Journal cover Journal topic
Annales Geophysicae An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 1.490
IF1.490
IF 5-year value: 1.445
IF 5-year
1.445
CiteScore value: 2.9
CiteScore
2.9
SNIP value: 0.789
SNIP0.789
IPP value: 1.48
IPP1.48
SJR value: 0.74
SJR0.74
Scimago H <br class='widget-line-break'>index value: 88
Scimago H
index
88
h5-index value: 21
h5-index21
ANGEO | Articles | Volume 37, issue 1
Ann. Geophys., 37, 89–100, 2019
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: Advanced Global Navigation Satellite Systems tropospheric...

Ann. Geophys., 37, 89–100, 2019
https://doi.org/10.5194/angeo-37-89-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular paper 01 Feb 2019

Regular paper | 01 Feb 2019

An improved pixel-based water vapor tomography model

Yibin Yao et al.

Related authors

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
Ann. Geophys., 37, 25–36, https://doi.org/10.5194/angeo-37-25-2019,https://doi.org/10.5194/angeo-37-25-2019, 2019
Short summary
An empirical zenith wet delay correction model using piecewise height functions
YiBin Yao and YuFeng Hu
Ann. Geophys., 36, 1507–1519, https://doi.org/10.5194/angeo-36-1507-2018,https://doi.org/10.5194/angeo-36-1507-2018, 2018
An optimal tropospheric tomography approach with the support of an auxiliary area
Qingzhi Zhao, Yibin Yao, Wanqiang Yao, and Pengfei Xia
Ann. Geophys., 36, 1037–1046, https://doi.org/10.5194/angeo-36-1037-2018,https://doi.org/10.5194/angeo-36-1037-2018, 2018
Short summary
Capturing the signature of heavy rainfall events using the 2-d-/4-d water vapour information derived from GNSS measurement in Hong Kong
Qingzhi Zhao, Yibin Yao, and Wanqiang Yao
Ann. Geophys. Discuss., https://doi.org/10.5194/angeo-2018-76,https://doi.org/10.5194/angeo-2018-76, 2018
Manuscript not accepted for further review
Short summary
Establishment of a regional precipitable water vapor model based on the combination of GNSS and ECMWF data
Yibin Yao, Xingyu Xu, and Yufeng Hu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-227,https://doi.org/10.5194/amt-2018-227, 2018
Revised manuscript not accepted

Related subject area

Subject: Terrestrial atmosphere and its relation to the sun | Keywords: Instruments and techniques
A numerical method to improve the spatial interpolation of water vapor from numerical weather models: a case study in South and Central America
Laura I. Fernández, Amalia M. Meza, M. Paula Natali, and Clara E. Bianchi
Ann. Geophys., 37, 1181–1195, https://doi.org/10.5194/angeo-37-1181-2019,https://doi.org/10.5194/angeo-37-1181-2019, 2019
Short summary

Cited articles

Aghajany, S. H. and Amerian, Y.: Three dimensional ray tracing technique for tropospheric water vapor tomography using GPS measurements, J. Atmos. Sol.-Terr. Phys., 164, 81–88, 2017. 
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. 
Publications Copernicus
Download
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.
In this paper, we propose an improved pixel-based water vapor tomography model, which uses...
Citation