Annales Geophysicae
Annales Geophysicae
ANGEO
Articles | Volume 37, issue 1
Articles | Volume 37, issue 1
https://doi.org/10.5194/angeo-37-89-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/angeo-37-89-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 37, issue 1
Regular paper
 | 
01 Feb 2019
Regular paper |  | 01 Feb 2019

An improved pixel-based water vapor tomography model

Yibin Yao, Linyang Xin, and Qingzhi Zhao

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Latest update: 22 Nov 2024
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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.
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