the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Isolating the boreal winter response to the Pinatubo and Krakatoa eruptions using large-ensemble single-forcing simulations
Abstract. The Northern Hemisphere wintertime circulation response to the eruptions of Krakatoa and Pinatubo is revisited in large ensembles from eight modeling centers with only one time-varying external forcing: volcanic eruptions. All eight models show a warming of the tropical lower stratosphere. In six of the models, the meridional temperature gradient in the winter stratosphere is enhanced, leading to a strengthened stratospheric polar vortex, a positive phase of the North Atlantic Oscillation, a poleward shift in storm tracks, and warm surface temperatures during the winter over subpolar Eurasia. While this warming over subpolar Eurasia is statistically significant in the multi-model mean and in four of the individual models, at least 34 eruptions are needed before it can be robustly distinguished from the global mean cooling with 5 % confidence. An El Niño response is evident shortly after eruption in these models, which transitions from a Central Pacific morphology in the first winter to an East Pacific morphology in the second, and subsequently to an La Niña response in the third and fourth winters. While these ENSO responses require 48 or more eruptions to emerge from the noise, they nonetheless lead to surface impacts over North America. However, these surface impacts do not resemble those classically associated with ENSO in the first year after eruption, likely because the tropical precipitation response differs as well due to the large-scale reduction in tropical precipitation. There is substantial diversity in the magnitude of these responses across models, likely owing to differences in tropical stratospheric diabatic heating despite the models using the same forcing.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-3738', Anonymous Referee #1, 11 Aug 2026
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RC2: 'Comment on egusphere-2026-3738', Anonymous Referee #2, 11 Sep 2026
Review of 'Isolating the boreal winter response to the Pinatubo and Krakatoa eruptions using large-ensemble single-forcing simulations' by Garfinkel, Avisar, Huo, Kuchar, Minobe, Osprey, Perny and Wright
Summary
The paper reports on 200 simulations from 8 climate models as part of LESFMIP. Specifically, these single forcing simulations look at the climate response only to historical volcanic eruptions. The authors examine 5-year NH winter climate responses to the 1883 Krakatau eruption and the 1991 Pinatubo eruption, both apparently of similar magnitude in terms of sulphur dioxide (SO2). They suggest that both runs highlight a forced response in the NAO to both eruptions, as well as in NINO4, However, the signals only emerge after 30-50 simulations are performed. Individual model differences are significant to my eye
Major comments
'1. 'sulfur burden…is similar for both eruptions…'. How true is this? Based on Arfuielle, it looks to me that P has a sulfur load of about 15 Tg and K of about 11 Tg… Similar-ish I suppose. The forcings in Aubry look a lot stronger for K.
In any case, you probably didn't use Aubry, as it was designed for CMIP7 and was presumably produced after the simulations used here were made (which are early 2020s?). So is the citation relevant? It doesn’t matter which you used, but you need to be clear in the paper which it was and interpret the results accordingly.
From the abstract of Aubry: '…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…'
From Arafuielle: 'For instance, the Krakatau eruption of 1883, previously thought to have released more SO2 than Pinatubo, is now downgraded to 2/3 of Pinatubo release by Gao et al. (2008).'
The Aubry paper has a peak optical depth of > 0.7 for Krakatoa and an optical depth of 0.2 for Pinatubo. They are not that different between the eruptions in the Arafuielle paper (and P is probably higher). This suggests a source of variability different from SO2/aerosol forcing to produce the modelled differences. Clarifying which forcing was used might help to understand the results.
In general, it may be useful to summarize important model considerations (like the SO2 forcing) in a table outside the text to highlight and summarize key components of the paper for easy reference.
2. Figure 9. I find this figure and discussion is not explained very well at all. What is begin measured here? Why are there only 200 members instead of 400? Are you measuring the long-term global response? Why the comparison between the long-term surface data and the models? Please clarify the meaning and interpretation of the figure.
3. Figure 10. a.) improve the figure by noting what each panel is referring to, e.g. a.) Eurasia, b.) Eurasia, global cooling removed, etc in the title of each panel
Figure 10. b) Doesn’t the relatively large number of simulations required to identify a particular response suggest that other factors beyond SO2 are playing a role. The eruption itself may somewhat force an NAO response 4-6 months later, but lots of other things happen due to internal variability to prevent or enhance these chances. It seems more complicated than simply saying tropical volcanic eruptions that reach the stratosphere with relatively high SO2 push a positive NAO response. Maybe it 'skews' the internal variability towards that state, but doesn’t guarantee it? More like 'biased internal variability' rather than a 'forced response'.
Minor comments
Fig 1. Legend text is a bit small at normal size for my eyes. Maybe just enlarge the figure a bit.
Line 101., What would happen if you just chose the same number of ensemble members for each model, and so didn't bias the result to particular models? About half the runs (40%) come from two models. Not saying this needs to be done, but I'm curious about what effect it would have on the results.
Line 109, 'Krakatoa has stronger impact…', that may be true (and figures suggest that), but why? It seems the response is not linearly related to the SO2 forcing. But it depends on which forcing was used for K.
Line 110, 2.5° horizontal grid. Can you summarize what the vertical resolution and domain in the stratosphere is in the different models? Presumably they are high-top models with 10-15 levels in strat, but can you specify in the paper? Perhaps a table…
Line 131, '…consistent with observations', Perhaps pedantic, but there were no stratospheric observations after Krakatoa, so you are tacitly assuming responses are the same. The findings here are not necessarily incorrect, but it is an assumption based on modelling and not observations.
Also Fig 1. Is the oscillating equatorial wind near 35 km a manifestation of the QBO? It seems a bit high altitude for QBO (more 25-30 km)… Is the QBO that present and consistent across the ensemble? Why no comments about it, I know it is not the focus of the paper, but it could be worthy of a general note…There appears to be some significance there, clearly in years 1,2 and 4.
Line 149. …'response is stronger', be specific about which response you are discussing (which is presumably the Scandinavian response...For example, the North American response is much cooler (i.e. stronger) during LN years and appears to remain so globally in the years following.
Line 150. Can you give the number of members in the EL Nino/La Nina groups? Are sample sizes even or strongly different?
Line 156. El Nino response is the consensus, but it is not uniform, even excluding paleo runs. Location of eruption (even in tropics), time of year, etc all appear to matter. See e.g. Pausata et al 2020 or Macgregor and Timmerman 2011.
Line 184. Is 'wettening' a real word?
Figure 6. HADGEM3, MPI and CMCC all produce very strong cooling responses over the pole, while the equatorial response between the models is less variable (but certainly not zero!)
Line 232. I suppose this is suggesting that the MIROC response is not just a model formulation issue, as it gives you the response you are expecting in some cases. Further, in some places it is written as MIROC6 and in others just MIROC. Choose one and be consistent.
Line 256. I find the section beginning here a bit cryptic. Are you really raising the number of samples from 1000 to 5000? Is it supposed to be 500? Is the selection random? Isn’t 400 the total of all members, so it isn’t really random in the last case? Later it says how many *months* must be selected? Please rewrite for clarity and to explain better.
I suppose you are taking 1000 random samples of 2 and seeing how often you get the response, 500 of 4, 333 of 6, etc and identifying when the spread of these samples no longer crosses zero.
Line 282, 'Primarily because ACCESS…', That's undoubtedly part of the reason, but the different models also simulate different amounts of activity in slightly different latitudes which creates a broader peak than most individual models shown. Further, the CMCC model response is just as much of an outlier (5x the mean!) as the ACCESS model, just in a different direction and possibly dominates the response even more so.
Line 290. I appreciate that it is probably 'beyond the scope of the paper', but why not discuss the SH response as well? From Fig 11, there is a clearly just as strong of SAM response around Antarctica (in years 1 and 2) as that in the NH. It's not the NH, but it is still a 'boreal winter' (aka DJF) response. You already discuss ENSO, why not more?
Line 291. '…no statistical significant response in the zonal mean'. I'm confused here, don’t the thick lines in Figure 11 clearly show a significant response in year 2 in both NH and SH?
Citation: https://doi.org/10.5194/egusphere-2026-3738-RC2
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It is generally believed that the "parasol effect" following volcanic eruptions causes cooling, thereby leading to short-term tropospheric cooling. However, this study, using ensemble data from numerical models, demonstrates that after the eruptions of Krakatoa and Pinatubo, the meridional temperature gradient in the winter stratosphere is enhanced, leading to a strengthened stratospheric polar vortex, a positive phase of the North Atlantic Oscillation, a poleward shift in storm tracks, and warm surface temperatures during winter over subpolar Eurasia. The analytical approach employs large ensemble simulations from eight climate models participating in the LESFMIP Project, with up to 200 ensemble members (equivalent to 400 independent samples) to investigate this issue. The statistical sample size far exceeds that of previous studies. The study quantitatively addresses the core question of "how many eruption events are needed for the signal to emerge from internal variability," and the conclusions are highly convincing. It also points out that the discrepancies in paleoclimate reconstructions are precisely due to insufficient sample sizes. The manuscript also presents the ENSO response to volcanic eruption events. Based on a large volume of data and employing statistical methods, the work complements our previous understanding with rigorous evidence and clear structure. Below are some questions regarding this manuscript.