Relating climate sensitivity indices  to projection uncertainty

Sanderson, Benjamin

doi:https://doi.org/10.5194/esd-11-721-2020

Articles | Volume 11, issue 3

https://doi.org/10.5194/esd-11-721-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-11-721-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 3

Research article

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04 Aug 2020

Research article | Highlight paper |

| 04 Aug 2020

Relating climate sensitivity indices to projection uncertainty

Benjamin Sanderson

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Final revised paper (published on 04 Aug 2020)
Supplement to the final revised paper
Preprint (discussion started on 10 Dec 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of 'Relating Climate Sensitivity Indices to projection uncertainty'', Anonymous Referee #1, 13 Jan 2020
- AC1: 'Response to Reviewer 1', Ben Sanderson, 09 Mar 2020
RC2: 'Interactive comment on “Relating Climate Sensitivity Indices to projection uncertainty” by Benjamin Sanderson', Anonymous Referee #2, 23 Jan 2020
- AC2: 'Response to Reviewer 2', Ben Sanderson, 09 Mar 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (07 Apr 2020) by Valerio Lucarini

AR by Ben Sanderson on behalf of the Authors (09 Apr 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (16 Apr 2020) by Valerio Lucarini

RR by Anonymous Referee #2 (27 Apr 2020)

Suggestions for revision or reasons for rejection

The manuscript in the current version has substantially improved compared to the initial draft. The order of the sections is more suitable for the ESD format and a number of details have been added to clarify the methodology.
Particularly, I appreciated that the authors now explicitly discuss the choice of the two timescales for the optimisation in section 1 and, again, in the conclusions. Still, not only Proistosescu and Huybers, 2017, but also other authors (Caldeira et al. 2013; Joos et al. 2013; Tsutsui 2017) have chosen the three timescales for a pulse-response exponential relaxation model, similarly through an educated guess based on heuristic considerations. Therefore, I wonder if the author might explicitly mention the motivation behind his choice, the same way he did in the response to the reviewers.
Provided that the author accounts for this general comment, and for the specific suggestions listed in the following, I thereby recommend that the manuscript is accepted for publication.

Specific comments
- l. 66 and elsewhere: there are probably some LaTeX problems with the citation format for several references throughout the manuscript;
- Eq.2: the equations appear a bit packed here. Consider introducing a broader spacing;
- ll. 87-88: as far as my memory goes, the value of 3.7 Wm-2 for the CO2 radiative forcing is computed at doubling compared to pre-industrial baseline (see IPCC AR4, sect. 2.3). Can the authors explain why they refer to it as for CO2 quadrupling?
- l. 174: this is the only explicit reference to Figure S3 in the manuscript. Nevertheless, this figure contains quite a relevant part of the information that this work aims at conveying. The author might consider moving it from the supplementary material, or at least attach it to a more extensive discussion, since it is crucial in order to support the discussion on the role of the historical forcing for the role of the metrics in the CMIP models (ll. 192-198);
- Figure S4: I think this figure might benefit by reducing the thickness of the lines, as those are barely legible in the current version;
- ll. 226-227: I do not understand the author's choice to generate noise that has the parameters of an hypothetical multi-model mean noise. Particularly, it is not clear to me why the statistics of the noise including model would would be more representative of the metrics relation with the warming than the actual model if a model-dependent noise is applied;
- ll- 281-283: the point that I made in my previous revision is not that there is an indefinite number of exponentials that can be combined to describe the response function. Rather, I wanted to stress that other methods, as those based on the Ruelle's response theory (cfr. Ragone et al. 2016, Lucarini et al. 2017, Lembo et al. 2019; I believe that the correct reference here is "Lembo V., Lucarini V., and Ragone F., 2019, Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model, ArXiv, 1912.03996"), allow to extract a (linear) response function without making any assumption on the parameters describing its optimal fit. Consequent to the theory, it can be proven (see Lucarini, V., 2018, Revising and extending the linear response theory for statistical mechanical systems: Evaluating observables as predictors and predictands) that any Green function can be expressed as an infinite sum of exponentials.

Technical comments:
- l. 28: replace "Response at" with "Response at time of";
- l. 33: replace "given the" with "given that the";
- l. 73: insert blank space before "(Smith";
- l. 112: replace "inefficient requires" with "inefficient, as it requires";
- l. 250: replace "given we" with "given that we";

References
- K. Caldeira, N. P. Myhrvold, Projections of the pace of warming following an abrupt increase in atmospheric carbon dioxide concentration. Environ. Res. Lett. 8, 034039 (2013)
- Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F. T., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys., 13, 2793–2825 (2013)
- J. Tsutsui, Quantification of temperature response to CO2 forcing in atmosphere–ocean general circulation models. Clim. Change 140, 287–305 (2017)

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RR by Anonymous Referee #1 (30 Apr 2020)

ED: Publish subject to minor revisions (review by editor) (20 May 2020) by Valerio Lucarini

AR by Ben Sanderson on behalf of the Authors (28 May 2020) Author's response Manuscript

ED: Publish subject to technical corrections (19 Jun 2020) by Valerio Lucarini

AR by Ben Sanderson on behalf of the Authors (23 Jun 2020) Author's response Manuscript

Post-review adjustments

AA: Author's adjustment | EA: Editor approval

AA by Ben Sanderson on behalf of the Authors (24 Jul 2020) Author's adjustment Manuscript

EA: Adjustments approved (02 Aug 2020) by Valerio Lucarini

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Short summary

Here, we assess the degree to which the idealized responses to transient forcing increase and step change forcing increase relate to warming under future scenarios. We find a possible explanation for the poor performance of transient metrics (relative to equilibrium response) as a metric of high-emission future warming in terms of their sensitivity to non-equilibrated initial conditions, and propose alternative metrics which better describe warming under high mitigation scenarios.