Systematic errors between VLBI and GPS precipitable water vapor estimations from 5-year co-located measurements

Jin, Shuanggen; Luo, O. F.; Cho, J.

doi:10.1016/j.jastp.2008.11.018

Cited by 15 publications

(5 citation statements)

References 32 publications

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“…With increased altitude, PWV value decreases due to lower surface temperature at high altitudes. Also, as the altitude increases, the depth of atmospheric column decreases and accordingly PWV decreases (Jin et al 2009). The atmospheric pressure varies with the increase in elevation.…”

Section: Spatial Variation Of Pwvmentioning

confidence: 96%

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: 96%

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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“…Researchers have been shown that the ZTD differences between VLBI and GPS were smaller than 1 cm 42 , 43 and the VLBI technique was one of the most accurate method of obtaining the ZTD 7 . Therefore, the post-processed GPS-derived ZTD data were compared with another collocated independent technique: Very Long Baseline Interferometry (VLBI).…”

Section: The Retrieval Of Ztd and Accuracy-testingmentioning

confidence: 99%

“…Therefore, the precipitable water vapour (PWV) can be converted from zenith wet delay (ZWD) which is extracted from ZTD by removing ZHD 1 . PWV is the average water vapour content from many signals with different elevation angles and azimuths projected to the vertical direction using the mapping function 7 .…”

Section: Introductionmentioning

confidence: 99%

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

Zhao

Yao

2018

Sci Rep

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GPS-based Zenith Tropospheric Delay (ZTD) estimation should be easily obtained in a cost-effective way, however, the most previous studies focus on post-processed ZTD estimates using satellite orbit and clock products with at least 3–9 hours latency provided by International GNSS Service (IGS), which limits the GNSS meteorological application for nowcasting. With the development of IGS’s real-time pilot project (RTPP), this limitation was removed by April, 2013 as real-time satellite orbit and clock products can be obtained on-line. In this paper, on the one hand, the GPS-derived ZTD estimation was evaluated using the IGS final and real-time satellite products based on independently developed PPP software. On the other hand, the analysis of the time series of GPS-derived ZTD by least-square fitting of a broken line tendency for a full year of observations, and a forecasting method for precipitation is proposed based on the ZTD slope in the ascending period. The agreement between ZTD slope and the ground rainfall records suggested that the proposed method is useful for the assisted forecasting, especially for short-term alarms.

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“…Moreover, it is also observed that the PWV from VLBI and the PWV from GPS have the same pattern but the PWV from VLBI is generally less than the PWV from GPS. Similar observations have been reported in the literature [138]. Small differences can be observed between PWV calculated for the same GPS station but using different sources (from NASA and from GGOS).…”

Section: Independent Station Validationsupporting

confidence: 90%

“…The proposed model is further validated using the VLBI database. The CDDIS archive of VLBI products consists of solutions derived by IVS analysis centers from the analysis of VLBI experiment files [138]. These products include the troposphere parameters like ZT D and ZW D. These tropospheric parameters with meteorologically important surface parameters such as temperature, pressure and humidity, is downloaded from IVS data center [139].…”

Section: Vlbi Databasementioning

confidence: 99%

GPS signal derived precipitable water vapor and its applications in rainfall prediction

Manandhar¹

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I would like to take this opportunity to thank my supervisor, Prof. Lee Yee Hui, for supervising me during my PhD years. I got to learn a lot of technical and practical things under her guidance. She is a wonderful supervisor who has not only motivated me in doing my research but also has equally supported me in my other co-curricular interests. I feel lucky to have gotten the chance to do my PhD under her. I would like to thank my co-supervisor Dr. Yu Song Meng for his support during my PhD journey. He is a very hardworking and a dedicated researcher. Thank you Yusong for your effort in going through my works and giving me constructive feedback, always. I would like to thank Dr. Stefan Winkler and Prof Ong. for working closely with our project and guiding us in our work. I feel extremely fortunate to have a group of lovely lab mates with whom I spent most of my PhD days. I would like to thank my senior cum mentor Sutha Mam for her guidance during my initial days of PhD. Thank you Sutha Mam for your constant support and well wishes. I would like to thank my seniors Jun Xiang, Soumya, Siya, Yuan Feng and Florian. I had had most wonderful memories and have shared a warm bonding with Soumya and Yuan Feng. I would also like to thank my junior Shravan who extends his helping hands whenever needed. Apart from my lab-mates, I feel extremely lucky of having a bunch of friends who were there during my thick and thins. I would like to thank my friends Niroj, Milan, Dipu, Ujjal, Rakesh and Shiva for being around and supporting me. I would like to thank Anna and Vasilisa for all those unforgetful and fun-filled memories. And of course, Pradeep, thank you very much for your constant encouragement, support and unconditional love. Without the support of my friends, my PhD journey would vi not have been a joyous experience. My acknowledgement is incomplete without thanking my parents. I would like to thank my father and mother, Shree Hari Manandhar & Sarojani Manandhar for their love and constant support. Especially my mother who has always encouraged me to live my dreams and follow my passion. I am also thankful towards my sister, Sarbada Manandhar, not only for loving and supporting me but also for looking after my family during my PhD years when I am away from home. Also a huge thanks to my grandpa and grandma for their blessings and well-wishes. I would like to express my sincere gratitude towards each and every individual who has directly or indirectly helped me in reaching my goal. Thank you.

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Systematic errors between VLBI and GPS precipitable water vapor estimations from 5-year co-located measurements

Cited by 15 publications

References 32 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

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

GPS signal derived precipitable water vapor and its applications in rainfall prediction

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