the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Stratospheric aerosol forcing for CMIP7 (part 1): Optical properties for pre-industrial, historical, and scenario simulations (version 2.2.1)
Abstract. Stratospheric aerosols, most of which originate from explosive volcanic sulfur emissions into the stratosphere, are a key natural driver of climate variability. They are thus a forcing provided by the Coupled Model Intercomparison Project (CMIP) Climate Forcings Task Team to climate modelling groups participating in phase 7 of CMIP. For the historical period, we provide two datasets covering 1750–2023: i) a volcanic upper tropospheric-stratospheric sulfur emission dataset, documented in a companion paper; and ii) a stratospheric sulfate aerosol optical property dataset, which we document here at version 2.2.1. For the satellite era (from 1979 onwards), stratospheric aerosol optical properties are derived from the Global Space-based Stratospheric Aerosol Climatology (GloSSAC) dataset. For the pre-satellite era (1750–1978), optical properties are derived from our volcanic SO2 emission dataset using a new version of the reduced-complexity volcanic aerosol model Easy Volcanic Aerosol (Height) (EVA_H). A background, non-volcanic stratospheric aerosol climatology is derived from the 1998–2001 period with a trend over 1850–1978 accounting for increasing anthropogenic aerosols. A monthly stratospheric aerosol climatology is derived from the 1850–2021 average for both pre-industrial and Scenario (future) simulations, with a 9-year ramp over 2022–2030 for scenario simulations to ensure a smooth transition from the historical period. Our methodology to produce historical aerosol optical properties significantly differs from CMIP6 for the pre-satellite era, and the resulting forcings in turn largely differ. In particular, the CMIP6 dataset was mostly based on the sparse and uncertain pyrheliometer record, which resulted in strongly underrepresented emissions from small-to-moderate magnitude eruptions. The resulting bias is addressed in CMIP7, which is entirely emission-derived in the pre-satellite era and uses more recent ice-core-based volcanic sulfur emission inventories than CMIP6. Our approach results in an overall larger volcanic aerosol forcing for CMIP7, with the 1850–2014 mean mid-visible global mean stratospheric aerosol optical depth (SAOD) in CMIP7 (0.0138) being 29 % higher than in CMIP6 (0.0107). The pre-industrial mean of the same variable is 26 % higher in CMIP7 (0.0135, derived from the historical 1850–2021) than CMIP6 (0.0107, derived from the historical 1850–2014 mean). Using a reduced-complexity climate model, we simulate a global mean surface temperature that is 0.07 °C colder for 1850–1900 when using the CMIP7 dataset instead of CMIP6, whereas 2000–2014 is 0.03 °C warmer in CMIP7. Our dataset also exhibits lower forcing for 1960–1980, resulting in temperatures 0.06 °C warmer when averaged over 1960–1990, a period for which CMIP6 climate models exhibit a cold bias. Given the large uncertainties characterizing the dataset, in particular for the pre-satellite era, we advise against treating the CMIP7 or CMIP6 dataset as uniquely superior for any specific year and highlight the need for further evaluation. We conclude the study by discussing sources of uncertainty for the dataset, future research avenues to improve it, as well as requirements to operationalize the production of the dataset, i.e. extend it and update it on an annual basis instead of every 5–7 years following CMIP cycles.
Competing interests: Vaishali Naik is a topic editor of this special issue. The authors have no other competing interests to declare.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 11 Dec 2025)
- RC1: 'Comment on egusphere-2025-4990', Helene Hewitt, 17 Nov 2025 reply
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RC2: 'Comment on egusphere-2025-4990', Anonymous Referee #2, 20 Nov 2025
reply
General comments:
The Coupled Model Intercomparison Project (CMIP) provides a framework for climate modeling groups to coordinate experiments, compare their latest developments and provide the latest climate projections. Set to enter its 7th iteration, CMIP7 requires various model forcings to be distributed to all participating groups. This work describes the updated stratospheric aerosol forcing optical properties - an important natural climate forcing - for use in CMIP7, with a companion paper about volcanic emissions that this paper partly relies on, intended for publication in the same special issue.
The authors contextualize their work by outlining the CMIP6 stratospheric aerosol forcing - which is the predecessor dataset to the one described here - previous challenges, and objectives to adhere to with this work. Then, source datasets are described in some detail including steps taken to prepare them for CMIP7 dataset production.
For the satellite period, aerosol extinction is directly observed, however, before that aerosol optical properties need to be modelled based on emission data. For production of the pre-satellite forcing (spanning 1750-1981) the reduced-complexity volcanic aerosol model EVA_H v2 is employed. Since this is an update over the previously documented version 1, the changes and improvements are documented here.
The authors detail the full procedure followed to model the stratospheric aerosol in the past, merge the resulting record with satellite observations and extend the dataset into the future with a scenario forcing based on a climatology. From there they produce the complete input variables for climate models. For wavelength-dependent variables this involves transposing the data onto new wavelengths using a Mie scattering code. They offer datasets on a wide variety of commonly used wavelengths bands and also provide a program to interpolate these variables onto any custom wavelength band by the potential user. Finally, the CMIP7 dataset is compared to the one used in CMIP6. Key differences are noted, which could have implications for the analysis of climate data produced with this forcing. There are also suggestions for the future handling and operationalization of stratospheric aerosol forcing production.
This manuscript covers a variety of aspects related to the production of the CMIP7 stratospheric aerosol forcing, how it compares to the past efforts and what may be improved in the future. As such, it is a comprehensive article for both readers familiar with the matter and potential readers outside the field that work with the provided dataset.
The science and technical descriptions are both thorough and logical. The manuscript is structured effectively and the figures and tables are relevant and illustrate the important points well. The title and abstract are concise and representative of the contents. The methods used are clear and well documented and all materials for reproduction of the results are provided. There are only minor inconsistencies and inaccuracies that need to be addressed.
This manuscript is a cornerstone in the documentation of CMIP7 forcing production and provides the greater climate modelling community with a valuable reference on important considerations on volcanic and background stratospheric aerosol dataset production.
I therefore recommend the manuscript for publication after minor revisions.
Specific comments:
Line 75; Section 1.2:
It is correct that there is no complete published CMIP6 dataset description, however, in the supplement to Jörimann et al. (2025) the SAGE-3λ record is documented, which was the latest iteration that went directly into the CMIP6 forcings. Using this source, you can confirm that for 1961-1978 pyrheliometer data from Stothers (2001) - which you cite - are used. Please also check in this entire subsection and Fig. 1a, if the supplement can complement your overview of the CMIP6 forcing. Since SAGE-3λ uses three wavelengths (wherever possible), it should also be specified that GloSSAC provides more than two wavelengths (line 83) on occasion.
Line 108:
(e.g. extinction coefficient, single-scattering albedo, asymmetry factor or surface area density)
Line 140:
Suggestion to use the “proper” name Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), since this is in the title of its citation (Zanchettin et al, 2016) you give directly after introducing VolMIP.
Line 211:
You choose the VEI 4 SO2 mass for GVP events to match the anomaly from 1998-2023 “… (defined as the deviation from its minimum) …”. I agree that the chosen time period is fit for this purpose, but it is not exactly clear what the deviation from the minimum is. Is the minimum the very lowest SAOD data point found in this time period? If so, is it representative for an “undisturbed” stratospheric aerosol or could it be an outlier? Or could an average such as 1999-2003 (quasi-quiescent state) be taken as the minimum to derive the deviation against? Please elaborate what is meant by the minimum and why it was chosen this way.
Line 232:
Periods without SAGE coverage are supplemented, but periods with SAGE coverage are also partly supplemented, especially at high latitudes, can you confirm this? The sentence could simply be extended similar to: “Periods without SAGE coverage and high latitude data not captured during SAGE coverage are supplemented by complementary spaceborne and ground-based observations …”
Lines 294-297:
I find this sentence hard to understand due to its length. Consider splitting it into two sentences for the reader’s convenience.
Line 308:
Please define the missing mathematical notation in the text, similar to: “… of the injected SO2 mass MSO2 and a linear function of the injection height HSO2.”
Line 322:
Suggest to write “Australian Black Summer pyrocumulonimbus” or “Black Summer pyrocumulonimbus in Australia” instead of “Black Summer Australian pyrocumulonimbus” to keep naming consistent with line 329 and literature.
Line 329:
I assume that you mean to either write “… to ensure that it has no influence” or “… to ensure that it has minimal influence”. Please correct.
Line 334:
The wording in this sentence “… it does not favor closest matching exactly GloSSAC …” is hard to read and unclear, please change it.
Line 347:
It says that after the initial model parameter search with eruption masses higher than 0.1 Tg SO2, the refined search then respects the other eruptions “… with an upper end of stratospheric SO2 mass higher than 0.1 Tg SO2.” Is it not supposed to be “lower” here, instead of “higher” again? Otherwise I do not understand the distinction between the initial and refined search.
Lines 416-419:
“H2SO4 number concentration” should be “H2 SO4 number density” everywhere, the same way the variable nd is called just after (line 420) and also in Table 2.
Line 423:
MH2SO4 must be the molar weight, not the molar concentration of H2SO4. This follows from dimensional analysis of your Eq. (2), which yields mass per mole for MH2SO4, not number per volume as it would be for molar concentration.
Line 505:
From previous description it seems that the extinction coefficients are derived using version 2 (exclusively) of EVA_H. If so, specify ”EVA_H v2”, as the term “EVA_H” has been used before to distinctly talk about the EVA_H group (v1 and v2). The version number should also be used in the subplot titles of Fig. 7 & 8
Line 526:
In this section the wavelengths, on which you produced ext, ssa, asy are given, however, the radiative transfer models operate with wavelength bands. In the data you provide both “wavelength” and “wavelength_bnds” variables and it seems that the wavelength is the (linear!) center or midpoint of each wavelength band. The wavelength bands are continuous across the spectrum. Do the data (e.g. ext) you report on the 39 wavelengths, correspond to the data you computed for the respective wavelength band? If so, can you make it clear in the text, notably in this section (4.3)? Also specify what exactly is meant by “properties at arbitrary wavelengths” on line 545 in this context.
Lines 574-575:
The colors you mention (red, green, and black) do not correspond to what is shown in Fig. 9 (different shades of red). Change the caption or the lines in the plot.
Line 578:
Please introduce the abbreviation ESGF before using it.
Line 667:
You call the stronger negative anomaly of the radiative forcing “enhanced”, yet it would seem reasonable to assume an enhancement in RF should be a positive change.
Line 1130:
Please add the ETH research collection item Luo (2017), which was created as a more accessible and persistent item that contains the CMIP6 data and some documentation and also has a DOI (https://doi.org/10.3929/ethz-b-000715155).
Since the specific file on the FTP file server that you reference in Luo (2018) is not in the ETH research collection item, I suggest that you either keep the FTP link as the separate citation you already have, or add a note to the Luo (2017) citation to mention that some description documents are only available there, similar to (“with additional information accessible at …”).
Finally, update the last access.
Citations not already in the manuscript:
Luo, B.: SAGE-3λv4: Stratospheric aerosol data for use in CMIP6 models, ETH Research Collection [data set], https://doi.org/10.3929/ethz-b-000715155, previously distributed through ftp://iacftp.ethz.ch/pub_read/luo/CMIP6_SAD_radForcing_v4.0.0 (last access: 8 June 2025), 2017.
Technical comments:
Fix affiliation number on lines 8 & 15.
Throughout the manuscript make sure to separate units from the corresponding number with a space (e.g. % and °C in the abstract, 550[ ]nm e.g. Fig. 1 caption). Also, the Copernicus guidelines state: “Coordinates need a degree sign and a space when naming the direction (e.g. 30° N, 25° E)”, e.g. subplot titles in Fig. 4 and caption in Fig. 6. Further “The abbreviation "Fig." should be used when it appears in running text…”
Suggestion to write “scenario” instead of “Scenario” throughout the document. If you prefer to capitalize, make sure to capitalize “Scenario” everytime when the Scenario simulations are mentioned.
Line 73:
Standard plural of spacecraft is also spacecraft.
Line 404:
“… where aerosol effective radii are below 0.4 …”
Line 416:
“There properties…” should be “These properties…”
Line 432-433:
“…, nor from eruptions that that injected sulfur into the upper troposphere that was rapidly (typically within weeks) transported into the stratosphere, …”
Line 441:
I am not sure what common practice is, but I have seen “Mt Etna” and “Mt Ruang” instead of “Etna” and “Ruang” before. You also use “Mt” in other places in the text. Please choose whatever is most appropriate.
Figure 8:
X-axis label of subplot 1 collides with title below. Also, this is the only time the year axis is labelled, so it can be omitted.
Line 881:
Do not include a dash in the section title.
Line 885:
“… using version 2 of EVA_H …”
Line 942:
Sometimes initials are used in the financial support section, sometimes full names are used. Suggestion to always use initials.
The references are not all rendered in the same citation style, compare e.g. the formatting of Dhomse (line 1041) and Eyring (line 1048). This applies to many items in the bibliography.
Citation: https://doi.org/10.5194/egusphere-2025-4990-RC2
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- 1
Review of ‘Stratospheric aerosol forcing for CMIP7 (part 1): Optical properties for pre-industrial. Historical and scenario simulations (version 2.2.1) by Thomas Aubry et al.
This paper sets out to document the choices made in the production of the stratospheric aerosol forcing datasets for CMIP7. I congratulate the author team on this paper – I found this to be an excellently written paper with clear descriptions and explanations of the choices made as well as the caveats and drawbacks of the choices.
I believe that the description given in the paper and the associated links to code and data, would enable the CMIP7 dataset to be reproduced. I would however like to request that all the code used to produce the forcing dataset archived in a github directory that has WCRP or CMIP ownership to ensure the long-term legacy of the dataset.
The authors produce a nice summary of how the CMIP6 dataset was produced. The differences between the CMIP6 and CMIP7 dataset are clearly laid out throughout the paper both in terms of the choices made and the resulting data. I believe that the analysis in section 5 demonstrates the requirement in the future to provide uncertainty estimates with the forcing datasets.
Since I am not an aerosol expert, my comments are directed towards improving clarity, reproducibility and usability in CMIP7 as well as future perspectives. However, none of my comments are major and I therefore recommend that the paper is published with minor revisions.
Comments:
L33: I think it would be more logical to swap around i and ii in this description since the current paper is Part 1 in the series
L197: Can the authors comment on whether there are likely gaps in small to medium volcanoes in the Southern hemisphere in the pre satellite period given that the ice core is from Greenland?
L272: The relatively cheap EVA model is perhaps in contrast to the computational cost of the models used to produce the ozone datasets. This is perhaps worth commenting on in the future perspectives discussion
L308: For completeness please include the symbols for the terms in the sentence
L329-331: This sentence didn’t make sense to me in particular ‘deemed less risky to bias the model calibration’. Please reword
L355: Is the EVA_H v2 model in figures 4b-f the calibrated one? Please clarify
Figure 4a: The calibrated model looks particularly smooth between ~2000 and 2005. Is it obvious why that might be the case?
L384: ‘uses’
L386: ‘the complex’
L394: Is it possible to quantify the impact of using a coarser resolution index?
Figure 6c: The comparison with UKESM1 suggests that the background SAOD is too high in 1850. Can you comment further on that?
L556: It would be worth noting that the impact of Hunga Tonga eruption can be assessed in CMIP7 if historical simulations are continued in parallel to the projections forced by scenarios (as described in Hewitt et al., PLOS Climate, 2025)
L578: ‘to any’
L586: It is great that these scripts are on github but this is an example of code which I think should be curated centrally by WCRP/CMIP
L639: I think that the conclusion here is that the two datasets could be used to explore the uncertainty in the forcing datasets and a future aim might be to provide some indication of uncertainty with the datasets. Is it possible to make an initial estimate of the order of magnitude of the uncertainty on SAOD given the comparison between CMIP6 and CMIP7?
Table 3: It would be good to clarify in the table caption and column headings that the only difference in forcing between the two columns is the SAOD dataset used. I would also suggest adding a ‘difference due to choice of CMIP6/7 dataset’ column
L745: As above, I think it would be good to recommend providing uncertainties in a future update of the dataset
L830: I was very pleased to see this list of key resources and suggest adding a comment that these need to be included in GCOS considerations
L860: It would be good to include an estimate of the person effort for extensions and updates
L869: Is it possible for the code to be in WCRP/CMIP curated github?