The precision of sea surface altimetry using bistatically reflected signals of the Global Navigation Satellite System (GNSS) is typically one to two orders of magnitude worse than dedicated radar altimeters. However, when the scattering is coherent, the electromagnetic phase of the carrier signal can be tracked, providing precise ranging measurements. Under grazing angle (GA) geometries, the conditions for coherent scattering are maximized, enabling carrier phase-delay altimetric techniques over sea waters. This work presents the first implementation of GA carrier phase sea surface altimetry using data acquired from a spaceborne platform (NASA Cyclone GNSS mission) and transmitted from both GPS and Galileo constellations. The altimetric results show that the measurement system precision is 3/4.1 cm (median/mean) at 20 Hz sampling, cm level at 1 Hz, comparable to dedicated radar altimeters. The combined precision, including systematic errors, is 16/20 cm (median/mean) precision at 50 ms integration (a few cm level at 1 Hz). The wind and wave requirements to enable coherent scattering at GA geometries appear to be below 6 m/s wind and 1.5 m significant wave height, although only 33% of tracks under these conditions present sufficient coherence. Given that this technique could be implemented by firmware updates of existing GNSS radio occultation missions, and given the large number of such missions, the study indicates that the resulting precision and spatio–temporal resolution would contribute to resolving some submesoscale ocean signals.

The multiconstellation Global Navigation Satellite Systems (GNSS) (e.g., GPS, GLObal NAvigation Satellite System (GLONASS), Galileo, and BeiDou) offers great opportunities for real‐time retrieval of atmospheric parameters for supporting numerical weather prediction nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined to retrieve atmospheric parameters based on the real‐time precise point positioning technique. The atmospheric parameters, retrieved from multi‐GNSS observations of a 180 day period from about 100 globally distributed stations, including zenith total delay, integrated water vapor, horizontal gradient, and slant total delay (STD), are analyzed and evaluated. The water vapor radiometer data and a numerical weather model, the operational analysis of the European Centre for Medium‐Range Weather Forecasts (ECMWF), are used to independently validate the performance of individual GNSS and also demonstrate the benefits of multiconstellation GNSS for real‐time atmospheric monitoring. Our results show that the GLONASS and BeiDou have the potential capability for real‐time atmospheric parameter retrieval for time‐critical meteorological applications as GPS does, and the combination of multi‐GNSS observations can improve the performance of a single‐system solution in meteorological applications with higher accuracy and robustness. The multi‐GNSS processing greatly increases the number of STDs. The mean and standard deviation of STDs between each GNSS and ECMWF exhibit a good stability as function of the elevation angle, the azimuth angle, and time, in general. An obvious latitude dependence is confirmed by a map of station specific mean and standard deviations. Such real‐time atmospheric products, provided by multi‐GNSS processing with higher accuracy, stronger reliability, and better distribution, might be highly valuable for atmospheric sounding systems, especially for nowcasting of extreme weather.

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.

Accurate tropospheric delays from Numerical Weather Models (NWM) are an important input to space geodetic techniques, especially for precise real‐time Global Navigation Satellite Systems, which are indispensable to earthquake and tsunami early warning systems as well as weather forecasting. The NWM‐based tropospheric delays are currently provided either site‐specific with a limited spatial coverage, or on two‐dimensional grids close to the Earth surface, which cannot be used for high altitudes. We introduce a new method of representing NWM‐derived tropospheric zenith hydrostatic and wet delays. A large volume of NWM‐derived data is parameterized with surface values and additional two or three coefficients for their vertical scaling to heights up to 14 km. A precision of 1–2 mm is achieved for reconstructing delays to the NWM‐determined delays at any altitudes. The method can efficiently deliver NWM‐derived tropospheric delays to a broader community of space geodetic techniques.