW products. Since 2013, GFZ hosts a GRUAN central processing facility for the GNSS-PW. GFZ is responsible for the installation of GNSS hardware, data transfer, processing and archiving, derivation of GNSS PW products according to GRUAN requirements including PW uncertainty estimation, as well as for quality check and archiving of the GNSS-PW products. Currently half of the GRUAN sites are equipped with GNSS receivers. At the beginning of this year the data processing of GNSS-PW and its associated documentation has been GRUAN certified. GNSS-PW products including uncertainty estimation and results of selected validation studies are presented.