Articles | Volume 37, issue 1
https://doi.org/10.5194/angeo-37-25-2019
https://doi.org/10.5194/angeo-37-25-2019
Regular paper
 | 
15 Jan 2019
Regular paper |  | 15 Jan 2019

Comparisons between the WRF data assimilation and the GNSS tomography technique in retrieving 3-D wet refractivity fields in Hong Kong

Zhaohui Xiong, Bao Zhang, and Yibin Yao

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Cited articles

Adams, K., Fernandes, S., and Maia, F.: GNSS Precipitable Water Vapor from an Amazonian Rain Forest Flux Tower, J. Atmos. Ocean. Tech., 28, 1192–1198, https://doi.org/10.1175/jtech-d-11-00082.1, 2011. 
Adavi, Z. and Mashhadi-Hossainali, M.: 4D tomographic reconstruction of the tropospheric wet refractivity using the concept of virtual reference station, case study: northwest of Iran, Meteorol. Atmos. Phys., 126, 193–205, https://doi.org/10.1007/s00703-014-0342-4, 2014. 
Altshuler, E. E.: Tropospheric range-error corrections for the Global Positioning System, IEEE T. Antenn. Propag., 46, 643–649, https://doi.org/10.1109/8.668906, 2002. 
Altuntac, E.: Quasi-Newton Approach for an Atmospheric Tomography Problem, eprint arXiv:1511.08022, available at: https://arxiv.org/pdf/1511.08022.pdf (last access: 4 May 2018), 2015. 
Askne, J. and Nordius, H.: Estimation of Tropospheric Delay for Microwaves from Surface Weather Data, Radio Sci., 22, 379–386, https://doi.org/10.1029/rs022i003p00379, 1987. 
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Short summary
A comparison between the GNSS tomography technique and WRFDA in retrieving wet refractivity (WR) is conducted in HK during a wet period and a dry period. The results show that both of them can retrieve good WR. In most of the cases, the WRFDA output outperforms the tomographic WR, but the tomographic WR is better than the WRFDA output in the lower troposphere in the dry period. By assimilating better tomographic WR in the lower troposphere into the WRFDA, we slightly improve the retrieved WR.