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

<p>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...

Full description

Bibliographic Details
Main Authors: C. Oikonomou, F. Tymvios, C. Pikridas, S. Bitharis, K. Balidakis, S. Michaelides, H. Haralambous, D. Charalambous
Format: Article
Language:English
Published: Copernicus Publications 2018-11-01
Series:Advances in Geosciences
Online Access:https://www.adv-geosci.net/45/363/2018/adgeo-45-363-2018.pdf
id doaj-1ea15bdee22c4ed7811a8b4606dc06ce
record_format Article
spelling doaj-1ea15bdee22c4ed7811a8b4606dc06ce2020-11-24T20:51:11ZengCopernicus PublicationsAdvances in Geosciences1680-73401680-73592018-11-014536337510.5194/adgeo-45-363-2018Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological dataC. Oikonomou0F. Tymvios1F. Tymvios2C. Pikridas3S. Bitharis4K. Balidakis5S. Michaelides6H. Haralambous7H. Haralambous8D. Charalambous9D. Charalambous10Frederick Research Center, Nicosia, 1303, CyprusCyprus Department of Meteorology, Nicosia, CyprusThe Cyprus Institute, Nicosia, 2121, CyprusAristotle University of Thessaloniki, Department of Geodesy and Surveying, Thessaloniki, 54124, GreeceAristotle University of Thessaloniki, Department of Geodesy and Surveying, Thessaloniki, 54124, GreeceGerman Research Centre for Geosciences, Space Geodetic Techniques, Potsdam, 14473, GermanyThe Cyprus Institute, Nicosia, 2121, CyprusFrederick Research Center, Nicosia, 1303, CyprusFrederick University, Nicosia, 1036, CyprusCyprus Department of Meteorology, Nicosia, CyprusThe Cyprus Institute, Nicosia, 2121, Cyprus<p>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.</p>https://www.adv-geosci.net/45/363/2018/adgeo-45-363-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C. Oikonomou
F. Tymvios
F. Tymvios
C. Pikridas
S. Bitharis
K. Balidakis
S. Michaelides
H. Haralambous
H. Haralambous
D. Charalambous
D. Charalambous
spellingShingle C. Oikonomou
F. Tymvios
F. Tymvios
C. Pikridas
S. Bitharis
K. Balidakis
S. Michaelides
H. Haralambous
H. Haralambous
D. Charalambous
D. Charalambous
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
author_facet C. Oikonomou
F. Tymvios
F. Tymvios
C. Pikridas
S. Bitharis
K. Balidakis
S. Michaelides
H. Haralambous
H. Haralambous
D. Charalambous
D. Charalambous
author_sort C. Oikonomou
title Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data
title_short Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data
title_full Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data
title_fullStr Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data
title_full_unstemmed Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data
title_sort tropospheric delay performance for gnss integrated water vapor estimation by using gpt2w model, ecmwf's ifs operational model and in situ meteorological data
publisher Copernicus Publications
series Advances in Geosciences
issn 1680-7340
1680-7359
publishDate 2018-11-01
description <p>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.</p>
url https://www.adv-geosci.net/45/363/2018/adgeo-45-363-2018.pdf
work_keys_str_mv AT coikonomou troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT ftymvios troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT ftymvios troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT cpikridas troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT sbitharis troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT kbalidakis troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT smichaelides troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT hharalambous troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT hharalambous troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT dcharalambous troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
AT dcharalambous troposphericdelayperformanceforgnssintegratedwatervaporestimationbyusinggpt2wmodelecmwfsifsoperationalmodelandinsitumeteorologicaldata
_version_ 1716802470964887552