the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jun 2023
Opinion: The importance of historical and paleoclimate aerosol radiative effects
Abstract. Estimating the past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols interacted with the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo observations and in part because less attention has been paid to the problem. Because of the lack of information we do not seek here to show the change in the radiative forcing due to aerosol changes, but rather just estimate the uncertainties in those changes. Here we argue that current uncertainties from emission uncertainties (90 % confidence interval range spanning 2.8 W/m2) are just as large as model spread uncertainties (2.8 W/m2) in calculating preindustrial to current day aerosol radiative effects. There are no estimates for radiative forcing for important aerosols such as wildfire and dust aerosols in most paleoclimate time periods. However, qualitative analysis of paleoclimate proxies suggests that changes in aerosols in different past times are similar in magnitude to changes in aerosols between preindustrial and current day, plus there is the added uncertainty from the variability in aerosols and fires in the preindustrial. From the limited literature we estimate a paleoclimate aerosol uncertainty for the last glacial maximum relative to preindustrial of 4.8 W/m2. The uncertainty in the aerosol feedback in the natural Earth system over the paleoclimate (last glacial maximum to preindustrial) is estimated to be about 3.2 W/m2/°K as a first estimate of the 90 % confidence interval range. In order to assess the uncertainty in historical aerosol radiative effects, we propose a new model intercomparison project, which would include multiple plausible emission scenarios tested across a range of state-of-the art climate models over the historical period. These emission scenarios would then be compared to the available aerosol observations to constrain which are most probable. In addition, future efforts should work to characterize and constrain paleoaerosol forcings and uncertainties. Careful propagation of aerosol uncertainties in the literature is required to ensure consideration of all the uncertainties.
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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.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1174', Anonymous Referee #1, 01 Jul 2023
This is a nice summary of what is known about natural sources of aerosols and their uncertainties. I recommend publication. I unfortunately was unable to get a copy of the Kok et al. 2023 preprint, so I could not check on many of the facts noted in this paper which were based on that paper. However, assuming it is well written, I have no problem with publishing this. I note the follow which should be clarified:
Line 47: Van Marle et al 2017 is not in the reference list.
Line 72-74: point 1 mentions natural aerosol feedbacks, and this is repeated in point 2
Line 81: you mention “among others”, which made me think about DMS (sulfate), NOx lightning (nitrate). Might be better to list a few of these, even though you don’t really discuss them in the paper.
Line 133: process rather than processes? Or restate
Line 153: change “that is” to “that it is”
Line 210: you mention the timecale in (ii) and again in (iii). If there is a different point you are trying to make, please explain.
Line 221-222: why do you conclude that it is best to treat the historical dust change as a forcing when you don’t know whether it is due to a forcing or a feedback. This should be clearly argued as opposed to just saying it should be treated as a forcing when you don’t know.
Line 931: should “ranges” be “range”?
Line 248: Reword/Expand on the explanation that much of anthropogenic radiative forcing is from fires and how this explains the large emission uncertainty from fires.
Line 311-313: I think you mean to say that estimates of anthropogenic aerosol radiative forcing today would be smaller. If I’m not correct, please explain more thoroughly.
Line 961,962: the gold oval makes sense if you read the explanation for B) (i.e. the last glacial maximum had higher dust), but not if you look at the y-axis (the gold oval is not the present day/preindustrial or present day/last glacial maximum)
Line 353: change describe to described; also, why wouldn’t increased knowledge reduce these uncertainties? Please clarify.
Line 401-402: are you missing a word? Or should “one of the largest aerosols” be “one of the largest uncertainties”
Line 516: CACTI stands for Composition, Air quality, Climate inTeractions Initiative
Citation: https://doi.org/10.5194/egusphere-2023-1174-RC1 -
RC2: 'Comment on egusphere-2023-1174', Anonymous Referee #2, 17 Jul 2023
The authors highlight the uncertainties in evolution of aerosol radiative forcing, particularly due to aerosols from natural systems (using dust and wildfire as example) and review the current status of paleo observations to constrain past modeled aerosols and their radiative effects. They argue for dust and wildfire emissions to be considered as external forcing driving the climate system rather than as feedbacks. The primary premise of this paper to recognize and quantify the cascade of uncertainties in aerosols radiative effects beginning from emissions to radiative effects. I think this will be a very useful review for the community. I recommend publication after consideration of my comments below.
L26: This may work in theory but we know that there is variation across models in the simulation of aerosols even with the same emissions dataset. How would good model-obs comparison of one model with one emissions dataset be reconciled with another model using another emissions dataset?
L33-35: It would be helpful to cite the specific IPCC 2021 chapter(s) being referred to here and throughout the paper.
L43-45: Following on from the previous sentence, it may be more logical to discuss uncertainties in these natural emissions and then relate to uncertainties in radiative forcing.
L45-47 – This sentence is focused on past climates but is referencing Gidden et al which deals with future projections of emissions.
L50-59 – Note that most ESMs in CMIP6 include interactive representation of many natural aerosol emissions or their precursors (e.g., dust, DMS, sea-salt, BVOCs…). This implies that constraining models’ past emissions of natural aerosols would require constraining the parameterizations to the limited and uncertain paleo-observations. And it is possible that when constrained to paleo obs, these parametrizations may not represent the modern day emissions (as evaluated against current observations). It would be helpful if authors could shed light on this catch-22 situation.
L66-67 – My understanding is that attribution of forcing (or specifically climate change) is needed to inform climate change mitigation policies. It is therefore important to attribute the radiative perturbations in aerosols to either natural processes or human activities. However, quantifying the extent of human modification of dust, wildfire or any naturally occurring process emissions is difficult and is largely uncertain (the authors note this difficulty on L180-L183). This then translates into large uncertainties in the attribution of forcing for natural system emissions perturbed by human activities. In principle, I agree with the authors’ argument that forcing due to perturbations in any natural system emissions modified by human activities should be quantified but I am not convinced that we have reached a point in our state of knowledge to be able to do this without large uncertainties.
L74 – note that the CMIP6 emissions did not include dust emissions
L99-100 – Note that there are proxies for other aerosols such as black carbon and sulphate assessed by Gulev et al. (2021) (section 2.2.6). IPCC AR6 WGI Chapter 6 should be cited as Szopa et al (2021) here and throughout the paper.
L122-123 – What drove this large increase in dust – land use changes, climate change or both?
L125-128: All models or a subset? There were a number of models that prescribed aerosol properties to capture the influence of aerosols on climate. These models presumably did not simulate dust.
L148-153 – sentence is too long, revise. Define AEROCOM and provide a reference for the emissions dataset
L155 – is Gidden et al the correct reference here?
L159-160 – This reasoning is not clear to me – how could higher fire amounts during 1850 be due to less land use change? Wouldn’t land-use require clearing of land and therefore more fires?
L172-174 – Please specify the IPCC 2021 chapter that assessed the radiative effect of fire aerosols to be -2 Wm-2. Are there any uncertainties associated with this estimate? Ditto for IPCC 2019 and -1Wm-2.
L189-192 – Although the radiative forcing due to changes in dust emissions is not explicitly accounted for, the IPCC assesses the influence of human activities on emissions and the large associated uncertainties (section 6.2.2.4) – “In summary, there is high confidence that atmospheric dust source and loading are sensitive to changes in climate and land use, however, there is low confidence in quantitative estimates of dust emission response to climate change.”
L223-225 – It would be also helpful to recommend a specific dust emissions dataset that the modelers could use to prescribe dust emissions. This could inform the CMIP7 process.
L245-249 – It would be helpful to place the relevant citation next to the uncertainty estimate from the literature so that the source of these numbers is clear. What is the source of the 10% error for industrial emissions? Note that the Unger et al reference is now 13 years old…emission estimates have changed, models have changed. Any updates to that study?
254 – “…emission scenario for the historical period…” it would be better to replace scenario with another word to avoid confusion with future scenarios.
L281 – Gidden et al should be replaced with van Marle et al (2017).
L402 – “aerosol uncertainties remain one of the largest aerosols in those times…” largest aerosols?
L511 – The success of the proposed AEROHISTMIP will depend on the availability of multiple emission realizations for the historical period. It would be helpful to provide some indication of how these datasets will be put together and who would be responsible for making the files available to the CMIP effort. Without this information, I don’t see this recommendation leading to a tangible action. Additionally, if specific simulations are being suggested, I would recommend adding them to the AerChemMIP2 (https://airtable.com/shrtJ4jc08OEk7Vcq/tblAfxwzZTy4soluj) effort rather than a new intercomparison.
L518-521 – This goes back to my earlier point, models vary in their representation of aerosol processes in part driven by lack of full understanding of the various processes that determine the evolution of their atmospheric burden and radiative effects. With such gaps in process understanding can we really characterize the reliability of models for aerosols? I think some thought needs to be given to this recommendation.
L542 – It is not clear if Hodzic et al is in preparation or submitted?
Figure 3 – It should be noted somewhere on the figure that ∑ represents uncertainties to avoid confusion.
Finally, the paper needs a thorough proof-read and editing to improve the quality of text.
References:
Please provide the full reference for Kok et al 2023 - Kok, J.F., Storelvmo, T., Karydis, V.A. et al. Mineral dust aerosol impacts on global climate and climate change. Nat Rev Earth Environ 4, 71–86 (2023). https://doi.org/10.1038/s43017-022-00379-5
Gulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004.
Szopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 817–922, doi:10.1017/9781009157896.008.
Citation: https://doi.org/10.5194/egusphere-2023-1174-RC2 - AC1: 'Comment on egusphere-2023-1174', Natalie Mahowald, 05 Sep 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1174', Anonymous Referee #1, 01 Jul 2023
This is a nice summary of what is known about natural sources of aerosols and their uncertainties. I recommend publication. I unfortunately was unable to get a copy of the Kok et al. 2023 preprint, so I could not check on many of the facts noted in this paper which were based on that paper. However, assuming it is well written, I have no problem with publishing this. I note the follow which should be clarified:
Line 47: Van Marle et al 2017 is not in the reference list.
Line 72-74: point 1 mentions natural aerosol feedbacks, and this is repeated in point 2
Line 81: you mention “among others”, which made me think about DMS (sulfate), NOx lightning (nitrate). Might be better to list a few of these, even though you don’t really discuss them in the paper.
Line 133: process rather than processes? Or restate
Line 153: change “that is” to “that it is”
Line 210: you mention the timecale in (ii) and again in (iii). If there is a different point you are trying to make, please explain.
Line 221-222: why do you conclude that it is best to treat the historical dust change as a forcing when you don’t know whether it is due to a forcing or a feedback. This should be clearly argued as opposed to just saying it should be treated as a forcing when you don’t know.
Line 931: should “ranges” be “range”?
Line 248: Reword/Expand on the explanation that much of anthropogenic radiative forcing is from fires and how this explains the large emission uncertainty from fires.
Line 311-313: I think you mean to say that estimates of anthropogenic aerosol radiative forcing today would be smaller. If I’m not correct, please explain more thoroughly.
Line 961,962: the gold oval makes sense if you read the explanation for B) (i.e. the last glacial maximum had higher dust), but not if you look at the y-axis (the gold oval is not the present day/preindustrial or present day/last glacial maximum)
Line 353: change describe to described; also, why wouldn’t increased knowledge reduce these uncertainties? Please clarify.
Line 401-402: are you missing a word? Or should “one of the largest aerosols” be “one of the largest uncertainties”
Line 516: CACTI stands for Composition, Air quality, Climate inTeractions Initiative
Citation: https://doi.org/10.5194/egusphere-2023-1174-RC1 -
RC2: 'Comment on egusphere-2023-1174', Anonymous Referee #2, 17 Jul 2023
The authors highlight the uncertainties in evolution of aerosol radiative forcing, particularly due to aerosols from natural systems (using dust and wildfire as example) and review the current status of paleo observations to constrain past modeled aerosols and their radiative effects. They argue for dust and wildfire emissions to be considered as external forcing driving the climate system rather than as feedbacks. The primary premise of this paper to recognize and quantify the cascade of uncertainties in aerosols radiative effects beginning from emissions to radiative effects. I think this will be a very useful review for the community. I recommend publication after consideration of my comments below.
L26: This may work in theory but we know that there is variation across models in the simulation of aerosols even with the same emissions dataset. How would good model-obs comparison of one model with one emissions dataset be reconciled with another model using another emissions dataset?
L33-35: It would be helpful to cite the specific IPCC 2021 chapter(s) being referred to here and throughout the paper.
L43-45: Following on from the previous sentence, it may be more logical to discuss uncertainties in these natural emissions and then relate to uncertainties in radiative forcing.
L45-47 – This sentence is focused on past climates but is referencing Gidden et al which deals with future projections of emissions.
L50-59 – Note that most ESMs in CMIP6 include interactive representation of many natural aerosol emissions or their precursors (e.g., dust, DMS, sea-salt, BVOCs…). This implies that constraining models’ past emissions of natural aerosols would require constraining the parameterizations to the limited and uncertain paleo-observations. And it is possible that when constrained to paleo obs, these parametrizations may not represent the modern day emissions (as evaluated against current observations). It would be helpful if authors could shed light on this catch-22 situation.
L66-67 – My understanding is that attribution of forcing (or specifically climate change) is needed to inform climate change mitigation policies. It is therefore important to attribute the radiative perturbations in aerosols to either natural processes or human activities. However, quantifying the extent of human modification of dust, wildfire or any naturally occurring process emissions is difficult and is largely uncertain (the authors note this difficulty on L180-L183). This then translates into large uncertainties in the attribution of forcing for natural system emissions perturbed by human activities. In principle, I agree with the authors’ argument that forcing due to perturbations in any natural system emissions modified by human activities should be quantified but I am not convinced that we have reached a point in our state of knowledge to be able to do this without large uncertainties.
L74 – note that the CMIP6 emissions did not include dust emissions
L99-100 – Note that there are proxies for other aerosols such as black carbon and sulphate assessed by Gulev et al. (2021) (section 2.2.6). IPCC AR6 WGI Chapter 6 should be cited as Szopa et al (2021) here and throughout the paper.
L122-123 – What drove this large increase in dust – land use changes, climate change or both?
L125-128: All models or a subset? There were a number of models that prescribed aerosol properties to capture the influence of aerosols on climate. These models presumably did not simulate dust.
L148-153 – sentence is too long, revise. Define AEROCOM and provide a reference for the emissions dataset
L155 – is Gidden et al the correct reference here?
L159-160 – This reasoning is not clear to me – how could higher fire amounts during 1850 be due to less land use change? Wouldn’t land-use require clearing of land and therefore more fires?
L172-174 – Please specify the IPCC 2021 chapter that assessed the radiative effect of fire aerosols to be -2 Wm-2. Are there any uncertainties associated with this estimate? Ditto for IPCC 2019 and -1Wm-2.
L189-192 – Although the radiative forcing due to changes in dust emissions is not explicitly accounted for, the IPCC assesses the influence of human activities on emissions and the large associated uncertainties (section 6.2.2.4) – “In summary, there is high confidence that atmospheric dust source and loading are sensitive to changes in climate and land use, however, there is low confidence in quantitative estimates of dust emission response to climate change.”
L223-225 – It would be also helpful to recommend a specific dust emissions dataset that the modelers could use to prescribe dust emissions. This could inform the CMIP7 process.
L245-249 – It would be helpful to place the relevant citation next to the uncertainty estimate from the literature so that the source of these numbers is clear. What is the source of the 10% error for industrial emissions? Note that the Unger et al reference is now 13 years old…emission estimates have changed, models have changed. Any updates to that study?
254 – “…emission scenario for the historical period…” it would be better to replace scenario with another word to avoid confusion with future scenarios.
L281 – Gidden et al should be replaced with van Marle et al (2017).
L402 – “aerosol uncertainties remain one of the largest aerosols in those times…” largest aerosols?
L511 – The success of the proposed AEROHISTMIP will depend on the availability of multiple emission realizations for the historical period. It would be helpful to provide some indication of how these datasets will be put together and who would be responsible for making the files available to the CMIP effort. Without this information, I don’t see this recommendation leading to a tangible action. Additionally, if specific simulations are being suggested, I would recommend adding them to the AerChemMIP2 (https://airtable.com/shrtJ4jc08OEk7Vcq/tblAfxwzZTy4soluj) effort rather than a new intercomparison.
L518-521 – This goes back to my earlier point, models vary in their representation of aerosol processes in part driven by lack of full understanding of the various processes that determine the evolution of their atmospheric burden and radiative effects. With such gaps in process understanding can we really characterize the reliability of models for aerosols? I think some thought needs to be given to this recommendation.
L542 – It is not clear if Hodzic et al is in preparation or submitted?
Figure 3 – It should be noted somewhere on the figure that ∑ represents uncertainties to avoid confusion.
Finally, the paper needs a thorough proof-read and editing to improve the quality of text.
References:
Please provide the full reference for Kok et al 2023 - Kok, J.F., Storelvmo, T., Karydis, V.A. et al. Mineral dust aerosol impacts on global climate and climate change. Nat Rev Earth Environ 4, 71–86 (2023). https://doi.org/10.1038/s43017-022-00379-5
Gulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004.
Szopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 817–922, doi:10.1017/9781009157896.008.
Citation: https://doi.org/10.5194/egusphere-2023-1174-RC2 - AC1: 'Comment on egusphere-2023-1174', Natalie Mahowald, 05 Sep 2023
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Natalie Marie Mahowald
Longlei Li
Samuel Albani
Douglas Stephen Hamilton
Jasper Kok
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1127 KB) - Metadata XML