Artículo
Comprehensive Study on the Tropospheric Wet Delay and Horizontal Gradients during a Severe Weather Event
Graffigna, Victoria
; Hernández-pajares, Manuel; Azpilicueta, Francisco Javier
; Gende, Mauricio Alfredo
Fecha de publicación:
02/2022
Editorial:
MDPI
Revista:
Remote Sensing
ISSN:
2072-4292
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
GNSS meteorology is today one of the most growing technologies to monitor severe weather events. In this paper, we present the usage of 160 GPS reference stations over the period of 14 days to monitor and track Hurricane Harvey, which struck Texas in August 2017. We estimate the Zenith Wet Delay (ZWD) and the tropospheric gradients with 30 s interval using TOMION v2 software and carry out the processing in Precise Point Positioning (PPP) mode. We study the relationship of these parameters with atmospheric variables extracted from Tropical Rainfall Measuring Mission (TRMM) satellite mission and climate reanalysis model ERA5. This research finds that the ZWD shows patterns related to the rainfall rate and to the location of the hurricane. We also find that the tropospheric gradients are correlated with water vapor gradients before and after the hurricane, and with the wind and the pressure gradients only after the hurricane. This study also shows a new finding regarding the spectral distribution of the gradients, with a clear diurnal period present, which is also found on the ZWD itself. This kind of study approaches the GNSS meteorology to the increasing requirements of meteorologist in terms of monitoring severe weather events.
Palabras clave:
GNSS METEOROLOGY
,
MARINE DISASTERS
,
TROPOSPHERIC GRADIENTS
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Articulos(CCT - LA PLATA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - LA PLATA
Citación
Graffigna, Victoria; Hernández-pajares, Manuel; Azpilicueta, Francisco Javier; Gende, Mauricio Alfredo; Comprehensive Study on the Tropospheric Wet Delay and Horizontal Gradients during a Severe Weather Event; MDPI; Remote Sensing; 14; 4; 2-2022; 1-14
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