Adaptive observation weighting in TCKF1D-Var for  ground-based multi-sensor thermodynamic retrievals  prior to nocturnal heavy precipitation over China

Zhang, Qi; Chen, Tianmeng; Guo, Jianping; Deng, Bin; Li, Han; Wu, Yu

doi:10.5194/gmd-19-9555-2026

Articles | Volume 19, issue 19

https://doi.org/10.5194/gmd-19-9555-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-9555-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 19

Model description paper

|

09 Oct 2026

Model description paper |

| 09 Oct 2026

Adaptive observation weighting in TCKF1D-Var for ground-based multi-sensor thermodynamic retrievals prior to nocturnal heavy precipitation over China

Qi Zhang, Tianmeng Chen, Jianping Guo, Bin Deng, Han Li, and Yu Wu

Data sets

Ground-Based Multi-Sensor Thermodynamic Retrievals Prior to Nocturnal Heavy Precipitation over China Qi Zhang et al. https://doi.org/10.5281/zenodo.20603287

Short summary

This study presents an adaptive observation-weighting scheme for thermodynamic profile retrievals from ground-based microwave radiometers and Mie–Raman lidars. The method dynamically estimates observational contributions during the retrieval process, replacing the commonly used static weighting assumption. Evaluation using 107 heavy-precipitation cases shows improved retrieval accuracy, particularly for atmospheric moisture profiles.