14 citations as recorded by crossref.

1. A GNSS ZTD enhancement framework integrating physical constraints and hybrid neural networks H. Li et al. https://doi.org/10.1016/j.asr.2026.05.078
2. A GNSS PWV filling and short-term forecasting framework fused hybrid neural network H. Li et al. https://doi.org/10.1016/j.atmosres.2025.108508
3. Accuracy evolution of precipitable water vapor products from Medium Resolution Spectral Imager (MERSI) on Fengyun-3 series satellites H. Sun et al. https://doi.org/10.1016/j.asr.2026.06.028
4. Evaluation of oceanic precipitable water vapor products from Microwave Radiation Imager (MWRI) onboard the Fengyun-3D satellite Y. Zhou et al. https://doi.org/10.1016/j.asr.2023.02.033
5. Novel Validation and Calibration Strategy for Total Precipitable Water Products of Fengyun-2 Geostationary Satellites Z. Du et al. https://doi.org/10.1109/TGRS.2023.3295091
6. Evolution of Atmospheric Water Vapor and Cloud Liquid Water During Non- and Pre-Precipitation Conditions over the Middle Yangtze River Basin in the Warm Season W. Zhang et al. https://doi.org/10.3390/rs18101642
7. Improving Fengyun-3D satellite atmospheric precipitable water vapor products through machine learning-based post-processing correction M. Li et al. https://doi.org/10.1016/j.atmosres.2025.108133
8. Constructing High-Precision and Spatial Resolution Precipitable Water Vapor Product Using Multiple Fusion Models Y. Zhou et al. https://doi.org/10.1109/JSTARS.2024.3459051
9. Comprehensive evaluation of the precipitable water vapor products of Fengyun satellites via GNSS data over mainland China Y. Zhou et al. https://doi.org/10.1016/j.atmosres.2024.107235
10. Precipitable water vapor estimation from Himawari-8/AHI observations using a stacking machine learning model Z. Du et al. https://doi.org/10.1016/j.atmosres.2024.107281
11. An Empirical Grid Model for Precipitable Water Vapor X. Wang et al. https://doi.org/10.3390/rs14236174
12. Global total precipitable water variations and trends over the period 1958–2021 N. Wan et al. https://doi.org/10.5194/hess-28-2123-2024
13. Independent Validation of Total Precipitable Water From Morphed Integrated Microwave Imagery at CIMSS: A Global Study Using GNSS and Radiosonde Measurements J. Xu et al. https://doi.org/10.1109/TGRS.2026.3656168
14. Machine Learning-Based Calibration Study of MERSI-II Atmospheric Precipitable Water Vapor Product M. Li https://doi.org/10.54097/xnwft166