Articles | Volume 19, issue 14
https://doi.org/10.5194/amt-19-4853-2026
https://doi.org/10.5194/amt-19-4853-2026
Research article
 | 
28 Jul 2026
Research article |  | 28 Jul 2026

Extended TCKF1D-Var framework for Mie–Raman lidar boundary layer water vapor profiling: insights into nocturnal preprecipitation moisture evolution

Qi Zhang, Tianmeng Chen, Jianping Guo, and Xun Li

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Short summary
Accurate monitoring of boundary-layer water vapor prior to nocturnal heavy precipitation remains challenging. This study extends a physically constrained retrieval framework by integrating Raman lidar observations to improve water vapor profile estimation. The method shows improved accuracy compared to reanalysis data and captures coherent pre-precipitation moisture evolution, demonstrating its potential for studying and monitoring severe weather processes.
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