11 citations as recorded by crossref.

1. Ground visibility prediction using tree-based and random-forest machine learning algorithm: Comparative study based on atmospheric pollution and atmospheric boundary layer data F. Wang et al. https://doi.org/10.1016/j.apr.2024.102270
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3. Formation Mechanism of Consecutive Dense Fog Events over the Ma-Zhao Expressway in Yunnan, Southwest China, Late Autumn 2022 Y. Ding et al. https://doi.org/10.3390/atmos17040416
4. Numeral simulation of impacts of sea land breeze on the formation and dissipation of the Bohai Sea fog L. Meng et al. https://doi.org/10.1016/j.atmosres.2025.108190
5. Thermodynamic and microphysical properties of summertime marine fog observed from Sable Island K. Rowe et al. https://doi.org/10.1002/qj.70098
6. A multi-parameter diagnostic framework for radiation fog and nocturnal visibility A. Eken & S. Sırdaş https://doi.org/10.1007/s00704-026-06254-3
7. Multiscale Visibility Forecasting over Complex Terrain Using High-Temporal-Resolution WRF Fields and a Physics-Informed Spatial Prior C. Yuan et al. https://doi.org/10.3390/forecast8050091
8. Overestimated Fog-Top Entrainment in WRF Simulation Leading to Unrealistic Dissipation of Sea Fog: A Case Study L. Zhang et al. https://doi.org/10.3390/rs16101656
9. A novel balloon/UAV-borne lightweight cloud particle imager sonde: instrumentation and field study L. Cai et al. https://doi.org/10.1088/1361-6501/ae74fd
10. High‐Resolution Simulation of Dense Fog in Tianjin City: Effect of Horizontal Resolutions From Mesoscale to Large Eddy Scale M. Tian et al. https://doi.org/10.1002/met.70053
11. DBTF-Net: dual-branch decoupled network for laser-spot restoration and channel sensing in hybrid turbulence–fog FSO systems Y. Yan et al. https://doi.org/10.1364/JOCN.584987