the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean
Abstract. We present BIOPERIANT12, a regional model configuration of the Southern Ocean (SO) at a mesoscale-resolving 1/12°. This is a stable, ocean–ice–biogeochemical configuration derived from the Nucleus for European Modelling of the Ocean (NEMO) modelling platform. It is specifically designed to investigate questions related to the mean state, seasonal cycle variability and mesoscale processes in the mixed layer and within the upper ocean (<1000 m). In particular, the focus is on understanding processes behind carbon and heat exchange, systematic errors in biogeochemistry and assumptions underlying the parameters chosen to represent these SO processes. The dynamics of the ocean model play a large role in driving ocean biogeochemistry and we show that over the chosen period of analysis 2000–2009 that the simulated dynamics in the upper ocean provide a stable mean state, as compared to observation-based datasets (themselves subject to biases such as sparsity of data, cloud cover, etc.), and through which the characteristics of variability can be described. Using ocean biomes to delineate the major regions of the SO, the model demonstrates a useful representation of ocean biogeochemistry and partial pressure of carbon dioxide (pCO2). In addition to a reasonable model mean state performance, through model–data metrics BIOPERIANT12 highlights several pathways for improving Southern Ocean model simulations such as the representation of temporal variability and the overestimation of biological biomass.
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Status: final response (author comments only)
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CC1: 'Comment on gmd-2024-182', Takaya Uchida, 29 Oct 2024
I appreciate the authors for citing our work but Uchida et al. (2019, 2020) increased the horizontal model resolution up to 2km and their results are not limited to a resolution of 20km as implied by the authors here (line 49).
Citation: https://doi.org/10.5194/gmd-2024-182-CC1 -
AC1: 'Reply on CC1', Nicolette Chang, 29 Oct 2024
Thank you for your feedback. My sincere apologies, model experiments with resolutions up to 2 km should definitely be referenced properly! The statement references examples of different model design choices for coupled physics-BGC models, it will be revised.Citation: https://doi.org/
10.5194/gmd-2024-182-AC1
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AC1: 'Reply on CC1', Nicolette Chang, 29 Oct 2024
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CEC1: 'Comment on gmd-2024-182 - No compliance with the policy of the journal', Juan Antonio Añel, 02 Dec 2024
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlFirst, the Code Availability section of your manuscript is incomplete. Please, check it, because there is missing information.
Second, you have not shared all the models, code and data necessary to replicate your work. This includes the NEMO-PISCES v3.4 and all the input data used to run your model.
Therefore, the current situation with your manuscript is irregular. Please, publish your code and data in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible, as we can not accept manuscripts in Discussions that do not comply with our policy.
Moreover, you must include the modified 'Code Availability' and Data Availability' sections in a potentially reviewed manuscript, including the DOIs and links to the new repositories.
Please, note that if you do not fix this problem in a quick manner, we will have to reject your manuscript for publication in our journal.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/gmd-2024-182-CEC1 -
AC2: 'Reply on CEC1', Nicolette Chang, 04 Dec 2024
Please accept updates to the code and data availability statement as below. This includes corrected links to Zenodo repositories with updated contents, containing:
1. model code (cpp keys, modified files, base code) https://doi.org/10.5281/zenodo.13910092
2. Python notebooks and data to produces manuscript figures and model input files (grids, initial, boundary conditions and weights) https://doi.org/10.5281/zenodo.13919282Code and data availability. The current version of NEMO is available from the project website: https://www.nemo-ocean.eu/ under the CeCILL license. The exact version of the model used to produce the results used in this paper is archived on Zenodo (https://doi.org/10.5281/zenodo.13910092), as are input data and scripts to run the model and produce the plots for all the simulations presented in this paper (https://doi.org/10.5281/zenodo.13919282).
Citation: https://doi.org/10.5194/gmd-2024-182-AC2 -
CEC2: 'Reply on AC2', Juan Antonio Añel, 04 Dec 2024
Dear authors,
Many thanks for addressing this issue. Now we can consider the current version of your manuscript compliant with our policy.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/gmd-2024-182-CEC2
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CEC2: 'Reply on AC2', Juan Antonio Añel, 04 Dec 2024
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AC2: 'Reply on CEC1', Nicolette Chang, 04 Dec 2024
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RC1: 'Comment on gmd-2024-182', Anonymous Referee #1, 03 Feb 2025
The article discuss a new model for the Southern Ocean named BIOPERIANT12. Even if the scientific knowledge of the article is good the introduction needs to be re-written considering that is is now just one paragraph. I would also suggest to put the references in a different color.
-I think the initial condition section needs to be expanded
-In line 122, can you references where the numbers come from ?
-In line 232, do you think if you would run the model for longer than 10 years it would be less stable?
-In 425, in the article you have used two phytoplankton classes. IS there a reason why you choose only two classes?
Overall the manuscript gives a valuable advance in modelling the Southern Ocean but the author needs to improve the writing before I can endorse.
Citation: https://doi.org/10.5194/gmd-2024-182-RC1 -
AC3: 'Reply on RC1', Nicolette Chang, 20 Mar 2025
Thank you for your suggestions, they been noted and implemented.Line 122: Background values were obtained from default ORCA configurations.Line 232, if the model were to be run over a longer duration, the model would be forced with increasing atmospheric CO2 and radiation/temperature and a trend at the surface would become more apparent. While I consider the model to be still stable if run for a further decade (I expect/hope no spurious mesoscale instabilities will develop), I cannot account for potential drift in the ocean interior and deeper layers which may have time to develop, altering the vertical water column thus affecting the surface from below.Line 425: For this reference run, two phytoplankton classes were provided with the PISCES NEMO v3.4 version used. Future runs/sensitivity experiments can address this choice.Citation: https://doi.org/
10.5194/gmd-2024-182-AC3
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AC3: 'Reply on RC1', Nicolette Chang, 20 Mar 2025
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RC2: 'Comment on gmd-2024-182', Anonymous Referee #2, 13 Mar 2025
The manuscript does a good job at describing a relatively high-resolution circulation, sea ice and biogeochemistry model for the Southern Ocean and evaluating its strengths and weaknesses. The authors describe the difficulties of properly representing the complex dynamics of the SO and of validating the results with limited available data often biased towards warmer months, and describe biases found by other studies.
One of my main concerns with the manuscript is the description of its purpose. The conclusion seems to focus on the limitations of the model and on improvements needed, while arguing that it this novel setup can be used for future studies. This section would benefit from a comparison of what this model improves relative to other SO models, and of what type of studies it would be suited for. Even if this document is just to document the model evaluation, a more in-depth discussion of solutions to current biases and mismatches with observations, as well as recommendations for observations would add value to the manuscript.
Some more pointed suggestions are highlighted below.
L53: “run duration which relies on periods of sufficient observations” seems vague
L54-58: Sentence is too long and a bit confusing
L60-61: matters more for simulations of hundreds of years, but does it matter at this scale? If not, why bring this up?
L75-76: “although more recent versions were available” – for which components?
L79: what is the resolution of the eddy-permitting?
L96-97: maybe add some references for how well inputs extracted from ORCA05 are represented in that run?
L103-104: I think you could expand a bit here. What biases were observed? My initial thought was that using a “normal year” would also introduce errors, so why one versus the other?
L116: Is this shown somewhere, to inform users?
L147-148: Maybe a sentence on how mean transport was calculated?
L163: It’s hard to see where 36-43˚S is, would be helpful to add latitudes to the maps
L169: Do you mean higher resolution in the model compared to observations?
L179-183: Sentence is too long
L185: Do you mean monthly mean for the 2000-2009 period?
L200-204: I’m confused about the message on the final sentences. Does the variability of the front position complicate the analysis or improve bgc representation?
Figure 3: grey shadings are all the same, and should specify which satellite
L238: area-weighing of which dataset? WOA?
L239-240: Reasoning is not super clear to me.
Section 3.1.5: could the negative SST bias and positive sub-surface temperature bias be influencing MLD?
L265-267: Need more information on the calculations
L271: What does SP-STPS, SA-STPS and IND-STPS stand for?
L325: would be useful to have a more in-depth description of the data product for readers to interpret the model-data differences
L239-243: Might want to rephrase it. At some point it becomes unclear if you are talking about ICE or the whole domain
L356: Avoid repeating thus?
L363-365: Doesn’t that depend on dFE sources, since it will not stay in the surface long? Are you talking about biases in the initialization files? I would assume this has more to do with model setup than with the choice of model
L381-381: respectively, after the values?
L382: How is the representation of simulated silicate dictated by laboratory experiments? This sentence was a bit confusing to me.
Figure 11: There are substantial differences in the summer pattern that need to be discussed
L396-397: wouldn’t the overestimation be true regardless of biome classification?
Section 3.4.3: How good is the satellite temporal coverage in the different biomes? Is it properly representing intra seasonal to interannual variability? Discussing potential biases in the observation might help the discussion here
Citation: https://doi.org/10.5194/gmd-2024-182-RC2 -
AC4: 'Reply on RC2', Nicolette Chang, 20 Mar 2025
Thank you for the feedback, I will implement suggestions and stengthen points.
Citation: https://doi.org/10.5194/gmd-2024-182-AC4
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AC4: 'Reply on RC2', Nicolette Chang, 20 Mar 2025
Model code and software
BIOPERIANT12-CNCLNG01 N. Chang https://doi.org/10.5281/zenodo.8475
BIOPERIANT12-manuscript Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, and Tumelo C. Moalusi https://github.com/nicolettechang/BIOPERIANT12-manuscript
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