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https://doi.org/10.5194/egusphere-2026-5104
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-5104
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
23 Sep 2026
| 23 Sep 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Modification of the Quasi-Biennial Oscillation by Stratospheric Water Vapor From the Hunga Tonga–Hunga Ha'apai Eruption
Abstract. The Hunga Tonga–Hunga Ha'apai (HTHH) undersea volcano injected approximately 0.5 Tg of sulfur dioxide (SO2) and about 150 Tg of water vapor (H2O) into the stratosphere. Using a combination of observations and model simulations, we investigate the response of the Quasi-Biennial Oscillation (QBO) to these stratospheric SO2 and H2O perturbations, as well as the dynamic mechanisms underlying the QBO modification. A portion of the sulfate aerosols and H2O remained in the tropical stratosphere for over a year. The water-rich HTHH eruption significantly influenced the QBO amplitude, with the simulated 30 hPa QBO index anomalies accounting for 11–32% of the anomalies observed in the 2022 reanalysis data. The combined effect of H2O and sulfate aerosols on stratospheric temperature is mainly concentrated in the tropical stratosphere (south of 15°N). H2O-induced radiative cooling reshapes the residual circulation and tropical upwelling response, reducing the upward advective tendency acting on positive zonal wind perturbations in key regions and favoring their downward propagation into the 30–100 hPa layer. This process effectively modulates the amplitude of the stratospheric QBO through the “upwelling mechanism”. Additionally, the cooling of the stratosphere caused by H2O and sulfate aerosols generates easterly and westerly wind shear through the “thermal wind balance mechanism” between April and October, further influencing the stratospheric QBO.
How to cite. Lu, J., Lou, S., Wang, W., Zhang, J., Ding, K., Huang, X., Jiang, Y., Liu, T., Liu, Y., Xie, Q., Xue, L., Wang, Z., Zhou, C., Zhu, A., and Ding, A.: Modification of the Quasi-Biennial Oscillation by Stratospheric Water Vapor From the Hunga Tonga–Hunga Ha'apai Eruption, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-5104, 2026.
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Jinpeng Lu
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
now at: Chengdu Vocational & Technical College of Industry, Chengdu 610218, China
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Wuke Wang
Department of Atmospheric Science, China University of Geosciences, Wuhan 430074, China
Jiankai Zhang
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Xin Huang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Yiquan Jiang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
China Meteorological Administration Key Laboratory for Climate Prediction Studies, Nanjing University, Nanjing 210023, China
Tengyu Liu
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Yawen Liu
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Qingyan Xie
Chengdu Research Institute of Education Science, Chengdu 610036, China
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Zilin Wang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Chen Zhou
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Anbao Zhu
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Aijun Ding
State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences (JirLATEST), Nanjing University, Nanjing 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Short summary
The 2022 Hunga Tonga eruption injected sulfur gases and massive water vapor into the stratosphere. With observations and simulations, we assessed effects on the tropical quasi-biennial oscillation (QBO). Pollutants lingered over a year; the water-rich eruption notably altered QBO winds. Cooling from excess vapor and particles, concentrated south of 15° N, reshaped upper circulation and drove downward wind anomalies modulating the QBO, with April–October 2022 cooling causing more wind shifts.
The 2022 Hunga Tonga eruption injected sulfur gases and massive water vapor into the...
This manuscript investigates how stratospheric water vapor and sulfate aerosols injected by the Hunga volcanic eruption alter the Quasi-Biennial Oscillation in the first year following eruption in a global climate model. The authors report a strengthening of QBO amplitude between April to October 2022, which is attributed to changes in the Brewer-Dobson circulation following the radiative cooling of the stratospheric water vapor anomaly as well as the temperature anomalies in the tropical stratosphere. Given the uniqueness of the Hunga eruption, it is interesting to study its potential impacts on atmospheric circulations. However, the analysis methods used here are not clearly documented and the interpretation may be misleading or mistaken. In addition, many of the results are already reported in previous publications. Therefore, I cannot recommend publication of this manuscript at ACP. Below are my detailed comments:
Major comments:
1. Previous literature. Simulating Hunga volcano’s impacts has been done in several previous studies and there is an APARC report published in 2025 summarizing the Hunga volcanic eruption’s atmospheric impacts. The stratospheric water vapor’s impacts on sulfate aerosols presented in section 3.1 are reported in Zhu et al. (2022). Hunga’s impacts on QBO have been discussed in Chapter 4 of the APARC report. Temperature, zonal wind and Brewer-Dobson circulation changes following Hunga eruption are discussed in Chapter 4 of the APARC report as well as Wang et al. (2023) and Yook et al. (2025). In particular, Wang et al. (2023) and Yook et al. (2025) utilized a similar model (WACCM) and simulation experiment setup as this study, but they found much less cooling in the tropical stratosphere from the volcano. The authors need to properly discuss these previous studies and show what is new in this study and why some of the results here are different from earlier ones despite similar model setup.
2. Definition of QBO amplitude. It seems the QBO amplitude is defined as the amplitude of equatorial zonal wind at 30 hPa at each month. Given the oscillating nature of the QBO, the wind speed at a fixed time is not a good representation of its amplitude, since a shifting in its phase would also alter wind speed at a fixed time. Typically, the QBO amplitude is defined as the maximum wind amplitude within a full QBO cycle (e.g., Bushell et al. 2020). Studies have also utilized EOF decomposition to define the amplitude and the phase of the QBO (e.g., Wallace et al. 1993). Reading from Fig. S5, it seems the volcanic impact on the QBO is mostly a faster transition in phase rather than increase in amplitude.
3. Definition of anomaly in ERA5 reanalysis. The authors constructed the anomaly by subtracting year 2022 from 2007-2021 climatology and further remove ENSO and background QBO using linear regression. It is not clear how the “background QBO” is defined? QBO is expected to vary from cycle to cycle without external forcing. I am not sure how the authors quantify the natural variability in QBO versus the potential volcanic impact on QBO. Also, how is the statistical significance estimated in Fig. 3a? I am surprised that most the anomalies are significant given the general large internal variability there.
4. Planetary waves. The authors showed “zonal mean planetary wave 1 and 2” in Fig. S7. The authors have not clearly stated how this is calculated, but it seems the authors are calculate harmonics in the latitudinal direction for the time mean zonal mean geopotential height. While planetary waves are of large scale in both latitudinal and longitudinal direction, the planetary wave 1 or 2 is typically referred to wavenumber in the longitudinal direction. The meridional wave number 1 and 2 shown in Fig. S7 are therefore irrelevant to the EP flux calculated using the deviations from zonal mean. Furthermore, the planetary waves propagating into the stratosphere consist of both stationary and transient components and thus looking at the time mean variables does not provide a full picture of changes in the planetary waves.
5. “Thermal wind balance mechanism”. The thermal wind balance is a general rule for all geostrophic flow. That is, the spatial distribution of zonal wind is always consistent with the spatial distribution of temperature. This does not guarantee a causal relationship between wind and temperature. Also, any other mechanisms altering the circulation (such as the upwelling mechanism) would change wind and temperature simultaneously to satisfy the thermal wind balance. The statement regarding the “combined effects of thermal wind balance and tropical upwelling changes” is therefore confusing. Perhaps what the authors referring to is a radiatively driven temperature anomaly pattern leads to changes in zonal wind. However, claiming that the temperature differences between the simulations are mostly radiatively driven lacks sufficient evidence.
6. Radiative heating rates. The authors only show the long wave heating rate difference between sim_SO2+H2O and sim_control, and only the shortwave component for SO2 perturbation. But it is known that sulfate aerosols alters both long wave and shortwave heating rates in the stratosphere (e.g., Ramachandran et al. 2000), so as water vapor. So what presented in the paper does not give a full picture of the radiative effects from the volcano eruption. Changes in long wave heating rate are especially a bad proxy for the radiative effect of water vapor, as changing temperature alone would alter the long wave heating rate.
Minor comment:
Line 25 and later in the main text: “the simulated .. anomalies accounting for 11-32% of the anomalies observed”. The model simulate a QBO of much weaker amplitude than observations (as shown in Fig. S1). Directly comparing changes in the simulated QBO versus the observation may be misleading.
Line 204: “5-100 hPa” Earlier in the text, it is stated that SO2 and H2O are injected at 20-30km. Which one is correct?
Fig. 2: The simulated AOD changes seem to be much weaker than observation. Does that imply that the model may underestimate the response to SO2?
Line 370-372: The sulfate aerosols not only scatter the shortwave radiation, but also absorb shortwave radiation, especially in the near-IR band. The shortwave heating rate changes due to sulfate aerosols shown in Fig. 7b, 7d, 7f are consistent with what is shown by Ramachandran et al. (2000) for visible band, but not consistent with their total shortwave response (visible plus nearIR).
Line 421-426: The similarity between the latitudinal distribution of the H2O or aerosol anomalies versus temperature anomalies does NOT provide “robust statistical support” for attributing the temperature changes to radiation. The radiative effect is often nonlinear, and the dynamical changes may co-locate with the radiative anomalies.
References:
APARC, 2025: The Hunga Volcanic Eruption Atmospheric Impacts Report. Yunqian Zhu, Graham Mann, Paul A. Newman, and William Randel (Eds.), APARC Report No. 11, WCRP-10/2025, doi: 10.34734/FZJ-2025-05237, available at www.aparc-climate.org/publications/
Bushell, A.C., Anstey, J.A., Butchart, N., Kawatani, Y., Osprey, S.M., Richter, J.H., Serva, F., Braesicke, P., Cagnazzo, C., Chen, C.-.-C., Chun, H.-.-Y., Garcia, R.R., Gray, L.J., Hamilton, K., Kerzenmacher, T., Kim, Y.-.-H., Lott, F., McLandress, C., Naoe, H., Scinocca, J., Smith, A.K., Stockdale, T.N., Versick, S., Watanabe, S., Yoshida, K. and Yukimoto, S. (2022), Evaluation of the Quasi-Biennial Oscillation in global climate models for the SPARC QBO-initiative. QJR Meteorol Soc, 148: 1459-1489. https://doi.org/10.1002/qj.3765
Ramachandran, S., V. Ramaswamy, G. L. Stenchikov, and A. Robock (2000), Radiative impact of the Mount Pinatubo volcanic eruption: Lower stratospheric response, J. Geophys. Res., 105(D19), 24409–24429, doi:10.1029/2000JD900355.
Wallace, J. M., R. L. Panetta and J. Estberg (1993). ‘Representation of the Equatorial Stratospheric QuasiBiennial Oscillation in EOF Phase Space’. J. Atmos. Sci., 50, pp. 1751–1762. doi: 10.1175/1520-0469 (1993)050<1751:ROTESQ>2.0.CO;2.
Wang, X., Randel, W., Zhu, Y., Tilmes, S., Starr, J., Yu, W., et al. (2023). Stratospheric climate anomalies and ozone loss caused by the Hunga Tonga-Hunga Ha'apai volcanic eruption. Journal of Geophysical Research: Atmospheres, 128, e2023JD039480. https://doi.org/10.1029/2023JD039480
Yook, S., Solomon, S., & Wang, X. (2025). The impact of 2022 hunga tonga-hunga ha'apai (hunga) eruption on stratospheric circulation and climate. Journal of Geophysical Research: Atmospheres, 130, e2024JD042943. https://doi.org/10.1029/2024JD042943
Zhu, Y., Bardeen, C.G., Tilmes, S. et al. Perturbations in stratospheric aerosol evolution due to the water-rich plume of the 2022 Hunga-Tonga eruption. Commun Earth Environ 3, 248 (2022). https://doi.org/10.1038/s43247-022-00580-w