Articles | Volume 14, issue 10
https://doi.org/10.5194/amt-14-6379-2021
https://doi.org/10.5194/amt-14-6379-2021
Research article
 | 
01 Oct 2021
Research article |  | 01 Oct 2021

A new zenith hydrostatic delay model for real-time retrievals of GNSS-PWV

Longjiang Li, Suqin Wu, Kefei Zhang, Xiaoming Wang, Wang Li, Zhen Shen, Dantong Zhu, Qimin He, and Moufeng Wan

Related authors

Evaluation of reanalysis precipitable water vapor under typhoon conditions using multi-source observations
Jiaqi Shi, Min Li, Andrea K. Steiner, Sebastian Scher, Minghao Zhang, Jiayu Hu, Wenliang Gao, Yongzhao Fan, and Kefei Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4438,https://doi.org/10.5194/egusphere-2025-4438, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
A new vertical reduction model for enhancing the interpolation accuracy of VMF1/VMF3 tropospheric delay products
Peng Sun, Kefei Zhang, Dantong Zhu, Shuangshuang Shi, Xuexi Liu, Dongsheng Zhao, Minghao Zhang, and Suqin Wu
Geosci. Model Dev., 18, 6167–6176, https://doi.org/10.5194/gmd-18-6167-2025,https://doi.org/10.5194/gmd-18-6167-2025, 2025
Short summary
A comprehensive 22-year global GNSS climate data record from 5085 stations
Xiaoming Wang, Haobo Li, Suelynn Choy, Qiuying Huang, Wenhui Cai, Anthony Rea, Hongxin Zhang, Luis Elneser, and Yuriy Kuleshov
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-283,https://doi.org/10.5194/essd-2025-283, 2025
Revised manuscript under review for ESSD
Short summary
A new global grid-based weighted mean temperature model considering vertical nonlinear variation
Peng Sun, Suqin Wu, Kefei Zhang, Moufeng Wan, and Ren Wang
Atmos. Meas. Tech., 14, 2529–2542, https://doi.org/10.5194/amt-14-2529-2021,https://doi.org/10.5194/amt-14-2529-2021, 2021
Short summary

Cited articles

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. 
Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., and Ware, R. H.: GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system, J. Geophys. Res., 97, 15787, https://doi.org/10.1029/92JD01517, 1992. 
Böhm, J., Heinkelmann, R., and Schuh, H.: Short Note: A global model of pressure and temperature for geodetic applications, J. Geodesy, 81, 679–683, https://doi.org/10.1007/s00190-007-0135-3, 2007. 
Böhm, J., Möller, G., Schindelegger, M., Pain, G., and Weber, R.: Development of an improved empirical model for slant delays in the troposphere (GPT2w), GPS Solut., 19, 433–441, https://doi.org/10.1007/s10291-014-0403-7, 2015. 
Bosser, P., Bock, O., Pelon, J., and Thom, C.: An Improved Mean-Gravity Model for GPS Hydrostatic Delay Calibration, IEEE Geosci. Remote S., 4, 3–7, https://doi.org/10.1109/LGRS.2006.881725, 2007. 
Download
Short summary
The zenith hydrostatic delay (ZHD) derived from blind models are of low accuracy, especially in mid- and high-latitude regions. To address this issue, the ratio of the ZHD to zenith total delay (ZTD) is firstly investigated; then, based on the relationship between the ZHD and ZTD, a new ZHD model was developed using the back propagation artificial neural network (BP-ANN) method which took the ZTD as an input variable. The model outperforms blind models.
Share