Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data

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Abstract

Tropospheric delay comprises one of the most important error sources in satellite navigation and is caused when radio signals broadcasted by GPS satellites propagate into the atmosphere. It is usually projected onto zenith direction by using mapping functions named as Zenith Tropospheric Delay (ZTD). ZTD is described as the sum of the Zenith Hydrostatic Delay (ZHD) and the Zenith Wet Delay (ZWD) and with the aid of surface pressure and temperature the integrated water vapor can be estimated. The main objective of this study is to evaluate the tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS (ECMWF stands for the European Centre for Medium-Range Weather Forecasts) reanalysis model and ground meteorological data from two stations of the permanent network of Cyprus and Greece. The period from 27 May to 3 June 2018 is characterized by two different synoptic conditions: high pressure with fair weather in central Mediterranean (Greece), on the one hand, and high instability over the upper levels of the atmosphere that resulted in thunderstorms inland and mountainous areas during midday over the Eastern Mediterranean (Cyprus), on the other hand. In general, the results show that both the empirical blind model GPT2w and the ECMWF (IFS) operational model perform well in particular over Nicosia when used for the retrieval of Integrated Water Vapor (IWV) from GNSS measurements, although appreciable deviations were observed between ECMWF (IFS)-retrieved IWV and the one retrieved from GNSS observations by using meteorological measurements. A sharp increase of IWV prior to the abrupt rainfall events during noon on 30 and 31 May over Nicosia was also found.

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APA

Oikonomou, C., Tymvios, F., Pikridas, C., Bitharis, S., Balidakis, K., Michaelides, S., … Charalambous, D. (2018). Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF’s IFS operational model and in situ meteorological data. Advances in Geosciences, 45, 363–375. https://doi.org/10.5194/adgeo-45-363-2018

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