Articles | Volume 20, issue 22
https://doi.org/10.5194/bg-20-4591-2023
© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
Chromophoric dissolved organic matter dynamics revealed through the optimization of an optical–biogeochemical model in the northwestern Mediterranean Sea
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- Final revised paper (published on 24 Nov 2023)
- Preprint (discussion started on 06 Mar 2023)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on bg-2023-48', Anonymous Referee #1, 03 Apr 2023
- AC1: 'Reply on RC1', Eva Alvarez, 19 May 2023
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RC2: 'Comment on bg-2023-48', Anonymous Referee #2, 05 Apr 2023
- AC2: 'Reply on RC2', Eva Alvarez, 19 May 2023
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Reconsider after major revisions (20 May 2023) by Yuan Shen
AR by Eva Alvarez on behalf of the Authors (27 Jun 2023)
Author's response
Author's tracked changes
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ED: Referee Nomination & Report Request started (04 Jul 2023) by Yuan Shen
RR by Anonymous Referee #2 (14 Jul 2023)
ED: Publish subject to minor revisions (review by editor) (26 Aug 2023) by Yuan Shen
AR by Eva Alvarez on behalf of the Authors (08 Sep 2023)
Author's response
Author's tracked changes
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ED: Publish as is (17 Sep 2023) by Yuan Shen
AR by Eva Alvarez on behalf of the Authors (20 Sep 2023)
The paper titled "Chromophoric dissolved organic matter dynamics revealed through the optimization of an optical-biogeochemical model in the NW Mediterranean Sea" presents a coupled 1D physical-biogeochemical-optical modelling suite inbedded in a parameter optimization tool. The models are run at the Boussole site in the Ligurian Sea. The large observational database allows tuning the model parameters (except a few parameters who could not be sufficiently constrained by the observed variables).
The authors show a convincing case. The paper is very clear and well written and the figures are relevant. The fully coupled approach is novative. The parameter optimization is very relevant and seems to improve all model variables. The authors also present important possible limitations of the method and justify the choices made (e.g. in section 4.1).
Therefor I have no major comments. I only would have been interested to see a couple of details explained:
(1) the authors state themselves that it remains a future objective to see how the optimized parameteres will behave in a 3D model. It is indeed well known that parameter optimization can be sensitive to particular configurations (see e.g. https://egusphere.copernicus.org/preprints/2023/egusphere-2023-363/#discussion for a very recent example). For example it can compensate poorly represented features by adapting other features as the authors also propose (line 570). Based on their experience, could the authors estimate if the model parameters would lead to realistic results in e.g. areas with more lateral contributions compared to the Boussole station ? The switch from one model to another (GOTM to NEMO) may also be discussed (if relevant). However if no trials have been realized yet, I do not suggest that the authors need to speculate.
(2) can the authors explain if there is any limit imposed on parameters ranges during the creation of new values by the genetic algorithm ? Positivity, statistical distribution, inter-relations or consistency between pairs of parameters, ... ?
(3) the model-satellite comparison is realized over the 9 upper meters. Can the authors justify this choice e.g. in relation to observed optical depth during the year ? Are the model variables simply averaged over the layers corresponding to these 9 meters ?
(4) there is a type line 800, "parameterisation" (without "s")