The GNSS for Meteorology (G4M) Procedure and Its Application to Four Significant Weather Events
The authors conceived the GNSS for Meteorology (G4M) procedure to remote-sense the Precipitable Water Vapor (PWV) content in atmosphere with the aim to detect severe meteorological phenomena. It can be applied over an orographically complex area, exploiti
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Abstract
The authors conceived the GNSS for Meteorology (G4M) procedure to remote-sense the Precipitable Water Vapor (PWV) content in atmosphere with the aim to detect severe meteorological phenomena. It can be applied over an orographically complex area, exploiting existing networks of Global Navigation Satellite System (GNSS) Permanent Stations (PSs) and spread meteorological sensors, not necessarily co-located. The results of a posteriori analysis of four significant meteorological events are here presented, also in comparison with rain gauge data, to show the effectiveness of the method. The potentiality of G4M to detect and locate in space and time intense rainfall events is highlighted. The upcoming application of G4M in near-real time could provide a valuable support to existing Decision Support System for meteorological alerts. Keywords
GNSS for Meteorology (G4M) procedure Precipitable Water Vapor (PWV) Severe meteorological events monitoring
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Introduction
The use of Global Navigation Satellite System (GNSS) allows the monitoring of meteorological phenomena, including severe ones, at detailed temporal and spatial scales. It is independent from the other observation techniques (e.g. rain gauges, meteorological radars, satellite images), thus it can represent an innovative source of data, which could help in improving the existing observational systems (Barindelli et al. 2018; Inoue and Inoue 2007; Oigawa et al. 2015). L. Benvenuto DICCA - Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy Gter s.r.l. Innovazione in Geomatica, GNSS e GIS, Genoa, Italy e-mail: [email protected] I. Ferrando () · B. Federici · D. Sguerso DICCA - Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy e-mail: [email protected]; [email protected]; [email protected]
GNSS-derived products, Zenith Total Delay (ZTD) and Precipitable Water Vapor (PWV) in particular, are already routinely assimilated into some forecasting Numerical Weather Prediction (NWP) models (Guerova et al. 2016; Oigawa et al. 2018) and estimated within now-casting NWP models (Douša and Vaclavovic 2014). In this context, the authors have conceived an automatic procedure, termed GNSS for Meteorology (G4M) (Ferrando et al. 2018). G4M is intended to produce 2D PWV maps and describe its spatial and temporal evolution by means of PWV maps obtained by time differentiation with respect to a reference epoch. The input data are ZTD estimates from GNSS observations, Pressure (P) and Temperature (T) measurements, both derived from existing sensors spread over the considered domain and not necessarily co-located. Starting from Bevis’ formulation (Bevis et al. 1992), that describes how to obtain 1D PWV values from co-located ZTD, P and T data, the G4M procedure adds a simplified mathematical model to describe P and T fields, besides data interpolation and map algebra (performed in a GIS environment), to create PWV maps (Ferrando et al. 2018). Despite
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