Title:

  Chlorophyll-a concentration effects on equatorial Atlantic Ocean mean-state and interannual variability

Authors

  Arthur Prigent, Riccardo Farneti , Manfredi Manizza and Rodrigue Anicet Imbol Koungue

A well written relatively short paper discussing the effect of plankton, represented by the concentration of chlorophyll-a, on the surface layers of the equatorial Atlantic.  However the paper does appear to have one major fault in that, in a system where SST and near surface stratification is important, the paper does not consider the interaction of the ocean and atmospheric temperature fields.  I discuss the problem more below.

This review concentrates primarily on the ocean physics aspects of the study.  I do not have the right background to review the comparisons with studies in the Pacific or with observations of Atlantic upwelling systems.

Detailed Comments

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Abstract

Line 7:

    This does not explain which part of the 'vertical temperature gradient' is weakened.  Later are you referring to the surface thermocline or the main oceanic thermocline.

Line 8

    Equatorial upwelling is not reduced.  If the winds used in the different runs are the same then the Ekman transports will be the same, as will equatorial upwelling.

Line 10

    'non-linearly'.  After reading the rest of the paper I find this bland statement misleading.  It needs something which implies that a reduction in chlorophyll has a large effect - and so will be the focus of the paper - with increases in concentration have a smaller effect.

Introduction

Line 14

    'The underlying dynamics ...'.  I am not sure why 'underlying' is needed.  Given that the best predictions of El Ninos are produced by computers and nobody understands the 'underlying' 'why', this is a slightly dangerous statement.

Line 33

    'well observed' is a bit clumsy - how about something like 'accurately and easily measured'.

Line 59

    After a detailed discussion of previous studies, the paper states some aims of the study - but I felt it would help the reader to have some clues along the lines of "As will be shown ... ".

Data and Methods

Line 90

    It would be cleaner just to say that in the model the incident radiation is split into three components, infra-red, red visible and green visible, in the ratios 0.58, 0.21 and 021.

Line 95

    Given the importance of the depth of heating in the following analysis, it would help to give the e-folding distance (i.e. 1/k) for each of the three 'k'.  For the two which depend on concentration and the seasonal cycle, minimum and maximum depths would also be important.

Line 99

    The paper states "this climatology is considered vertically uniform".  It then states

    "This is certainly a limitation as the maximum on Chi-a is usually found close to the nutricline".

    The phrase "considered vertically uniform" is too vague.  I presume that this means the chlorophyll field is independent of depth in the model.

    But I think a more serious problem is that the paragraph hints that the model is not suitable for many studies involving chlorophyll.  In reality the chlorophyll and nutrient distribution will depend on surface mixed layer depth and stratification.  It therefor needs to explain why the model is suitable for the different runs.  I can understand it may have been tuned for the standard case and still be valid with no chlorophyll, but with double chlorophyll one might expect additional feedbacks.

Methods

Line 108

    It would help to state here that the paper will focus on the changes in the low chlorophyll run.

Line 118

    This needs to be clear about the difference between the near surface thermocline and main oceanic thermocline.

Line 122

    The null and alternative hypotheses statements are misleading.  The null hypothesis should probably be that on the basis of the evidence the signal cannot be distinguished from zero.  But I don't than that a yes/no argument is valid.  What the paper discusses later is the 'probability' that the signal is different from zero.

    The bootstrap method of resampling with replacement is one way of doing this.  I think the paragraph needs a good rewrite, with some good references describing the method, the quality of the results and how it compares with other methods for estimating the probability that results are significant.

Results

Line 132

    The paper appears to make a serious mistake in not considering the strong interactions between air temperature and sea surface temperature.

    It states that the JRA-55 atmospheric fields have been used.  As well as the wind stress fields and the downward radiation fluxes JRA-55 also includes the 10m air temperature and humidity.  Within the ocean model these variables will normally be used to calculate the sensible and latent heat fluxes across the air sea interface.

    If this does not happen in the version of Mom used, they my following comments should be ignored and the paper corrected with a better explanation of the way the ocean model handles the JRA-55 data.

    The sensible heat flux depends just on the air-sea temperature difference.  The latent heat flux is a function of both the temperature difference and the humidity of the atmosphere.  Ocean models usually include code to represent these processes and I would be surprised in Mom is different.  The fluxes are not small and in reality this means that SST and the surface atmospheric temperature are usually close.

    In the present case, where the atmospheric temperature is fixed, it means that the SST will always be close to the imposed air temperature.  This helps explains why the two functions in Fig. 4c stay so close over such a long period of time.  The SST differences seen in Fig 4a, are thus really a measure of how hard to system is trying to get away from the imposed air temperature.  In a fully coupled system the differences will be larger.

    I am not sure how the surface boundary condition affects the rest of the results.  I suspect that they also show the direction in which changes will occur in a fully coupled system - but this is really up to the authors to think through.

Lines 165-180

    The statement of line 170 correctly implies that because the winds are the same in the different runs, the Ekman net transport will be the same.  This further means that Ekman driven upwelling at the Equator will also be the same.  So nothing can "strengthen equatorial upwelling through poleward volume transports"

    What can change is the vertical distribution of the Ekman transport and this will change the velocities at each level.  The changed transport will also affect the vertical structure of equatorial upwelling.

    As an example of the Ekman transport profile changing, over much of the ocean a large fraction of the Ekman transports is usually found in the surface mixed layer.  In this case if the mixed layer shallows but the transport in the layer stays the same, then velocities in the layer will increase to give the same total transport.

    Anyway both paragraphs need to be rewritten as do any similar statements elsewhere in the paper.

Line 200

    "weakened equatorial upwelling".  See above.

Line 206

    "MJJ", "ND".  Expand.

General Comments

The manuscript investigates how the presence of chlorophyll affects near surface ocean temperature and stratification around the equatorial Atlantic. The study uses idealised experiments with a coarse-resolution ocean model where a monthly chlorophyll climatology is scaled to represent varying levels of chlorophyll abundance. Additionally, it uses a satellite chlorophyll product to demonstrate a declining trend in the equatorial Atlantic and two eastern Atlantic coastal upwelling systems.

In my opinion, this study is interesting and although idealised, it offers much needed insight into the effects of chlorophyll on the physical ocean conditions of the equatorial Atlantic; which is a biophysical feedback mechanism that is currently underexplored and often overlooked in models and theoretical frameworks. Hence, the study has strong merit and is suitable for publication in EGUsphere. However, I have some comments and queries aimed at improving the clarity of the methodology, results, and discussion. Therefore, I recommend minor revisions before the manuscript is published.

Specific comments

1. Abstract, lines 9–10. For clarity, I suggest replacing "of chlorophyll-a concentration scaled by 0.01, 0.5..." with something along the lines of: "The response of eastern equatorial Atlantic SST to chlorophyll changes is non-linear, such that doubling or halving the chlorophyll-a concentration does not have a proportional impact."
2. Line 58. For clarity, consider clarifying that instead of using different climatologies, you are using "experiments forced with different scaling factors applied to the same monthly Chl-a climatology."
3. Section 2. I recommend splitting Section 2 into three distinct subsections to improve readability: (i) Subsection 2.1- Observational Data (focusing on the current Section 2.1.1). (ii) Subsection 2.2 - Model Configuration and Experiments (combining the current 2.1.2 and 2.2.1, the model setup and experiment details). (iii) Subsection 2.3 - Analysis Methods (covering the current 2.2.2 and 2.2.3 to anomaly definitions and significance testing). Additionally, to aid the reader, I suggest including a summary table of your experiments. For example, explicitly showing that ITCP-MOM5-CTRL corresponds to the SeaWiFS Chl-a monthly climatology, ITCP-MOM5-0.5 corresponds to 50% of the SeaWiFS Chl-a monthly climatology, etc.
4. Section 2.2.1. I found the introduction of the observational data somewhat confusing, as it is not immediately clear how they are used at this stage. Are they used as a reference for comparison/validation, or as a baseline to create the climatological forcing for your control run? Please clarify if these data are used strictly for comparison/validation and are distinct from the forcing data (if I have understood correctly).
5. Line 85. If I understand correctly, this is the baseline climatology used across all experiments (albeit scaled). I suggest explicitly highlighting this point.
6. Section 2.2.1. Please clearly state the integration periods for both your control and sensitivity simulations. (Maybe is mentioned elsewhere and I missed it but this is probably the place to clarify it).
7. Line 99. I am unsure what is meant by "if” a monthly climatology is provided here. My understanding is that a monthly climatology is forced across all experiments; please clarify.
8. Line 113. Could you please clarify what is meant by "raw data"? Do you mean the model outputs? Additionally, please specify the temporal frequency of the model outputs that you are using.
9. Lines 125–126. I believe you mean the difference between the “two model simulations/experiments” rather than "the two models" (e.g., CTL vs. CHL0.01).
10. Lines 158–161. It is not entirely clear how Figure 2 (showing seasonal SST climatology across experiments and observations) demonstrates the importance of accounting for phytoplankton effects on the vertical distribution of shortwave heating. The SST bias in this region is not necessarily driven by a misrepresentation of Chl-a. While increasing Chl-a makes the surface cooler, it does not mean it reduces the bias for the correct physical reasons, as evidenced by the persistent year round bias between observations and all model configurations regardless of Chl-a scaling. I recommend rephrasing this part to focus strictly on the physical effects/changes induced by the scaling, rather than framing it as a correction of model bias. Furthermore, because you later argue that Chl-a controlling the vertical distribution of shortwave heating is not the dominant mechanism in the equatorial Atlantic (if I understood correctly), introducing it this way here creates some confusion.
11. Lines 162–169. I agree with your argument. However, for completeness, maybe highlight here that this specific response occurs within the equatorial Atlantic (and other upwelling regions, along the easter coastal Atlantic). Outside this (e.g., in Fig. 2a), we do see a typical surface cooling associated with a reduction in chlorophyll, which aligns with the traditional view that lower chlorophyll allows shortwave radiation to penetrate deeper, cooling the surface. Highlighting that this counterintuitive warming response is unique to the upwelling zones (the equator and potentially the Senegal/Namibia coasts in Fig. 2) would add valuable context.
12. Line 167. Please clarify what you mean by "opposite what is done here"? In your setup, you have a control run and experiments where chlorophyll is fractionally increased or decreased. How does this contrast with traditional experiments featuring active or not active bioheating?
13. Lines 168–169. Please clarify the phrase "strengthens the upwelling". Do you mean it leads to a faster upwelling velocity that is more regionally confined and draws water from different depths?
14. Lines 170–180 (and Discussion lines 229–231). I would welcome some clarification on the physical mechanism proposed here. While I agree that a deeper mixed layer in an upwelling region can coincide with higher SST under steady winds, the explanation could be clearer. Mechanistically, volume transport and upwelling are determined by wind stress, so they should remain relatively unaltered by changes in mixed layer depth . Instead, when the mixed layer deepens (as seen in CHL-0.01), the meridional velocity decreases to matches changes in the vertical velocity (consistent with Fig. 3b). The mixed layer deepening pushes the thermocline and the underlying cold water downward. Consequently, under identical wind forcing, the water being upwelled is warmer, and at the same time because the horizontal transport of this water away from the equator is slower, it has more time to warm from the atmosphere. The combination of these two would lead to the surface temperature increase in the CHL-0.01 experiment. Maybe I have misunderstood but please consider revising this part for clarify of the dynamics.
15. Lines 179-180. This links to my comment above. Maybe I have misunderstood, but it is not clear how a shallower mixed layer would lead to weaker upwelling under identical wind forcing. Please consider rephrasing to clarify.
16. Lines 190, 193, Figures 4 and 5. Please explicitly define the abbreviations SSTA and TEMPA in the text and captions (I am not sure what they mean).
17. Figure 5. Could you please clarify your trend estimates? Specifically, why are the values multiplied by 120 and 100?

1. Figure 6. Please clarify both in the text (lines 215–220) and in the figure caption whether these estimates are derived from the GlobColour product (which I think is the case) or the model's control run.