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Author: search.filters.author.Rangsanseri, YuttapongSubject: search.filters.subject.GNSS Remote Sensing

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    Empirical model for total precipitable water retrieval from ground-based GNSS observations in Thailand
    (2020-08-14)
    Rangsanseri, Yuttapong
    ;
    Phasamak, Weeranat
    ;
    Soisuvarn, Seubson
    Retrieval of Total Precipitable Water (TPW) from ground-based Global Navigation Satellite System (GNSS) observations is a challenging task due to its real-time and high temporal resolution nature. In this paper, we present a method for establishing an analytical model for retrieving the TPW based on the GNSS observations over 1-year period from 12 stations distributed across Thailand. The derived Zenith Total Delay (ZTD) at all stations agrees well with the TPW data available from the Global Data Assimilation System (GDAS) Numerical Weather Prediction (NWP) model. First, a unique relationship between the ZTD and the TPW was established by taking into account the variations in station altitudes. Then, a bias correction technique with Probability Distribution Function (PDF) matching was applied to improve the final model. The inversion model of the TPW from ZTD was then easily obtained by using a numerical technique. The performance of our method has been successfully evaluated on an independent test data. This model can be useful for near real-time TPW measurements from globally available GNSS receivers.
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    Determination of total precipitable water from GNSS data in Thailand
    (2019-01-01)
    Phasamak, Weeranat
    ;
    Soisuvarn, Seubson
    ;
    Rangsanseri, Yuttapong
    The relationship between the total precipitable water (TPW) in the atmosphere and Global Navigation Satellite System (GNSS) Zenith Total Delay (ZTD) has been investigated. The study was performed for ZTD observations derived from GPS measurements at 5 sites across Thailand, over one-year period, July 2017 to August 2018. The ZTD was then collocated in space and time with the TPW data available from Global Data Assimilation System (GDAS) Numerical Weather Prediction (NWP) model. The result showed that the ZTD observations are highly correlated with the TPW but there are some biases between the ground base station locations largely due to the altitude differences. An empirical model was then developed to remove the altitude dependence and provide a unique relationship between the ZTD and the TPW. This model can be useful in the further TPW measurements from widely available GNSS receivers.