Global navigation satellite systems (GNSSs) have revolutionised positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is now an established atmospheric observing system, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60–70 % of atmospheric warming. In Europe, the application of GNSS in meteorology started roughly two decades ago, and today it is a well-established field in both research and operation. This review covers the state of the art in GNSS meteorology in Europe. The advances in GNSS processing for derivation of tropospheric products, application of GNSS tropospheric products in operational weather prediction and application of GNSS tropospheric products for climate monitoring are discussed. The GNSS processing techniques and tropospheric products are reviewed. A summary of the use of the products for validation and impact studies with operational numerical weather prediction (NWP) models as well as very short weather prediction (nowcasting) case studies is given. Climate research with GNSSs is an emerging field of research, but the studies so far have been limited to comparison with climate models and derivation of trends. More than 15 years of GNSS meteorology in Europe has already achieved outstanding cooperation between the atmospheric and geodetic communities. It is now feasible to develop next-generation GNSS tropospheric products and applications that can enhance the quality of weather forecasts and climate monitoring. This work is carried out within COST Action ES1206 advanced global navigation satellite systems tropospheric products for monitoring severe weather events and climate (GNSS4SWEC, http://gnss4swec.knmi.nl).

A new concept is described for calculating the tropospheric zenith wet delay (ZWD) and its vertical approximation derived from the original profile of meteorological data. A new parameter of ZWD exponential decay is introduced which, together with a reference value, represents ZWD corrections accurately up to 10 km altitude. The new parameter considerably improves ZWD vertical reduction and surface ZWD calculation using the model of Askne and Nordius (1987). This development reduces the original large data set of a numerical weather model to an accurate grid representation at a reference level that may be more effectively disseminated. This can be used in regional augmentation models for precise positioning and navigation.

Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013–2017) are described in the paper. This campaign has aimed to support the development and validation of advanced Global Navigation Satellite System (GNSS) tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTDs) and tropospheric gradients derived from a dense permanent network. A complex data set was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from GNSS products and numerical weather models (NWMs) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities, and thus a potential for improvements of a synergy in their optimal exploitations in future. Reference GNSS and NWM results were intercompared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim reanalysis resulted in accuracy at the 10 mm level in terms of the root mean square (rms) with a negligible overall bias, comparisons to Global Forecast System (GFS) forecasts showed accuracy at the 12 mm level with the overall bias of −5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in accuracy at the 8 mm level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications, such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. In an initial study on the contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather, the effect reached up to 17 mm, and it was suggested that hydrometeors should be carefully accounted for within the functional model. The reference products will be further exploited in various specific studies using the Benchmark data set. It is thus going to play a key role in these highly interdisciplinary developments towards better mutual benefits from advanced GNSS and meteorological products.

In a previous study we developed an elegant technique to compute the signal travel time delay due to the neutral atmosphere, also known as slant total delay (STD), between a Global Positioning System (GPS) satellite and a ground‐based receiver utilizing data from a numerical weather model (NWM). Currently, we make use of NWM data from the Global Forecast System (GFS) because short‐range forecasts are easily accessible. In this study we introduce some modifications which double the speed of our algorithm without altering its precision; on an ordinary PC (using a single core) we compute about 2000 STDs per second with a precision of about 1 mm. The data throughput and precision are independent of the vacuum elevation (azimuth) angle of the receiver satellite link. Hence, the algorithm allows the computation of STDs in a mesobeta‐scale NWM with an unprecedented speed and precision. A practical by‐product of the algorithm is introduced as well; the Potsdam Mapping Factors (PMFs), which are generated by fast direct mapping utilizing short‐range GFS forecasts. In fact, it appears that the PMFs make the application of parameterized mapping in GPS processing obsolete.