This paper focuses on the injection of SO2 to the stratosphere by volcanic eruptions, and the resulting variability of the stratospheric aerosol layer. It presents a new volcanic SO2 emission database, derived from a collection of satellite instruments, covering the period 1990-2019. It also presents results from a chemistry climate model which uses the updated injection database, and compares the results of the model to various satellite data sets, focusing on the multi-wavelength aerosol optical depth and instantaneous radiative forcing produced by the aerosols.

The construction of such detailed SO2 injection estimates covering the 1990-2019 period is an impressive accomplishment. It is also to my knowledge quite novel, as I believe it is the first attempt to produce SO2 injection values from sulfate aerosol extinction measurements. Unfortunately, the description of the methods used to produce these estimates is lacking. Furthermore, assumptions and choices made in the methods are not given justification. More detailed comments are included in “Major Comments” below.

Chemistry climate model simulations using the new SO2 injection data set are performed and some results shown. Good agreement with observations is achieved, but there is insufficient analysis to provide any improved understanding of the physical or chemical processes that control stratospheric aerosol evolution.

Major comments:

1. The description of how SO2 amounts were calculated lacks sufficient detail. I am not aware of any other study that has estimated SO2 injection amounts based on aerosol extinction measurements. This is thus a novel technique, but the method used is not described beyond a few statements along the lines of “The SO2 mixing ratio perturbation is derived from the extinction perturbation observed in a 10-day period beginning about a week after the eruption by dividing by air density, multiplying by a constant and subtracting a typical background.” This explains extremely little: what constant is used, and why? How is the typical background determined? How well can the volume of the aerosol cloud be estimated a week after eruption from the satellite measurements? SAGE in particular has a very sparse sampling density, how does this impact the estimates? Can the method be validated? It would seem that the method could be applied to SAGE and OSIRIS during periods of overlap with MIPAS and the values from the new method compared to the “direct” MIPAS measurements. This would help increase confidence in the method, and provide some idea of the uncertainties in the estimates.
2. I highly recommend that the emission database be provided as an electronic supplement (e.g., csv or xls), to allow it to be readily used by other researchers. The table, as text, presently takes up almost 8 pages of the manuscript: it would be more efficient to visulatize the data somehow and include the values as supplemental information. Also, I strongly suggest that the format of the table be modified so that each individual eruption be listed per row, even if there are multiple eruptions on a given date. This will greatly improve the ease in which the data can be read within a computer program and thus used in other studies.
3. The model resuls show good agreement with observations, but it’s impossible to know whether the improved agreement (compared to prior works from the same group) is a result of the updated SO2 injection data, or to model improvements or changes in model resolution. Given the theme of the ACP journal, the reader expects that this work should improve our understanding of the chemical and/or physical processes that control stratospheric aerosol evolution, but it remains unclear if there is any improvement in understanding being extracted from the study. Nor is there any real motivation or objectives stated in the introduction for the model simulations.

Specific comments:

L11: “Reproduce” is too strong

L12: Here it is said that “slight deviations … were found only for the large volcanic eruption of Pinatubo in 1991”, but later in the document deviations in other time periods, e.g., 2010 are discussed, so this is inconsistent.

L19: precise language is needed here, is this the peak radiative forcing produced by a typical “small” eruption, or the time average forcing from these eruptions? And what is a small or medium eruption? Also, it’s not clear how this number is estimated, a value of 0.10 W/m^2 is not mentioned in the results or conclusions, and if it comes from Fig 11, how is the effect of small eruptions separated from that of “background” sulfur (e.g., DMS, OCS) transported into the stratosphere via atmospheric circulation?

L22-24: references needed for these statements.

L25: I believe Bruehl et al., 2015 were not making the actual measurements of the size distribution of stratospheric aerosols. Better reference needed.

L31: part of the aims stated here is apparently related to the interaction of aerosols with ozone, but this is not shown in the manuscript.

L34ff: Reference(s) needed.

L37: I am skeptical of a 3-year upper limit on the impact from volcanic eruptions: if ocean temperatures are a part of “climate”, then there is good evidence that volcanic impacts on climate can last much longer than 3 years (e.g., McGregor et al., 2015). Obviously the period of impact depends on many factors, but we should be careful to not overly simplify statements which might be misleading to some readers.

L44: Reference(s)?

L65: Some information should be given on how the SO2 column data was used, especially in regards to how a stratospheric component was estimated from the full column.

L130: The gaps in spatial coverage of the OSIRIS data at 17 km extend significantly beyond the polar night: they seem to extend even in best cases to 20-30deg. Some rephrasing needed.

L136: It’s not apparent how the sensitivity to clouds can be seen in Figure 4.

L140: How is the correction factor determined? This sounds suspiciously like numbers have been chosen only to produce best agreement.

L157: The study of Grainger et al. (1995) does not seem to provide a relationship between SAD and SO2 mixing ratio. More explanation needed.

L190: It is not clear how differences in the “vertical transport of tracers, like dust and water vapor or ozone” between model resolutions has any importance to the present study.

L216: What parameters?

L218ff: The double radiation call most likely calculates the “instantaneous radiative forcing”. It is important to be clear about this and consistent with the terminology.

L219: There is a double radiation call, but how exactly is the radiative forcing calculated?

L220: Not understanding this, are you diagnosing the impact of volcanic aerosol on upper stratospheric UV absorption? Nothing like this is shown in the results.

L241: What is the justification for the lower limits to the vertical integration given? You use 12 km as the lower limit in high latitudes, but the climatological tropopause height in high latitudes is 9-10 km. Conversely, you use 14 km in low latitudes, but the tropopause there is around 17 km. A thorough explanation for these counterintuitive thresholds will need to be given.

L251: An “integration time” has not been introduced, it is not clear what this means in terms of the method.

Table 2: There are a number of cases where the number of values do not match between the different columns in a particular row, e.g., 11 Feb 1990, 19 Aug 1992, 18 Sep 1996. Expanding the table so each eruption is listed in a single row would help this issue, as well as improve the machine readability of the table more generally. There is also a case (14 Jan 2002) where values are listed within brackets, and I did not find an explanation for what this means.

Table 2: The methods used produce an estimate of about 17 Tg for Pinatubo, which is in line with direct measurements of SO2 (e.g., Guo et al., 2004), but in contrast to recent model studies which suggest the effective injection for Pinatubo was much less (e.g., Mills et al., 2016; Dhomse et al., 2014). Some discussion of this issue would fit well into the paper.

L269: Mixing ratios appear quite variable, what is meant here by “typical”?

L271: What upper limit is referred to here?

L281: References should be included to support this statement on the transport of aerosols from Nabro.

L290: “The comparison of the simulated and observed SO2 values” is really hard to do since Figures 1 and 6 use different units and color schemes. It would be helpful to extract the MIPAS years from the simulations and show them with the same units and color scheme in comparison to the observations.

L293: Is the statement on SO2 lifetimes made here a result of this study, or are the lifetimes equivalent to those given by Hoepfner et al. (2015)? If the result is the same as Hoepfner et al., (2015), that should be explicitly stated. If estimated lifetime are different from Hopefner et al. (2015), how and why?

L300: This sentence seems to say that stratospheric aerosol optical properties were calculated using a range of different aerosol types (sulfate, dust etc.). Is this correct, or is the sentence just misleading?

L330: The OSIRIS data is converted from 750 nm to 550 nm, which is fine, but this contradicts the statement just a couple sentences earlier that “Unlike most other studies, the stratospheric AOD is compared at the original wavelengths derived from different optical channels of the satellite instrument measurements.”

L333: The statement that “differences after the large Pinatubo eruption in 1991 between the model simulations and the SAGE II observations are related to the “saturation” effects of the satellite instrument” seems much too confidently worded. It seems quite possible that “saturation” effects explain some of the difference, but how certain can you be sure that it is the only, or even the primary reason? In the tropics, the simulated AOD appears to be ~3 times larger than the SAGE II measurements—is it likely that the SAGE II measurement is so strong an underestimate of the true total AOD?

Fig. 11: The ERBE measurements are not described at all in the text. Are they anomalies? What is the global coverage of the measurements? Likewise, the data from Solomon is only mentioned in passing in the text, and a little more detail should be included on how those radiative forcing estimates were calculated.

L352: “The new model simulations with the additional volcanic eruptions (red line) are closer to the calculated estimates from satellite extinction measurements of SAGE, GOMOS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) by Solomon et al. (2011) (green crosses) than in previous studies (e.g., Brühl et al. (2015)).” This statement, a concrete conclusion of the study, is impossible for the reader to verify without accessing the prior study, finding the relevant figure, and trying to visually compare the two. This is asking too much of the reader. Please include the result of Bruehl et al. (2015) directly on Fig 11 here so we can directly assess the validity of this statement.

L361: Are the results of Minnis et al. (1993) equivalent to the ERBE data shown in Fig 11? Please clarify.

L362: clarify that the *simulated* AOD drops too quickly compared to the observations.

L374: “2019” is not an eruption.

L375ff: This paragraph is quoting results from other papers, not showing work from this study. If these statements are important, they should be moved out of the Results section or linked directly with results of the study.

L385: The fact that this study uses a higher resolution model than previous studies should have been mentioned earlier, in the model description and/or introduction.

L386: This appears to be a result of the study by Bruehl et al. (2018), which would be important in describing the experiment earlier in the manuscript but not here in the conclusions.

L388: The SAGE II and OSIRIS extinction measurements are not really “newly available”, some version of this data has been available for many years. The estimation of SO2 from these data sets is quite new—it’s what this paper is presenting!

L402ff: This conclusion is not supported by the results: there is no quantification of the impact the increased number of eruptions included in the database has on the radiative forcing, or its level of agreement with observations.

L408ff: This is an interesting conclusion, but it is not supported by the results. There is no demonstration that including the injections below the tropical tropopause improves the agreement. Even a comparison with prior studies will not prove necessarily support the statement since those prior studies used a different resolution model.

L418: This is not a new result, as it has been shown by prior studies.

L422: The impact of volcanic aerosol on tropical upwelling is not diagnosed in this study. Prior studies have explored this, but statements like this can not be included in the conclusions of this work if there are no new results shown to support it and build upon prior work.

L437ff: This paragraph talks about meteoritic dust, which was not investigated in the study. Perhaps simply adding a sentence or two on the agreement between the model and observed aerosol extinction in the upper stratosphere to motivate the discussion of meteoritic dust would help the reader follow the logic here.

448: Confirming the findings of the IPCC report is, firstly, incorrectly phrased, since the IPCC report only summarizes and reports findings gathered from the published literature. It would be more important to compare the results here with the primary sources, including studies that have been published since the IPCC AR5 (e.g., Schmidt et al., 2018). Second, confirming some general results from prior studies does not make an overwhelming case for publication. What does this study add to the understanding of volcanic radiative forcing that wasn’t known before?

L450: Radiative forcing is stated to be that at the surface here, where Fig 11 is said to be RF at the tropopause. Also the numbers quoted here don’t seem to agree with Fig 11. It would be best to only refer to calculations for which the results are shown in the paper.

Editorial comments:

Line 9: Volcanic SO2 is not “pollution” in the usual sense of the word, suggest it be cut here.

L49: “Distribution”?

L53: “constitute a source of background…”

L55: Awkwardly phrased: the processes aren’t structured, the paper is, and not strictly according to processes.

L80: I’ve never seen pptv written with v as a subscript, is this a new standard?

L111: confusingly phrased.

References

Dhomse, S. S., Emmerson, K. M., Mann, G. W., Bellouin, N., Carslaw, K. S., Chipperfield, M. P., Hommel, R., Abraham, N. L., Telford, P., Braesicke, P., Dalvi, M., Johnson, C. E., O’Connor, F., Morgenstern, O., Pyle, J. A., Deshler, T., Zawodny, J. M. and Thomason, L. W.: Aerosol microphysics simulations of the Mt.~Pinatubo eruption with the UM-UKCA composition-climate model, Atmos. Chem. Phys., 14(20), 11221–11246, doi:10.5194/acp-14-11221-2014, 2014.

Guo, S., Bluth, G. J. S., Rose, W. I., Watson, I. M. and Prata, A. J.: Re-evaluation of SO 2 release of the 15 June 1991 Pinatubo eruption using ultraviolet and infrared satellite sensors, Geochemistry Geophys. Geosystems, 5(4), Q04001, doi:10.1029/2003GC000654, 2004.

McGregor, H. V., Evans, M. N., Goosse, H., Leduc, G., Martrat, B., Addison, J. A., Mortyn, P. G., Oppo, D. W., Seidenkrantz, M.-S., Sicre, M.-A., Phipps, S. J., Selvaraj, K., Thirumalai, K., Filipsson, H. L. and Ersek, V.: Robust global ocean cooling trend for the pre-industrial Common Era, Nat. Geosci., 8(9), 671–677, doi:10.1038/ngeo2510, 2015.

Mills, M. J., Schmidt, A., Easter, R., Solomon, S., Kinnison, D. E., Ghan, S. J., Neely, R. R., Marsh, D. R., Conley, A., Bardeen, C. G. and Gettelman, A.: Global volcanic aerosol properties derived from emissions, 1990-2014, using CESM1(WACCM), J. Geophys. Res. Atmos., 121(5), 2332–2348, doi:10.1002/2015JD024290, 2016.

Schmidt, A., Mills, M. J., Ghan, S., Gregory, J. M., Allan, R. P., Andrews, T., Bardeen, C. G., Conley, A., Forster, P. M., Gettelman, A., Portmann, R. W., Solomon, S. and Toon, O. B.: Volcanic Radiative Forcing From 1979 to 2015, J. Geophys. Res. Atmos., 123(22), 12,491-12,508, doi:10.1029/2018JD028776, 2018.   

This study investigates the impact of explosive volcanic eruptions on the stratospheric aerosol burden, optical depth and Earth’s radiative balance using a chemistry-climate-model and a new inventory of volcanic SO2 emissions. Comparison with satellite observations are presented and with the exception of the Pinatubo period, the simulations are shown to be in good agreement.

Although the overall methodology of this paper is not new, there exists very few studies of the historical stratospheric aerosol forcing that use chemistry-climate models and SO2 inventories and this paper is thus a useful contribution. Furthermore, the study brings two novel elements: i) the use of a new volcanic SO2 emission inventory, argued to be more comprehensive and better compared to other inventories; ii) the strategy used to inject volcanic SO2 into the model, consisting in injecting 3D SO2 plumes instead of the standard “point source” injection. Unfortunately, I find these two points to be not sufficently motivated and explained (in the case of the second one), and analyses conducted do not enable to assess whether the new inventory and injection strategy result in improved volcanic forcing, which undermines the key contributions of this study. Furthermore, there is little to no comparison with previous work (e.g. different emission inventories, or different emission strategies). Many important references are lacking. To sum-up, I think this manuscript has the potential to become a really valuable paper for the community, but that further analyses as well as an improvement of the discussion section are still required.

Major comments:

1) The first novel aspect of the paper is the way in which volcanic SO2 is injected in the model. Previous studies have used a “point-source” approach with SO2 injected in one model column over a range of altitudes, with a few studies also injecting over a range of latitude for Pinatubo. However, in this study, the authors instead inject a “plume” consistent with spatially-resolved satellite observations. First, I think that this novel aspect is not highlighted enough in the introduction section and throughout the text, and it could be one of the key point of the manuscript. I also find your new method to be poorly explained and justified, in particular in section 5. On line 264, you say that the total amount of SO2 is calculated by integrating the SO2 profile but then mentioned that you add a 3-dimensionnal perturbation to the model which confused me. In section 5, you also don’t clearly state how these 3D plumes are obtained. My understanding from sections 3/4/5 is that:

• For each eruption, 3D SO2 plumes are obtained from time-averaged SO2 observations between the 8^th and 17^th day following each eruption?
• The 3D plumes , obtained from measurement 8-17 days after the eruption, are injected at the time of the eruption
• The 3D plumes are injected at latitude consistent with measurement taken but centered on the longitude of the volcano

Did I get this right? It all need to be crystal-clear and more detailed in the text as this is key to your method and a very unusual approach? You need to justify these choices better and show sensitivity tests for a large and small eruption (or ideally a full 1990-2019 simulation) showing how this differ from a standard “point” injection at the volcano location/plume height with a mass of SO2 corresponding to the initial total SO2 (not the SO2 after 8-17 days). Such tests seems really critical to demonstrate that your proposed method is better than standard methods, otherwise any related claim is unfounded. One of the main justification you provide to justify your injection strategy is that it removes any tropospheric SO2 that is not climatically relevant but: i) you already only consider SO2 above a threshold height (which is not justified; e.g. why 14km at the tropics instead of the tropopause height? If it’s because of radiative heating and lofting where does the threshold come from?) so why do you need further processing to remove potential “short-lived” SO2?; ii) The SO2 e-fold time is on the order of days-weeks (Carn et al. 2016, Fig 14); Even for stratospheric SO2 one would expect a significant amount of SO2 to be already converted to aerosol by the end of your 8-17 day time window, in particular for lower stratospheric injections. So would your method not result in large underestimation of SO2 amounts injected? I can see reasons why your method could make sense, e.g. fast SO2 scavenging by ash during the first days-weeks, but I think it is still not justified enough in the paper. More importantly, you need to show comparison between your approach vs standard point injection with the full SO2 mass to be able to really discuss the strengths and weaknesses of your strategy.

2) Overall, your paper really lacks comparison with existing work – including that from Bruhl et al 2015 – and a lot of key references are missing. As an example, on line 245-247, you suggest that your SO2 mass estimates will be very different from those in the dataset by Carn et al. (2016). Why not show a figure, at least in SI, comparing SO2 masses and heights for all events in common? This would be really informative. Regarding your simulations, you do not mention at all the work by Schmidt et al. (2018) which conducted exactly the same type of simulations, albeit with a different SO2 inventory and model. Citing it seems critical, and some of their time series (SAOD, radiative forcing) are likely available and could be compared to your model which would really improve the discussion. Also, it would have been nice to see a comparison of your new simulations with the previous model version/inventory used by some of the co-authors (Bruhl et al 2015) to get a sense of whether there is improved agreement with observations. Last, you compare your simulations with observations from multiple satellite instruments which is welcome, but I was under the impression that the GloSSAC dataset – built using some of the data you use – is now the reference for the community (at least for CMIP6 forcing). Could you add a comparison to GloSSAC?

Minor comments

Title: I think the title does not convey clearly enough the novelty of the new injection method; consider replacing “vertically-resolved satellite measurements” by something else? Maybe “Reconstructing volcanic forcing since 1990 using a comprehensive volcanic emission inventory and spatially resolved sulfur injection in a chemistry-climate model”? Your 3D plume are not just vertically resolved?

Abstract: the long list of satellite instruments and their acronym is not needed in an abstract? I find that the abstract does not highlight enough the novel and extensive character of the SO2 emission inventory nor the 3D plume injection method.

Abstract, lines 17-20: you say that your results “show” and that eruption “are found to”; I would instead say that your “confirm” these results as this has been shown by Schmidt et al. (2018)?

Line 36: is it important to specify at which level it affects Earth radiative balance? If so also mention surface level in addition to TOA and tropopause.

Line 38: Multiple papers discuss how climate-volcano feedback could modulate future volcanic forcing though, and it may be a good place to mention it? See e.g. Swindles et al. (2017) (deglaciation effect on eruption frequency), Fasullo et al. (2018) (modulation of volcanic influence on surface temperature by changes in ocean stratification), Aubry et al. (2021) (impact of climate change on the volcanic stratospheric sulfate aerosol cycle)

Line 40: unless I misunderstand I guess you are talking about (mostly CMIP5) simulations that did not account for this forcing? Many model studies have accounted for this forcing since then, including CMIP6 historical simulations that use GloSSAC or e.g. Mills et al. (2016) and Schmidt et al. (2018)?

Line 43/44: please add references

Line 50: The SO2 emission and time-averaged volcanic forcing of degassing volcanoes and small eruptions is one order of magnitude larger than that of eruptions associated with stratospheric SO2 injections (e.g. Schmidt et al. 2012, Carn et al 2016). So clarify what you mean by “smaller natural source of aerosols” as this seems wrong as written.

Line 46: do you mean “overlooked” instead of “underestimated”? If not what was underestimated? Their radiative forcing? But does it not contradict the previous sentence?

Introduction: I think the work of Mills et al (2016) and Schmidt et al 2018 (not cited) need to be discussed more given strong similarities with your study. Also you don’t mention ISA-MIP at all (Timmreck et al 2018) whereas your simulations are obviously relevant to this MIP?

Introduction: Also see major comment 1: the two main novelties of your study are overall not motivated in your intro (i.e. new injection strategy and improved SO2 inventory).

Section 2: could you group satellite instruments in terms of those used to constrain SO2 inputs in your model vs those used to evaluate the output of the model simulations? This would add a lot of clarity to this section. Also why not using GloSSAC (Thomason et al. 2018, 2020)?

Line 119-120: as said in my major comment I think you need to discuss the strength and limitations of choosing such a time window, and in particular how it compares to the SO2 e-folding time and the fact that choosing this time window may result in neglecting a large portion of SO2 converted to aerosols (even though I understand the argument that an earlier time window could account for SO2 estimates accounting for SO2 that will be rapidly scavenged by co-injected ash or hydrometeors; but this all needs to be discussed carefully). Sensitivity tests for this time window and understanding its impact on your SO2 estimates would be welcome.

Line 137: again this time window needs to be justified better. Also I’m not at all a remote sensing expert but I think it’s the first time I see SO2 estimated from extinction coefficients in visible wavelength? Is that a standard method? How is the effect of SO2 on radiation properties isolated from other species, in particular sulfate aerosols? It may be standard techniques that I’m not aware of about but it would be good to clarify.

Line 139: My understanding here is that you are saying that if there is a data gap during the peak perturbation, you scale up by an arbitrary factor to recover a reasonable peak value? How is that factor chosen? There is absolutely no explanation nor reference and it may deserve dedicated SI plots?

Line 139 and 170: about data gaps and how to treat them, I’m just wondering why not using GloSSAC where the same problem had to be addressed and which is the reference dataset for the community? I understand you can’t use it for SO2 but surely for aerosol properties it would make sense? The fact that major initiatives such as GloSSAC or ISA-MIP are not mentioned is a bit surprising.

Line 236: no apostrophe needed for Global Volcanism Program

Line 241: The tropopause altitude varies between ca. 8-9 and 16-17km depending on latitude and season, why not using the model diagnostic tropopause instead of the three thresholds used? Justify rigorously why you consider a threshold way below the tropopause height in the tropics but potentially way above at high latitudes. Also why do you need to mask tropospheric SO2? Would your model not account for the fact that tropospheric aerosol would have minimal impact on climate? I get that you don’t want an overlap between the tropospheric and stratospheric volcanic SO2 inventory, but does the tropospheric SO2 inventory really account for emissions as high as 12-14 km or is it only passively degassing volcanoes?

Lines 243-247: see my major comment #1

Table 2: this table really must be made available as a csv file or something that researchers can download and read in scientific programming software. Remove the table from the body of text as it is way too big.

Lines 257-264: see my major comment #1. While I think this is at the moment poorly explained and that you have to show analyses demonstrating the advantages and challenges with this injection method, I do think that it is one of the most novel and important aspect of the paper (combined with your inventory) and that it should be highlighted and motivated a lot more.

Line 275-276: you either need a reference backing this claim or data analysis to support it (e.g. does the GVP database have a comparable number/frequency of VEI 3-5 eruptions during 1991-2002 relative to 2002-present day? Or was it really a more quiescent period?

 Lines 293-294: a brief comparison with observations in Carn et al. 2016 would be welcome here (I think they suggest even lower UTLS e-folding time). Also you say yourself here that the conversion time is about 2 weeks, which seems to strongly undermine your chosen 8-17 day time window to constrain SO2 emission from satellites?

Line 303-304: please clarify what you mean by “feedback to atmospheric dynamics” and cite appropriate references

Line 309-310: the reader has to look at three different figures and compare them to verify this statement. It would me much better if you could present equivalent observations and model plots on the same figure and different panels. This would greatly facilitate model-observation comparisons.

Line 326: the vast majority of studies use SAOD at 550nm like you (e.g. Schmidt et al. 2018), and also 1020nm (e.g. Aubry et al. 2021) which is another standard one for some instruments? So this statement seem really not justified and should be removed or modulated.

Line 331: clarify that the AOD of 0.4 is in the tropics and isn’t a global mean value

Line 334: There could be other factors explaining model-observation differences in the post-Pinatubo period including flaws in the model (as evident from the different decay timescales) and uncertainty in the SO2 mass, or at least the “climatically relevant” portion of it (you use 17Tg, other studies use as little as 10 which should be briefly discussed; see Zhu et al. 2021, Mills et al. 2016, Schmidt et al. 2018).

Line 337: unless major eruptions are missing, is it really likely that imperfections in your inventory explain the large SAOD differences over 1993-1996?

Figure 11: it may be better to show horizontal bars (with a length of 1 year) instead of green crosses as these are time-average measurement and it would facilitate comparison with your high-resolution output?

Figure 11: Here and on Figure 9 and 10, could you not show for comparison the simulations from at least Bruhl et al. (2015) and maybe Schmidt et al. 2018 assuming their data are available with the paper? Discussing the differences would really improve the discussion.

Legend of Figure 11: specify the time resolution of the ERBE data. Is there no other observational estimate of radiative forcing to complement observations shown? E.g. CERES data?

Line 354: “previous studies”-> show their data and discuss comparison? On that note making sure that your key outputs (SAOD/radiative forcing time series) are easily available is important and I don’t think it’s the case yet? Key outputs should not be made “available upon request” but should ideally be provided as SI or in a data repository.

Line 359: For reference, can you indicate the SO2 mass for Merapi used in your and other (e.g. Carn et al. 2016) inventories? Overall, it would be really useful to have a comparison of your inventories with other standard ones, in particular those used in ISA-MIP (Timmreck et al. 2018). Another potentially useful reference, showing how different inventories affect the SAOD prediction by a simple model, is Aubry et al. (2020) (see Figure 8 there).

Figure 12: could you discuss how these results compare with recent studies, e.g. Rieger et al. (2020) or Stocker et al. (2019)

Section 7: Overall I find that some of the most natural lines of discussion (and accompanying analyses) are completely missing including: i) comparison of your new inventory with other ones, including Carn et al.; ii) comparison of your new simulations with other equivalent ones, including Schmidt et al (2018) and Bruhl et al (2015); iii) discussion of how your 3D-plume injection strategy compares to a point injection.  

Line 385: provide numbers (e.g. latitude resolution at equator) that make it easier for the reader to understand the difference between these resolutions.

Line 410: Missing reference?

Line 429-430: Zhu et al. (2020) should be cited here

Line 429-432: On model difference/setup and how it may affect simulated aerosol properties, Clyne et al. (2021) is an important difference and should be discussed here and elsewhere.

Lines 448-455: This whole paragraph doesn’t acknowledge the contribution of previous studies when most of the statements made are not really new. First maybe you should refer to the AR6 report now that it is out instead of the AR5? Second, for radiative forcing estimate, the contribution of Schmidt et al. (2018) should be acknowledged and you should compare in details your forcing estimates to theirs. Third, for temperature effects, you should cite the papers by Santer and co-authors (2014, 2015) and Schmidt et al. (2018). I personally think that the novel aspects of your paper would be highlighted better if you ended it on key points related to the new inventory and the 3D plume injection method.

References

Aubry, Thomas J., et al. "A new volcanic stratospheric sulfate aerosol forcing emulator (EVA_H): Comparison with interactive stratospheric aerosol models." Journal of Geophysical Research: Atmospheres 125.3 (2020): e2019JD031303.

Aubry, Thomas J., et al. "Climate change modulates the stratospheric volcanic sulfate aerosol lifecycle and radiative forcing from tropical eruptions." Nature Communications 12.1 (2021): 1-16.

Brühl, C., et al. "Stratospheric sulfur and its implications for radiative forcing simulated by the chemistry climate model EMAC." Journal of Geophysical Research: Atmospheres 120.5 (2015): 2103-2118.

Carn, S. A., Lieven Clarisse, and Alfred J. Prata. "Multi-decadal satellite measurements of global volcanic degassing." Journal of Volcanology and Geothermal Research 311 (2016): 99-134.

Clyne, Margot, et al. "Model physics and chemistry causing intermodel disagreement within the VolMIP-Tambora Interactive Stratospheric Aerosol ensemble." Atmospheric Chemistry and Physics 21.5 (2021): 3317-3343.

Fasullo, J. T., et al. "The amplifying influence of increased ocean stratification on a future year without a summer." Nature communications 8.1 (2017): 1-10.

Kovilakam, Mahesh, et al. "The Global Space-based Stratospheric Aerosol Climatology (version 2.0): 1979–2018." Earth System Science Data 12.4 (2020): 2607-2634.

Rieger, Landon A., et al. "Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment." Geoscientific Model Development 13.10 (2020): 4831-4843.

Santer, Benjamin D., et al. "Observed multivariable signals of late 20th and early 21st century volcanic activity." Geophysical Research Letters 42.2 (2015): 500-509.

Schmidt, Anja, et al. "Volcanic radiative forcing from 1979 to 2015." Journal of Geophysical Research: Atmospheres 123.22 (2018): 12491-12508.

Schmidt, Anja, et al. "Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate." Atmospheric Chemistry and Physics 12.16 (2012): 7321-7339.

Stocker, Matthias, et al. "Quantifying Stratospheric Temperature Signals and Climate Imprints From Post‐2000 Volcanic Eruptions." Geophysical research letters 46.21 (2019): 12486-12494.

Swindles, Graeme T., et al. "Climatic control on Icelandic volcanic activity during the mid-Holocene." Geology 46.1 (2018): 47-50.

Timmreck, Claudia, et al. "The interactive stratospheric aerosol model intercomparison project (ISA-MIP): Motivation and experimental design." Geoscientific Model Development 11.7 (2018): 2581-2608.

Zhu, Yunqian, et al. "Persisting volcanic ash particles impact stratospheric SO 2 lifetime and aerosol optical properties." Nature communications 11.1 (2020): 1-11.

Review of “Radiative forcing by volcanic eruptions since 1990, calculated with a chemistry-climate model and a new emission inventory based on vertically resolved satellite measurements by Jennifer Schallock et al.

Using various (occultation and limb based) satellite instruments, with vertical SO2 profiles from different satellite instruments and chemistry climate simulations, this study characterizes the influence of stratospheric volcanic aerosols for the period between 1990 and 2019. The results show that small but relatively frequently eruptions contribute to the stratospheric aerosol layer and could cause a global radiative forcing in the order of−0.1 Wm−2 at the tropopause. In specific, the objective of this study was to generate a detailed volcanic sulfur emission inventory, to improve the EMAC model simulations of the global stratospheric aerosol and sulfate burden, and to compute the volcano-induced radiative forcing through validation with satellite data.

Honestly, the paper keeps me a bit loss, as I am not sure if it is a more scientifically or more technically oriented paper. The scientific objective is not clear to me in particular the added value to the recent literature. I am wondering if the paper would not better fit in Earth System Science data (ESSD, https://www.earth-system-science-data.net/) or in Geoscientific Model Development (GMD, https://www.geoscientific-model-development.net/). The topic of the paper is in general very suitable for ACP but the paper needs major substantial revisions before publishing in ACP, see my major comments below.

Major comments:

• The introduction needs a complete rewriting, less text book more scientific background with respect to the questions to be addressed. The paper is a successor of Brühl et al. (2015; 2018) and Bingen et al. (2017) but I miss a clear separation and explanation about the added values of this paper compared to its predecessors. The better horizontal resolution has already been discussed in Brühl et al. (2018), so the new aspect, as far as I understood it, is the increased amount of volcanic eruptions and the extend time period by using new satellite data.
• I completely miss references to recent literature in the introduction with respect to radiative forcing estimates of recent eruptions. There are several publications e.g. Andersson et al., (2015); Friberg et al., (2018), Schmidt et al.,(2018); Kloss et al;(2021) just to name a few which have addressed the radiative forcing of small to moderate volcanic eruptions in the recent years. These papers have to be cited and differences/added values to their work have to be addressed in the introduction.
• The discussion needs also to be rewritten. As mentioned above the lack of references of recent literature is astonishing. The results of the study need to be discussed in the context of recent literature, e.g. what do we learn from this paper, what we didn’t know before from previous studies.
• I am also wondering about the importance of the small eruptions for the global radiative forcing. It would be interesting if you neglect all small eruptions below a certain threshold values e.g. 10 kT SO2, how this would really change the global radiative forcing. What is range of uncertainties, the range of interannual variability in background periods? Estimates about the uncertainty range are completely missing in the paper.
• Last but not least, differences between the model simulations and satellite measurement need not to be the only cause of missing SO2 sources. There could be several other reasons for the discrepancies (transport, microphysics), neither model simulations nor satellite measurements are perfect. This has to be discussed here as well.

Specific comments

• Abstract, line 17: “significantly” is a big word. I did not find any significance tests in the paper.
• Page 3, which SSTs do you use? I suppose you run only  one ensemble members did you check for  the influence of internal variability at least in short  sensitivity studies?
• Description of the EMAC module could be reduced, to only the parts which are really relevant for the paper,. e.g. the calculation of the radiative forcing. This part could be more elaborated. More detailed model descriptions can be put in the appendix.
• Page 12, lines 245-247 It would be nice to see a comparison with Carn et al (2017) and other recent emission data
• Table 2: It would be nice to see (e.g. with different color) which entries are new or changed with respect to the previous data set. Will the data set be published?
• Page 21, line 279 “strong” I wouldn’t call Kasatochi or Raikoke a strong eruption
• Figures 9, 10, 11: A comparison with Brühl et al. (2015) for the Pinatubo period and with Brühl et al (2018) for 2002 to 2012 would be nice, to better asses the improvements of this study. Also a validation with GloSSAC (Thomason et al., 2018; Kovilakam et al., 2020) would more than beneficial.
• Section 6.3: Any reason why you look at the tropopause? What is the uncertainty range in your forcing estimates?
• Figure 11  I recommend a comparison with Schmidt et al (2018) here
• Page 409, 410: “This was demonstrated to be essential for correctly assessing the extinction coefficient in volcanically quiescent periods.”  By whom? Maybe I have overseen it but I didn’t find it in the paper.
• Page 445, Which studies?

References:

Andersson, S. M., Martinsson, B. G., Vernier, J. P., Friberg, J., Brenninkmeijer, C. A. M., Hermann, M., Van Velthoven, P. F. J., and Zahn, A.: Significant radiative impact of volcanic aerosol in the lowermost stratosphere, Nat. Commun., 6, 1–8, https://doi.org/10.1038/ncomms8692, 2015. 

Bingen, C., Robert, C. E., Stebel, K., Brühl, C., Schallock, J., Vanhellemont, F., Mateshvili, N., Höpfner, M., Trickl, T., Barnes, J. E., Jumelet, J., Vernier, J.-P., Popp, T., de Leeuw, G., and Pinnock, S.: Stratospheric aerosol data records for the climate change initiative: Development, validation and application to chemistry-climate modelling, Remote Sensing of Environment, 203, 296–321,https://doi.org/10.1016/j.rse.2017.06.002, 2017.

Brühl, C., Lelieveld, J., Tost, H., Höpfner, M., and Glatthor, N.: Stratospheric sulphur and its implications for radiative forcing simulated by the chemistry climate model EMAC, J. Geophys. Res.-Atmos. 120, 2103–2118, https://doi.org/10.1002/2014JD022430, 2015.

Brühl, C., Schallock, J., Klingmüller, K., Robert, C., Bingen, C., Clarisse, L., Heckel, A., and North, P.: Stratospheric aerosol radiative forcing simulated by the chemistry climate model EMAC using aerosol CCI satellite data, Atmospheric Chemistry and Physics, 18, 1–15, https://doi.org/https://doi.org/10.5194/acp-18-12845-2018, 2018.

Friberg, J., Martinsson, B. G., Andersson, S. M., and Sandvik, O. S.: Volcanic impact on the climate – the stratospheric aerosol load in the period 2006–2015, Atmos. Chem. Phys., 18, 11149–11169, https://doi.org/10.5194/acp-18-11149-2018, 2018

Kloss, C., Berthet, G., Sellitto, P., Ploeger, F., Taha, G., Tidiga, M., Eremenko, M., Bossolasco, A., Jégou, F., Renard, J.-B., and Legras, B.: Stratospheric aerosol layer perturbation caused by the 2019 Raikoke and Ulawun eruptions and their radiative forcing, Atmos. Chem. Phys., 21, 535–560, https://doi.org/10.5194/acp-21-535-2021, 2021.

Kovilakam, M., Thomason, L. W., Ernest, N., Rieger, L., Bourassa, A., and Millán, L.: The Global Space-based Stratospheric Aerosol Climatology (version 2.0): 1979–2018, Earth Syst. Sci. Data, 12, 2607–2634, https://doi.org/10.5194/essd-12-2607-2020, 2020.

Schmidt, A., Mills, M. J., Ghan, S., Gregory, J. M., Allan, R. P., Andrews, T., Bardeen, C. G., Conley, A.,Forster, P. M., Gettelman, A., Portmann, R. W., Solomon, S., and Toon, O. B.: Volcanic Radiative Forcing From 1979 to 2015, J. Geophys.  Res.-Atmos.,123, 12491–12508, https://doi.org/10.1029/2018jd028776, 2018.

Thomason, L. W., Ernest, N., Millán, L., Rieger, L., Bourassa, A., Vernier, J.-P., Manney, G., Luo, B., Arfeuille, F., and Peter, T.: A global space-based stratospheric aerosol climatology: 1979–2016, Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018, 2018.