17 citations as recorded by crossref.

1. High-precision tropospheric correction method for NRTK regions with significant height differences X. Lei et al. https://doi.org/10.1088/1361-6501/ad6343
2. Comparative analysis of blind tropospheric correction models in Ghana S. Osah et al. https://doi.org/10.1515/jogs-2020-0104
3. Global zenith wet delay modeling with surface meteorological data and machine learning Q. Li et al. https://doi.org/10.1007/s10291-023-01595-2
4. Modelling the Altitude Dependence of the Wet Path Delay for Coastal Altimetry Using 3-D Fields from ERA5 T. Vieira et al. https://doi.org/10.3390/rs11242973
5. GNSS-retrieved precipitable water vapour in the Atlantic coast of France and Spain with GPT3 model R. Perdiguer-Lopez et al. https://doi.org/10.1007/s40328-023-00427-6
6. A refined zenith tropospheric delay model for Mainland China based on the global pressure and temperature 3 (GPT3) model and random forest J. Li et al. https://doi.org/10.1007/s10291-023-01513-6
7. Dynamic Estimation of the Wet Path Delay Vertical Gradients From ERA5 for Satellite Altimetry M. Fernandes & T. Vieira https://doi.org/10.1109/TGRS.2024.3398809
8. An improved global pressure and zenith wet delay model with optimized vertical correction considering the spatiotemporal variability in multiple height-scale factors C. Jiang et al. https://doi.org/10.5194/gmd-17-5939-2024
9. Tropospheric delay model estimation using GNSS observations with fixed station positions and forecasting application G. Zhu et al. https://doi.org/10.1016/j.asr.2026.04.124
10. Estimating tropospheric delay with GNSS observations to provide a model product H. Li et al. https://doi.org/10.1088/1361-6501/addc88
11. Multi-sensor study of precipitable water vapor and atmospheric profiling from microwave radiometer, GNSS/MET, radiosonde, and ECMWF reanalysis in Beijing H. Hu et al. https://doi.org/10.1117/1.JRS.14.044514
12. Varying model estimation of precipitable water vapor from GNSS observations and its forecasting performance G. Zhu et al. https://doi.org/10.1016/j.atmosres.2026.109008
13. A stacking ensemble learning approach for enhancing global real-time zenith total delay modeling using global forecast system forecasts X. Gao et al. https://doi.org/10.1088/1361-6501/ae1aa7
14. Impact of a priori zenith hydrostatic delay errors on ground-based GNSS tropopause height determinations L. Qin et al. https://doi.org/10.3389/fspas.2026.1852394
15. A Self-Supervised Uncertainty-Hybrid Machine Learning Approach for Modeling Tropospheric Zenith Wet Delay M. Sharouda et al. https://doi.org/10.1109/JSTARS.2026.3694884
16. Estimation of precipitable water vapour by GNSS meteorology in Black Sea region of Türkiye E. Kayıkçı et al. https://doi.org/10.1515/jag-2025-0102
17. Development of a ZTD Vertical Profile Model Considering the Spatiotemporal Variation of Height Scale Factor with Different Reanalysis Products in China X. Wang et al. https://doi.org/10.3390/atmos13091469