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

Authors

  • 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

DOI:

https://doi.org/10.13052/jmm1550-4646.16128

Keywords:

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

Abstract

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.

References

Mears, C. A., J. Wang, D. Smith, F. J. Wentz, “Intercomparison of Total Precipitable Water Measurements Made by Satellite-Borne Microwave Radiometers and Ground-Based GPS Instruments,” Journal of Geophysical Research: Atmospheres, 120, pp. 2492–2504, 2015.

T. Kawanishi, T. Sezai, Y. Ito, K. Imaoka, T. Ishido, A. Shibata, M. Inahata, R. W. Spencer, “The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E),” Geosci. Remote Sens., 41, pp. 184–194, 2003.

Wentz, F. J., “A 17-Year Climate Record of Environmental Parameters Derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager,” Journal of Climate, 28, pp. 6882–6902, 2015.

Japan Meteorological Agency, “Outline of Operational Numerical Weather Prediction at Japan Meteorological Agency,” http://www.jma. go.jp/jma/jma-eng/jma-center/nwp/outline-nwp/index.htm.

L. Bengtsson, “The Use of GPS Measurements for Water Vapour Determination,” Bull. Amer. Meteor. Soc., 84, pp. 1249–1258, 2003.

M. Bevis, S. Businger, T. Herring, C. Rocken, R. Anthes, R. Ware, “GPS Meteorology: Remote Sensing of Atmospheric Water Vapor using the Global Positioning System,” J. Geophys. Res., 97, pp. 787–801, 1992.

P. Poli, P. Moll, F.-Z. EL Guelai, S.B. Healy, E. Andersson, “Forecast Impact Studies of Zenith Total Delay Data from European Near Realtime GPS Stations in Météo France 4DVAR,” J. Geophys. Res., 112, 2007.

K. Boniface, V. Ducrocq, G. Jaubert, X. Yan, P. Brousseau, F. Masson, C. Champollion, J. Chery, E. Doerflinger, “Impact of High-resolution Data Assimilation of GPS Zenith Delay on Mediterranean Heavy Rainfall Forecasting,” Ann. Geophys., 27, pp. 2739–2753, 2009.

S. R. Macpherson, G. Deblonde, J. M. Aparicio, B. Casati, “Impact of NOAA Ground-based GPS Observations on the Canadian Regional Analysis and Forecast System,” Mon. Wea. Rev., 136, pp. 2727–2746, 2008.

H. Vedel, and X.-Y. Huang, “Impact of Ground based GPS Data on Numerical Weather Prediction,” J. Meteor. Soc., 82, pp. 459–472, 2004.

C. Faccani, R. Ferretia, R. Pacione, T. Paolucci, F. Vespe, L. Cucurull, “Impact of a High Density GPS Network on the Operational Forecast,” Adv. Geosci., 2, pp. 73–76, 2005.

Gutman, S. I., S. R. Sahm, S. G. Benjamin, B. E. Schwartz, K. L. Holub, J. Q. Stewart, T. L. Smith, “Rapid Retrieval and Assimilation of Ground-based GPS Precipitable Water Observations at the NOAA Forecast Systems Laboratory: Impact on Weather Forecasts,” J. Meteorol. Soc. Jpn., 82, pp. 351– 360, 2004.

T.Aoki, T.Inoue, “Estimation of the Precipitable Water from the IR Channel of the Geostationary Satellite,” Remote Sensing of Environment, 12, 219–228, 1982.

B. N. Holben, T. Eck, “Precipitable Water in Sahel Measured using Sunphotometry,” Agric. and Forest Meteo, 52, 95–107, 1990.

J. Jones, “An Assessment of The Quality of GPS Water Vapour Estimates and Their Use in Operational Meteorology and Climate Monitoring,” PhD thesis, Institute of Engineering Surveying and Space Geodesy, University of Nottingham. 2010.

J. Wang, L. Zhang, A. Dai, T. Van Hove, J. Van Baelen, “A Near-global, 2-hourly Data Set of Atmospheric Precipitable Water from Ground-based GPS Measurements,” J. Geophys. Res., 112, D11107.

Thai GNSS and Space Weather Information Data Center, http://iono-gnss.kmitl.ac.th

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Published

2020-08-24

How to Cite

Phasamak, W., Soisuvarn, S., & Rangsanseri, Y. (2020). Empirical Model for Total Precipitable Water Retrieval from Ground-based GNSS Observations in Thailand. Journal of Mobile Multimedia, 16(1-2), 161–180. https://doi.org/10.13052/jmm1550-4646.16128

Issue

2020: Vol 16 Iss 1-2

Section

Smart Innovative Technology for Future Industry and Multimedia Applications