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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Discussion papers | Copyright
https://doi.org/10.5194/angeo-2018-84
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular paper 16 Jul 2018

Regular paper | 16 Jul 2018

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Annales Geophysicae (ANGEO).

A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

Zhaohui Xiong, Bao Zhang, and Yibin Yao Zhaohui Xiong et al.
  • School of Geodesy and Geomatics, Wuhan University, Wuhan 430079

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

Zhaohui Xiong et al.
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Zhaohui Xiong et al.
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We conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model in retrieving wet refractivity (WR) in Hong Kong area during a rainy period and a rainless period. Results show that both methods can retrieve good WR and the WRF model outperforms the tomography technique in most cases. Rainy weather seems not to influence the results but the sharp vertical variations in WR decreased both method's capabilities in retrieving WR.
We conduct an interesting comparison between the GNSS tomography technique and the Weather...
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