Empirical Model for Total Precipitable Water Retrieval from Ground-based GNSS Observations in Thailand


  • Weeranat Phasamak Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Ladkrabang, Bangkok, Thailand
  • Seubson Soisuvarn NOAA/NESDIS/Center for Satellite Applications and Research, College Park, MD, USA https://orcid.org/0000-0002-1373-8974
  • Yuttapong Rangsanseri Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Ladkrabang, Bangkok, Thailand




GNSS Remote Sensing, Zenith Total Delay, Total Precipitable Water, PDF Matching


Retrieval of Total Precipitable Water (TPW) using ground-based Global Navigation Satellite System (GNSS) observations is a challenging task due to its real‐time and high temporal resolution. In this paper, we present a method for establishing an analytic model for retrieving the total precipitable water (TPW) based on Global Navigation Satellite System (GNSS) observations over one-year period from 12 distributed stations across Thailand. The derived zenith total delay (ZTD) at all stations agrees well with the TPW data available from Global Data Assimilation System (GDAS) Numerical Weather Prediction (NWP) model. At first, a unique relationship between the ZTD and the TPW was established by taking into account of the variation of station altitudes. In addition, the bias correction technique using probability distribution function (PDF) matching was also applied to improve the final model. The inversion model of TPW from ZTD is then easily obtained using a numerical technique. The performance of our method has been successfully evaluated on an independent test data. This model can be useful in the further near real-time TPW measurements from widely available GNSS receivers.


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Author Biographies

Weeranat Phasamak, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Ladkrabang, Bangkok, Thailand

Weeranat Phasamak received his B.Eng. degree in telecommunication engineering and M.Eng. degree in electrical engineering, both from the King Mongkut’s Institute of Technology Ladkrabang (KMITL). He is currently pursuing his doctoral degree in electrical engineering at the KMITL. His research interests include Global Navigation Satellite System (GNSS) remote sensing, signal and image processing, and communication systems.

Seubson Soisuvarn, NOAA/NESDIS/Center for Satellite Applications and Research, College Park, MD, USA

Seubson Soisuvarn received his B.Eng. degree in electrical engineering from the Kasetsart University, Bangkok, Thailand, in 1998, and the M.S.E.E. and Ph.D. degrees in electrical engineering from the University of Central Florida, Orlando, FL in 2001 and 2006, respectively.

Since 2006, he has been with the Ocean Surface Winds Team as a UCAR Project Scientist at the Center for Satellite Applications and Research, National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA). His research interests include active and passive microwave remote sensing, scatterometer wind retrieval algorithm and product development, and GNSS reflectometry of ocean surface winds and waves. He has worked on calibration and validation of scatterometers from ASCAT, Oceansat-2, RapidScat, ScatSAT-1,GNSS reflectometry from TechDemoSat-1, and CYGNSS. He has developed a high wind geophysical model function (CMOD5.H) for C-band scatterometer that has been operationally utilized by the US National Weather Service. He is currently working on operational wind data products from the ScatSAT-1 to be utilized by NOAA.

Yuttapong Rangsanseri, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Ladkrabang, Bangkok, Thailand

Yuttapong Rangsanseri received his B.Eng. and M.Eng. degrees in electrical engineering from the King Mongkut’s Institute of Technology Ladkrabang (KMITL), Thailand, in 1985 and 1987, respectively, and his Ph.D. degree from the Institute National Polytechnique de Grenoble, France, in 1992. He is currently an associate professor in the Department of Telecommunications Engineering at the KMITL. His research interests include image processing, pattern reognition, and remote sensing.


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