Articles | Volume 3, issue 3
https://doi.org/10.5194/wcd-3-825-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-3-825-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jul 2022
Research article |
| 29 Jul 2022
| 29 Jul 2022
The tropical route of quasi-biennial oscillation (QBO) teleconnections in a climate model
Jorge L. García-Franco
CORRESPONDING AUTHOR
Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
Lesley J. Gray
Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
National Centre for Atmospheric Science, Oxford, UK
Scott Osprey
Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
National Centre for Atmospheric Science, Oxford, UK
Robin Chadwick
Met Office Hadley Centre, Exeter, UK
Global Systems Institute, Department of Mathematics, University of Exeter, Exeter, UK
Zane Martin
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
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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
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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.
Reinhard K. H. Schiemann, Grenville Lister, Rosalyn Hatcher, Dan Hodson, Bryan Lawrence, Len Shaffrey, Jeff Cole, Andrea Dittus, Jenny Mecking, Jon Robson, Simon Wilson, Yevgeny Aksenov, Adam T. Blaker, Ben Harvey, Oscar Martínez-Alvarado, Annette Osprey, Stephanie Rynders, Sharar Ahmadi, Jake Aylmer, Laura Baker, David Case, Emanuele Silvio Gentile, Steve George, Kevin Hodges, Eliza Karlowska, Charlotte Lang, Hua Lu, Niamh O'Callaghan, Weronika Osmolska, Scott Osprey, Tony Phillips, David Schröder, Robin Smith, Andrew G. Turner, Steve Woolnough, Martin Andrews, Andrew Coward, Steven Hardiman, James Harle, John W. Rostron, David M. H. Sexton, Bablu Sinha, Jonny Williams, and Chris Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2026-2281, https://doi.org/10.5194/egusphere-2026-2281, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This paper presents a new large ensemble of climate model simulations: The CANARI HadGEM3 Large Ensemble (CANARI LE). The CANARI LE has a comparatively high resolution, provides sub-daily output on atmospheric pressure levels, and boundary conditions for driving regional model simulations. The CANARI LE is thus a community resource that lends itself for the study of physical coupled climate processes, weather systems, and impacts in a changing climate.
Chaim I. Garfinkel, David Avisar, Wenjuan Huo, Ales Kuchar, Shoshiro Minobe, Scott Osprey, Katharina Perny, and Jonathon S. Wright
EGUsphere, https://doi.org/10.5194/egusphere-2026-3738, https://doi.org/10.5194/egusphere-2026-3738, 2026
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Whether tropical volcanic eruptions lead to a circulation response in winter is still unclear. We re-evaluate this effect using large ensembles from eight separate models with only one time-varying external forcing: volcanic aerosols. We find that 75 % of models simulate the previously proposed effect, but that the signal requires at least 30 eruptions before it emerges robustly from the noise. Furthermore, we demonstrate that the El Niño signal differs from natural El Niño events.
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.
Chaim I. Garfinkel, David Avisar, Scott M. Osprey, Doug Smith, Jian Rao, and Jonathon S. Wright
Weather Clim. Dynam., 7, 1133–1152, https://doi.org/10.5194/wcd-7-1133-2026, https://doi.org/10.5194/wcd-7-1133-2026, 2026
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The Quasi-biennial Oscillation (QBO) dominates variability in the tropical stratosphere, & it impacts surface climate in several parts of the world. However, climate models have been shown to systematically under-estimate the influence of the QBO. Here, we re-evaluate this finding using much larger ensemble sizes than have been previously available based on four separate models. We find that the models are comparatively more successful in capturing QBO influences than reported by previous work.
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
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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.
Dillon Elsbury, Federico Serva, Julie M. Caron, Seung-Yoon Back, Clara Orbe, Jadwiga H. Richter, James A. Anstey, Neal Butchart, Chih-Chieh Chen, Javier García-Serrano, Anne Glanville, Yoshio Kawatani, Tobias Kerzenmacher, Francois Lott, Hiroaki Naoe, Scott Osprey, Froila M. Palmeiro, Seok-Woo Son, Masakazu Taguchi, Stefan Versick, Shingo Watanabe, and Kohei Yoshida
Weather Clim. Dynam., 7, 317–339, https://doi.org/10.5194/wcd-7-317-2026, https://doi.org/10.5194/wcd-7-317-2026, 2026
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We used climate models to test how constant El Niño and La Niña ocean conditions shape the Madden-Julian Oscillation during northern winter. El Niño made this weather pattern move faster, while La Niña slowed it down. The Quasi-Biennial Oscillation, a repeating wind pattern high in the atmosphere, had little effect. This shows that long-lasting ocean conditions mainly drive the changes we found.
Hiroaki Naoe, Jorge L. García-Franco, Chang-Hyun Park, Mario Rodrigo, Froila M. Palmeiro, Federico Serva, Masakazu Taguchi, Kohei Yoshida, James A. Anstey, Javier García-Serrano, Seok-Woo Son, Yoshio Kawatani, Neal Butchart, Kevin Hamilton, Chih-Chieh Chen, Anne Glanville, Tobias Kerzenmacher, François Lott, Clara Orbe, Scott Osprey, Mijeong Park, Jadwiga H. Richter, Stefan Versick, and Shingo Watanabe
Weather Clim. Dynam., 6, 1419–1442, https://doi.org/10.5194/wcd-6-1419-2025, https://doi.org/10.5194/wcd-6-1419-2025, 2025
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Links between the stratospheric Quasi-Biennial Oscillation (QBO) and atmospheric circulations in the tropics, subtropics, and polar regions, as well as their modulation by the El Nino–Southern Oscillation, are examined through model experiments. The QBO–polar vortex connection is reproduced by a multi-model ensemble at about half the observed amplitude. Weak performance of QBO signals in these regions is likely due to unrealistically weak QBO amplitudes in the lower stratosphere.
Yoshio Kawatani, Kevin Hamilton, Shingo Watanabe, Masakazu Taguchi, Federico Serva, James A. Anstey, Jadwiga H. Richter, Neal Butchart, Clara Orbe, Scott M. Osprey, Hiroaki Naoe, Dillon Elsbury, Chih-Chieh Chen, Javier García-Serrano, Anne Glanville, Tobias Kerzenmacher, François Lott, Froila M. Palmeiro, Mijeong Park, Stefan Versick, and Kohei Yoshida
Weather Clim. Dynam., 6, 1045–1073, https://doi.org/10.5194/wcd-6-1045-2025, https://doi.org/10.5194/wcd-6-1045-2025, 2025
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The Quasi-Biennial Oscillation (QBO) of the tropical stratospheric mean winds has been relatively steady over the 7 decades it has been observed, but there are always cycle-to-cycle variations. This study used several global atmospheric models to investigate systematic modulation of the QBO by the El Niño/La Niña cycle. All models simulated shorter periods during El Niño, in agreement with observations. By contrast, the models disagreed even on the sign of the El Niño effect on QBO amplitude.
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.
Paula L. M. Gonzalez, Lesley J. Gray, Stergios Misios, Scott Osprey, and Hedi Ma
EGUsphere, https://doi.org/10.5194/egusphere-2024-2487, https://doi.org/10.5194/egusphere-2024-2487, 2024
Preprint archived
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This study has examined a set of reanalyses, both modern and 20th Century, to evaluate the robustness of the signatures of the 11-yr solar cycle in the North Atlantic climate. We find a robust response to the 11-yr solar cycle over the North Atlantic sector with a positive SLP anomaly north of the Azores region at lags of +2–3 years following solar maximum. An ocean reanalysis dataset shows that thermal inertia of the ocean could explain the lag in the SC response.
Timothy P. Banyard, Corwin J. Wright, Scott M. Osprey, Neil P. Hindley, Gemma Halloran, Lawrence Coy, Paul A. Newman, Neal Butchart, Martina Bramberger, and M. Joan Alexander
Atmos. Chem. Phys., 24, 2465–2490, https://doi.org/10.5194/acp-24-2465-2024, https://doi.org/10.5194/acp-24-2465-2024, 2024
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In 2019/2020, the tropical stratospheric wind phenomenon known as the quasi-biennial oscillation (QBO) was disrupted for only the second time in the historical record. This was poorly forecasted, and we want to understand why. We used measurements from the first Doppler wind lidar in space, Aeolus, to observe the disruption in an unprecedented way. Our results reveal important differences between Aeolus and the ERA5 reanalysis that affect the timing of the disruption's onset and its evolution.
Oscar Dimdore-Miles, Lesley Gray, Scott Osprey, Jon Robson, Rowan Sutton, and Bablu Sinha
Atmos. Chem. Phys., 22, 4867–4893, https://doi.org/10.5194/acp-22-4867-2022, https://doi.org/10.5194/acp-22-4867-2022, 2022
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This study examines interactions between variations in the strength of polar stratospheric winds and circulation in the North Atlantic in a climate model simulation. It finds that the Atlantic Meridional Overturning Circulation (AMOC) responds with oscillations to sets of consecutive Northern Hemisphere winters, which show all strong or all weak polar vortex conditions. The study also shows that a set of strong vortex winters in the 1990s contributed to the recent slowdown in the observed AMOC.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Cited articles
Abdelmoaty, H. M., Papalexiou, S. M., Rajulapati, C. R., and AghaKouchak, A.: Biases beyond the mean in CMIP6 extreme precipitation: A global investigation, Earths Future, 9, e2021EF002196, https://doi.org/10.1029/2021EF002196, 2021. a, b
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, 2003. a
Adler, R., Wang, J. J., Sapiano, M., Huffman, G., Chiu, L., Xie, P. P., Ferraro, R., Schneider, U., Becker, A., Bolvin, D., Nelkin, E., Gu, G., and NOAA CDR Program: Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly), National Centers for Environmental Information [data set], https://doi.org/10.7289/V56971M6, 2016. a
Adler, R. F., Sapiano, M. R., Huffman, G. J., Wang, J.-J., Gu, G., Bolvin, D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R., and Shin, D.-B.: The Global Precipitation Climatology Project (GPCP) monthly analysis (new version 2.3) and a review of 2017 global precipitation, Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138, 2018. a
Andrews, M. B., Knight, J. R., Scaife, A. A., Lu, Y., Wu, T., Gray, L. J., and Schenzinger, V.: Observed and simulated teleconnections between the stratospheric quasi-biennial oscillation and Northern Hemisphere winter atmospheric circulation, J. Geophys. Res.-Atmos., 124, 1219–1232, 2019. a
Anstey, J. A. and Shepherd, T. G.: High-latitude influence of the quasi-biennial oscillation, Q. J. Roy. Meteor. Soc., 140, 1–21, 2014. a
Bayr, T., Dommenget, D., Martin, T., and Power, S. B.: The eastward shift of the Walker Circulation in response to global warming and its relationship to ENSO variability, Clim. Dynam., 43, 2747–2763, 2014. a
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., and Ziese, M.: GPCC full data reanalysis version 6.0 at 1.0: monthly land-surface precipitation from rain-gauges built on GTS-based and historic data, Global Precipitation Climatology Centre (GPCC), Berlin, Germany, https://doi.org/10.5676/DWD_GPCC/CLIM_M_V2011_100, 2011. a
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U., and Ziese, M.: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, Earth Syst. Sci. Data, 5, 71–99, https://doi.org/10.5194/essd-5-71-2013, 2013. a
Brönnimann, S., Annis, J. L., Vogler, C., and Jones, P. D.: Reconstructing the quasi-biennial oscillation back to the early 1900s, Geophys. Res. Lett., 34, L22805, https://doi.org/10.1029/2007GL031354, 2007 (data available at: https://climexp.knmi.nl/getindices.cgi?WMO=BernData/qbo_90&STATION=QBO_90&TYPE=i&id=someone@somewhere, last access: 1 June 2022). a, b
Bushell, A. C., Butchart, N., Derbyshire, S. H., Jackson, D. R., Shutts, G. J., Vosper, S. B., and Webster, S.: Parameterized gravity wave momentum fluxes from sources related to convection and large-scale precipitation processes in a global atmosphere model, J. Atmos. Sci., 72, 4349–4371, 2015. a
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.: Evaluation of the Quasi-Biennial Oscillation in global climate models for the SPARC QBO-initiative, Q. J. Roy. Meteor. Soc., 148, 1459-1489, https://doi.org/10.1002/qj.3765, 2022. a, b, c, d
Butchart, N., Anstey, J. A., Hamilton, K., Osprey, S., McLandress, C., Bushell, A. C., Kawatani, Y., Kim, Y.-H., Lott, F., Scinocca, J., Stockdale, T. N., Andrews, M., Bellprat, O., Braesicke, P., Cagnazzo, C., Chen, C.-C., Chun, H.-Y., Dobrynin, M., Garcia, R. R., Garcia-Serrano, J., Gray, L. J., Holt, L., Kerzenmacher, T., Naoe, H., Pohlmann, H., Richter, J. H., Scaife, A. A., Schenzinger, V., Serva, F., Versick, S., Watanabe, S., Yoshida, K., and Yukimoto, S.: Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi), Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, 2018. a
Cai, W., Wu, L., Lengaigne, M., Li, T., McGregor, S., Kug, J.-S., Yu, J.-Y., Stuecker, M. F., Santoso, A., Li, X., Ham, Y.-G., Chikamoto, Y., Ng, B., McPhaden, M. J., Du, Y., Dommenget, D., Jia, F., Kajtar, J. B., Keenlyside, N., Lin, X., Luo, J.-J., Martín-Rey, M., Ruprich-Robert, Y., Wang, G., Xie, S.-P., Yang, Y., Kang, S. M., Choi, J.-Y., Gan, B., Kim, G.-I., Kim, C.-E., Kim, S., Kim, J.-H., and Chang, P.: Pantropical climate interactions, Science, 363, eaav4236, https://doi.org/10.1126/science.aav4236, 2019. a
Camargo, S. J. and Sobel, A. H.: Revisiting the influence of the quasi-biennial oscillation on tropical cyclone activity, J. Climate, 23, 5810–5825, 2010. a
Carvalho, L. M., Jones, C., and Liebmann, B.: The South Atlantic convergence zone: Intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall, J. Climate, 17, 88–108, 2004. a
Christiansen, B., Yang, S., and Madsen, M. S.: Do strong warm ENSO events control the phase of the stratospheric QBO?, Geophys. Res. Lett., 43, 10489–10495, https://doi.org/10.1002/2016GL070751, 2016. a, b
Claud, C. and Terray, P.: Revisiting the possible links between the quasi-biennial oscillation and the Indian summer monsoon using NCEP R-2 and CMAP fields, J. Climate, 20, 773–787, 2007. a
Coelho, C. A. S., de Souza, D. C., Kubota, P. Y., Cavalcanti, I. F. A., Baker, J. C. A., Figueroa, S. N., Firpo, M. A. F., Guimarães, B. S., Costa, S. M. S., Gonçalves, L. J. M., Bonatti, J. P., Sampaio, G., Klingaman, N. P., Chevuturi, A., and Andrews, M. B.: Assessing the representation of South American monsoon features in Brazil and UK climate model simulations, Climate Resilience and Sustainability, 1, e27, https://doi.org/10.1002/cli2.27, 2022. a
Dawson, A.: Windspharm: A high-level library for global wind field computations using spherical harmonics, Journal of Open Research Software, 4, e31, https://doi.org/10.5334/jors.129, 2016. a
Deser, C., Alexander, M. A., Xie, S.-P., and Phillips, A. S.: Sea surface temperature variability: Patterns and mechanisms, Annu. Rev. Mar. Sci., 2, 115–143, 2010. a
Deser, C., Simpson, I. R., McKinnon, K. A., and Phillips, A. S.: The Northern Hemisphere extratropical atmospheric circulation response to ENSO: How well do we know it and how do we evaluate models accordingly?, J. Climate, 30, 5059–5082, 2017. a
Dommenget, D., Bayr, T., and Frauen, C.: Analysis of the non-linearity in the pattern and time evolution of El Niño Southern Oscillation, Clim. Dynam., 40, 2825–2847, 2013. a
Freie Universität Berlin: The Quasi-Biennial-Oscillation (QBO) Data Serie, Freie Universität Berlin [data set], http://www.geo.fu-berlin.de/en/met/ag/strat/produkte/qbo/ (last access: 1 July 2022), 2020. a
Garfinkel, C. I. and Hartmann, D.: Influence of the quasi-biennial oscillation on the North Pacific and El Niño teleconnections, J. Geophys. Res., 115, D20116, https://doi.org/10.1029/2010JD014181, 2010. a
Garfinkel, C. I. and Hartmann, D. L.: Effects of the El Niño–Southern Oscillation and the quasi-biennial oscillation on polar temperatures in the stratosphere, J. Geophys. Res., 112, D19112, https://doi.org/10.1029/2007JD008481, 2007. a, b
Garfinkel, C. I. and Hartmann, D. L.: The influence of the quasi-biennial oscillation on the troposphere in winter in a hierarchy of models. Part I: Simplified dry GCMs, J. Atmos. Sci., 68, 1273–1289, 2011a. a
Garfinkel, C. I., Gerber, E. P., Shamir, O., Rao, J., Jucker, M., White, I., and Paldor, N.: A QBO Cookbook: Sensitivity of the Quasi-Biennial Oscillation to Resolution, Resolved Waves, and Parameterized Gravity Waves, J. Adv. Model. Earth Sy., 14, e2021MS002568, https://doi.org/10.1029/2021MS002568, 2022. a
Gray, W. M., Sheaffer, J. D., and Knaff, J. A.: Influence of the stratospheric QBO on ENSO variability, J. Meteorol. Soc. Jpn. Ser. II, 70, 975–995, 1992. a
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. a
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 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.6860a573, 2019. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hitchman, M. H., Yoden, S., Haynes, P. H., Kumar, V., and Tegtmeier, S.: An observational history of the direct influence of the stratospheric quasi-biennial oscillation on the tropical and subtropical upper troposphere and lower stratosphere, J. Meteorol. Soc. Jpn. Ser. II, 99, 239–267, https://doi.org/10.2151/jmsj.2021-012, 2021. a, b, c, d, e, f
Ho, C.-H., Kim, H.-S., Jeong, J.-H., and Son, S.-W.: Influence of stratospheric quasi-biennial oscillation on tropical cyclone tracks in the western North Pacific, Geophys. Res. Lett., 36, L06702, https://doi.org/10.1029/2009GL037163, 2009. a
Holton, J. R. and Tan, H.-C.: The influence of the equatorial quasi-biennial oscillation on the global circulation at 50 mb, J. Atmos. Sci., 37, 2200–2208, 1980. a
Huang, B., Hu, Z.-Z., Kinter, J. L., Wu, Z., and Kumar, A.: Connection of stratospheric QBO with global atmospheric general circulation and tropical SST. Part I: Methodology and composite life cycle, Clim. Dynam., 38, 1–23, 2012. a
Huesmann, A. S. and Hitchman, M. H.: The stratospheric quasi-biennial oscillation in the NCEP reanalyses: Climatological structures, J. Geophys. Res.-Atmos., 106, 11859–11874, 2001. a
Jaramillo, A., Dominguez, C., Raga, G., and Quintanar, A. I.: The Combined QBO and ENSO Influence on Tropical Cyclone Activity over the North Atlantic Ocean, Atmosphere, 12, 1588, 2021. a
Jorgetti, T., da Silva Dias, P. L., and de Freitas, E. D.: The relationship between South Atlantic SST and SACZ
intensity and positioning, Clim. Dynam., 42, 3077–3086, 2014. a
Kennedy, J. J., Rayner, N. A., Atkinson, C. P., and Killick, R. E.: An ensemble data set of sea surface temperature change from 1850: The Met Office Hadley Centre HadSST.4.0.0.0 data set, J. Geophys. Res.-Atmos., 124, 7719–7763, https://doi.org/10.1029/2018JD029867, 2019 (data available at: https://www.metoffice.gov.uk/hadobs/hadsst4/data/download.html, last access: 1 June 2022). a, b
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. a
Kuhlbrodt, T., Jones, C. G., Sellar, A., Storkey, D., Blockley, E., Stringer, M., Hill, R., Graham, T., Ridley, J., Blaker, A., Calvert, D., Copsey, D., Ellis, R., Hewitt, H., Hyder, P., Ineson, S., Mulcahy, J., Siahaan, A., and Walton, J.: The low-resolution version of HadGEM3 GC3. 1: Development and evaluation for global climate, J. Adv. Model. Earth Sy., 10, 2865–2888, 2018. a
Lee, J., Planton, Y. Y., Gleckler, P. J., Sperber, K. R., Guilyardi, E., Wittenberg, A. T., McPhaden, M. J., and Pallotta, G.: Robust evaluation of ENSO in climate models: How many ensemble members are needed?, Geophys. Res. Lett., 48, e2021GL095041, https://doi.org/10.1029/2021GL095041, 2021. a
Lim, Y., Son, S.-W., Marshall, A. G., Hendon, H. H., and Seo, K.-H.: Influence of the QBO on MJO prediction skill in the subseasonal-to-seasonal prediction models, Clim. Dynam., 53, 1681–1695, 2019. a
Liu, M., Ren, H.-L., Zhang, R., Ineson, S., and Wang, R.: ENSO phase-locking behavior in climate models: from CMIP5 to CMIP6, Environmental Research Communications, 3, 031004, https://doi.org/10.1088/2515-7620/abf295, 2021. a
Lu, H., Hitchman, M. H., Gray, L. J., Anstey, J. A., and Osprey, S. M.: On the role of Rossby wave breaking in the quasi-biennial modulation of the stratospheric polar vortex during boreal winter, Q. J. Roy. Meteor. Soc., 146, 1939–1959, 2020. a
Ma, T., Chen, W., Huangfu, J., Song, L., and Cai, Q.: The observed influence of the Quasi-Biennial Oscillation in the lower equatorial stratosphere on the East Asian winter monsoon during early boreal winter, Int. J. Climatol., 41, 6254–6269, https://doi.org/10.1002/joc.7192, 2021. a
Mantua, N. J., Hare, S. R., Zhang, Y., Wallace, J. M., and Francis, R. C.: A Pacific interdecadal climate oscillation with impacts on salmon production, B. Am. Meteorol. Soc., 78, 1069–1080, 1997. a
Martin, Z., Vitart, F., Wang, S., and Sobel, A.: The Impact of the Stratosphere on the MJO in a Forecast Model, J. Geophys. Res.-Atmos., 125, e2019JD032106, https://doi.org/10.1029/2019JD032106, 2020. a
Martin, Z., Orbe, C., Wang, S., and Sobel, A.: The MJO–QBO Relationship in a GCM with Stratospheric Nudging, J. Climate, 34, 4603–4624, 2021a. a
Martin, Z., Sobel, A., Butler, A., and Wang, S.: Variability in QBO temperature anomalies on annual and decadal time scales, J. Climate, 34, 589–605, 2021b. a
McKenna, S., Santoso, A., Gupta, A. S., Taschetto, A. S., and Cai, W.: Indian Ocean Dipole in CMIP5 and CMIP6: characteristics, biases, and links to ENSO, Sci. Rep.-UK, 10, 1–13, 2020. a
Menary, M. B., Kuhlbrodt, T., Ridley, J., Andrews, M. B., Dimdore-Miles, O. B., Deshayes, J., Eade, R., Gray, L., Ineson, S., Mignot, J., Roberts, C. D., Robson, J., Wood, R. A., and Xavier, P.: Preindustrial Control Simulations With HadGEM3-GC3. 1 for CMIP6, J. Adv. Model. Earth Sy., 10, 3049–3075, 2018. a, b
Peña-Ortiz, C., Manzini, E., and Giorgetta, M. A.: Tropical deep convection impact on southern winter stationary waves and its modulation by the quasi-biennial oscillation, J. Climate, 32, 7453–7467, 2019. a
Richter, J. H., Anstey, J. A., Butchart, N., Kawatani, Y., Meehl, G. A., Osprey, S., and Simpson, I. R.: Progress in Simulating the Quasi-Biennial Oscillation in CMIP Models, J. Geophys. Res.-Atmos., 125, e2019JD032362, https://doi.org/10.1029/2019JD032362, 2020. a, b
Saji, N., Goswami, B. N., Vinayachandran, P., and Yamagata, T.: A dipole mode in the tropical Indian Ocean, Nature, 401, 360–363, 1999. a
Scaife, A., Butchart, N., Warner, C., and Swinbank, R.: Impact of a spectral gravity wave parameterization on the stratosphere in the Met Office Unified Model, J. Atmos. Sci., 59, 1473–1489, 2002. a
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., and Ziese, M.: GPCC Full Data Reanalysis Version 6.0 at 0.5∘: monthly land-surface precipitation from rain-gauges built on GTS-based and historic data, Global Precipitation Climatology Centre (GPCC), Deutscher Wetterdienst (DWD) [data set], https://doi.org/10.5676/DWD_GPCC/FD_M_V6_050, 2011. a
Sellar, A. A., Jones, C. G., Mulcahy, J., Tang, Y., Yool, A., Wiltshire, A., O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de Mora, L., Kuhlbrodt, T., Rumbold, S., Kelley, D. I., Ellis, R., Johnson, C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and Zerroukat, M.: UKESM1: Description and evaluation of the UK Earth System Model, J. Adv. Model. Earth Sy., 11, 4513–4558, https://doi.org/10.1029/2019MS001739, 2019. a, b
Serva, F., Anstey, J. A., Bushell, A. C., Butchart, N., Cagnazzo, C., Gray, L., Kawatani, Y., Osprey, S. M., Richter, J. H., and Simpson, I. R.: The impact of the QBO on the region of the tropical tropopause in QBOi models: present-day simulations, Q. J. Roy. Meteor. Soc., 148, 1945–1964, https://doi.org/10.1002/qj.4287, 2022. a, b, c
Sutton, R. T. and Hodson, D. L.: Atlantic Ocean forcing of North American and European summer climate, Science, 309, 115–118, 2005. a
Taguchi, M.: Observed connection of the stratospheric quasi-biennial oscillation with El Niño–Southern Oscillation in radiosonde data, J. Geophys. Res., 115, D18120, https://doi.org/10.1029/2010JD014325, 2010. a, b, c, d
Tegtmeier, S., Anstey, J., Davis, S., Ivanciu, I., Jia, Y., McPhee, D., and Pilch Kedzierski, R.: Zonal Asymmetry of the QBO Temperature Signal in the Tropical Tropopause Region, Geophys. Res. Lett., 47, e2020GL089533, https://doi.org/10.1029/2020GL089533, 2020. a
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019. a, b
Wang, B. and Ding, Q.: Global monsoon: Dominant mode of annual variation in the tropics, Dynam. Atmos. Oceans, 44, 165–183, 2008. a
Wang, B., Biasutti, M., Byrne, M. P., Castro, C., Chang, C.-P., Cook, K., Fu, R., Grimm, A. M., Ha, K.-J., Hendon, H., Kitoh, A., Krishnan, R., Lee, J., Li, J., Liu, J., Moise, A., Pascale, S., Roxy, M. K., Seth, A., Sui, C., Turner, A., Yang, S., Yun, K., Zhang, L., and Zhou, T.: Monsoons climate change assessment, B. Am. Meteorol. Soc., 102, E1–E19, 2021. a
Wang, P. X., Wang, B., Cheng, H., Fasullo, J., Guo, Z., Kiefer, T., and Liu, Z.: The global monsoon across time scales: Mechanisms and outstanding issues, Earth-Sci. Rev., 174, 84–121, 2017. a
Wang, S., Tippett, M. K., Sobel, A. H., Martin, Z., and Vitart, F.: Impact of the QBO on prediction and predictability of the MJO convection, J. Geophys. Res.-Atmos., 124, 11766–11782, https://doi.org/10.1029/2019JD030575, 2019. a
Wang, X. and Wang, C.: Different impacts of various El Niño events on the Indian Ocean Dipole, Clim. Dynam., 42, 991–1005, 2014. a
Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder, P., Ineson, S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae, J. G. L., Roberts, M. J., Scaife, A. A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I. G., Walters, D. N., West, A., Wood, R. A., Woollings, T., and Xavier, P. K.: The Met Office global coupled model 3.0 and 3.1 (GC3.0 and GC3.1) configurations, J. Adv. Model. Earth Sy., 10, 357–380, 2018. a, b
World Climate Research Programme (WCRP): Coupled Model Intercomparison Project (Phase 6), WCRP, https://esgf-index1.ceda.ac.uk/projects/cmip6-ceda/, last access: 22 October 2021. a
Yu, B. and Zwiers, F. W.: Changes in equatorial atmospheric zonal circulations in recent decades, Geophys. Res. Lett., 37, L05701, https://doi.org/10.1029/2009GL042071, 2010. a
Short summary
This paper establishes robust links between the stratospheric quasi-biennial oscillation (QBO) and several features of tropical climate. Robust precipitation responses, as well as changes to the Walker circulation, were found to be robustly linked to the variability in the lower stratosphere associated with the QBO using a 500-year simulation of a state-of-the-art climate model.
This paper establishes robust links between the stratospheric quasi-biennial oscillation (QBO)...
