Quasi-Biennial Oscillation Modulation of the Semi-Annual Oscillation in QBOi Models

M. Jaison, Aleena; Gray, Lesley J.; Osprey, Scott M.; Anstey, James A.; Andrews, Martin B.; Butchart, Neal; Chai, Zhaoyang; Hong, Dong-Chan; Huang, Kai; Kawatani, Yoshio; Knight, Jeff R.; Lin, Pu; Lott, Francois; Lu, Yixiong; Naoe, Hiroaki; Richter, Jadwiga H.; Rosenbloom, Nan; Serva, Federico; Smith, Anne K.; Son, Seok-Woo; Tang, Qi; Watanabe, Shingo; Xie, Jinbo; Yoshida, Kohei

doi:10.5194/egusphere-2026-4135

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https://doi.org/10.5194/egusphere-2026-4135

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22 Jul 2026

| 22 Jul 2026

Status: this preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).

Quasi-Biennial Oscillation Modulation of the Semi-Annual Oscillation in QBOi Models

Aleena M. Jaison, Lesley J. Gray, Scott M. Osprey, James A. Anstey, Martin B. Andrews, Neal Butchart, Zhaoyang Chai, Dong-Chan Hong, Kai Huang, Yoshio Kawatani, Jeff R. Knight, Pu Lin, Francois Lott, Yixiong Lu, Hiroaki Naoe, Jadwiga H. Richter, Nan Rosenbloom, Federico Serva, Anne K. Smith, Seok-Woo Son, Qi Tang, Shingo Watanabe, Jinbo Xie, and Kohei Yoshida

Abstract. As part of the Quasi-Biennial Oscillation initiative (QBOi) phase 1, a model-intercomparison study explored the representation of the semi-annual oscillation (SAO) in participating models and found a common easterly bias of several tens of m/s compared to observations, mostly with weaker westerly phases and stronger easterly phases. QBOi phase 1 results also reported biases in model representations of the QBO, which dominates the region below the SAO, with most models displaying a westerly time mean wind bias, and generally weaker QBO easterly phases. Given that the SAO forcing terms can be influenced by the QBO, in this paper we explore the influence of these QBO biases on the representation of the SAO. A multi-model analysis is conducted here using QBOi phase 2 data from current state-of-the-art climate models to examine changes in representation of the SAO in response to corrections in zonal-mean zonal wind QBO biases. Most models show an improvement with a reduced easterly SAO bias in response to the corrected QBO bias. The extent of this response is found to vary significantly across models with SAO time-mean winds changing by 6 % to 403 % in simulations with a bias-corrected QBO relative to the control simulations. Changed gravity wave drag in response to the improved QBO is attributed as the forcing term having the largest overall impact.

How to cite. M. Jaison, A., Gray, L. J., Osprey, S. M., Anstey, J. A., Andrews, M. B., Butchart, N., Chai, Z., Hong, D.-C., Huang, K., Kawatani, Y., Knight, J. R., Lin, P., Lott, F., Lu, Y., Naoe, H., Richter, J. H., Rosenbloom, N., Serva, F., Smith, A. K., Son, S.-W., Tang, Q., Watanabe, S., Xie, J., and Yoshida, K.: Quasi-Biennial Oscillation Modulation of the Semi-Annual Oscillation in QBOi Models, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-4135, 2026.

Received: 10 Jul 2026 – Discussion started: 22 Jul 2026

Competing interests: JA serves as co-editor for the special issue to which this paper belongs. The remaining authors declare that they have no conflict of interest.

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.

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RC1:
'Comment on egusphere-2026-4135', MATTHEW HITCHMAN, 19 Aug 2026 reply
This paper describes the effects of zonal wind nudging of the QBO on the amplitude and phase of the SAO (QBOi phase 2) in ~10 numerical models. It shows that models with better gravity wave drag parameterizations, higher model tops, and perhaps less diffusion near the model top can be more readily improved by QBO nudging, with regard to fidelity in representing the SAO. In the abstract it is stated that most models show an improvement with a reduced easterly SAO bias in response to the corrected QBO bias and that changed gravity wave drag in response to the improved QBO is attributed as the forcing term having the largest overall impact, which is parameterized unresolved gravity wave drag. This paper functions well as a medium of exchange of information for the community and it is useful and clear. It shows that gravity wave drag is of primary importance in explaining their results, but does not elaborate on the mechanism. I recommend that the authors include a description of what they think is happening in the models with regard to changes in gravity wave drag and recommend minor revision.

The primary conclusion in the abstract, restated on lines 109-110 and elsewhere, is robust, but the paper does not say much more about any physical process. I encourage the authors to provide a description of how the gravity wave filtering works, with regard to stating what happens to westward travelling waves and to eastward travelling waves for changes in a given wind layer imposed by the nudging. What are the gravity wave parameterizations used? Which models try to represent deep convective gravity waves from first principles? What are the ways that parameterized gravity waves can be absorbed in these models, going upward into the mesosphere, where both shear and reduced density can cause them to break?

l2-22: It would be helpful to briefly characterize vertical resolutions in the QBO and SAO layers. Does vertical resolution matter for parameterized gravity wave drag?

l148-149 and elsewhere: This is an important issue. I suggest that you describe a bit more about the upper layer in the models. Which models use Rayleigh friction? In your model standard, HadGEM3, what is the damping/numerical diffusion profile into the mesosphere?

l164 – I agree that nudging zonal wind is the right way to do it, in order to have the right relationship between temperature anomaly and vertical motion for a wave-driven MMC (e.g., downward / warm). If some models nudged temperature, then in the conclusions you could suggest more strongly that this might be a major reason why their results weren't as hoped. Vertical motion would be upward in an imposed warm anomaly in QBO W shear in a model with a radiative code, which is opposite to our understanding.

l180-190: You could introduce the idea here that another significant metric for evaluating model processes could be the difference in amplitude between the first and second phases of the SAO in each year. The reason that I mention this is that your definition of SAO blends both the first and second together. You could have a mean and a difference "PC" to intercompare models.

l215-220 - It may also be the case that vertical wind structure near 10 hPa is more important than near 50 hPa for filtering gravity waves, which might affect the more immediately-adjacent SAO layer more readily. But maybe that is not true. What do you think?

l245: You effectively treat HadGEM3 as the reference model in section 3.1, which seems fine. Do you think that the property of a higher model top is the primary reason? Suggest describe the damping properties of HadGEM3 in the upper layers a bit more.

l296-301 – In light of this discussion, what does this imply about the vertical profile of gravity wave drag? Perhaps add the thread of how it is that the models err here, which can be elaborated on in the conclusions?

Are there any models that represent the seasonal variation in deep convective gravity wave driving? If the greatest tropical deep convection occurs in DJFM, then a model which can represent that might be expected do better at the 1st v 2nd phase SAO amplitude asymmetry.

l357-358: The time mean vertical profile and how it is maintained is important. You could comment on quantification of GWD among models for the annual budget. It would give further useful information about GW behavior in the models.

l495-497: How are the gravity wave momentum fluxes for westerly and easterly gravity waves affected in each layer due to improving the QBO wind structure?

l505: Figure 8d shows the influence of the SAO on the QBO down to 50 hPa, due to the MMCs associated with the SAO. I think this is similar to what was shown by Coy (circa 1990).

l511-512: Please describe for the reader what this statement implies about what is missing in the models re GWD.

I notice that in this paper tropical GWD is deemed important for the westerly SAO phase, but I think it is also important for the easterly phase. The cross-equatorial flow is primarily a gravity-wave driven flow, a response to the large winter and summer gravity wave drag patterns. As air travels meridionally through the tropics it is exposed to a lot of deep convective gravity wave drag. In addition to GWD driving the pole to pole circulation during the SAO easterly phase, gravity wave drag integrated along the pathway from one hemisphere to the other also helps to explain why a maximum in easterly wind does not occur right at the equator, which would occur in inviscid flow starting with zero zonal velocity at a pole. Tropical westerly GWD, in addition to treatment of inertial instability parameterization in models on the winter subtropical side, can help to limit easterly advection.

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Short summary

The tropical upper stratosphere has winds that switch between westerly and easterly every six months known as the semi-annual oscillation (SAO). Climate models commonly show an easterly bias in the SAO. We analysed data from many models to test if correcting the biases in winds lower in the stratosphere could improve SAO. We find correcting the lower-level wind biases reduces the SAO easterly bias, though further improvements, such as better representation of atmospheric waves, are still needed.


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