Articles | Volume 15, issue 22
Geosci. Model Dev., 15, 8541–8559, 2022
https://doi.org/10.5194/gmd-15-8541-2022
Geosci. Model Dev., 15, 8541–8559, 2022
https://doi.org/10.5194/gmd-15-8541-2022
Development and technical paper
22 Nov 2022
Development and technical paper | 22 Nov 2022

Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a)

Sujeong Lim et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-333', Juan Antonio Añel, 20 Nov 2021
    • AC1: 'Reply on CEC1', Sujeong Lim, 12 Jan 2022
  • RC1: 'Comment on gmd-2021-333', Anonymous Referee #1, 02 Feb 2022
    • AC2: 'Reply on RC1', Sujeong Lim, 10 Mar 2022
  • RC2: 'Comment on gmd-2021-333', Anonymous Referee #2, 21 Feb 2022
    • AC3: 'Reply on RC2', Sujeong Lim, 10 Mar 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sujeong Lim on behalf of the Authors (22 Apr 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (28 Apr 2022) by Yuefei Zeng
RR by Anonymous Referee #3 (18 May 2022)
RR by Anonymous Referee #1 (24 May 2022)
ED: Reconsider after major revisions (26 May 2022) by Yuefei Zeng
AR by Sujeong Lim on behalf of the Authors (22 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (23 Jul 2022) by Yuefei Zeng
ED: Publish subject to minor revisions (review by editor) (06 Sep 2022) by Yuefei Zeng
AR by Sujeong Lim on behalf of the Authors (26 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (27 Sep 2022) by Yuefei Zeng
AR by Sujeong Lim on behalf of the Authors (09 Oct 2022)  Author's response    Manuscript

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Sujeong Lim on behalf of the Authors (16 Nov 2022)   Author's adjustment   Manuscript
EA: Adjustments approved (17 Nov 2022) by Yuefei Zeng
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Short summary
The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.