Articles | Volume 37, issue 1
Ann. Geophys., 37, 89–100, 2019

Special issue: Advanced Global Navigation Satellite Systems tropospheric...

Ann. Geophys., 37, 89–100, 2019

Regular paper 01 Feb 2019

Regular paper | 01 Feb 2019

An improved pixel-based water vapor tomography model

Yibin Yao et al.

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Cited articles

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Alber, C., Ware, R., Rocken, C., and Braun, J. J.: Obtaining single path phase delays from GPS double differences, Geophys. Res. Lett., 27, 2661–2664, 2000. 
Baltink, H. K., Marel, H. V. D., and Der Hoeven, A. V.: Integrated atmospheric water vapor estimates from a regional GPS network, J. Geophys. Res.-Atmos., 107, ACL 3-1–ACL 3-8, 2002. 
Bender, M., Stosius, R., Zus, F., Dick, G., Wickert, J., and Raabe, A.: GNSS water vapour tomography – Expected improvements by combining GPS, GLONASS and Galileo observations, Adv. Space Res., 47, 886–897, 2011. 
Bevis, M., Businger, S., Chiswell, S. R., Herring, T. A., Anthes, R. A., Rocken, C., and Ware, R.: GPS meteorology: mapping zenith wet delays onto precipitable water, J. Appl. Meteorol., 33, 379–386, 1994. 
Short summary
In this paper, we propose an improved pixel-based water vapor tomography model, which uses layered optimal polynomial functions by adaptive training for water vapor retrieval. Under different scenarios, tomography results show that the new model outperforms the traditional one by reducing the root-mean-square error (RMSE), and this improvement is more pronounced, at 5.88 % in voxels without the penetration of GNSS rays. The improved model also has advantages in more convenient expression.