the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Jun 2022
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Abstract. While the IPCC’s physical science report usually assesses a handful of future scenarios, the IPCC Sixth Assessment Working Group III report (AR6 WGIII) on climate mitigation assesses hundreds to thousands of future emissions scenarios. A key task is to assess the global-mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emission scenarios from different integrated assessment models come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth System Models. In this work, we describe the “climate assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1,202 mitigation scenarios in AR6 WGIII. We evaluate the global-mean temperature projections and effective radiative forcing characteristics (ERF) of climate emulators FaIRv1.6.2, MAGICCv7.5.3, and CICERO-SCM, discuss overshoot severity of the mitigation pathways using overshoot degree years, and look at an interpretation of compatibility with the Paris Agreement. We find that the lowest class of emission scenarios that limit global warming to “1.5 °C (with a probability of greater than 50 %) with no or limited overshoot” includes 90 scenarios for MAGICCv7.5.3, and 196 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 °C for up to a few decades, before returning to below 1.5 °C by or before the year 2100. For more than half of the scenarios of this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, are projected to see median temperatures decline by about 0.3–0.4 °C after peaking at 1.5–1.6 °C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss the implications. This article also introduces a ‘climate-assessment’ Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work can be the start of a community tool for assessing the temperature outcomes related to emissions pathways, and potential further work extending the workflow from emissions to global climate by downscaling climate characteristics to a regional level and calculating impacts.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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Supplement
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Interactive discussion
Status: closed
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CC1: 'Comment on egusphere-2022-471', Richard Rosen, 09 Jul 2022
My main reaction is that the article is far too long and detailed given that the issue of how to translate emissions scenarios into temperature changes is not primarily a problem that has been attributed to simplied models like MAGICC. The main uncertainties in going from emissions to temperatures derive from the levels of uncertainty from the full-blown climate models themselves the results of which are used to create models like MAGICC. Unfortunately, in the IPCC reports and similar reports on emissions scenarios, the underlying physical uncertainties in translating from emissions to temperature changes are discussed little if at all.
The fact that these reports include hundreds of emissions scenarios makes it difficult in practice to then include the uncertainties for each scenario itself. In my opinion, the IPCC reports should focus on just a few key emissions scenarios, and thereby making it possible to show how the uncertainties in calculating temperature scenarios based on those relatively few emissions scenarios makes hitting temperature goals or targets by a date certain almost impossible to assure. In addition, of course, there are many other kinds of uncertainty buried in other variables in the integrated assessment models. Thus, I think this much too lengthy a paper is not necessary and appropriate to publish if the goal is to educate policy makers about the range of uncertainty in temperature scenarios. It is huge, but most of the sources of uncertainty are not discussed here.
Citation: https://doi.org/10.5194/egusphere-2022-471-CC1 -
AC1: 'Reply on CC1', Jarmo Kikstra, 21 Sep 2022
Thank you for your comment and engagement with our manuscript. The goal of our work is indeed not to try to examine uncertainty as captured in complex Earth System Models. Rather, we describe how the Working Group III report of the IPCC Sixth Assessment Report on Climate Mitigation used climate emulators to help in assessing a large set of alternative mitigation scenarios, and make these tools available to the public. We believe this is a worthwhile effort in itself, notwithstanding that valuable other research may also be done to better understand the uncertainties in complex climate modelling and detailed integrated assessment modelling.
Citation: https://doi.org/10.5194/egusphere-2022-471-AC1
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AC1: 'Reply on CC1', Jarmo Kikstra, 21 Sep 2022
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RC1: 'Comment on egusphere-2022-471', Anonymous Referee #1, 20 Jul 2022
This paper describes a key set of processes used by the Intergovernmental Panel on Climate Change to estimate climate outcomes from emissions scenarios. The text is well-written. As such it is worthy of publication. I do however have some comments and proofing points for the authors to consider, as follows:
- There is no discussion as far as I can tell of the impact of harmonisation and infilling at the regional scale. Basing these steps on global values (of CO2) implicitly assumes that the ratio of CO2 to other species is homogeneous across space, which is unlikely to be true. What are the implications of this workflow for use of the regional emissions data in the AR6 database?
- This is a question so naive that I am slightly embarrassed to ask... Are the emissions data in the AR6 database the unadjusted submitted data, or are they adjusted data (harmonised, infilled, or both)? If unadjusted, then users should exercise caution in estimating emissions-climate properties (such as TCRE) from the database. If adjusted, users should know they do not necessarily match the submitted data and may exhibit biases from processing. Either way, this should be clear in the database metadata (e.g. https://data.ece.iiasa.ac.at/ar6/#/about) and in the paper. Perhaps it is and I am unobservant, but I did spend a while looking!
- What is the justification for the scenario selection criteria? And what is the sensitivity of the number of included scenarios to variations in these criteria? The selection criteria are described briefly in lines 300-310 and listed in Supplementary Figure 1, but no reasoning for these criteria or the threshold values is given, either in this manuscript or in IPCC WG3 AR6 Annex 3.
- Table 1 appears to show harmonisation methods only, not infilling methods as suggested by the caption. It would be good to see the infilling procedures included in the table - perhaps as an extra column?
- Lines 561-564: while I think the authors are correct that sensitivity to absolute warming can act as a proxy for sensitivity to uncertainty in a bundle of other factors, the relationships are not intuitive. The reader would benefit from a brief explanation of how to infer from Supplementary Figure 1 the implications for uncertainty in forcing or of harmonisation & infilling emissions.
- In Figure 7, can the authors provide an additional panel showing the impact of infilling and harmonisation on other forcings beyond Kyoto Gases? These are also important, and perhaps where some of the largest (proportional) changes arise from infilling and harmonisation.
And a few proofing suggestions:
- Line 75: italicise "climate"?
- Line 112: missing "the" between "of" and "limited".
- Lines 466-467: this sentence needs completing.
- Table 1 caption: A ** footnote is explained, but I don't see that symbol used in the table.
- Figure 5, panels B-D: Could the authors explain in the caption how the scenarios have been ordered? Would it be informative to order them by magnitude of ODY_1.5, for instance?
Citation: https://doi.org/10.5194/egusphere-2022-471-RC1 -
RC2: 'Comment on egusphere-2022-471', Anonymous Referee #2, 03 Aug 2022
This paper details the climate assessment processing steps developed between IPCC Working Groups I and III to assess temperature outcomes of emissions pathways and introduces an open source climate assessment Python package that can facilitate this processing. The processing steps include (1) vetting of emissions scenarios submitted to the AR6 Scenario Explorer, (2) harmonization of vetted emissions scenarios with historical emissions, (3) infilling of missing species in the emissions scenario, and (4) assessment of the emissions-climate response with three climate emulators. The paper then evaluates the impact of this processing on global-mean temperature projections and effective radiative forcing statistics before analyzing overshoot degree years and ‘Paris-compatible’ emissions scenarios.
The paper is well-written and provides a valuable reference for elucidating the IPCC scenario-emissions process. I would recommend publication with a few qualifications below to better emphasize the novelty of this contribution (for instance fore-fronting the statement in lines 245-248).
General
- This paper read to me as part review/part analysis/part overview of a new community tool, which is a lot to take on but is very useful to the climate community at large. My recommendation would be to highlight the community tool more clearly throughout the methods section to encourage its uptake. This could include providing a schematic of the workflow either in the main text or supplement or clarifying throughout the methods section how and where the climate assessment workflow package was used. I’ll note that while the workflow illustrated in Figure 1 is excellent, it is more supportive of the review portion of the text as opposed to elucidating the packages, emulators, and analysis included in the community tool.
- Why aren’t CICERO-SCM results reported in the abstract? Or make it clearer that it is used only for sensitivity analysis.
- Suggestion: In addition to Table 2 in the Supplementary file, a bar graph displaying the vetting ‘success’ of scenarios from each model would be useful. It would emphasize the number of scenarios that are included by a disproportionate number of IAMs (as discussed in section 5.1.1).
- It is exciting to consider the use of emulators for variables beyond global estimates of GSAT, but other variables have not yet been comprehensively evaluated, such as precipitation. Should there be some discussion of the uncertainty and potential of emulators to provide societally relevant metrics beyond GSAT? Similarly, more discussion of the regional emissions data vetting and application would be useful as a means of underpinning the recommendation in the concluding sentence.
Specific
- Line 300: delete in: ‘...climate mitigation options [in] were extensively...’
- Line 490: Chen et al. 2021 not included in the references
- Style: Remove the indent from lines 219, 223, 226, 228
- Line 252: “A growing body of research has been developed to describe[ing] analyses that compare…” (Or something along these lines)
- Line 296: italicize ‘climate assessment’ as is done on line 814
- Line 300: delete 'in': “Global scenarios used to assess climate mitigation options [in] were extensively…”
- Line 444: delete 'above': “Beyond these, AR6 WGIII includes categories [above] relevant for higher emissions scenarios that…”
- Line 765: delete 'a': “While overshoot indicators like ODY5 may immediately be [a] useful as an…
- Supplement: Include the number of scenarios considered in Table 2.
Citation: https://doi.org/10.5194/egusphere-2022-471-RC2 - AC2: 'Final author comment (AC) on behalf of all co-authors, responding to RC1 and RC2', Jarmo Kikstra, 21 Sep 2022
Interactive discussion
Status: closed
-
CC1: 'Comment on egusphere-2022-471', Richard Rosen, 09 Jul 2022
My main reaction is that the article is far too long and detailed given that the issue of how to translate emissions scenarios into temperature changes is not primarily a problem that has been attributed to simplied models like MAGICC. The main uncertainties in going from emissions to temperatures derive from the levels of uncertainty from the full-blown climate models themselves the results of which are used to create models like MAGICC. Unfortunately, in the IPCC reports and similar reports on emissions scenarios, the underlying physical uncertainties in translating from emissions to temperature changes are discussed little if at all.
The fact that these reports include hundreds of emissions scenarios makes it difficult in practice to then include the uncertainties for each scenario itself. In my opinion, the IPCC reports should focus on just a few key emissions scenarios, and thereby making it possible to show how the uncertainties in calculating temperature scenarios based on those relatively few emissions scenarios makes hitting temperature goals or targets by a date certain almost impossible to assure. In addition, of course, there are many other kinds of uncertainty buried in other variables in the integrated assessment models. Thus, I think this much too lengthy a paper is not necessary and appropriate to publish if the goal is to educate policy makers about the range of uncertainty in temperature scenarios. It is huge, but most of the sources of uncertainty are not discussed here.
Citation: https://doi.org/10.5194/egusphere-2022-471-CC1 -
AC1: 'Reply on CC1', Jarmo Kikstra, 21 Sep 2022
Thank you for your comment and engagement with our manuscript. The goal of our work is indeed not to try to examine uncertainty as captured in complex Earth System Models. Rather, we describe how the Working Group III report of the IPCC Sixth Assessment Report on Climate Mitigation used climate emulators to help in assessing a large set of alternative mitigation scenarios, and make these tools available to the public. We believe this is a worthwhile effort in itself, notwithstanding that valuable other research may also be done to better understand the uncertainties in complex climate modelling and detailed integrated assessment modelling.
Citation: https://doi.org/10.5194/egusphere-2022-471-AC1
-
AC1: 'Reply on CC1', Jarmo Kikstra, 21 Sep 2022
-
RC1: 'Comment on egusphere-2022-471', Anonymous Referee #1, 20 Jul 2022
This paper describes a key set of processes used by the Intergovernmental Panel on Climate Change to estimate climate outcomes from emissions scenarios. The text is well-written. As such it is worthy of publication. I do however have some comments and proofing points for the authors to consider, as follows:
- There is no discussion as far as I can tell of the impact of harmonisation and infilling at the regional scale. Basing these steps on global values (of CO2) implicitly assumes that the ratio of CO2 to other species is homogeneous across space, which is unlikely to be true. What are the implications of this workflow for use of the regional emissions data in the AR6 database?
- This is a question so naive that I am slightly embarrassed to ask... Are the emissions data in the AR6 database the unadjusted submitted data, or are they adjusted data (harmonised, infilled, or both)? If unadjusted, then users should exercise caution in estimating emissions-climate properties (such as TCRE) from the database. If adjusted, users should know they do not necessarily match the submitted data and may exhibit biases from processing. Either way, this should be clear in the database metadata (e.g. https://data.ece.iiasa.ac.at/ar6/#/about) and in the paper. Perhaps it is and I am unobservant, but I did spend a while looking!
- What is the justification for the scenario selection criteria? And what is the sensitivity of the number of included scenarios to variations in these criteria? The selection criteria are described briefly in lines 300-310 and listed in Supplementary Figure 1, but no reasoning for these criteria or the threshold values is given, either in this manuscript or in IPCC WG3 AR6 Annex 3.
- Table 1 appears to show harmonisation methods only, not infilling methods as suggested by the caption. It would be good to see the infilling procedures included in the table - perhaps as an extra column?
- Lines 561-564: while I think the authors are correct that sensitivity to absolute warming can act as a proxy for sensitivity to uncertainty in a bundle of other factors, the relationships are not intuitive. The reader would benefit from a brief explanation of how to infer from Supplementary Figure 1 the implications for uncertainty in forcing or of harmonisation & infilling emissions.
- In Figure 7, can the authors provide an additional panel showing the impact of infilling and harmonisation on other forcings beyond Kyoto Gases? These are also important, and perhaps where some of the largest (proportional) changes arise from infilling and harmonisation.
And a few proofing suggestions:
- Line 75: italicise "climate"?
- Line 112: missing "the" between "of" and "limited".
- Lines 466-467: this sentence needs completing.
- Table 1 caption: A ** footnote is explained, but I don't see that symbol used in the table.
- Figure 5, panels B-D: Could the authors explain in the caption how the scenarios have been ordered? Would it be informative to order them by magnitude of ODY_1.5, for instance?
Citation: https://doi.org/10.5194/egusphere-2022-471-RC1 -
RC2: 'Comment on egusphere-2022-471', Anonymous Referee #2, 03 Aug 2022
This paper details the climate assessment processing steps developed between IPCC Working Groups I and III to assess temperature outcomes of emissions pathways and introduces an open source climate assessment Python package that can facilitate this processing. The processing steps include (1) vetting of emissions scenarios submitted to the AR6 Scenario Explorer, (2) harmonization of vetted emissions scenarios with historical emissions, (3) infilling of missing species in the emissions scenario, and (4) assessment of the emissions-climate response with three climate emulators. The paper then evaluates the impact of this processing on global-mean temperature projections and effective radiative forcing statistics before analyzing overshoot degree years and ‘Paris-compatible’ emissions scenarios.
The paper is well-written and provides a valuable reference for elucidating the IPCC scenario-emissions process. I would recommend publication with a few qualifications below to better emphasize the novelty of this contribution (for instance fore-fronting the statement in lines 245-248).
General
- This paper read to me as part review/part analysis/part overview of a new community tool, which is a lot to take on but is very useful to the climate community at large. My recommendation would be to highlight the community tool more clearly throughout the methods section to encourage its uptake. This could include providing a schematic of the workflow either in the main text or supplement or clarifying throughout the methods section how and where the climate assessment workflow package was used. I’ll note that while the workflow illustrated in Figure 1 is excellent, it is more supportive of the review portion of the text as opposed to elucidating the packages, emulators, and analysis included in the community tool.
- Why aren’t CICERO-SCM results reported in the abstract? Or make it clearer that it is used only for sensitivity analysis.
- Suggestion: In addition to Table 2 in the Supplementary file, a bar graph displaying the vetting ‘success’ of scenarios from each model would be useful. It would emphasize the number of scenarios that are included by a disproportionate number of IAMs (as discussed in section 5.1.1).
- It is exciting to consider the use of emulators for variables beyond global estimates of GSAT, but other variables have not yet been comprehensively evaluated, such as precipitation. Should there be some discussion of the uncertainty and potential of emulators to provide societally relevant metrics beyond GSAT? Similarly, more discussion of the regional emissions data vetting and application would be useful as a means of underpinning the recommendation in the concluding sentence.
Specific
- Line 300: delete in: ‘...climate mitigation options [in] were extensively...’
- Line 490: Chen et al. 2021 not included in the references
- Style: Remove the indent from lines 219, 223, 226, 228
- Line 252: “A growing body of research has been developed to describe[ing] analyses that compare…” (Or something along these lines)
- Line 296: italicize ‘climate assessment’ as is done on line 814
- Line 300: delete 'in': “Global scenarios used to assess climate mitigation options [in] were extensively…”
- Line 444: delete 'above': “Beyond these, AR6 WGIII includes categories [above] relevant for higher emissions scenarios that…”
- Line 765: delete 'a': “While overshoot indicators like ODY5 may immediately be [a] useful as an…
- Supplement: Include the number of scenarios considered in Table 2.
Citation: https://doi.org/10.5194/egusphere-2022-471-RC2 - AC2: 'Final author comment (AC) on behalf of all co-authors, responding to RC1 and RC2', Jarmo Kikstra, 21 Sep 2022
Peer review completion
Journal article(s) based on this preprint
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Model code and software
Climate assessment of long-term emissions pathways: IPCC AR6 WGIII version Jarmo S. Kikstra, Zebedee R.J. Nicholls, Jared Lewis, Christopher J. Smith, Robin D. Lamboll, Edward Byers, Marit Sandstad, Laura Wienpahl, Philip Hackstock https://doi.org/10.5281/zenodo.6624519
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Cited
3 citations as recorded by crossref.
- A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses S. Gebrechorkos et al. 10.1038/s41597-023-02528-x
- Uncompensated claims to fair emission space risk putting Paris Agreement goals out of reach G. Ganti et al. 10.1088/1748-9326/acb502
- Changes in IPCC Scenario Assessment Emulators Between SR1.5 and AR6 Unraveled Z. Nicholls et al. 10.1029/2022GL099788
Zebedee R. J. Nicholls
Christopher J. Smith
Jared Lewis
Robin D. Lamboll
Edward Byers
Marit Sandstad
Malte Meinshausen
Matthew J. Gidden
Joeri Rogelj
Elmar Kriegler
Glen P. Peters
Jan S. Fuglestvedt
Ragnhild B. Skeie
Bjørn H. Samset
Laura Wienpahl
Detlef P. van Vuuren
Kaj-Ivar van der Wijst
Alaa Al Khourdajie
Piers M. Forster
Andy Reisinger
Roberto Schaeffer
Keywan Riahi
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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(2460 KB) - Metadata XML
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Supplement
(332 KB) - BibTeX
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- Final revised paper