Within TWIGA, in situ GNSS time series and satellite SAR maps of atmospheric water vapor contents will be used to enhance the predictability of convective storms.
This will be achieved by assimilating these products into Numerical Weather Prediction Models (NWP).
The Weather and Research Forecasting (WRF) model has been selected to perform the assimilation experiments. Sensitivity tests on the setup of the model for the prediction of heavy rain events in tropical regions are needed to account for the specific weather dynamics of those areas.
Two case studies of heavy rains in southern Africa region have been selected: January 2017 and March 2018, by looking at the Floodlist archive. A validation against in situ observations, from TAHMO network and from the SAWS network, both available through the HydroNet platform will follow.
WRF numerical domains (d01, d02, d03) at 13.5, 4.5 and 1.5 km
horizontal resolutions and the location of all the geodetic stations available.
The color shading shows the model orography
For the selected events, data from available GNSS permanent stations have been processed obtaining time series of atmospheric delays. These products will be used for the next assimilation experiments.
GNSS atmospheric delays time series of some geodetic permanent stations
in the area of the heavy precipitation event in January 2017.
Preliminary results on sensitivity tests consist of cumulated rain maps for three different turbulence schemes. By comparing these predictions with corresponding observed maps we will be able to select the best setup.
Maps of cumulated rain between January 4th and 7th simulated with three different turbulence schemes.
Written by Giovanna Venuti
Politecnico di Milano
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.