Abstract
This study presents an innovative procedure to monitor the precipitable water vapor (PWV) content of a wide and orographically complex area with low-density networks. The procedure, termed G4M (global navigation satellite system, GNSS, for Meteorology), has been developed in a geographic information system (GIS) environment using the free and open source GRASS GIS software (https://grass.osgeo.org). The G4M input data are zenith total delay estimates obtained from GNSS permanent stations network adjustment and pressure (P) and temperature (T) observations using existing infrastructure networks with different geographic distributions in the study area. In spite of the wide sensor distribution, the procedure produces 2D maps with high spatiotemporal resolution (up to 250 m and 6 min) based on a simplified mathematical model including data interpolation, which was conceived by the authors to describe the atmosphere’s physics. In addition to PWV maps, the procedure provides ∆PWV and heterogeneity index maps: the former represents PWV variations with respect to a “calm” moment, which are useful for monitoring the PWV evolution; and the latter are promising indicators to localize severe meteorological events in time and space. This innovative procedure is compared with meteorological simulations in this paper; in addition, an application to a severe event that occurred in Genoa (Italy) is presented.
Highlights
It is widely known that the positioning precision determined by global navigation satellite system (GNSS) observations is affected by different sources of bias because of structural and nonstructural issues
Conclusions and future perspectives The present work focuses on the possibility of obtaining 2D precipitable water vapor (PWV) maps using the GNSS and P and T data from existing infrastructure for a large and orographically complex area, as a contribution to GNSS meteorology
Based on Bevis et al (1992), a procedure called GNSS for Meteorology (G4M) has been conceived by the authors to produce 2D PWV maps with high spatiotemporal resolution
Summary
It is widely known that the positioning precision determined by global navigation satellite system (GNSS) observations is affected by different sources of bias because of structural and nonstructural issues. This work presents an innovative procedure, termed GNSS for Meteorology (G4M), to monitor the PWV content on a wide and orographically complex area in space and time using ZTD estimates obtained from GNSS permanent station (PS) network adjustment and pressure (P) and temperature (T) observations. The G4M spatially combines ZTD, P, and T 1D data originating from networks with different locations and spacing by applying a simplified mathematical model describing the atmospheric P and T distributions.
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