In addition to positioning and navigation, GNSS (Global Navigation Satellite Systems, such as GPS, GLONASS, Galileo or BeiDou) signals are also used to determine the atmospheric water vapor content. Such data have been used for more than two decades in weather forecasting and climate research. Water vapor is a very important gas for the greenhouse effect and the heat balance of our earth.
Together with OSZ Lise Meitner School in Berlin, Germany (https://www.osz-lise-meitner.eu/) and other international partners, GFZ has launched the European TRYAT project (https://www.tryat.eu/) in 2017. The main goal of TRYAT is the international exchange of learners, teachers and researchers and the creation of open educational resources on the relevant subject areas of physics, meteorology, computer science and electrical engineering. The GFZ has installed three GNSS receivers on the roofs of school buildings in Berlin (station TAD3), Pau (France, station TAF1) and Naples (Italy, station TAI1), and continuously processes the data in near real-time. Learners can query and evaluate these satellite data in an online learning platform and link them to their own measurements (e.g., via smartphone or a do-it-yourself weather station).
GNSS-derived tropospheric products, such as Integrated Water Vapour (IWV) and Slant Total Delays (STDs) are compared daily to corresponding tropospheric parameters, provided by the global numerical weather model ERA5 of the European Centre for Medium-Range Weather Forecasts (ECMWF) (https://www.ecmwf.int/). The following links provide access to results of these comparisons for the three TRYAT stations at Berlin, Pau and Naples. One can see a good agreement between the weather model and the IWV measurements based on GNSS.
The GFZ processes GNSS data of the TRYAT stations very fast and continuously around the clock. Together with GNSS-derived tropospheric products from different regional and global GNSS networks, they are used by several weather services as, e.g., U.K. Met Office, Météo-France and the German DWD for their day-by-day forecasts.