Among the different techniques for atmosphere monitoring, the GNSS (Global Navigation Satellite System) can provide an innovative contribution (Bevis et al., 1992; Crespi et al., 2004; Sguerso et al., 2013, 2015). The Laboratory of Geomatics, Geodesy and GIS of the University of Genoa has identified a GIS procedure and a simplified physical model to monitor the Precipitable Water Vapour (PWV) content, using data measured by existing infrastructures. The starting points are local estimations of Zenith Total Delay (ZTD) from a GNSS Permanent Stations (PSs) network, a Digital Terrain Model (DTM) and local Pressure (P) and Temperature (T) measurements (Sguerso et al., 2014; Ferrando et al., 2016). The present paper shows the study of the most appropriate interpolation technique for P and T data to create PWV maps in a quick, stable and automatic way, to support the monitoring of intense meteorological events for both a posteriori and near real-time applications. The resulting P and T maps were compared to meteorological re-analysis, to check the reliability of the simplified physical model. Additionally, the Regression Kriging (RK) was employed to evaluate the data correlation with elevation and to study the applicability of the technique.

Spatial interpolation techniques for near real-time mapping of Pressure and Temperature data

Ferrando I.;Federici B.;Sguerso D.
2016

Abstract

Among the different techniques for atmosphere monitoring, the GNSS (Global Navigation Satellite System) can provide an innovative contribution (Bevis et al., 1992; Crespi et al., 2004; Sguerso et al., 2013, 2015). The Laboratory of Geomatics, Geodesy and GIS of the University of Genoa has identified a GIS procedure and a simplified physical model to monitor the Precipitable Water Vapour (PWV) content, using data measured by existing infrastructures. The starting points are local estimations of Zenith Total Delay (ZTD) from a GNSS Permanent Stations (PSs) network, a Digital Terrain Model (DTM) and local Pressure (P) and Temperature (T) measurements (Sguerso et al., 2014; Ferrando et al., 2016). The present paper shows the study of the most appropriate interpolation technique for P and T data to create PWV maps in a quick, stable and automatic way, to support the monitoring of intense meteorological events for both a posteriori and near real-time applications. The resulting P and T maps were compared to meteorological re-analysis, to check the reliability of the simplified physical model. Additionally, the Regression Kriging (RK) was employed to evaluate the data correlation with elevation and to study the applicability of the technique.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/888490
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