Towards near real-time atmospheric water vapor monitoring in Africa
Water vapour content of the atmosphere lowest layer (up to about 15 km from the ground), which is known as troposphere or neutral atmosphere, affects GNSS satellite signals propagation velocities, causing delays in their observation from ground-based stations. Based on a proper analysis of such data, one can quantify this delay and therefore have an indirect observation of the water vapour content along the signal travel path.
In recent years, time series of zenith total delays (ZTDs) obtained as by-product of high-accuracy GNSS positioning have started to be assimilated into numerical weather prediction models. Several countries have already established country-wide networks of permanent GNSS stations, typically for precise positioning and surveying purposes. The figure below shows the current distribution of GNSS stations in Africa.
GNSS observations from such networks can be used to monitor the ZTD (and/or the integrated water vapour) continuously. GNSS networks established to provide positioning services are already designed to provide real-time streams of GNSS data over the Internet, which allows to set up a near real-time data processing system for ZTD estimation.
Realizing a working near real-time monitoring system of ZTD in Africa is a fundamental step to improving numerical weather forecasts, which is particularly useful for extreme events such as convective thunderstorms.
In the framework of the TWIGA project, GReD is setting up a demonstrator of a near real-time ZTD monitoring system. Now the demonstrator is working on five GNSS stations belonging to the International GNSS Service (IGS). The following figure shows the current TWIGA portal displaying near real-time estimates of ZTD for the IGS station in Accra, Ghana.
In the next few months, it will be extended to other African GNSS stations providing real-time data streams, including the TWIGA GNSS networks in Uganda and Kenya.
Written by: Eugenio Realini
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No.776691. The opinions expressed on the web page are of the authors only and no way reflect the European Commission’s opinions. The European Union is not liable for any use that may be made of the information.