the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Offline Fennel: A High-Performance and Computationally Efficient Biogeochemical Model within the Regional Ocean Modeling System (ROMS)
Abstract. Ocean biogeochemical models are essential for advancing our understanding of oceanographic processes. Here we present the Offline Fennel model, an offline biogeochemical model implemented within the Regional Ocean Modeling System (ROMS). We evaluated the model performance against a fully coupled physical-biogeochemical online application in the Northern Gulf of Mexico, a region with an intense biogeochemical activity including rather frequent hypoxia events. By leveraging physical hydrodynamic outputs, we ran the Offline Fennel model using various time-step multiples from the coupled configuration, significantly enhancing computational efficiency. This approach reduced simulation time from 6 hours to approximately 30 minutes. The accuracy of the offline model was assessed using three different mixing schemes: the Generic Length Scale (GLS), Large–McWilliams–Doney (LMD, and Mellor and Yamada 2.5 (MY25). The offline model achieved an average skill score of 93 %, with minimal impact on performance from the time-step choice. While the GLS configuration yielded the highest accuracy, all three mixing schemes performed well. Although some discrepancies appeared between offline and coupled simulation outputs, these were smaller than those observed when using different mixing schemes within the same model configuration. The promising results achieved so far validate the Offline Fennel model’s capability and efficiency, thus offering a powerful tool for researchers aiming to conduct extensive biogeochemical simulations without rerunning the hydrodynamic component, thus significantly reducing computational demands.
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Status: open (until 15 May 2025)
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RC1: 'Comment on egusphere-2025-865', Anonymous Referee #1, 11 Apr 2025
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The paper describes the details of the biogeochemical Fennel model for ROMS that can be run in an offline model. The aim of the paper is to report on the model’s capability to reproduce the biogeochemical fields in comparison to an online model and to report on the model’s efficiency. The validation of the model itself is outside of the scope. The links to a github page and detailed instructions to the potential users of the model are also provided in the Appendices to the paper.
The aim of the paper is achieved, and the paper reads very well and is well structured. English is impeccable and I really enjoyed reading this paper. I particularly welcome the detailed instructions contained in the Appendices and I would like to congratulate the authors on this development and on putting together a solid and very well written manuscript. Being a biogeochemical modeller myself I thoroughly understand the need for running the biogeochemical models in an offline mode and all computational savings this approach offers. It has been known for years that the biogeochemical models do not need to run with the same time stepping as the hydrodynamic models and yet few developments tool place so far in this regard.
There are only some minor deficiencies that it would be good to see addressed by the authors:
Ln 88 and the paragraph starting ln 91: I did not follow relevant literature, but the changes to the original Fennel model (2006, 2008) reported in this sentence, in my view, are likely to significantly alter the solution that would be achieved with the original Fennel model. I note the modifications were published in the papers by Laurent et al. (2012), Fennel et al., 2013, Yu et al., 2015 and Laurent et al. 2017. Is this model still called the Fennel model in the literature? The original Fennel model does not contain the phosphates and has only two detrital pools
Ln 140 Is surface net heat flux used in the biogeochemical model? How? Solar shortwave radiation provides the light intensity for the growth equation, but what is the net heat flux used for?
Ln 141 Same question as above for the u- and v- momentum stress
Ln 145 This is a repetition of line 117
Ln 201 What weights were applied and what is n in equation (2)?
Ln 335 It is reported that the biggest difference between the offline and online calculations is observed for NH4, but potential reasons are not discussed. I suggest a paragraph is added in the discussion section. Is it because it is short lived and undergoes relatively quick oxygenation to nitrates? If that was the reason, how about then the accuracy of the solution for other biogeochemical variables, e.g. NO3 and CHL during the times of rapid transformations, e.g. rapid blooms?
Figure 5: I appreciate this is somewhat outside of the scope of the paper, but the differences in the predictions of individual biogeochemical variables appear to be very significant when using different turbulence schemes. Do the authors report on it in a separate manuscript? Is there a scope to include some discussion on it in this paper?
Ln 337 and Figure 6: What are the potential reasons for the GLS scheme resulting in least discrepancies between the online and offline simulations. Some comments on it would be useful in this manuscript.
Figure 6: I suggest it would be more informative if the differences here were reported in the percentage terms.
Ln 431 ‘…, but the time allocated for file writing was insufficient’ – I do not understand this statement. Couldn’t this time be increased? What was the exact reason of the failure of x15 option? I was of an impression from the earlier parts of the manuscript that it had to do with model stability.
Discussion section: The discussion seems to be missing an important aspect: how is the accuracy of the biogeochemical model affected by the sampling rate of the hydrodynamic archive? Are there differences in the currents when the model is running with DT x1 vs DT x10? The differences in the biogeochemical variables under different DTs may be due to the discrepancies in advection due to the sampling rates of the hydrodynamic archive. This will become even more pronounced in highly tidal regions and/or coastal locations under strong influence of the wind.
Ln 584: ‘river detritus computations’ – is river modelled or is it just a forcing in the model? I thought river flows and river inputs are simply prescribed in the model, but this statement suggests that some sort of computations take place – see also line 605, a CPP flag RIVER_BIOLOGY.
Ln 641: add ‘Surface’
Ln 662: ‘and that it cannot be larger than the latter’ – I suggest the word WARNING is added before this statement
Citation: https://doi.org/10.5194/egusphere-2025-865-RC1
Model code and software
Offline Fennel: Offline biogeochemical model within the Regional Ocean Modeling System (ROMS) Júlia Crespin https://doi.org/10.5281/zenodo.14916223
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