Precipitable Water Vapor Estimates in the Australian Region from Ground-Based GPS Observations

Choy, Suelynn; Wang, Chuansheng; Yeh, Teng Kuang; Dawson, John; Jia, Minghai; Kuleshov, Yuriy

doi:10.1155/2015/956481

Cited by 26 publications

(21 citation statements)

References 47 publications

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“…Basically, the temporal and spatial variability of water vapor concentration depends on the topography, season and other regional climate conditions Fig. 11 Observed scatter plots of GNSS-PWV variation on randomly selected day (15 March 2017) (Choy et al 2015). Most of the GNSS sites showing higher amount of PWV are located relatively close to the coast of Black sea region and close to the Marmara and Aegean region in western part of the country.…”

Section: Spatial Variation Of Pwvmentioning

confidence: 99%

Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model

Ansari

Corumluoǧlu

Panda

et al. 2018

J. Glob. Position. Syst.

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The present paper investigates precipitable water vapor (PWV) variations over the lower middle latitude Turkish region from the International GNSS Services (IGS) and Turkish Permanent GNSS Network (TPGN) observations. The diurnal, seasonal, annual, and rainfall time behavior of PWV and their relative deviations are presented covering the period from 2009 to 2017. Additionally, the predictions from Auto Regressive Moving Average (ARMA) model and ERA-Interim reanalysis datasets are analyzed to understand their effectiveness over the region. In the first observation, diurnal profile indicates maximum value of PWV over the ocean climate regions whereas minimum value is noticed over the semi-arid continental climate areas of Turkey. The seasonal maximum value of PWV is observed in June solstice followed by September equinox and the lowest value is seen in December solstice followed March equinox. The studies also cover annual variation, grand-mean of tropospheric PWV and PWV intensity from the TPGN confirming the range of PWV between 0 to 45 mm. The PWV time series during 2009 to 2017 exhibit a strong annual variation at all sites, with distinctive peaks and dips occurring approximately in summer and winter, respectively. The precipitation plots displayed a clear increasing pattern in summer but the values are less in winter. However, the annual relative deviation of PWV lies in the range of − 0.5 to 1.5 units for all stations. The highest grand-mean of PWV is registered in 2010 (~22 mm) whereas the lowest value is seen in 2011 (~11 mm). The spatial variation of PWV shows that the northern boundary of the Turkey, western part of the country and Northern Cyprus have higher magnitude of PWV while the other part of the country like Central and Eastern Turkey have the lower magnitudes of PWV. PWV analysis during the precipitation period reconfirms that the rainfall pattern is not necessary to follow the PWV time series due to interlinked atmospheric processes. However, we found the PWV predictability of ARMA model is relatively better than the ERA-Interim model. Comprehensive analysis of TPGN data over the region may complement towards a better understanding of the tropospheric dynamics, their effects and the future refinements of atmospheric models over the lower middle latitude Turkish region.

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Section: Spatial Variation Of Pwvmentioning

confidence: 99%

Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model

Ansari

Corumluoǧlu

Panda

et al. 2018

J. Glob. Position. Syst.

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“…The variability of ZTD depends on season, topography and climatic conditions of the region (Choy et al, 2015). The range of ZTD in East African tropical Region is between 1.9 m and 2.6 m depending on the GNSS site (Table 3).…”

Section: Variation Of Ztd Over the East Africa Tropical Regionmentioning

confidence: 99%

Variability and accuracy of Zenith Total Delay over the East African tropical region

Ssenyunzi

Oruru

D’ujanga

et al. 2019

Advances in Space Research

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The Global Navigation Satellite System (GNSS) can be used to derive accurately the Zenith Tropospheric Delay (ZTD) under allweather conditions. The derived ZTDs play a vital role in climate studies, weather forecasting and are operationally assimilated into numerical weather prediction models. In this study, variations and statistical analysis of GNSS-derived ZTD over the East African tropical region are analysed. The data is collected from 13 geodetic permanent stations for the period of 4 years from 2013 to 2016. The 13 stations consist of 5 International GNSS Service (IGS) stations plus 8 stations as follows: 4 Africa Array stations and 4 Malawi Rifting stations from Uganda, Kenya, Tanzania and Rwanda. The ZTD time series were processed using goGPS software version 1.0 beta1, a MATLAB based GNSS processing software, originally developed for kinematic applications but recently re-engineered for quasi static applications. The annual variation of the ZTD time series was investigated using Lomb Scargle periodograms. The semi-annual frequency has the dominant power in subregion 1 (latitudes 4 S and 4 N) and the annual frequency has the dominant power in subregion 2 (latitudes 12 S to 4 S). The highest ZTD estimates occur during the rainy seasons, at all stations, and the lowest estimates occur during the dry seasons. The results also show that the ZTD estimates are largest at stations located at low elevation (regions close to the Indian Ocean). The derived ZTDs are compared to the values derived from the GIPSY-OASIS via Jet Propulsion Laboratory (JPL) online Automatic Precise Positioning Service (APPS) and the Unified Environmental Modelling System (UEMS) numerical weather prediction (NWP) model. The comparison of goGPS and APPS ZTD at the 13 stations shows an overall average bias, Root Mean Square (RMS) and standard deviation (stdev) of À0.9 mm, 3.2 mm and 3.0 mm respectively, with correlation coefficients ranging from 0.974 to 0.999. The comparison of goGPS ZTD against UEMS NWP ZTD at 8 selected stations shows average bias, RMS and stdev of À12.4 mm, 22.0 mm and 17.6 mm respectively, with correlation coefficients ranging from 0.802 to 0.974. The agreement between the GPS ZTD and the NWP ZTD indicates that goGPS ZTD can be assimilated into NWP models in the East African region.

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“…The difference between our and IGS computed ZTD values was in the range of ±15 mm [30]. Such difference is attributed usually to the different network configuration and processing strategy [31]. Further, in order to apply ZTD data for climatology and meteorology studies, the ZTD is decomposed into the Zenith Hydrostatic Delay (ZHD) and the Zenith Wet Delay (ZWD) [32].…”

Section: Zenith Total Delaymentioning

confidence: 99%

Space geodetic activities at the Astronomical Observatory of Mongolia

Amarjargal

Baatarkhuu

Sanjjav

et al. 2016

Journal of Geodetic Science

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We present in this paper some results obtained in the field of space geodesy based on continuous GPS observations at the Astronomical Observatory of Mongolia. Starting with a brief historical overview of the main space geodetic activities carried out by the Astronomical Observatory in the past, we outline here current achievements in the application of GPS techniques in the geosciences research in Mongolia. We setup a local GNSS Data Center of the Mongolian Academy of Sciences to receive, quality control and process into derivative products the observation data coming from its continuously recording stations. The quality check performed on three non-real-time permanent stations reveals that all three stations show smooth trends of each parameter indicating good quality in data record and operation without any anomalous behavior.

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Precipitable Water Vapor Estimates in the Australian Region from Ground-Based GPS Observations

Cited by 26 publications

References 47 publications

Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model

Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model

Variability and accuracy of Zenith Total Delay over the East African tropical region

Space geodetic activities at the Astronomical Observatory of Mongolia

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