the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Nov 2021
A missing link in the carbon cycle: phytoplankton light absorption
Abstract. Marine biota and biogeophysical mechanisms, such as phytoplankton light absorption, have attracted increasing attention in recent climate studies. Under global warming, the impact of phytoplankton on the climate system is expected to change. Previous studies analyzed the impact of phytoplankton light absorption under prescribed future atmospheric CO2 concentrations. However, the role of this biogeophysical mechanism under freely-evolving atmospheric CO2 concentration and future CO2 emissions remain unknown. To shed light on this research gap, we perform simulations with the EcoGEnIE Earth system model and prescribe CO2 emissions following the four Representative Concentration Pathways (RCP) scenarios. Under all the RCP scenario, our results indicate that phytopankton light absorption increases the surface chlorophyll biomass, the sea surface temperature, the atmospheric CO2 concentrations and the atmospheric temperature. Under the RCP2.6, RCP4.5 and RCP6.0 scenarios, the magnitude of changes due to phytoplankton light absorption are similar. However, under the RCP8.5 scenario, the changes in the climate system are less pronounced due to the temperature limitation of phytoplankton growth, highlighting the reduced effect of phytoplankton light absorption under strong warming. Additionally, this work evidences the major role of phytoplankton light absorption on the climate system, suggesting a highly uncertain feedbacks on the carbon cycle with uncertainties that are in the range of those known from the land biota.
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RC1: 'Comment on esd-2021-91', Pearse Buchanan, 07 Jan 2022
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AC1: 'Reply on RC1', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC1-supplement.pdf
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AC1: 'Reply on RC1', Rémy Asselot, 23 Feb 2022
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RC2: 'Comment on esd-2021-91', Anonymous Referee #2, 07 Jan 2022
Phytoplankton in the ocean absorbs light, and the amount of phytoplankton exists changes the degree of shortwave penetration into the ocean. Since shortwave radiation raises water temperature, there may be differences in water temperature, primary production, and climate change if phytoplankton light absorption is taken into account in water temperature fluctuations in a model or not. Using an Earth system model of intermediate complexity, the authors conducted future scenario experiments with and without phytoplankton light absorption to evaluate how phytoplankton light absorption would affect primary production and climate change. I believe that this study points out what has been lacking in conventional climate research and provides important implications for future model development. However, before accepting this manuscript, I think that there are some aspects of the authors’ analysis that could be improved as follows. I may have misread some things, and I do not think the authors need to follow all my comments, but I hope that the following comments will help the authors to improve their manuscript.
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Model validity
l.154 “Figure 3 shows that our increase in SAT are in agreement with Zickfeld et al. (2013)”
In order to show the validity of the model, the authors compared the change in SAT with a previous study, but what about the distribution of SST, nutrients, chlorophyll concentration, etc.? Since these are directly relevant to this study, I think it would be better to compare climatic values, etc. with observations to see if the model reproduces the approximate distribution. -
Mechanism enhancing upwelling
l.180 “an enhanced vertical velocity which is triggered by changes in the oceanic heat budget”
In this model, the shortwave penetrates down to the sixth layer at 221.84 m, but the authors insisted the upwelling at 326 m depth is enhanced due to the phytoplankton light absorption (l.180). It is not clear why the upwelling is enhanced.
l.235 “this biogeophysical mechanisms enhances the upward vertical velocity”
I could not understand why that would happen.
In addition, the concentration of chlorophyll depends not only on nutrients but also on water temperature and shortwave radiation. It would be good to have a discussion of how these factors might have affected the results. -
Difference from the concentration runs
l.213 “However, in Asselot et al. (2021a) we do not prescribe any CO2 emissions, neglecting their effect on the atmospheric CO2 concentration.”
It is ambiguous why the increase in atmospheric CO2 concentration of the emission driven runs is different from that of the concentration-driven runs, so it would be better to add some analysis. For example, by considering the phytoplankton light absorption, can we estimate how the water temperature changes, how it changes the carbon concentration in the ocean and the atmosphere-ocean carbon flux, and how it changes the concentration of the atmospheric CO2? If the authors could figure this out, it would clarify the difference from concentration driven experiments and the importance of this study. -
Results and analysis on RCP8.5 runs
l.249–251 “This is due to the model setup where a SST higher than 20C limits phytoplankton growth. This threshold is only exceeded for the simulations RCP8.5-LA and RCP8.5 (Appendix D1), therefore phytoplankton growth is limited by the ocean temperature in these two simulations (Figure 10).”
First, I think that this 20 degreeC limit is arbitrary (part of tuning), so I am not confident that the results of the RCP8.5 experiments relying on it are correct.
Even in the current climate, water temperatures are above 20 degreeC in equatorial regions, etc. Is this high SST in these regions not reproduced in the model? I do not believe this is the case, so the authors may want to reconsider their analysis for RCP8.5 runs.
Figure 10
How was this calculated? Was it calculated from the global-mean SST? If so (see Table D1), I do not understand why the temperature limitation is calculated from the global-mean SST, since the growth rate of phytoplankton is determined by the water temperature and other conditions at each location.
As mentioned above, there are some points that need to be improved regarding the analysis of the results. Hopefully the authors will revise the manuscript to make it more convincing.
Some minor comments are listed below. I hope they will be useful for the authors to revise their manuscript.
Minor comments:
Section 2.1
There is no description of the emissions from 2100 to 2250, so it would be good to describe them briefly.l.75 “The Earth system mode (ESM)l”
This should be “The Earth system model (ESM)”l.78–82
I think the authors want to show how much EcoGEnIE was used, and for that, it would be better to use past tense or present perfect tense.Section 2.2.4
It would be easier to understand if the previous method without phytoplankton light absorption is also described and compared.l.136 “dT/dt denotes the temperature changes”
The dT/dt term here is the water temperature change only associated with radiative heating, so I think it should be clearly stated as such.l.139 “(Asselot et al., 2021a)”
This should be “Asselot et al. (2021a)”l.143 “The spin-up is run with a constant pre-industrial atmospheric CO2 concentration of 278 ppm.”
l.154 “In the pre-industrial simulation, the atmospheric CO2 concentration is constant and set to 278 ppm.”
I thought the model was emission driven, but do these sentences mean that it is concentration driven during spin-up? Instead of a spin-up with zero emissions? If so, when is the timing of changing from concentration driven to emission driven? Was there any shock at the timing when it became emission driven?l.144 “after the spin-up for 737 years-long, since the CO2 emissions data are only available for this time span”
Does this 737 years refer to the past 737 years? Or does it include future data? I think it is unclear how the spin-up was done after ECOGEM was switched on, so it would be good if the authors could write it clearly.l.147 “In total, we run 8 similations following the RCP scenarios”
Before the RCP scenarios, there should be a historical run (Figure 1), but the description of the method for the historical run is ambiguous.l.176 “This pronounced chlorophyll increase is due to the coarse grid resolution”
Why does chlorophyll increase if the grid resolution is coarse?l.178–179 “the upwelling and mid-latitude regions” / “the subtropical gyres”
The upwelling, mid-latitude, and subtropical regions can be overlapping, so the meaning of the sentence is unclear.l.186 “the SST is the zonally-averaged temperature from the surface to 29 m depth”
“vertically-averaged”?l.204 “the expected atmospheric CO2 concentrations in 2500 under the RCP scenarios are not reached.”
It is difficult to understand for me, I am glad if the authors rewrite it.l.205 “EcoGEnIE has not been tuned yet.”
Are the authors saying that more tuning is needed? Since the concentrations in emission-driven runs are the result of various balances and it is difficult to adjust the concentrations in the model to reality, why not simply state the fact that atmospheric CO2 concentrations are low here?l.217 “The global changes in oceanic and atmospheric properties due to phytoplankton light absorption lead to an increase of surface atmospheric temperature (SAT) (Figure 8).”
I believe that the importance of plankton light absorption can be conveyed to readers by clearly describing the mechanism of how plankton light absorption affects SAT through the changes in ocean and atmosphere conditions.l.234 “increasing the remineralization and thus the nutrient concentrations at the ocean surface”
Since there has been no mention of remineralization before, it is difficult to follow the discussion.l.241 “the sea-air CO2 flux”
This is not clear whether the authors are referring to upward flux or ocean carbon uptake, so please specify.l.259 “the model has not been tuned in this configuration yet.”
See comments on l.205.l.286 “phytoplankton-induced global warming”
I do not think phytoplankton will induce global warming. I can see how the light absorption of phytoplankton can affect the progress of global warming, and in my opinion, the word “induced” is not appropriate here.Figure 3
Does this figure represent global mean SAT changes?Figure 4 caption “Zonally”
“Globally”?Citation: https://doi.org/10.5194/esd-2021-91-RC2 -
AC2: 'Reply on RC2', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC2-supplement.pdf
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RC3: 'Comment on esd-2021-91', Anonymous Referee #3, 07 Jan 2022
This paper describes a set of long (> 500 y) simulations with an EMIC, with and without phytoplankton absorption of solar radiation and the associated ocean heating, and argues that this represents an important and mostly neglected process in the climate system. What is novel and interesting is that (1) phytoplankton biomass tends to increase rather than decrease under enhanced greenhouse forcing, (2) the effect is not monotonic with increasing emissions, and tends to be damped or reversed in the highest emission scenario examined, and (3) the effect on atmospheric CO2 concentration appears to be large.
I believe that this is an important experiment that deserves to be published, but the paper is not well written and requires, at least, major revision. Possibly it would be better if the editors declined the paper and returned it to the authors so that they could take the time required to craft a more substantial contribution. The English is adequate, but it would be best if the authors could find a native-speaker colleague to give it a thorough English editing before resubmission. The title could be revised to be more specific about what the actual content of the paper is; the present wording is fairly generic and uninformative.
Major points:
(1) The authors do not make a lot of effort to explain the mechanisms underlying the differences observed between the Light Absorption (hereafter LA) case and the non-LA case. Combined with the inadequacies of the model description, this makes it difficult to credit some of the more dramatic claims made, in particular the much higher atmospheric CO2 concentration in the LA case.
I estimate that by temperature-dependence of CO2 solubility alone, an increase in the global mean ocean temperature of 1 C would increase atmosphere CO2 by ~14 PgC. In the experiments shown here the increase in SST (which would be an extreme upper limit for the change in the ocean mean) is <1 C (Figs 4+6, Table D1). A weaker biological pump could add another ~5 PgC, assuming Delta-DIC/Delta-PO4 = 106 and a net increase of ~0.1 mmol P m^-3 (Table C1) over a surface layer 100 m thick. The atmospheric CO2 increase shown here is extremely large by comparison, ranging from ~75 PgC in RCP2.6 to ~250 Pg in RCP8.5, assuming that it takes ~2 PgC as CO2 to increase the atmosphere concentration by 1 ppm (Figure 7).
Maybe these are simplistic, static calculations. The experiments are long and the ocean is continuously overturning, so maybe the explanation lies in upwelling of the existing ocean inventory of DIC into a surface ocean that is getting warmer and therefore outgassing more CO2 to the atmosphere. A problem with this hypothesis is that RCP8.5 has by far the largest amount of excess atmospheric CO2 associated with LA (Figure 7), but the smallest increase in SST (Figure 4, Table D4). However, RCP8.5 also has the largest cumulative CO2 uptake (both LA and non-LA), so maybe this could be explained by greater outgassing of anthropogenic CO2 taken up earlier. Possibly the authors could consider comparing the 3D distribution of DIC at the beginning and the end of the experiments, or making a map of net outgassing of CO2. At any rate, I think more effort to identify the underlying mechanisms is warranted. It could also help if they cited some previous publications that demonstrate that this very coarse-resolution model can produce at least approximately realistic ocean upwelling.
(2) There are some important details missing from the model description. I understand that all of the submodels are previously published, but key details that are directly relevant to the results presented should be briefly reiterated. Most disturbingly, the assertion that the ocean biology model operates in a static fashion at each grid point, without ocean transport of the related tracers, appears from nowhere in the Results (198), whereas the Methods appears to say the opposite (90). One could imagine, for example, that increased upwelling of nutrients causes large increases in phytoplankton biomass at the grid points where upwelling occurs (with the additional heat being advected away), in a way that might not occur if the phytoplankton were also being advected by ocean currents. Could they show some profiles of how chlorophyll concentration evolves over time? Do they remain within the range of historical observed values? Or at least within the realm of plausibility? The paper also appears not to state whether chlorophyll concentration in the non-LA expts is given a constant, nonzero value, or is assumed to be 0 (k=k_w).
There is no description of parameterizations of phytoplankton photoacclimation or chlorophyll synthesis or degradation. As I understand it, the model has prognostic phytoplankton C, P, and chlorophyll (117). So there is no photoacclimation per se: both C and Chl are prognostic. But a brief description of the phytoplankton growth and chlorophyll synthesis model is warranted, and a statement of whether there is any loss of chlorophyll independent of grazing or other loss of cells. Chlorophyll synthesis requires N and Fe, but not P. I assume they use a fixed N/P ratio to estimate the dependence of chlorophyll synthesis on N; whether it also depends on Fe is not stated. Nor is it stated whether the C/P and C/Fe ratios are fixed or variable; I assume that C/Fe is fixed and C/P variable, as there is prognostic phytoplankton P but not Fe. This should be clearly explained and ratios used (where they are fixed) stated.
Nor is there any description of surface solar irradiance or of radiative transfer in the atmosphere. It is stated that the incoming shortwave varies seasonally (140), but there is nothing about its geographic distribution (for example, top-of-atmosphere irradiance might be calculated from astronomical formulae and atmospheric attenuation assumed constant). They should also specify the fraction of total solar irradiance that is assumed to be shortwave/longwave, as only the former is affected by phytoplankton absorption. The energy balance atmosphere presumably has a submodel for radiative transfer (e.g., how does upwelling/downwelling longwave radiation vary as a function of atmospheric CO2 concentration). The climate changes are strongly dependent on this, so at least a brief description is warranted.
Other less immediately relevant process that could use a brief description include carbon chemistry and gas exchange (106-107), the wind data used and the calculation of the wind stress and the drag coefficient (the non-dynamical energy balance atmosphere requires that wind speed and wind stress at the ocean surface be specified), and the dependence of ocean vertical mixing on stratification.
Finally, the description of the spinup and the experimental design is confusing. First they spun up the model for 10000 years with BIOGEM but not ECOGEM "to have a realistic distribution of nutrients" (142-143). Then there is possibly a further spinup with ECOGEM turned on, before the historical/RCP experiments are launched, but the description is confusing and I can't really tell what was done. Why would spinning up the model produce a realistic distribution of nutrients if there is no biological pump? I would have spun it up for a further 2000-3000 years with all of the biological processes active. Nor is it stated how they know that the system is in steady-state at 2500 (149).
(3) The Introduction is a grab-bag of literature citations intended to provide the impression that there is a broad consensus that phytoplankton biomass has declined over the historical period and is likely to decline further in the enhanced-greenhouse future. In my opinion this assertion is nowhere near as robust as the authors imply and gives the main premise of the paper a "straw man" quality. In Kwiatkowski et al., the average decline in NPP is only 3% by 2100, in the highest emissions scenario. Bopp et al (2022; 10.5194/bg-2021-320) suggest that phytoplankton biomass may be a more robust diagnostic than NPP (this paper is still in the Discussion stage, but the authors should at least take a look at it). Boyce et al 2010 drew some rather vigorous criticism (www.nature.com/articles/nature09953). Boyce et al (2014, 10.1016/j.pocean.2014.01.004) address some of these criticisms and should certainly be cited here. They claim that the basic conclusion that a long term secular (downward) trend is detectable remains sound, but this conclusion remains controversial and I think that the authors of the current contribution should treat it a bit more skeptically. The results of Polovina et al and McClain et al represent too short time series to be inferred to represent long-term secular trends, and should be discussed in the context of the difficulty of separating such trends from natural variability (e.g., 10.5194/bg-7-621-2010, 10.1029/2019GB006453). Behrenfeld et al show a statistical relationship between chlorophyll and stratification in the historical record of observed climate variability (mainly ENSO); their extrapolation of this to changes expected under anthropogenic warming is quite speculative (in any case, how can observations (21) tell us what will happen in the future?) I have not read Sonntag or Paulsen, and I can't say I find the synopses offered here very illuminating. As these are PhD theses rather than journal articles it is important to summarize their findings clearly, as the original text may not be accessible to the reader.
Minor points:
Terminology regarding IPCC and the RCPs (57-62): It is a common misconception that CMIPs/RCPs/SSPs are 'commissioned' or 'solicited' or 'approved' by IPCC. Proper citation format for IPCC Assessment (or other) Reports is given in the reports, but citing these in the present context is unnecessary. It is better to just cite Moss et al 2010 (10.1038/nature08823) for the RCPs and Taylor et al 2012 (10.1175/BAMS-D-11-00094.1) for CMIP5. Referring to scenarios as predictions (61) should be avoided (as should referring to scenario-based climate projections as predictions, e.g., 16, 270).
I don't think Section 3 is necessary, and it could be folded into the Results. I think this result is worth showing (although it might be better treated as Supplementary). But I think it is overreaching to say that it by itself 'validates' the model setup (and by implication all of the submodels that affect results shown in this paper). The wording should be a bit more tentative and simply describe what was actually tested against what.
Citation: https://doi.org/10.5194/esd-2021-91-RC3 -
AC3: 'Reply on RC3', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC3-supplement.pdf
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AC3: 'Reply on RC3', Rémy Asselot, 23 Feb 2022
Status: closed
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RC1: 'Comment on esd-2021-91', Pearse Buchanan, 07 Jan 2022
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AC1: 'Reply on RC1', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC1-supplement.pdf
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AC1: 'Reply on RC1', Rémy Asselot, 23 Feb 2022
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RC2: 'Comment on esd-2021-91', Anonymous Referee #2, 07 Jan 2022
Phytoplankton in the ocean absorbs light, and the amount of phytoplankton exists changes the degree of shortwave penetration into the ocean. Since shortwave radiation raises water temperature, there may be differences in water temperature, primary production, and climate change if phytoplankton light absorption is taken into account in water temperature fluctuations in a model or not. Using an Earth system model of intermediate complexity, the authors conducted future scenario experiments with and without phytoplankton light absorption to evaluate how phytoplankton light absorption would affect primary production and climate change. I believe that this study points out what has been lacking in conventional climate research and provides important implications for future model development. However, before accepting this manuscript, I think that there are some aspects of the authors’ analysis that could be improved as follows. I may have misread some things, and I do not think the authors need to follow all my comments, but I hope that the following comments will help the authors to improve their manuscript.
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Model validity
l.154 “Figure 3 shows that our increase in SAT are in agreement with Zickfeld et al. (2013)”
In order to show the validity of the model, the authors compared the change in SAT with a previous study, but what about the distribution of SST, nutrients, chlorophyll concentration, etc.? Since these are directly relevant to this study, I think it would be better to compare climatic values, etc. with observations to see if the model reproduces the approximate distribution. -
Mechanism enhancing upwelling
l.180 “an enhanced vertical velocity which is triggered by changes in the oceanic heat budget”
In this model, the shortwave penetrates down to the sixth layer at 221.84 m, but the authors insisted the upwelling at 326 m depth is enhanced due to the phytoplankton light absorption (l.180). It is not clear why the upwelling is enhanced.
l.235 “this biogeophysical mechanisms enhances the upward vertical velocity”
I could not understand why that would happen.
In addition, the concentration of chlorophyll depends not only on nutrients but also on water temperature and shortwave radiation. It would be good to have a discussion of how these factors might have affected the results. -
Difference from the concentration runs
l.213 “However, in Asselot et al. (2021a) we do not prescribe any CO2 emissions, neglecting their effect on the atmospheric CO2 concentration.”
It is ambiguous why the increase in atmospheric CO2 concentration of the emission driven runs is different from that of the concentration-driven runs, so it would be better to add some analysis. For example, by considering the phytoplankton light absorption, can we estimate how the water temperature changes, how it changes the carbon concentration in the ocean and the atmosphere-ocean carbon flux, and how it changes the concentration of the atmospheric CO2? If the authors could figure this out, it would clarify the difference from concentration driven experiments and the importance of this study. -
Results and analysis on RCP8.5 runs
l.249–251 “This is due to the model setup where a SST higher than 20C limits phytoplankton growth. This threshold is only exceeded for the simulations RCP8.5-LA and RCP8.5 (Appendix D1), therefore phytoplankton growth is limited by the ocean temperature in these two simulations (Figure 10).”
First, I think that this 20 degreeC limit is arbitrary (part of tuning), so I am not confident that the results of the RCP8.5 experiments relying on it are correct.
Even in the current climate, water temperatures are above 20 degreeC in equatorial regions, etc. Is this high SST in these regions not reproduced in the model? I do not believe this is the case, so the authors may want to reconsider their analysis for RCP8.5 runs.
Figure 10
How was this calculated? Was it calculated from the global-mean SST? If so (see Table D1), I do not understand why the temperature limitation is calculated from the global-mean SST, since the growth rate of phytoplankton is determined by the water temperature and other conditions at each location.
As mentioned above, there are some points that need to be improved regarding the analysis of the results. Hopefully the authors will revise the manuscript to make it more convincing.
Some minor comments are listed below. I hope they will be useful for the authors to revise their manuscript.
Minor comments:
Section 2.1
There is no description of the emissions from 2100 to 2250, so it would be good to describe them briefly.l.75 “The Earth system mode (ESM)l”
This should be “The Earth system model (ESM)”l.78–82
I think the authors want to show how much EcoGEnIE was used, and for that, it would be better to use past tense or present perfect tense.Section 2.2.4
It would be easier to understand if the previous method without phytoplankton light absorption is also described and compared.l.136 “dT/dt denotes the temperature changes”
The dT/dt term here is the water temperature change only associated with radiative heating, so I think it should be clearly stated as such.l.139 “(Asselot et al., 2021a)”
This should be “Asselot et al. (2021a)”l.143 “The spin-up is run with a constant pre-industrial atmospheric CO2 concentration of 278 ppm.”
l.154 “In the pre-industrial simulation, the atmospheric CO2 concentration is constant and set to 278 ppm.”
I thought the model was emission driven, but do these sentences mean that it is concentration driven during spin-up? Instead of a spin-up with zero emissions? If so, when is the timing of changing from concentration driven to emission driven? Was there any shock at the timing when it became emission driven?l.144 “after the spin-up for 737 years-long, since the CO2 emissions data are only available for this time span”
Does this 737 years refer to the past 737 years? Or does it include future data? I think it is unclear how the spin-up was done after ECOGEM was switched on, so it would be good if the authors could write it clearly.l.147 “In total, we run 8 similations following the RCP scenarios”
Before the RCP scenarios, there should be a historical run (Figure 1), but the description of the method for the historical run is ambiguous.l.176 “This pronounced chlorophyll increase is due to the coarse grid resolution”
Why does chlorophyll increase if the grid resolution is coarse?l.178–179 “the upwelling and mid-latitude regions” / “the subtropical gyres”
The upwelling, mid-latitude, and subtropical regions can be overlapping, so the meaning of the sentence is unclear.l.186 “the SST is the zonally-averaged temperature from the surface to 29 m depth”
“vertically-averaged”?l.204 “the expected atmospheric CO2 concentrations in 2500 under the RCP scenarios are not reached.”
It is difficult to understand for me, I am glad if the authors rewrite it.l.205 “EcoGEnIE has not been tuned yet.”
Are the authors saying that more tuning is needed? Since the concentrations in emission-driven runs are the result of various balances and it is difficult to adjust the concentrations in the model to reality, why not simply state the fact that atmospheric CO2 concentrations are low here?l.217 “The global changes in oceanic and atmospheric properties due to phytoplankton light absorption lead to an increase of surface atmospheric temperature (SAT) (Figure 8).”
I believe that the importance of plankton light absorption can be conveyed to readers by clearly describing the mechanism of how plankton light absorption affects SAT through the changes in ocean and atmosphere conditions.l.234 “increasing the remineralization and thus the nutrient concentrations at the ocean surface”
Since there has been no mention of remineralization before, it is difficult to follow the discussion.l.241 “the sea-air CO2 flux”
This is not clear whether the authors are referring to upward flux or ocean carbon uptake, so please specify.l.259 “the model has not been tuned in this configuration yet.”
See comments on l.205.l.286 “phytoplankton-induced global warming”
I do not think phytoplankton will induce global warming. I can see how the light absorption of phytoplankton can affect the progress of global warming, and in my opinion, the word “induced” is not appropriate here.Figure 3
Does this figure represent global mean SAT changes?Figure 4 caption “Zonally”
“Globally”?Citation: https://doi.org/10.5194/esd-2021-91-RC2 -
AC2: 'Reply on RC2', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC2-supplement.pdf
-
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RC3: 'Comment on esd-2021-91', Anonymous Referee #3, 07 Jan 2022
This paper describes a set of long (> 500 y) simulations with an EMIC, with and without phytoplankton absorption of solar radiation and the associated ocean heating, and argues that this represents an important and mostly neglected process in the climate system. What is novel and interesting is that (1) phytoplankton biomass tends to increase rather than decrease under enhanced greenhouse forcing, (2) the effect is not monotonic with increasing emissions, and tends to be damped or reversed in the highest emission scenario examined, and (3) the effect on atmospheric CO2 concentration appears to be large.
I believe that this is an important experiment that deserves to be published, but the paper is not well written and requires, at least, major revision. Possibly it would be better if the editors declined the paper and returned it to the authors so that they could take the time required to craft a more substantial contribution. The English is adequate, but it would be best if the authors could find a native-speaker colleague to give it a thorough English editing before resubmission. The title could be revised to be more specific about what the actual content of the paper is; the present wording is fairly generic and uninformative.
Major points:
(1) The authors do not make a lot of effort to explain the mechanisms underlying the differences observed between the Light Absorption (hereafter LA) case and the non-LA case. Combined with the inadequacies of the model description, this makes it difficult to credit some of the more dramatic claims made, in particular the much higher atmospheric CO2 concentration in the LA case.
I estimate that by temperature-dependence of CO2 solubility alone, an increase in the global mean ocean temperature of 1 C would increase atmosphere CO2 by ~14 PgC. In the experiments shown here the increase in SST (which would be an extreme upper limit for the change in the ocean mean) is <1 C (Figs 4+6, Table D1). A weaker biological pump could add another ~5 PgC, assuming Delta-DIC/Delta-PO4 = 106 and a net increase of ~0.1 mmol P m^-3 (Table C1) over a surface layer 100 m thick. The atmospheric CO2 increase shown here is extremely large by comparison, ranging from ~75 PgC in RCP2.6 to ~250 Pg in RCP8.5, assuming that it takes ~2 PgC as CO2 to increase the atmosphere concentration by 1 ppm (Figure 7).
Maybe these are simplistic, static calculations. The experiments are long and the ocean is continuously overturning, so maybe the explanation lies in upwelling of the existing ocean inventory of DIC into a surface ocean that is getting warmer and therefore outgassing more CO2 to the atmosphere. A problem with this hypothesis is that RCP8.5 has by far the largest amount of excess atmospheric CO2 associated with LA (Figure 7), but the smallest increase in SST (Figure 4, Table D4). However, RCP8.5 also has the largest cumulative CO2 uptake (both LA and non-LA), so maybe this could be explained by greater outgassing of anthropogenic CO2 taken up earlier. Possibly the authors could consider comparing the 3D distribution of DIC at the beginning and the end of the experiments, or making a map of net outgassing of CO2. At any rate, I think more effort to identify the underlying mechanisms is warranted. It could also help if they cited some previous publications that demonstrate that this very coarse-resolution model can produce at least approximately realistic ocean upwelling.
(2) There are some important details missing from the model description. I understand that all of the submodels are previously published, but key details that are directly relevant to the results presented should be briefly reiterated. Most disturbingly, the assertion that the ocean biology model operates in a static fashion at each grid point, without ocean transport of the related tracers, appears from nowhere in the Results (198), whereas the Methods appears to say the opposite (90). One could imagine, for example, that increased upwelling of nutrients causes large increases in phytoplankton biomass at the grid points where upwelling occurs (with the additional heat being advected away), in a way that might not occur if the phytoplankton were also being advected by ocean currents. Could they show some profiles of how chlorophyll concentration evolves over time? Do they remain within the range of historical observed values? Or at least within the realm of plausibility? The paper also appears not to state whether chlorophyll concentration in the non-LA expts is given a constant, nonzero value, or is assumed to be 0 (k=k_w).
There is no description of parameterizations of phytoplankton photoacclimation or chlorophyll synthesis or degradation. As I understand it, the model has prognostic phytoplankton C, P, and chlorophyll (117). So there is no photoacclimation per se: both C and Chl are prognostic. But a brief description of the phytoplankton growth and chlorophyll synthesis model is warranted, and a statement of whether there is any loss of chlorophyll independent of grazing or other loss of cells. Chlorophyll synthesis requires N and Fe, but not P. I assume they use a fixed N/P ratio to estimate the dependence of chlorophyll synthesis on N; whether it also depends on Fe is not stated. Nor is it stated whether the C/P and C/Fe ratios are fixed or variable; I assume that C/Fe is fixed and C/P variable, as there is prognostic phytoplankton P but not Fe. This should be clearly explained and ratios used (where they are fixed) stated.
Nor is there any description of surface solar irradiance or of radiative transfer in the atmosphere. It is stated that the incoming shortwave varies seasonally (140), but there is nothing about its geographic distribution (for example, top-of-atmosphere irradiance might be calculated from astronomical formulae and atmospheric attenuation assumed constant). They should also specify the fraction of total solar irradiance that is assumed to be shortwave/longwave, as only the former is affected by phytoplankton absorption. The energy balance atmosphere presumably has a submodel for radiative transfer (e.g., how does upwelling/downwelling longwave radiation vary as a function of atmospheric CO2 concentration). The climate changes are strongly dependent on this, so at least a brief description is warranted.
Other less immediately relevant process that could use a brief description include carbon chemistry and gas exchange (106-107), the wind data used and the calculation of the wind stress and the drag coefficient (the non-dynamical energy balance atmosphere requires that wind speed and wind stress at the ocean surface be specified), and the dependence of ocean vertical mixing on stratification.
Finally, the description of the spinup and the experimental design is confusing. First they spun up the model for 10000 years with BIOGEM but not ECOGEM "to have a realistic distribution of nutrients" (142-143). Then there is possibly a further spinup with ECOGEM turned on, before the historical/RCP experiments are launched, but the description is confusing and I can't really tell what was done. Why would spinning up the model produce a realistic distribution of nutrients if there is no biological pump? I would have spun it up for a further 2000-3000 years with all of the biological processes active. Nor is it stated how they know that the system is in steady-state at 2500 (149).
(3) The Introduction is a grab-bag of literature citations intended to provide the impression that there is a broad consensus that phytoplankton biomass has declined over the historical period and is likely to decline further in the enhanced-greenhouse future. In my opinion this assertion is nowhere near as robust as the authors imply and gives the main premise of the paper a "straw man" quality. In Kwiatkowski et al., the average decline in NPP is only 3% by 2100, in the highest emissions scenario. Bopp et al (2022; 10.5194/bg-2021-320) suggest that phytoplankton biomass may be a more robust diagnostic than NPP (this paper is still in the Discussion stage, but the authors should at least take a look at it). Boyce et al 2010 drew some rather vigorous criticism (www.nature.com/articles/nature09953). Boyce et al (2014, 10.1016/j.pocean.2014.01.004) address some of these criticisms and should certainly be cited here. They claim that the basic conclusion that a long term secular (downward) trend is detectable remains sound, but this conclusion remains controversial and I think that the authors of the current contribution should treat it a bit more skeptically. The results of Polovina et al and McClain et al represent too short time series to be inferred to represent long-term secular trends, and should be discussed in the context of the difficulty of separating such trends from natural variability (e.g., 10.5194/bg-7-621-2010, 10.1029/2019GB006453). Behrenfeld et al show a statistical relationship between chlorophyll and stratification in the historical record of observed climate variability (mainly ENSO); their extrapolation of this to changes expected under anthropogenic warming is quite speculative (in any case, how can observations (21) tell us what will happen in the future?) I have not read Sonntag or Paulsen, and I can't say I find the synopses offered here very illuminating. As these are PhD theses rather than journal articles it is important to summarize their findings clearly, as the original text may not be accessible to the reader.
Minor points:
Terminology regarding IPCC and the RCPs (57-62): It is a common misconception that CMIPs/RCPs/SSPs are 'commissioned' or 'solicited' or 'approved' by IPCC. Proper citation format for IPCC Assessment (or other) Reports is given in the reports, but citing these in the present context is unnecessary. It is better to just cite Moss et al 2010 (10.1038/nature08823) for the RCPs and Taylor et al 2012 (10.1175/BAMS-D-11-00094.1) for CMIP5. Referring to scenarios as predictions (61) should be avoided (as should referring to scenario-based climate projections as predictions, e.g., 16, 270).
I don't think Section 3 is necessary, and it could be folded into the Results. I think this result is worth showing (although it might be better treated as Supplementary). But I think it is overreaching to say that it by itself 'validates' the model setup (and by implication all of the submodels that affect results shown in this paper). The wording should be a bit more tentative and simply describe what was actually tested against what.
Citation: https://doi.org/10.5194/esd-2021-91-RC3 -
AC3: 'Reply on RC3', Rémy Asselot, 23 Feb 2022
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2021-91/esd-2021-91-AC3-supplement.pdf
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AC3: 'Reply on RC3', Rémy Asselot, 23 Feb 2022
Model code and software
Source code Rémy Asselot https://zenodo.org/record/5676165
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