SURFER v2.0: a flexible and simple model linking anthropogenic CO<sub>2</sub> emissions and solar radiation modification to ocean acidification and sea level rise

Martínez Montero, Marina; Crucifix, Michel; Couplet, Victor; Brede, Nuria; Botta, Nicola

doi:https://doi.org/10.5194/gmd-15-8059-2022

Articles | Volume 15, issue 21

https://doi.org/10.5194/gmd-15-8059-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-8059-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 21

Model description paper

|

09 Nov 2022

Model description paper |

| 09 Nov 2022

SURFER v2.0: a flexible and simple model linking anthropogenic CO₂ emissions and solar radiation modification to ocean acidification and sea level rise

Marina Martínez Montero, Michel Crucifix, Victor Couplet, Nuria Brede, and Nicola Botta

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Final revised paper (published on 09 Nov 2022)
Preprint (discussion started on 27 Apr 2022)

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-135', Anonymous Referee #1, 23 Jun 2022

see attached pdf

Citation: https://doi.org/10.5194/egusphere-2022-135-RC1
- AC1: 'Reply on RC1', Marina Martinez Montero, 24 Jun 2022
  
  We thank the referee for the insightful comments. We would like to emphasise that the model is primarily intended for commitment analyses in the
  
  timescales of millennia. In those timescales ice sheet tipping points become very relevant and, as shown by Van Breedam et al. (2020), the main contributions to sea level rise come from Greenland and Antarctic ice sheets. It is true, however, that we suggested SURFER could be used for policy assessments that include sea level rise also on shorter timescales. For those timescales, we agree with the referee that, the contributions from
  
  glaciers and thermal expansion are dominant. In the revised version we will explore the references mentioned by the referee and clarify the intended usage of the model. We will consider including contributions from glaciers and ocean thermal expansion to extend the usability of the model on shorter timescales.
  We will also take into account the other comments and they will undoubtedly improve the paper.
  
  Citation: https://doi.org/10.5194/egusphere-2022-135-AC1
RC2:
'Comments on the paper "SURFER v1.0: A flexible and simple model linking emissions to sea level rise"', Anonymous Referee #2, 30 Jun 2022
This paper presents a new simple and fast modelling tool (SURFER) that allow assessing carbon emission evolution and solar radiation management long-term impacts on sea-level rise and ocean acidification. The paper describes the tool, presents example of calibration and associated model results for a few set of experiments. Although I find this work interesting and I believe that SURFER could indeed be useful for the community, this paper does not really demonstrate why SURFER should be used and, in my opinion, somehow lacks of maturity in its present version. Please find below few suggestions/comments that I believe may help improving the manuscript.

Main comments:

Framing and motivation:

I think it would be good to make clearer what SURFER fills as a gap; because EMICs and ESMs can also be used for long runs (as shown in the paper actually), but I understand that they don’t allow estimating SLR and ocean acidification. Is that right?

Most of the introduction moves around the fact that such simple models are useful to explore impact of policy analyses, cost-benefit analyses, etc… for long-term concerns that are mostly omitted. These omissions may in turn lead to wrong decisions. In the conclusion, one can read “[…] it is well-suited for long-sighted multi-objective policy analyses: With this model we can not only assess the short and long-term effects of anthropogenic emissions, but also put future technologies into the mix, such as carbon dioxide removal and solar radiation management.” Although I find such motivation for developing that sort of model indeed appropriate, I don’t believe that results shown in the paper demonstrate this. My suggestion would thus to really perform some policy analyses-like case studies to make this more concrete and support the motivation of the paper. Otherwise, the introduction should rather focus on what the model provides as outputs and how this fills more direct needs.

Ocean acidification is another very important output that should be better emphasized in the title too, not just SLR.

Model design & description:

The model provides SLR estimates due to Greenland and Antarctic melting components but omit first order components such as glaciers, ice caps and thermal expansion. I’d suggest either to upgrade the model to allow accounting for those non-negligible contributions or otherwise to clarify that the model provides “SLR due to ice-sheets melting”.

In the model, the carbon cycle processes that rule carbon fluxes between the atmosphere and ocean rely on chemical & physical processes that are well known and constrained. For the land reservoir though, this appears to be derived from EMICs and ESM simulations and ends up to be model dependent. In this regard, I think it would be good to estimate or comment on how sensitive are the SURFER results to such a parameterization. Is there no other way or can we put additional constraints to lower the influence of external model results?

In my opinion, the ice-sheet module would deserve some more explanation on how the equations on ice volume are derived and to what the different terms refer to – note that I have basically no knowledge on ice-sheet modelling and physics. Details could be provided in a supplementary material.

Model validation & comparison

Section 3 shows some qualitative comparison with CMIP5 and CMIP6 results for some variables but in my opinion, it would be worth to perform a more systematic comparison with CMIP5 & CMIP6 outputs. These data that are easily accessible. Such an analysis would make the models comparison and SURFER performances assessment more convincing.

The Greenland ice-sheet contribution to SLR strongly departs from the other study to which the results are compared (Van Breedam et al., 2020). This suggests a strong sensitivity of the model results to the calibration phase. In this regard, I think that some illustration of the sensitivity to some parameters (e.g. from Table 3 or Table 4) could be very relevant. Moreover, this appears to be easily achievable because the model is particularly fast. From a more general point of view, I think the strength of the SURFER model is that it is very efficient to run long period. One could imagine using such a tool to propagate uncertainty on parameters or boundary conditions.

Specific comments:

L201: Planetary boundary => this is an important point and could be very use as a motivation in the introduction I believe.

Section 2.2: providing units would be useful to better follow the equations.

Eq 32: it would be good to describe all terms in the text below.

Section 2.3: see the main comments, but more details in a supplementary material would be welcome here.

L289: why reasonable value? compared to what ? Please clarify.
Citation: https://doi.org/10.5194/egusphere-2022-135-RC2
- AC2: 'Reply on RC2', Marina Martinez Montero, 05 Jul 2022
  
  We thank the referee for the comments, which we will take into account and will certainly improve the manuscript. We want to clarify that EMICs and ESMs can also be used for long runs and some also estimate sea level rise and ocean acidification. The problem when attempting to use them, for example, in solving a decision problem, is that in general a big quantity of runs are needed, specially when uncertainty is present. This makes the use of EMICs and ESMs slow and impractical for some purposes. This is where SURFER can make a difference. We will thus clarify what is the gap filled by SURFER and illustrate it with an example. We will also take into account and reply to the other comments in the revised version.
  
  Citation: https://doi.org/10.5194/egusphere-2022-135-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Marina Martinez Montero on behalf of the Authors (02 Aug 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (04 Aug 2022) by Ludovic Räss

RR by Daniele Visioni (20 Sep 2022)

Suggestions for revision or reasons for rejection

I’ve been asked to review the revised version of the manuscript for the first time. The aim of this paper is to describe a simple model linking CO2 emissions to ocean acidification and sea level rise; numerous updates have been suggested already in the first round of review.

I’m not an expert on ice sheet modeling, but I think the first 2 reviewers addressed that part already and the authors followed all of the suggestions and improved the manuscript compared to the fist iteration.

In general, I think that such a fast, simple model would be a pretty interesting addition to the literature. However, the results that the authors obtain for SRM have been already discussed in the literature before: for instance (Zarnetske et al. 2021) talk about the fact that ocean acidification wouldn’t be reduced, and while the land carbon sink might be increased (see for instance Cao and Jiang, 2017), that’s really not by much. It would be good for the authors to acknowledge the work done in this area and say that their results confirm (or not if they don’t) previous findings.

A few general comments:

The paper also deals with SRM but the title does not suggest that: “emissions” is a pretty vague term to include both anthropogenic CO2 emissions and SRM. I suggest to change it to something that actually explains it’s about both.

By the way, the term that is now more widely used for SRM is Solar Radiation Modification and not Management (see NASEM report in 2021) or Sunlight Reflection Methods.

Introduction

I would suggest at least explaining what SRM is in the introduction - it might not be so widely known as the authors think and a reader can’t be expected to go look at the references provided.

L 12: because of the long
L 14: not sure “value” is the right word here: assessing the efficacy is perhaps a better term

Section 2

L 79: SO2 is a gas, so “SO2 aerosol injections” is not really a meaningful definition.
L 412: I would remove the square brackets [] for the estimates of ECS and TCR.

Section 3

L 480: “ We have considered that the Solar Radiation Management sulphur injections remain zero during the whole simulation period.” unclear of why it is relevant here. The RCPs and SSPs do not have SRM, and the G6 experiment is another thing and discussed in another section. This phrase is repeated multiple times in the following paragraphs and it really doesn’t need to: maybe say at the beginning of Section 3 when you’ll be considering SRM instead of all the scenarios where you’re not.

Figure 9 (and following figures): it is customary to name the panels in alphabetical order to make it easy on the reader; the legend hides one of the panel’s results.

Fig. 18: The comparison between SURFER results and G6 is interesting, but it could be done in just one plot. If the authors want to contact me (being the author of the 2021 paper cited, dv224@cornell.edu) I’ll gladly give them the SO2 values to combine the two figures in one.

Cao, L., & Jiang, J. (2017). Simulated effect of carbon cycle feedback on climate response to solar geoengineering. Geophysical Research Letters, 44, 12,484– 12,491. https://doi.org/10.1002/2017GL076546

Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth,
P. L. Zarnetske, J. Gurevitch, J. Franklin, P. M. Groffman, C. S. Harrison, J. J. Hellmann,
Forrest M. Hoffman, S. Kothari, A. Robock, S. Tilmes, D. Visioni, J. Wu, L. Xia, C.
Yang, Proceedings of the National Academy of Sciences Apr 2021, 118 (15) e1921854118;
https://doi.org/10.1073/pnas.1921854118

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ED: Publish subject to minor revisions (review by editor) (20 Sep 2022) by Ludovic Räss

AR by Marina Martinez Montero on behalf of the Authors (30 Sep 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (02 Oct 2022) by Ludovic Räss

AR by Marina Martinez Montero on behalf of the Authors (11 Oct 2022) Manuscript

Short summary

We present SURFER, a lightweight model that links CO₂ emissions and geoengineering to ocean acidification and sea level rise from glaciers, ocean thermal expansion and Greenland and Antarctic ice sheets. The ice sheet module adequately describes the tipping points of both Greenland and Antarctica. SURFER is understandable, fast, accurate up to several thousands of years, capable of emulating results obtained by state of the art models and well suited for policy analyses.

SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise

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SURFER v2.0: a flexible and simple model linking anthropogenic CO₂ emissions and solar radiation modification to ocean acidification and sea level rise