On the Impact of GPS Multipath Correction Maps and Post-Fit Residuals on Slant Wet Delays for Tracking Severe Weather Events

Climate change has increased the frequency and intensity of weather events with heavy precipitation, making communities worldwide more vulnerable to flash flooding. As a result, accurate fore- nowcasting impending excessive rainfall is crucial for warning mitigating these hydro-meteorological hazards. The measurement integrated water vapour along slant paths made possible by ground-based global positioning system (GPS) receiver networks, delivering three-dimensional (3D) distributions at low cost in real-time. data are an invaluable supplementary source knowledge monitoring storm determining their paths. However, it generally known that multipath effects GPS stations have influence on incoming signals, particularly elevations. Although estimates zenith total delay horizontal linear gradients make up majority products meteorology date, not sufficient understanding full 3D distribution above station. Direct utilization delays can address this lack azimuthal information, although, elevations prone (MP) errors. This study uses convective event happened 27 July 2017 over Bulgaria, Greece, Turkey, which caused floods severe damage, examine multipath-corrected wet (SWD) estimations events. First, we reconstructed one-way SWD adding post-fit phase residuals, describing anisotropic component SWD. Because MP errors observables considerably impact from individual satellites, used averaging technique build station-specific correction maps stacking residuals acquired precise point (PPP) processing strategy. was created spatially organizing into congruent cells optimal resolution terms elevation azimuth local horizon.This enables approximately equal numbers be distributed across each cell. Finally, using maps, improved use analysis. We found accounts 20% overall estimates. For station strongly influenced site-specific error, reach 4.3 mm equivalent precipitable vapour. result also showed spatio-temporal changes as measured closely reflected moisture field estimated numerical prediction model (ERA5 reanalysis) associated event.