Articles | Volume 26, issue 19
https://doi.org/10.5194/acp-26-14403-2026
© 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/acp-26-14403-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The role of the QBO for tropical high-cloud variability in CMIP6 models and observations
Aleena M. Jaison
CORRESPONDING AUTHOR
Department of Physics, Imperial College London, London, United Kingdom
Paulo Ceppi
Department of Physics, Imperial College London, London, United Kingdom
Sarah Wilson Kemsley
School of Geography and the Environment, University of Oxford, Oxford, United Kingdom
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Martin B. Andrews, Neal Butchart, James A. Anstey, Ewa Bednarz, Dillon Elsbury, Jorge L. García-Franco, Vinay Kumar, Froila M. Palmeiro, Natasha E. Trencham, Kohei Yoshida, Zhaoyang Chai, Dong-Chan Hong, Kai Huang, Aleena M. Jaison, Yoshio Kawatani, Jeff R. Knight, Pu Lin, François Lott, Yixiong Lu, Hiroaki Naoe, Scott M. Osprey, Jadwiga H. Richter, Federico Serva, Seok-Woo Son, Qi Tang, Shingo Watanabe, and Jinbo Xie
Weather Clim. Dynam., 7, 1797–1820, https://doi.org/10.5194/wcd-7-1797-2026, https://doi.org/10.5194/wcd-7-1797-2026, 2026
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The observed winds in the upper atmosphere over the equator have alternating easterly and westerly regions that descend towards the lower atmosphere before dissipating, with a period of approximately 28 months. This is known as the Quasi-Biennial Oscillation (QBO). The QBO is known to influence remote regions of the atmosphere. This paper details the results of multi-model experiments where the QBO is nudged towards the observed QBO allowing the assessment of these remote connections.
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
EGUsphere, https://doi.org/10.5194/egusphere-2026-4135, https://doi.org/10.5194/egusphere-2026-4135, 2026
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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.
Kai Huang, Chang-Hyun Park, Seung-Yoon Back, Jorge L. García-Franco, Hera Kim, Pu Lin, Scott Osprey, Jadwiga Richter, Chih-Chieh Chen, Seok-Woo Son, Shigeo Yoden, Yuna Lim, Neal Butchart, James Anstey, Yoshio Kawatani, Martin B. Andrews, Francois Lott, Yixiong Lu, Zhaoyang Chai, Nan Rosenbloom, Qi Tang, Jinbo Xie, Federico Serva, Dong-Chan Hong, Shingo Watanabe, Aleena M. Jaison, Hiroaki Naoe, and Kohei Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2026-3744, https://doi.org/10.5194/egusphere-2026-3744, 2026
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The tropical atmosphere has large-scale wind and rainfall patterns shaping weather worldwide. Winds high above the tropics are thought to influence a major tropical rainfall system, but climate models fail to reproduce this link. We tested 12 climate models after constraining their high-altitude winds to match observations. Although the winds then matched, the models failed to capture the tropical response, as they did not realistically simulate it. Improving this is key to better prediction.
Hyun-Kyu Lee, James A. Anstey, Hye-Yeong Chun, Shingo Watanabe, Francois Lott, Zhaoyang Chai, Yixiong Lu, Qi Tang, Jinbo Xie, Dong-Chan Hong, Seok-Woo Son, Federico Serva, Pu Lin, Martin B. Andrews, Neal Butchart, Aleena M. Jaison, Jeff R. Knight, Scott Osprey, Hiroaki Naoe, Kohei Yoshida, Yoshio Kawatani, and Jadwiga H. Richter
EGUsphere, https://doi.org/10.5194/egusphere-2026-2856, https://doi.org/10.5194/egusphere-2026-2856, 2026
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This study investigates the systematic biases in equatorial wave forcing of the quasi-biennial oscillation (QBO) by comparing internally generated and bias-corrected experiments using a multi-model ensemble. Although nudging effectively mitigates QBO biases, systematic biases in wave forcing are not fully resolved. The equatorial wave forcing in the lower stratosphere remains weaker than that in reanalyses, while an eastward wave forcing bias is observed in the mid-to-upper stratosphere.
James A. Anstey, Neal Butchart, Scott Osprey, Yoshio Kawatani, Kevin Hamilton, Jadwiga H. Richter, Tim Stockdale, Martin B. Andrews, Zhaoyang Chai, Paolo Davini, Dong-Chan Hong, Kai Huang, Aleena M. Jaison, Tobias Kerzenmacher, Jeff R. Knight, Pu Lin, Francois Lott, Yixiong Lu, Hiroaki Naoe, Federico Serva, Isla Simpson, Seok-Woo Son, Qi Tang, Shingo Watanabe, Jinbo Xie, and Kohei Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2026-1165, https://doi.org/10.5194/egusphere-2026-1165, 2026
Short summary
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We describe experiments where modelled tropical stratosphere winds are adjusted by "nudging" them toward realistic time-evolving eastward and westward Quasi-Biennial Oscillation (QBO) winds. The effects of this bias correction on other atmospheric processes, such as the stratospheric polar vortex or tropical waves that force the QBO, can then be assessed. We describe details of the experiments, the multi-model ensemble that has performed them, and basic validation of the nudging response.
Aleena M. Jaison, Lesley J. Gray, Scott M. Osprey, Jeff R. Knight, and Martin B. Andrews
Weather Clim. Dynam., 5, 1489–1504, https://doi.org/10.5194/wcd-5-1489-2024, https://doi.org/10.5194/wcd-5-1489-2024, 2024
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Models have biases in semi-annual oscillation (SAO) representation, mainly due to insufficient eastward wave forcing. We examined if the bias is from increased wave absorption due to circulation biases in the low–middle stratosphere. Alleviating biases at lower altitudes improves the SAO, but substantial bias remains. Alternative methods like gravity wave parameterization changes should be explored to enhance the modelled SAO, potentially improving sudden stratospheric warming predictability.
Paulo Ceppi, Alejandro Bodas-Salcedo, Mark D. Zelinka, Timothy Andrews, Florent Brient, Robin Chadwick, An-Zhuo Dai, Jonathan M. Gregory, Yen-Ting Hwang, Sarah M. Kang, Jennifer E. Kay, Thorsten Mauritsen, Tomoo Ogura, George Tselioudis, Masahiro Watanabe, Mark J. Webb, and Allison A. Wing
Geosci. Model Dev., 19, 8693–8708, https://doi.org/10.5194/gmd-19-8693-2026, https://doi.org/10.5194/gmd-19-8693-2026, 2026
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Clouds constitute a key uncertainty for climate change projections. The Cloud Feedback Model Intercomparison Project (CFMIP) aims to address this challenge by evaluating and understanding clouds and their impacts on atmospheric circulation, precipitation, and climate sensitivity. The present paper describes the CFMIP experiment protocol for the Coupled Model Intercomparison Project phase 7 (CMIP7), and discusses the accompanying science questions and opportunities for progress.
Martin B. Andrews, Neal Butchart, James A. Anstey, Ewa Bednarz, Dillon Elsbury, Jorge L. García-Franco, Vinay Kumar, Froila M. Palmeiro, Natasha E. Trencham, Kohei Yoshida, Zhaoyang Chai, Dong-Chan Hong, Kai Huang, Aleena M. Jaison, Yoshio Kawatani, Jeff R. Knight, Pu Lin, François Lott, Yixiong Lu, Hiroaki Naoe, Scott M. Osprey, Jadwiga H. Richter, Federico Serva, Seok-Woo Son, Qi Tang, Shingo Watanabe, and Jinbo Xie
Weather Clim. Dynam., 7, 1797–1820, https://doi.org/10.5194/wcd-7-1797-2026, https://doi.org/10.5194/wcd-7-1797-2026, 2026
Short summary
Short summary
The observed winds in the upper atmosphere over the equator have alternating easterly and westerly regions that descend towards the lower atmosphere before dissipating, with a period of approximately 28 months. This is known as the Quasi-Biennial Oscillation (QBO). The QBO is known to influence remote regions of the atmosphere. This paper details the results of multi-model experiments where the QBO is nudged towards the observed QBO allowing the assessment of these remote connections.
Abel Shibu, Henrik Auestad, Paulo Ceppi, and Tim Woollings
EGUsphere, https://doi.org/10.5194/egusphere-2026-4895, https://doi.org/10.5194/egusphere-2026-4895, 2026
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We estimate the contributions from various processes to the strength of extratropical cyclones using a novel framework applied to cyclones tracked in climate model data. Diabatic processes increase in importance with cyclone strength and account for most of the strength of the strongest storms in both summer and winter. In a warmer climate with increased moisture availability, winter storms show a significant increase in strength, with implications for future weather extremes.
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
EGUsphere, https://doi.org/10.5194/egusphere-2026-4135, https://doi.org/10.5194/egusphere-2026-4135, 2026
Short summary
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.
Kai Huang, Chang-Hyun Park, Seung-Yoon Back, Jorge L. García-Franco, Hera Kim, Pu Lin, Scott Osprey, Jadwiga Richter, Chih-Chieh Chen, Seok-Woo Son, Shigeo Yoden, Yuna Lim, Neal Butchart, James Anstey, Yoshio Kawatani, Martin B. Andrews, Francois Lott, Yixiong Lu, Zhaoyang Chai, Nan Rosenbloom, Qi Tang, Jinbo Xie, Federico Serva, Dong-Chan Hong, Shingo Watanabe, Aleena M. Jaison, Hiroaki Naoe, and Kohei Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2026-3744, https://doi.org/10.5194/egusphere-2026-3744, 2026
Short summary
Short summary
The tropical atmosphere has large-scale wind and rainfall patterns shaping weather worldwide. Winds high above the tropics are thought to influence a major tropical rainfall system, but climate models fail to reproduce this link. We tested 12 climate models after constraining their high-altitude winds to match observations. Although the winds then matched, the models failed to capture the tropical response, as they did not realistically simulate it. Improving this is key to better prediction.
Omer Roi-Cohen, Gaea Hadary, Casey J. Wall, Paulo Ceppi, and Guy Dagan
EGUsphere, https://doi.org/10.5194/egusphere-2026-3075, https://doi.org/10.5194/egusphere-2026-3075, 2026
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When humans burn fossil fuels, released particles make clouds more reflective, cooling Earth. This effect is a major uncertainty in climate projections, and recent satellite studies disagree widely on its magnitude. We developed a framework, validated against models and observations, to test which analytical choices are most reliable. Our resulting estimate aligns with major international climate assessments, providing independent observational support for consensus climate projections.
Hyun-Kyu Lee, James A. Anstey, Hye-Yeong Chun, Shingo Watanabe, Francois Lott, Zhaoyang Chai, Yixiong Lu, Qi Tang, Jinbo Xie, Dong-Chan Hong, Seok-Woo Son, Federico Serva, Pu Lin, Martin B. Andrews, Neal Butchart, Aleena M. Jaison, Jeff R. Knight, Scott Osprey, Hiroaki Naoe, Kohei Yoshida, Yoshio Kawatani, and Jadwiga H. Richter
EGUsphere, https://doi.org/10.5194/egusphere-2026-2856, https://doi.org/10.5194/egusphere-2026-2856, 2026
Short summary
Short summary
This study investigates the systematic biases in equatorial wave forcing of the quasi-biennial oscillation (QBO) by comparing internally generated and bias-corrected experiments using a multi-model ensemble. Although nudging effectively mitigates QBO biases, systematic biases in wave forcing are not fully resolved. The equatorial wave forcing in the lower stratosphere remains weaker than that in reanalyses, while an eastward wave forcing bias is observed in the mid-to-upper stratosphere.
James A. Anstey, Neal Butchart, Scott Osprey, Yoshio Kawatani, Kevin Hamilton, Jadwiga H. Richter, Tim Stockdale, Martin B. Andrews, Zhaoyang Chai, Paolo Davini, Dong-Chan Hong, Kai Huang, Aleena M. Jaison, Tobias Kerzenmacher, Jeff R. Knight, Pu Lin, Francois Lott, Yixiong Lu, Hiroaki Naoe, Federico Serva, Isla Simpson, Seok-Woo Son, Qi Tang, Shingo Watanabe, Jinbo Xie, and Kohei Yoshida
EGUsphere, https://doi.org/10.5194/egusphere-2026-1165, https://doi.org/10.5194/egusphere-2026-1165, 2026
Short summary
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We describe experiments where modelled tropical stratosphere winds are adjusted by "nudging" them toward realistic time-evolving eastward and westward Quasi-Biennial Oscillation (QBO) winds. The effects of this bias correction on other atmospheric processes, such as the stratospheric polar vortex or tropical waves that force the QBO, can then be assessed. We describe details of the experiments, the multi-model ensemble that has performed them, and basic validation of the nudging response.
Paulo Ceppi, Sarah Wilson Kemsley, Hendrik Andersen, Timothy Andrews, Ryan J. Kramer, Peer Nowack, Casey J. Wall, and Mark D. Zelinka
Atmos. Chem. Phys., 26, 4153–4171, https://doi.org/10.5194/acp-26-4153-2026, https://doi.org/10.5194/acp-26-4153-2026, 2026
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Recent decades have seen a marked decrease in global low-level cloud cover, leading to more sunlight heating the Earth. This trend is poorly understood, raising the concern that clouds may amplify global warming more than previously thought. We show that the cloud decrease is mostly caused by human forcing on climate, and that it agrees with previous estimates of how clouds respond to decreasing aerosol pollution, increasing greenhouse gas concentration, and their effects on global temperature.
Richard G. Williams, Philip Goodwin, Paulo Ceppi, Chris D. Jones, and Andrew H. MacDougall
Biogeosciences, 22, 7167–7186, https://doi.org/10.5194/bg-22-7167-2025, https://doi.org/10.5194/bg-22-7167-2025, 2025
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How the climate system responds when carbon emissions cease is an open question: some climate models reveal a slight warming, whereas most models reveal a slight cooling. The temperature response after net zero is connected via a new framework to quantify and compare the opposing thermal and carbon drivers. The climate response after net zero is controlled by how the planet takes up heat and radiates heat back to space, and how the land and ocean sequester carbon from the atmosphere.
Philipp Breul, Paulo Ceppi, and Peer Nowack
Atmos. Chem. Phys., 25, 11991–12005, https://doi.org/10.5194/acp-25-11991-2025, https://doi.org/10.5194/acp-25-11991-2025, 2025
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We explore how Pacific low-level clouds influence projections of regional climate change by adjusting a climate model to enhance low-cloud response to surface temperatures. We find significant changes in projected warming patterns and circulation changes under increased CO2 conditions. Our findings are supported by similar relationships across state-of-the-art climate models. These results highlight the importance of accurately representing clouds for predicting regional climate change impacts.
Aleena M. Jaison, Lesley J. Gray, Scott M. Osprey, Jeff R. Knight, and Martin B. Andrews
Weather Clim. Dynam., 5, 1489–1504, https://doi.org/10.5194/wcd-5-1489-2024, https://doi.org/10.5194/wcd-5-1489-2024, 2024
Short summary
Short summary
Models have biases in semi-annual oscillation (SAO) representation, mainly due to insufficient eastward wave forcing. We examined if the bias is from increased wave absorption due to circulation biases in the low–middle stratosphere. Alleviating biases at lower altitudes improves the SAO, but substantial bias remains. Alternative methods like gravity wave parameterization changes should be explored to enhance the modelled SAO, potentially improving sudden stratospheric warming predictability.
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 5, 1269–1286, https://doi.org/10.5194/wcd-5-1269-2024, https://doi.org/10.5194/wcd-5-1269-2024, 2024
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Latent heating due to condensation can influence atmospheric circulation by strengthening or weakening horizontal temperature contrasts. Strong temperature contrasts intensify storms and imply the existence of strong upper tropospheric winds called jets. It remains unclear whether latent heating preferentially reinforces or abates the existing jet. We show that this disagreement is attributable to how the jet is defined, confirming that latent heating reinforces the jet.
Sarah Wilson Kemsley, Paulo Ceppi, Hendrik Andersen, Jan Cermak, Philip Stier, and Peer Nowack
Atmos. Chem. Phys., 24, 8295–8316, https://doi.org/10.5194/acp-24-8295-2024, https://doi.org/10.5194/acp-24-8295-2024, 2024
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Aiming to inform parameter selection for future observational constraint analyses, we incorporate five candidate meteorological drivers specifically targeting high clouds into a cloud controlling factor framework within a range of spatial domain sizes. We find a discrepancy between optimal domain size for predicting locally and globally aggregated cloud radiative anomalies and identify upper-tropospheric static stability as an important high-cloud controlling factor.
Philip Goodwin, Richard Williams, Paulo Ceppi, and B. B. Cael
EGUsphere, https://doi.org/10.5194/egusphere-2023-2307, https://doi.org/10.5194/egusphere-2023-2307, 2023
Preprint archived
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Climate feedbacks are normally evaluated by considering the change over time for Earth's energy balance and surface temperatures in the climate system. However, we only have around 1 degree Celsius of temperature change to utilise. Here, climate feedbacks are instead evaluated from the change in latitude of Earth's energy balance and surface temperatures, where we have around 70 degrees Celsius of temperature change to utilise.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
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This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Philipp Breul, Paulo Ceppi, and Theodore G. Shepherd
Weather Clim. Dynam., 4, 39–47, https://doi.org/10.5194/wcd-4-39-2023, https://doi.org/10.5194/wcd-4-39-2023, 2023
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Accurately predicting the response of the midlatitude jet stream to climate change is very important, but models show a variety of possible scenarios. Previous work identified a relationship between climatological jet latitude and future jet shift in the southern hemispheric winter. We show that the relationship does not hold in separate sectors and propose that zonal asymmetries are the ultimate cause in the zonal mean. This questions the usefulness of the relationship.
Philipp Breul, Paulo Ceppi, and Theodore G. Shepherd
Weather Clim. Dynam., 3, 645–658, https://doi.org/10.5194/wcd-3-645-2022, https://doi.org/10.5194/wcd-3-645-2022, 2022
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Understanding how the mid-latitude jet stream will respond to a changing climate is highly important. Unfortunately, climate models predict a wide variety of possible responses. Theoretical frameworks can link an internal jet variability timescale to its response. However, we show that stratospheric influence approximately doubles the internal timescale, inflating predicted responses. We demonstrate an approach to account for the stratospheric influence and recover correct response predictions.
Cited articles
Baldwin, M. P., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P. H., Randel, W. J., Holton, J. R., Alexander, M. J., Hirota, I., Horinouchi, T., Jones, D. B. A., Kinnersley, J. S., Marquardt, C., Sato, K., and Takahashi, M.: The quasi-biennial oscillation, Rev. Geophys., 39, 179–229, https://doi.org/10.1029/1999RG000073, 2001.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., and Bladé, I.: The effective number of spatial degrees of freedom of a time-varying field. J. Climate ,12, 1990–2009, 1999.
Bunge, L. and Clarke, A. J.: A Verified Estimation of the El Niño Index Niño-3.4 since 1877, J. Climate, 22, 3979–3992, https://doi.org/10.1175/2009JCLI2724.1, 2009.
Ceppi, P. and Nowack, P.: Observational evidence that cloud feedback amplifies global warming, P. Natl. Acad. Sci. USA, 118, e2026290118, https://doi.org/10.1073/pnas.2026290118, 2021.
Ceppi, P., Brient, F., Zelinka, M. D., and Hartmann, D. L.: Cloud feedback mechanisms and their representation in global climate models, WIREs Climate Change, 8, e465, https://doi.org/10.1002/wcc.465, 2017.
Chen, Y.-J. and Thompson, D. W. J.: A Novel Methodology for Probing the Observed Influence of the QBO on Tropical Tropospheric Climate, J. Geophys. Res.-Atmos., 131, e2025JD045491, https://doi.org/10.1029/2025JD045491, 2026.
Chepfer, H., Bony, S., Winker, D., Cesana, G., Dufresne, J. L., Minnis, P., Stubenrauch, C. J., and Zeng, S.: The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), J. Geophys. Res.-Atmos., 115, https://doi.org/10.1029/2009JD012251, 2010.
Collimore, C. C., Martin, D. W., Hitchman, M. H., Huesmann, A., and Waliser, D. E.: On The Relationship between the QBO and Tropical Deep Convection, J. Climate, 16, 2552–2568, https://doi.org/10.1175/1520-0442(2003)016<2552:OTRBTQ>2.0.CO;2, 2003.
Davis, S. M., Liang, C. K., and Rosenlof, K. H.: Interannual variability of tropical tropopause layer clouds, Geophys. Res. Lett., 40, 2862–2866, https://doi.org/10.1002/grl.50512, 2013.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016 (data available at: https://esgf-node.llnl.gov, last access: 9 September 2026).
Gray, L. J., Anstey, J. A., Kawatani, Y., Lu, H., Osprey, S., and Schenzinger, V.: Surface impacts of the Quasi Biennial Oscillation, Atmos. Chem. Phys., 18, 8227–8247, https://doi.org/10.5194/acp-18-8227-2018, 2018.
Haynes, P., Hitchcock, P., Hitchman, M., Yoden, S., Hendon, H., Kiladis, G., Kodera, K., and Simpson, I.: The Influence of the Stratosphere on the Tropical Troposphere, J. Meteorol. Soc. Jpn. Ser. II, 99, 803–845, https://doi.org/10.2151/jmsj.2021-040, 2021.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.6860a573, 2023.
Holton, J. R. and Lindzen, R. S.: An Updated Theory for the Quasi-Biennial Cycle of the Tropical Stratosphere, J. Atmos. Sci., 29, 1076–1080, https://doi.org/10.1175/1520-0469(1972)029<1076:AUTFTQ>2.0.CO;2, 1972.
Kim, H., Caron, J. M., Richter, J. H., and Simpson, I. R.: The Lack of QBO-MJO Connection in CMIP6 Models, Geophys. Res. Lett., 47, e2020GL087295, https://doi.org/10.1029/2020GL087295, 2020.
Lei, S., Zhu, X., Ling, Y., Teng, S., and Yao, B.: Tropical Tropopause Layer Cloud Properties from Spaceborne Active Observations, Remote Sens.-Basel, 15, https://doi.org/10.3390/rs15051223, 2023.
Lim, Y. and Son, S.-W.: QBO-MJO Connection in CMIP5 Models, J. Geophys. Res.-Atmos., 125, e2019JD032157, https://doi.org/10.1029/2019JD032157, 2020.
Lin, J. and Emanuel, K.: Stratospheric Modulation of the MJO through Cirrus Cloud Feedbacks, J. Atmos. Sci., 80, 273–299, https://doi.org/10.1175/JAS-D-22-0083.1, 2023.
Lindzen, R. S. and Holton, J. R.: A Theory of the Quasi-Biennial Oscillation, J. Atmos. Sci., 25, 1095–1107, https://doi.org/10.1175/1520-0469(1968)025<1095:ATOTQB>2.0.CO;2, 1968.
Luo, F., Xie, F., Zhou, T., Niu, Y., Xia, Y., Luo, J., Zhang, R., Wang, Y., Liang, W., and Tian, W.: The disappearing quasi-biennial oscillation under sustained global warming, Nat. Commun., 17, 2138, https://doi.org/10.1038/s41467-026-68922-2, 2026.
Martin, Z., Orbe, C., Wang, S., and Sobel, A.: The MJO–QBO Relationship in a GCM with Stratospheric Nudging, J. Climate, 34, 4603–4624, https://doi.org/10.1175/JCLI-D-20-0636.1, 2021.
MODIS Atmosphere Science Team: MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1 × 1 degree grid, NASA Level 1 and Atmosphere Archive and Distribution System Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD06COSP_M3_MODIS.062, 2022
Pincus, R., Platnick, S., Ackerman, S. A., Hemler, R. S., and Hofmann, R. J. P.: Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators, J. Climate, 25, 4699–4720, https://doi.org/10.1175/JCLI-D-11-00267.1, 2012.
Pincus, R., Hubanks, P. A., Platnick, S., Meyer, K., Holz, R. E., Botambekov, D., and Wall, C. J.: Updated observations of clouds by MODIS for global model assessment, Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, 2023.
Plumb, R. A. and Bell, R. C.: A model of the quasi-biennial oscillation on an equatorial beta-plane, Q. J. Roy. Meteor. Soc., 108, 335–352, https://doi.org/10.1002/qj.49710845604, 1982.
Reichler, T., Dameris, M., and Sausen, R.: Determining the tropopause height from gridded data, Geophys. Res. Lett., 30, https://doi.org/10.1029/2003GL018240, 2003.
Schiffer, R. A. and Rossow, W. B.: The International Satellite Cloud Climatology Project (ISCCP): The First Project of the World Climate Research Programme, B. Am. Meteorol. Soc., 64, 779–784, https://doi.org/10.1175/1520-0477-64.7.779, 1983.
Son, S.-W., Lim, Y., Yoo, C., Hendon, H. H., and Kim, J.: Stratospheric Control of the Madden–Julian Oscillation, J. Climate, 30, 1909–1922, https://doi.org/10.1175/JCLI-D-16-0620.1, 2017.
Swales, D. J., Pincus, R., and Bodas-Salcedo, A.: The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2, Geosci. Model Dev., 11, 77–81, https://doi.org/10.5194/gmd-11-77-2018, 2018.
Sweeney, A. and Fu, Q.: Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer, J. Geophys. Res.-Atmos., 129, e2023JD039002, https://doi.org/10.1029/2023JD039002, 2024.
Sweeney, A., Fu, Q., Pahlavan, H. A., and Haynes, P.: Seasonality of the QBO Impact on Equatorial Clouds, J. Geophys. Res.-Atmos., 128, e2022JD037737, https://doi.org/10.1029/2022JD037737, 2023.
Trencham, N. E. and Hood, L. L.: Causes of a Lack of QBO/Solar-MJO Connection in Certain CMIP6 Models, J. Geophys. Res.-Atmos., 129, e2024JD041606, https://doi.org/10.1029/2024JD041606, 2024.
Tseng, H.-H. and Fu, Q.: Temperature Control of the Variability of Tropical Tropopause Layer Cirrus Clouds, J. Geophys. Res.-Atmos., 122, 11–62, https://doi.org/10.1002/2017JD027093, 2017.
Wilson Kemsley, S., Ceppi, P., Andersen, H., Cermak, J., Stier, P., and Nowack, P.: A systematic evaluation of high-cloud controlling factors, Atmos. Chem. Phys., 24, 8295–8316, https://doi.org/10.5194/acp-24-8295-2024, 2024.
Wilson Kemsley, S., Nowack, P., and Ceppi, P.: Climate Models Underestimate Global Decreases in High-Cloud Amount With Warming, Geophys. Res. Lett., 52, e2024GL113316, https://doi.org/10.1029/2024GL113316, 2025.
Yoo, C. and Son, S.-W.: Modulation of the boreal wintertime Madden-Julian oscillation by the stratospheric quasi-biennial oscillation, Geophys. Res. Lett., 43, 1392–1398, https://doi.org/10.1002/2016GL067762, 2016.
Young, A. H., Knapp, K. R., Inamdar, A., Hankins, W., and Rossow, W. B.: The International Satellite Cloud Climatology Project H-Series climate data record product, Earth Syst. Sci. Data, 10, 583–593, https://doi.org/10.5194/essd-10-583-2018, 2018.
Short summary
We investigate how stratospheric winds influence high clouds using satellite observations and climate models. These winds, known as the quasi-biennial oscillation, alter meteorological conditions in the troposphere such as upper-tropospheric temperature, stability, and humidity, and clouds respond to these changes. Reducing model biases requires improving cloud sensitivity to these factors. This framework could also help assess cloud responses to stratospheric cooling driven by climate change.
We investigate how stratospheric winds influence high clouds using satellite observations and...
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