Preprints
https://doi.org/10.5194/amt-2018-227
https://doi.org/10.5194/amt-2018-227

  23 Jul 2018

23 Jul 2018

Review status: this preprint was under review for the journal AMT but the revision was not accepted.

Establishment of a regional precipitable water vapor model based on the combination of GNSS and ECMWF data

Yibin Yao1,2, Xingyu Xu1, and Yufeng Hu1 Yibin Yao et al.
  • 1School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China
  • 2Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China

Abstract. Water vapor is the engine of the weather. Owing to its large latent energy, the phase changes of water vapor significantly affect the vertical stability, structure and energy balance of the atmosphere. Many techniques are used for measuring the water vapor in the atmosphere such as radiosondes, Global Navigation Satellite System (GNSS) and water vapor radiometer (WVR). In addition, the method that uses European Centre for Medium-range Weather Forecasts (ECMWF) data is an important method for studying the variations in precipitable water vapor (PWV). This paper used both GNSS PWV and ECMWF PWV to establish a city-level local PWV fusion model using a Gaussian Processes method. The results indicate that by integrating the precipitable water vapor obtained from GNSS and ECMWF data, the accuracy of fusion PWV is improved by 1.89 mm in active tropospheric conditions and 2.61 mm in quiescent tropospheric conditions compared with ECMWF-PWV, reaching 3.87 mm and 3.97 mm, respectively. Furthermore, the proposed fusion model is used to study the spatial and temporal distribution of PWV in Hong Kong. It is found that the accumulation of PWV corresponds to monsoon and rainfall events.

Yibin Yao et al.

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Yibin Yao et al.

Yibin Yao et al.

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