the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessment of transparent exopolymer particles in the Arctic Ocean implemented into the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Abstract. We present an assessment of the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3, in which we integrated state equations for dissolved acidic polysaccharides (PCHO) and transparent exopolymer particles (TEP), as proposed by Engel et al. (2004), to explicitly describe these two organic carbon pools in the Arctic Ocean. PCHO is simulated as one fraction of the phytoplankton exudates, which can then aggregate to form larger particles, TEP. Since observational datasets on TEP are rare in time and space, we systematically assess the novel model implementation by stepwise discussing the essential components of the organic carbon cycle. Firstly, the simulated phytoplankton biomass yields good results when compared to in situ and remote-sensing products of total Chlorophyll a and particulate organic carbon. Secondly, we compare PCHO to observations in the Fram Strait, as an exemplary data-rich region, and to datasets in other regions of the Arctic Ocean. The model realistically reproduces a high phytoplankton exudation rate of PCHO under nutrient-depleted conditions. Thirdly, we assess simulated TEP concentrations by comparing them to in situ measurements from several campaigns to the Arctic Ocean. The simulation provides a first estimate of mean TEP concentrations of 200–400 μg C L−1 on the continental shelves and 10–50 μg C L−1 in the central basins (0–30 m depth range). Lastly, we put the model performance into a global context for TEP concentrations in the upper ocean layer. As such, the implementation of PCHO exudation, aggregation to TEP, and their remineralization processes into FESOM2.1–REcoM3 offers a reasonably good agreement with observations, on which further modeling work can build upon.
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Status: open (until 02 Dec 2025)
- RC1: 'Comment on egusphere-2025-4190', Anonymous Referee #1, 21 Oct 2025 reply
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Curated model results of TEP simulation in FESOM2.1-REcoM3 Moritz Zeising https://doi.org/10.5281/zenodo.15174190
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The paper by Zeising and co-authors, titled “Assessment of transparent exopolymer particles in the Arctic Ocean implemented into the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3”, describes the new implementation of PCHO and TEP tracers and respective processes in a global ocean BGC model, which is calibrated for the Arctic Ocean. The model was integrated for 1958-2019 period where the results from the last three decades is analyzed. In addition to evaluating the performance of the simulated PCHO and TEP, they present the mean states and spatial distribution of the simulated phytoplankton-related carbon state variables, including the seasonal cycle, and comparison with observational-based estimates. It is nicely written and easy to follow with clear figures to illustrate key messages the authors try to convey. As a model description, the paper contains sufficient details and result presentations. I have a few comments that hopefully the authors can address to further improve the paper.
Main comments
Impacts of adding these new processes and state variables. The motivation is well outlined in the introduction, nevertheless, how do these new processes change the carbon/nutrient cycling/export production/PP/etc., as compared to the model’s reference configuration without these new tracers, are not so clear after reading the paper. The readers should get some insights whether these processes are indeed important and/or worth implementing in other models.
Assuming similar baseline experiments exist but without the new improvements, some figures or performance metrics could be useful to have. For instance, a climatological seasonal vertical profile of nutrients from models with and without this modification (compared with observations) could be interesting to see.
How much of the 662Pg DOC (L17) are PCHO based on your model simulation? How much are converted to POC or what is the new POC export rate? Can you stipulate how future climate change may alter this and the broader ocean carbon cycle?
The results seem to be quite sensitive to limiter function (eqs. 5-6). Please briefly describe how the threshold 0.2 and 0.151 was determined and if they are spatially varying?
As the authors stated, this is an important first step toward advancing the air-sea coupling (L39-41) in ESMs. Can you elaborate your plans in this direction? Is it feasible to simulate the marine TEP emissions? What would be the cloud feedback and radiation budget effect mentioned? Will it be similar to DMS (Schwinger et al., 2017 BG, https://doi.org/10.5194/bg-14-3633-2017)? Can the authors estimate the magnitude of this effect?
Most (if not all) of the presented analysis are for surface processes. Are TEP and PCHO in the model only exist near the surface layers and none below? Is that why the spin up was so short and if they exist below the mixed layer, are they in sufficiently steady state? Some discussions or presentations of impacts on interior biogeochemistry (if any) would be appreciated.
Minor comments:
Fig3 caption: mention that this is from model simulation. Why not add observations here?
Fig3 caption: remove extra ‘)’
L295: add space after period.
L306: describe SIC
Fig4: why are there ‘discontinuity’ in the red lines?
Fig5: Any observations that can be plotted together (e.g. in same color dashed lines)?
Why only eastern Fram Strait in Fig. 5, I would think showing the western Fram Strait or N. Barents Sea could be interesting, showing also the sea-ice concentrations.
L340: in the eastern Fram Strait(?)
L344: ”It peaks at 150 µg C L−1 in August and quickly declines thereafter“, this is inconsistent with Fig. 5.
Table 5: Eurasian Basin (3e-51): is this a typo?
L429: remove ‘)’
L461-4: Vertical profiles comparing model and observations would be useful.
L471: at the beginning of
L472: and decrease toward
L481: A scatter plots of TEP vs TChla (from Fig. 4), including DIN values could support this statement.
L493-6: The statement gives the impression that the correlation of 0.71 considers the data from Caitlin Ice Base, when in fact data less than 1umol is excluded (Fig. A4 caption). Please rephrase.
L581: 10-150 is not ‘agreeing well’ with 0-39. Please rephrase.