Articles | Volume 19, issue 1
https://doi.org/10.5194/gmd-19-505-2026
https://doi.org/10.5194/gmd-19-505-2026
Model description paper
 | 
15 Jan 2026
Model description paper |  | 15 Jan 2026

Retrieving atmospheric thermodynamic and hydrometeor profiles using a thermodynamic-constrained Kalman filter 1D-Var framework based on ground-based microwave radiometer

Qi Zhang, Tianmeng Chen, Jianping Guo, Yu Wu, Bin Deng, and Junjie Yan

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'No compliance with the policy of journal - action needed', Juan Antonio Añel, 07 Oct 2025
    • AC1: 'Reply on CEC1', Qi Zhang, 08 Oct 2025
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 10 Oct 2025
        • AC2: 'Reply on CEC2', Qi Zhang, 11 Oct 2025
  • RC1: 'Comment on egusphere-2025-4381', Anonymous Referee #1, 27 Oct 2025
    • AC3: 'Reply on RC1', Qi Zhang, 06 Nov 2025
  • RC2: 'Comment on egusphere-2025-4381', Anonymous Referee #2, 01 Dec 2025
    • AC4: 'Reply on RC2', Qi Zhang, 09 Dec 2025
      • RC3: 'Reply on AC4', Anonymous Referee #2, 10 Dec 2025
        • AC5: 'Reply on RC3', Qi Zhang, 13 Dec 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Qi Zhang on behalf of the Authors (14 Dec 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (15 Dec 2025) by Cenlin He
RR by Anonymous Referee #2 (17 Dec 2025)
RR by Anonymous Referee #1 (29 Dec 2025)
ED: Publish subject to minor revisions (review by editor) (01 Jan 2026) by Cenlin He
AR by Qi Zhang on behalf of the Authors (05 Jan 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (08 Jan 2026) by Cenlin He
AR by Qi Zhang on behalf of the Authors (08 Jan 2026)  Author's response   Manuscript 
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Short summary
We propose TCKF1D-Var, a thermodynamic-constrained variational framework for ground-based microwave radiometer retrievals. Using virtual potential temperature, a ratio-based cost function, and a microphysics closure, it reduces biases relative to ERA5 and 1D-Var, improves cloud liquid water representation, and enhances heavy rainfall precursors, extending lead times. This approach strengthens continuous profiling and supports high-impact weather nowcasting.
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