The ability to do atmospheric sensing of the neutral atmosphere (troposphere and stratosphere) by space geodetic techniques has improved considerably over the last decade as a result of technological advances, larger regional and global ground-based networks, satellite-based missions and developments of appropriate models and algorithms. Water vapour is under sampled in current operational meteorological and climate observing systems. Advancements in Numerical Weather Prediction (NWP) Models (higher resolution and hourly cycling update), to improve forecasting of extreme precipitation, requires GNSS observations with a high resolution in space and short delivery times than currently available. The existence of more than 15 years of homogeneously reprocessed observations from permanent GNSS stations on a regional and global scale has high potential for monitoring trends and variability in atmospheric water vapour. This will enable the evaluation of systematic biases from several instruments, improve the knowledge of climatic trends of atmospheric water vapour and also be of benefit to global and regional NWP reanalyses and climate model simulations. NWP data has recently been used for deriving improved mapping functions. In Real-Time GNSS processing there is currently an interest in using atmospheric NWP data to initialise Precise Point Positioning (PPP) processing algorithms which can provide shorter convergence time and improve positioning.
We welcome contributions on the subjects below, but notice that also other subjects are welcome. Physical modelling of the neutral atmosphere using ground-based and radio-occultation data. Multi-GNSS (GPS, GLONASS, GALILEO, BEIDOU, ..), Real-Time and reprocessed tropospheric products. Studies on how to mitigate atmospheric effects for improving GNSS positioning and navigation, as well as observations at radio wavelengths. Technique validation, inter-technique comparisons and inter-system bias calibration. Usage of GNSS measurements in weather forecasting (e.g., NWP and now-casting) and in climate monitoring. Usage of NWP data in PPP processing algorithms.