the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Feb 2023
Advancing the estimation of future climate impacts within the United States
Erin E. McDuffie
Karen Noiva
Marcus Sarofim
Bryan Parthum
Jeremy Martinich
Sarah Barr
Jim Neumann
Jaqueline Willwerth
Allen Fawcett
Abstract. Evidence of the physical and economic impacts of climate change is a critical input to policy development and decision making. The potential magnitude of climate change damages, where, when, and to whom those damages may occur across the country, the types of impacts that will be most damaging, and the ability of adaptation to reduce potential risks are all important and interconnected. This study utilizes the reduced-complexity model, Framework for Evaluating Damages and Impacts (FrEDI), to rapidly assess economic and physical impacts of climate change in the contiguous United States (U.S.). Results from FrEDI show that net national damages increase overtime, with mean climate-driven damages estimated to reach $2.9 trillion USD (95 % CI: $510 billion to $12 trillion) annually by 2090. Climate-driven damages are largest for the health category, with the majority of damages in this category from the valuation estimates of premature mortality attributable to climate-driven changes in extreme temperature and air quality (O3 and PM2.5). Results from FrEDI also show that climate-driven damages vary by geographical region, with the Southeast experiencing the largest annual damages per capita (mean: $9,300 per person annually, 95 % CI: $1,800–$37,000 per person annually), whereas the smallest damages per capita are expected in the Southwest region (mean: $6,300 per person annually, 95 % CI: $840–$27,000 per person annually). Climate change impacts may also broaden existing societal inequalities, with Black or African Americans disproportionately affected by additional premature mortality from changes in air quality. This work significantly advances our understanding of the impacts from climate change to the U.S., in what U.S. regions impacts are happening, what sectors are being impacted, and which population groups being impacted the most.
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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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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
Corinne Hartin et al.
Interactive discussion
Status: closed
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CC1: 'Comment on egusphere-2023-114', Richard Rosen, 10 Feb 2023
Because this article depends on the results of running EPA's FrEDI model which has a long history of development and publications by EPA staff, it is impossible to review on it own. Namely, if one believes that the FrEDI model is fairly accurate and well developed based on real world data, then the results cited in this paper are worth publicizing. Even so I would not report results for after 2050, because in my view no one has a clue how to extrapolate future damages beyond that point. Climate impact data only exists for about the last 40 years at most, and climate impacts were barely measurable until 2000, or only about 20 years ago. Thus claiming to be able to extrapolate climate caused damages for more than 30 years into the future is not credible. (I have extensive experience writing about the economics of climate change as one can discover from my Research Gate files.) But EPA staff might disagree since their model is intended to make long-run projections. I just would not believe that it is possible for any model to do so. Of course, by its nature estimating future damages has always been a highly controversial research area where the uncertainty for results is extemely high but not acknowled enough in this paper.
In addition, the Burke, et.al. (2015) paper referenced in this paper is all wrong, but, fortunately, I don't think the methodology of that paper was used in FrEDI. If it was used, than the entire paper being proposed for publication here is all wrong, as well as all previous publications. More than one year ago I published a complete critique of the Burke paper. See the attached paper. A short version of my argument was also published as a letter to the PNAS in prior years, so these authors should have known not to rely on Burke (2015) and not to use it as a reference anymore.
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AC1: 'Reply on CC1', Corinne Hartin, 18 Apr 2023
We thank Dr. Rosen for providing public comments on the magnitude of uncertainty associated with projecting climate-driven damages as well for his concern about the analysis presented in Burke et al., 2015. We recognize that there are substantial challenges regarding projecting socio-economic characteristics such as GDP, technological advancement, adaptive capacity, and other factors more than a couple decades into the future (though we do have more confidence in the translation from emissions to climate than either our projections of emissions or the translation from climate to impacts, as the emissions to climate translation is based on our understanding of physical science which while challenging is easier to project than socioeconomics). However, choosing not to project results after 2050 effectively assumes that those damages are zero, and that is also unsatisfactory. See, e.g., the Center for Biol. Div. v. NHTSA, 538 F.3d 1172, 1200, (9th Cir, 2008) where the Court concluded, “...while the record shows that there is a range of values, the value of carbon emissions reduction is certainly not zero.” Our paper does not present a single value for future impacts that we would argue is “truth”, but rather that we have a well-documented approach that is our best attempt to value these impacts based on the current state of the science.
We do not include the Burke paper in our FrEDI analysis and have since deleted the reference.
Citation: https://doi.org/10.5194/egusphere-2023-114-AC1
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AC1: 'Reply on CC1', Corinne Hartin, 18 Apr 2023
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RC1: 'Comment on egusphere-2023-114', Anonymous Referee #1, 09 Mar 2023
The manuscript describes a framework for evaluating long-term damages from climate change to a large number of different specific U.S. economic sectors. The damage functions have generally been previously published, and have been extended to 2300 (from an original 21st century time horizon for most of them). The common FaIR climate model is used to simulate and take into account uncertainty in global climate, specifically temperature change, which is used as input to the various damage functions. Probabilistic projections for socioeconomic conditions (e.g., GDP, population change) from a recent study are used, and combined with different emissions scenarios. The work decomposes climate-driven damages by geographic region within the U.S. and by different vulnerable populations.
The manuscript is well-written and well-organized. As near as I can tell from the methodological descriptions of FrEDI provided in the manuscript, the conclusions and results follow nicely from the experiments that are conducted. However, my comments below revolve mostly around the theme of a need for further details about the structural assumptions baked into the damage function underlying FrEDI. You understandably defer a great deal to other recently published works that are the primary sources for these parameterizations, and I understand that this is not a model description paper. However, this makes it a bit more difficult for the reader to understand the context for the results presented, particularly for interpreting sector-specific damages. Most of these and my other comments I anticipate can be cleared up through adding some modeling details and/or caveats. Thus I recommend for minor revisions.
General comments:
L65-67 - Perhaps any of these FAIR warming scenarios *can* be paired with any socioeconomic projection, but *should* they? There are some SSP-RCP combinations (e.g.) that modelers use but shouldn’t. For example, see O’Neill et al 2020, https://doi.org/10.1038/s41558-020-00952-0, particularly their Figure 2. I can imagine that your probabilistic framework may account for this in some way, but I’d be interested to know more about how you ensuring that unlikely/implausible combinations of scenarios aren’t unduly biasing results?
L74, 159 - What assumptions about coastal adaptation (and other forms of adaptation/mitigation, and development) are baked into FrEDI? Can you comment on how realistic these are on such long time scales?
L186 - Related to above, looking specifically at marginal damages means that the assumed adaptation strategies could be masking the real magnitude of these climate risks. For example, if it is assumed that you make least-cost decisions, then these marginal damages will be more of a lower bound. While the adaptation assumptions are provided in an appendix, it may be worth discussing these in main text more, because (my impression is that) the results rely a great deal on these assumptions.
L210-212 - It isn’t totally clear here what the default adaptation assumptions are for each sector (maybe cite Table A2 here?), or what each of these adaptation assumptions represents with respect to the individual sectors. For example, what does “reasonably anticipated adaptation” mean for coastal properties? And how reasonable are these assumptions on such long time scales, for each sector?
Specific comments:
L23-27 - Is this by the year 2090? Or when?
L50 and 52 - “Climate Change Impacts and Risk Analysis (CIRA) project” and “Climate Impact Lab” - I’m aware of these projects/groups, but I’m not sure readers in general will know the context for these. Could be worth specifying where they’re housed.
L70 - In what way(s) is FrEDI distinguishable from a traditional IAM?
L114-116 - Are there or should there be correlations and/or feedbacks represented between the RFF-SP emission scenarios and the FaIR scenarios?
L116-118 - How sensitive are the results to this moderate assumption? And no uncertainty sampled in these other gases/aerosols.
L175 - should this be g_t?
Table 2 - should “2,1” be “2,100” in the 95% CI column?
L270-272 - I’m intrigued by this, and would love to see more work on this prominently featured in contemporary research. But I’m also curious about how this modeling is done within FrEDI and what scale data is being used, and what assumptions there are when disaggregating damages for socially vulnerable populations.
L424-430 - You cite two studies that used a power law relationship, finding that it fit the temperature-damage relationship better than linear. Why choose to use linear instead in FrEDI?
Figure A2 - There is a lot to unpack here, including a few of what appear to be some tipping points or other kinds of jumps in some of these sectoral damages around 2060 or so. E.g., wind damage, agriculture, or the sudden jump in coastal property damages after about 2080 - how do you make sense of these results, in light of the adaptation assumptions embedded in FrEDI?
L469 - perfect foresight over what time frame?
Figure A5 - Are some of these damage distributions in later years so heavily skewed that the means are outside of the 95% CI? It might be tidier to display the median, and perhaps more consistent with the use of percentiles for the 95% CI too.
Citation: https://doi.org/10.5194/egusphere-2023-114-RC1 -
CC2: 'Reply on RC1', Richard Rosen, 09 Mar 2023
I can't believe that any responsible scientist could recommend the publication of such an article. There is no scientific basis for projecting climate change caused damages for even the next 20 years, not to speak of to 2300. Are you afraid of rejecting completely unscientific papers, even if such nonsense has been published by other journals or government agencies? More specifically, since we cannot even project climate change accurately to 2050, and economists cannot project economic growth for a few years, how can one take seriously projecting economic damages for almost 300 years. 30 years ago, we had no idea at all as to the magnitude of climate related damages we are already seeing. It is not this journal's job to publish these kinds of economically related articles that your referees clearly have no relevant expertise for, or they would realize that there is no scientific basis to do so. I strongly recommend that this journal stiick to publishing articles in its realm of expertise. Even the IPCC reports have stopped publishing material on the economic costs and benefits of climate change. They finally realized in AR6 that the numbers were meaningless.
Citation: https://doi.org/10.5194/egusphere-2023-114-CC2 -
AC2: 'Reply on RC1', Corinne Hartin, 18 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-114/egusphere-2023-114-AC2-supplement.pdf
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CC2: 'Reply on RC1', Richard Rosen, 09 Mar 2023
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RC2: 'Comment on egusphere-2023-114', Anonymous Referee #2, 20 Mar 2023
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AC3: 'Reply on RC2', Corinne Hartin, 18 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-114/egusphere-2023-114-AC3-supplement.pdf
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AC3: 'Reply on RC2', Corinne Hartin, 18 Apr 2023
Interactive discussion
Status: closed
-
CC1: 'Comment on egusphere-2023-114', Richard Rosen, 10 Feb 2023
Because this article depends on the results of running EPA's FrEDI model which has a long history of development and publications by EPA staff, it is impossible to review on it own. Namely, if one believes that the FrEDI model is fairly accurate and well developed based on real world data, then the results cited in this paper are worth publicizing. Even so I would not report results for after 2050, because in my view no one has a clue how to extrapolate future damages beyond that point. Climate impact data only exists for about the last 40 years at most, and climate impacts were barely measurable until 2000, or only about 20 years ago. Thus claiming to be able to extrapolate climate caused damages for more than 30 years into the future is not credible. (I have extensive experience writing about the economics of climate change as one can discover from my Research Gate files.) But EPA staff might disagree since their model is intended to make long-run projections. I just would not believe that it is possible for any model to do so. Of course, by its nature estimating future damages has always been a highly controversial research area where the uncertainty for results is extemely high but not acknowled enough in this paper.
In addition, the Burke, et.al. (2015) paper referenced in this paper is all wrong, but, fortunately, I don't think the methodology of that paper was used in FrEDI. If it was used, than the entire paper being proposed for publication here is all wrong, as well as all previous publications. More than one year ago I published a complete critique of the Burke paper. See the attached paper. A short version of my argument was also published as a letter to the PNAS in prior years, so these authors should have known not to rely on Burke (2015) and not to use it as a reference anymore.
-
AC1: 'Reply on CC1', Corinne Hartin, 18 Apr 2023
We thank Dr. Rosen for providing public comments on the magnitude of uncertainty associated with projecting climate-driven damages as well for his concern about the analysis presented in Burke et al., 2015. We recognize that there are substantial challenges regarding projecting socio-economic characteristics such as GDP, technological advancement, adaptive capacity, and other factors more than a couple decades into the future (though we do have more confidence in the translation from emissions to climate than either our projections of emissions or the translation from climate to impacts, as the emissions to climate translation is based on our understanding of physical science which while challenging is easier to project than socioeconomics). However, choosing not to project results after 2050 effectively assumes that those damages are zero, and that is also unsatisfactory. See, e.g., the Center for Biol. Div. v. NHTSA, 538 F.3d 1172, 1200, (9th Cir, 2008) where the Court concluded, “...while the record shows that there is a range of values, the value of carbon emissions reduction is certainly not zero.” Our paper does not present a single value for future impacts that we would argue is “truth”, but rather that we have a well-documented approach that is our best attempt to value these impacts based on the current state of the science.
We do not include the Burke paper in our FrEDI analysis and have since deleted the reference.
Citation: https://doi.org/10.5194/egusphere-2023-114-AC1
-
AC1: 'Reply on CC1', Corinne Hartin, 18 Apr 2023
-
RC1: 'Comment on egusphere-2023-114', Anonymous Referee #1, 09 Mar 2023
The manuscript describes a framework for evaluating long-term damages from climate change to a large number of different specific U.S. economic sectors. The damage functions have generally been previously published, and have been extended to 2300 (from an original 21st century time horizon for most of them). The common FaIR climate model is used to simulate and take into account uncertainty in global climate, specifically temperature change, which is used as input to the various damage functions. Probabilistic projections for socioeconomic conditions (e.g., GDP, population change) from a recent study are used, and combined with different emissions scenarios. The work decomposes climate-driven damages by geographic region within the U.S. and by different vulnerable populations.
The manuscript is well-written and well-organized. As near as I can tell from the methodological descriptions of FrEDI provided in the manuscript, the conclusions and results follow nicely from the experiments that are conducted. However, my comments below revolve mostly around the theme of a need for further details about the structural assumptions baked into the damage function underlying FrEDI. You understandably defer a great deal to other recently published works that are the primary sources for these parameterizations, and I understand that this is not a model description paper. However, this makes it a bit more difficult for the reader to understand the context for the results presented, particularly for interpreting sector-specific damages. Most of these and my other comments I anticipate can be cleared up through adding some modeling details and/or caveats. Thus I recommend for minor revisions.
General comments:
L65-67 - Perhaps any of these FAIR warming scenarios *can* be paired with any socioeconomic projection, but *should* they? There are some SSP-RCP combinations (e.g.) that modelers use but shouldn’t. For example, see O’Neill et al 2020, https://doi.org/10.1038/s41558-020-00952-0, particularly their Figure 2. I can imagine that your probabilistic framework may account for this in some way, but I’d be interested to know more about how you ensuring that unlikely/implausible combinations of scenarios aren’t unduly biasing results?
L74, 159 - What assumptions about coastal adaptation (and other forms of adaptation/mitigation, and development) are baked into FrEDI? Can you comment on how realistic these are on such long time scales?
L186 - Related to above, looking specifically at marginal damages means that the assumed adaptation strategies could be masking the real magnitude of these climate risks. For example, if it is assumed that you make least-cost decisions, then these marginal damages will be more of a lower bound. While the adaptation assumptions are provided in an appendix, it may be worth discussing these in main text more, because (my impression is that) the results rely a great deal on these assumptions.
L210-212 - It isn’t totally clear here what the default adaptation assumptions are for each sector (maybe cite Table A2 here?), or what each of these adaptation assumptions represents with respect to the individual sectors. For example, what does “reasonably anticipated adaptation” mean for coastal properties? And how reasonable are these assumptions on such long time scales, for each sector?
Specific comments:
L23-27 - Is this by the year 2090? Or when?
L50 and 52 - “Climate Change Impacts and Risk Analysis (CIRA) project” and “Climate Impact Lab” - I’m aware of these projects/groups, but I’m not sure readers in general will know the context for these. Could be worth specifying where they’re housed.
L70 - In what way(s) is FrEDI distinguishable from a traditional IAM?
L114-116 - Are there or should there be correlations and/or feedbacks represented between the RFF-SP emission scenarios and the FaIR scenarios?
L116-118 - How sensitive are the results to this moderate assumption? And no uncertainty sampled in these other gases/aerosols.
L175 - should this be g_t?
Table 2 - should “2,1” be “2,100” in the 95% CI column?
L270-272 - I’m intrigued by this, and would love to see more work on this prominently featured in contemporary research. But I’m also curious about how this modeling is done within FrEDI and what scale data is being used, and what assumptions there are when disaggregating damages for socially vulnerable populations.
L424-430 - You cite two studies that used a power law relationship, finding that it fit the temperature-damage relationship better than linear. Why choose to use linear instead in FrEDI?
Figure A2 - There is a lot to unpack here, including a few of what appear to be some tipping points or other kinds of jumps in some of these sectoral damages around 2060 or so. E.g., wind damage, agriculture, or the sudden jump in coastal property damages after about 2080 - how do you make sense of these results, in light of the adaptation assumptions embedded in FrEDI?
L469 - perfect foresight over what time frame?
Figure A5 - Are some of these damage distributions in later years so heavily skewed that the means are outside of the 95% CI? It might be tidier to display the median, and perhaps more consistent with the use of percentiles for the 95% CI too.
Citation: https://doi.org/10.5194/egusphere-2023-114-RC1 -
CC2: 'Reply on RC1', Richard Rosen, 09 Mar 2023
I can't believe that any responsible scientist could recommend the publication of such an article. There is no scientific basis for projecting climate change caused damages for even the next 20 years, not to speak of to 2300. Are you afraid of rejecting completely unscientific papers, even if such nonsense has been published by other journals or government agencies? More specifically, since we cannot even project climate change accurately to 2050, and economists cannot project economic growth for a few years, how can one take seriously projecting economic damages for almost 300 years. 30 years ago, we had no idea at all as to the magnitude of climate related damages we are already seeing. It is not this journal's job to publish these kinds of economically related articles that your referees clearly have no relevant expertise for, or they would realize that there is no scientific basis to do so. I strongly recommend that this journal stiick to publishing articles in its realm of expertise. Even the IPCC reports have stopped publishing material on the economic costs and benefits of climate change. They finally realized in AR6 that the numbers were meaningless.
Citation: https://doi.org/10.5194/egusphere-2023-114-CC2 -
AC2: 'Reply on RC1', Corinne Hartin, 18 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-114/egusphere-2023-114-AC2-supplement.pdf
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CC2: 'Reply on RC1', Richard Rosen, 09 Mar 2023
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RC2: 'Comment on egusphere-2023-114', Anonymous Referee #2, 20 Mar 2023
-
AC3: 'Reply on RC2', Corinne Hartin, 18 Apr 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-114/egusphere-2023-114-AC3-supplement.pdf
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AC3: 'Reply on RC2', Corinne Hartin, 18 Apr 2023
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Corinne Hartin et al.
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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.
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