the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Aerosol dynamic processes in the Hunga plume in January 2022: Does water vapor accelerate aerosol aging?
Abstract. The 2022 Hunga eruption injected an unprecedented amount of 150 Tg of water vapor into the stratosphere, accelerating SO2 oxidation and sulfate aerosol formation. Despite releasing less ash than previous eruptions of similar magnitude, the role of ash in the early plume and its rapid removal remains unclear. We performed experiments with the ICOsahedral Nonhydrostatic model with Aerosols and Reactive Tracers (ICON-ART) to better understand the role of water vapor, SO2 and ash emission, aerosol-radiation interaction, and aerosol dynamical processes (nucleation, condensation, coagulation) in the Hunga plume in the first week after the eruption. Furthermore, we compared our results to satellite observations to validate SO2 oxidation and aerosol dynamical processes. Our results show that about 1.2 Tg SO2 emission as well as water vapor emission is necessary to explain both the SO2 column loadings and sulfate aerosol optical depth during the first week after the eruption. Although the model reproduces well the development of SO2 and sulfate aerosols, the aerosol dynamics alone cannot explain the ash removal after the eruption, as was seen in satellite images. However, some of the ash might not be detected because of the exceptionally strong coating of the ash particles. Both, the strong coating and a doubling of the sulfate effective radii within one week, occur only when the water vapor emission is considered in the chemistry. Furthermore, aerosol-radiation interaction warms the plume and reduces or, depending on the experiments, even reverses the descent of the water vapor plume due to radiative cooling.
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RC1: 'Comment on egusphere-2024-4062', Anonymous Referee #1, 20 Feb 2025
I don’t find this paper particularly interesting. It is long and detailed, with multiple small panels in each figure. The results either confirm what we already knew or failed to explain observations. The climate model setup is lacking in many details, and there is no explanation of why ensembles were not used and the statistical significance of the results.
There are various small English errors in the text. I corrected some of them, but the native-English-speaker author should have edited the paper for English grammar and usage, so as to not annoy the reviewers. And multiple acronyms were defined and never used again. Multiple acronyms were used without defining them.
I find the initial conditions used for the experiment very confusing. I don’t understand “about 500 Tg solid and less than 50 Tg liquid hydrometeors enter the stratosphere.” Is solid ice? Are there any observations of this? Where do the numbers come from. And how do the authors know how much water was injected at the surface? There are no observations of this. Are the numbers in Table 1 based on observations? How can the MER of water vapor be calculated from the model without data on how much water there was? How can this model result be validated? I find the presentation of the experiment circular. What were the observed model inputs and what were the model results? How were the model results evaluated with separate observations?
I also don’t understand what FPlume is and how it is coupled to the climate model.
And why was that particular climate model used?
Section 2.2 is missing details about the model runs. How long were the model runs? How many ensemble members did each experiment have? On what date and time were the simulations initialized? What did you do about the ocean? How was the climate model initialized as to land state and ocean state?
The term “validation” is used multiple times, when I think it is more correct to use “evaluation.” Validation is only correct if you are sure a priori that the results are correct, and you are trying to prove that.
You need to include this paper in your reference list and address what it has already shown:
Ukhov, A., Stenchikov, G., Osipov, S., Krotkov, N., Gorkavyi, N., Li, C., et al. (2023). Inverse modeling of the initial stage of the 1991 Pinatubo volcanic cloud accounting for radiative feedback of volcanic ash. Journal of Geophysical Research: Atmospheres, 128, e2022JD038446. https://doi.org/10.1029/2022JD038446
You should also consider this paper, although to my knowledge it has not been accepted for publication yet:
Georgiy Stenchikov, Alexander Ukhov, Sergey Osipov. Modeling the Direct Radiative Forcing and Climate Impacts of the 2022 Hunga Volcano Explosion. ESS Open Archive. July 11, 2024. DOI:10.22541/essoar.172070583.36131358/v1
And please address the 51 comments in the attached annotated manuscript.
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RC2: 'Comment on egusphere-2024-4062', Georgiy Stenchikov, 24 Feb 2025
General concerns:
This paper uses the novel ICON-ART modeling system to examine the initial one-week evolution of water vapor (WV), SO₂, SO₄, and ash plumes following the 2022 Hunga eruption. The authors implement volcanic plume initiation through the 1-D plume rise model, FPlume, which is tuned to match observed injection altitudes. This approach introduces an innovative method for representing volcanic injections in the model. Additionally, the study includes ash emissions, investigates ash-sulfate interactions, and compares results with CALIOP, OMPS, and IMS/IASI observations.
The simulations suggest that a 1.2 Tg SO₂ emission aligns more closely with observed plume characteristics than the 0.4 Tg estimate based on OMI/OMPS data. The findings also indicate that ash influences the plume's descent trajectory and that WV is critical in accelerating SO₂-to-SO₄ conversion. While some of these conclusions have been reported in previous studies, using a newly developed modeling system provides a fresh perspective. However, the presentation could be more focused.
Using a 1-D plume model for injecting volcanic materials is interesting but requires better documentation. At a minimum, the vertical distribution of injected materials should be discussed. Most WV is likely released in the form of solid hydrometeors (ice, snow, and graupel), but this is not explicitly stated. The energy required for melting or sublimation could influence atmospheric cooling, distinguishing this study from others—an aspect worth highlighting.
The simulation duration is notably short. Is there a specific reason for this limitation? Extending the simulations to at least a couple of months would enable a more robust comparison with observations. Furthermore, the initial ash amount and size distribution appear arbitrary, and the study does not clearly demonstrate ash's significance in improving observational agreement.
The description of the radiative transfer model is missing. Including stratospheric aerosol optical depth (SAOD) would be beneficial, as it is one of the best-constrained observational metrics. Addressing these concerns will strengthen the study and improve its readiness for publication.
Specific concerns:
L23: “dynamical” > “microphysical”
L80: Are these two emissions on January 15?
L136: uptake by sulfate or by ash?
L152: Is it a restriction?
L161-165: When did you start the run from initial conditions?
L171: Is it evenly distributed in number-density or volume? I doubt ash is evenly distributed.
L191-195: OMPS does not see the initial stage well because of insufficient sampling.
L276-279: What was the vertical distribution of volcanic debris soon after the injection?
Figure 4: No-ash experiment produces the most realistic results.
L341: Do you mean sulfate particles? 70% of sulfate absorption is coming from LW. WV cooling is the most important.
Subsection 4 should be first in the results section.
Figure 5: Explain how the amplitude, structure, and location factors are computed.
L403: Or you injected too much ash.
Section 5: Do you have background aerosols before the eruption?
L413: Use radius; do not switch to diameter in some places.
L415-420: Please be specific. Is it an effective radius or median radius makes a difference? I do not believe in these very big radii. It is not consistent radiatively. The mass of aerosol will be exaggerated. The lifetime will be shorter than it is observed. For example, Boichu et al. (2023) measure Hunga's size distribution through AERONET through the entire depth of the atmosphere. They could detect large cloud particles.
Figure 8 is difficult to read. What are the isolines for?
L435: How much sulfate is on the ash?
Citation: https://doi.org/10.5194/egusphere-2024-4062-RC2
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