The research activity concerned the development of an innovative methodology to monitor the content of Precipitable Water Vapour (PWV), starting from Zenith Tropospheric Delay (ZTD) estimations obtained from GNSS permanent stations, and Pressure (P) and Temperature (T) observed in meteorological sensors networks. In particular, an automatized procedure, named G4M (GNSS for Meteorology), for preparing and elaborating the data collected from the existing infrastructures and for producing PWV maps will be presented. The G4M procedure has been applied to study two critical events occurred on Genoa city; this analysis led to the definition of a “Heterogeneity Index”, accounting for PWV spatial variability, which has been considered a promising indicator to highlight and locate severe meteorological events in time and space. Additionally, ZTD and PWV time series have been obtained for selected GNSS Permanent Stations in order to identify recognizable patterns in ZTD/PWV that can be related to the occurrence of severe meteorological events.

GNSS contribution to monitor severe rainfalls: an innovative procedure for wide and orographically complex area with existing infrastructures

FERRANDO, ILARIA
2017-03-30

Abstract

The research activity concerned the development of an innovative methodology to monitor the content of Precipitable Water Vapour (PWV), starting from Zenith Tropospheric Delay (ZTD) estimations obtained from GNSS permanent stations, and Pressure (P) and Temperature (T) observed in meteorological sensors networks. In particular, an automatized procedure, named G4M (GNSS for Meteorology), for preparing and elaborating the data collected from the existing infrastructures and for producing PWV maps will be presented. The G4M procedure has been applied to study two critical events occurred on Genoa city; this analysis led to the definition of a “Heterogeneity Index”, accounting for PWV spatial variability, which has been considered a promising indicator to highlight and locate severe meteorological events in time and space. Additionally, ZTD and PWV time series have been obtained for selected GNSS Permanent Stations in order to identify recognizable patterns in ZTD/PWV that can be related to the occurrence of severe meteorological events.
30-mar-2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1018656
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