GNSS Meteorology in Support of Severe Weather Forecasting

Abstract

This Master thesis aims at proving the applicability of GNSS meteorology technique for severe weather forecasting. It provides the analysis of tropospheric products obtained by processing data from the network of 210 GNSS station in Bernese GNSS software with PPP technique. Dataset was collected for two months period from 1st of May to 30th of June 2016 when severe weather events occurred in Western Europe, particularly in Netherlands, Germany, France, Belgium, southern part of Great Britain and caused flooding. Zenith wet delays and horizontal tropospheric gradients estimated from GNSS stations in Bernese GNSS software were validated against tropospheric parameters from ERA-Interim NWM and official final products from IGS. The results obtained from all independent datasets were statistically compared and visually analyzed using animated time series maps. This comparison proves a good agreement between tropospheric parameters derived from dataset from GNSS stations, from IGS and NWM. Mean bias of zenith total delays estimated from GNSS and NWM at each GNSS station is 2.6 mm, mean standard deviation is 11 mm. These results reassure that GNSS meteorology technique has a good potential for severe weather event monitoring and nowcasting.