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
Related authors
Jorge L. García-Franco, Lesley J. Gray, and Scott Osprey
Weather Clim. Dynam., 1, 349–371, https://doi.org/10.5194/wcd-1-349-2020, https://doi.org/10.5194/wcd-1-349-2020, 2020
Short summary
Short summary
The American monsoon system is the main source of rainfall for the subtropical Americas and an important element of Latin American agriculture. Here we use state-of-the-art climate models from the UK Met Office in different configurations to analyse the performance of these models in the American monsoon. Resolution is found to be a key factor to improve monsoon representation, whereas integrated chemistry does not improve the simulated monsoon rainfall.
Yoshio Kawatani, Kevin Hamilton, Shingo Watanabe, 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. Palmerio, Mijeong Park, Federico Serva, Masakazu Taguchi, Stefan Versick, and Kohei Yoshioda
EGUsphere, https://doi.org/10.5194/egusphere-2024-3270, https://doi.org/10.5194/egusphere-2024-3270, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Aleena Moolakkunnel Jaison, Lesley J. Gray, Scott M. Osprey, Jeff R. Knight, and Martin B. Andrews
EGUsphere, https://doi.org/10.5194/egusphere-2024-1818, https://doi.org/10.5194/egusphere-2024-1818, 2024
Short summary
Short summary
Models have biases in SAO representation, primarily due to lack of strong enough eastward wave forcing. We investigated if this bias arises from increased wave absorption in low-mid stratosphere due to circulation biases. Using model experiments, we found that removing biases in lower altitudes improve the SAO, but a significant bias remains. Thus, modifications to gravity wave parametrisation is required to improve the modelled SAO, potentially leading to improved predictability of SSW.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Oscar Dimdore-Miles, Lesley Gray, and Scott Osprey
Weather Clim. Dynam., 2, 205–231, https://doi.org/10.5194/wcd-2-205-2021, https://doi.org/10.5194/wcd-2-205-2021, 2021
Short summary
Short summary
Observations of the stratosphere span roughly half a century, preventing analysis of multi-decadal variability in circulation using these data. Instead, we rely on long simulations of climate models. Here, we use a model to examine variations in northern polar stratospheric winds and find they vary with a period of around 90 years. We show that this is possibly due to variations in the size of winds over the Equator. This result may improve understanding of Equator–polar stratospheric coupling.
Jorge L. García-Franco, Lesley J. Gray, and Scott Osprey
Weather Clim. Dynam., 1, 349–371, https://doi.org/10.5194/wcd-1-349-2020, https://doi.org/10.5194/wcd-1-349-2020, 2020
Short summary
Short summary
The American monsoon system is the main source of rainfall for the subtropical Americas and an important element of Latin American agriculture. Here we use state-of-the-art climate models from the UK Met Office in different configurations to analyse the performance of these models in the American monsoon. Resolution is found to be a key factor to improve monsoon representation, whereas integrated chemistry does not improve the simulated monsoon rainfall.
Duncan Ackerley, Robin Chadwick, Dietmar Dommenget, and Paola Petrelli
Geosci. Model Dev., 11, 3865–3881, https://doi.org/10.5194/gmd-11-3865-2018, https://doi.org/10.5194/gmd-11-3865-2018, 2018
Short summary
Short summary
Climate models have been run using observed sea surface temperatures to identify biases in the atmospheric circulation. In this work, land surface temperatures are also constrained, which is not routinely done. Experiments include increasing sea surface temperatures, quadrupling atmospheric carbon dioxide and increasing solar radiation. The response of the land surface is then allowed or suppressed, and the global climate is evaluated. Information on how to obtain the model data is also given.
Lesley J. Gray, James A. Anstey, Yoshio Kawatani, Hua Lu, Scott Osprey, and Verena Schenzinger
Atmos. Chem. Phys., 18, 8227–8247, https://doi.org/10.5194/acp-18-8227-2018, https://doi.org/10.5194/acp-18-8227-2018, 2018
Short summary
Short summary
A major phenomenon in the stratosphere is the Quasi Biennial Oscillation (QBO). Although a feature of the equatorial stratosphere, its influence extends to surface weather at both equatorial and mid latitudes. Improved knowledge of mechanisms of influence should help to improve weather forecasts. In this paper, QBO impacts at the surface are characterized and dominant mechanisms explored. Three pathways are identified, referred to as the tropical, subtropical and polar routes.
Neal Butchart, James A. Anstey, Kevin Hamilton, Scott Osprey, Charles McLandress, Andrew C. Bushell, Yoshio Kawatani, Young-Ha Kim, Francois Lott, John Scinocca, Timothy N. Stockdale, Martin Andrews, Omar Bellprat, Peter Braesicke, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Mikhail Dobrynin, Rolando R. Garcia, Javier Garcia-Serrano, Lesley J. Gray, Laura Holt, Tobias Kerzenmacher, Hiroaki Naoe, Holger Pohlmann, Jadwiga H. Richter, Adam A. Scaife, Verena Schenzinger, Federico Serva, Stefan Versick, Shingo Watanabe, Kohei Yoshida, and Seiji Yukimoto
Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, https://doi.org/10.5194/gmd-11-1009-2018, 2018
Short summary
Short summary
This paper documents the numerical experiments to be used in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi), which was set up to improve the representation of the QBO and tropical stratospheric variability in global climate models.
Verena Schenzinger, Scott Osprey, Lesley Gray, and Neal Butchart
Geosci. Model Dev., 10, 2157–2168, https://doi.org/10.5194/gmd-10-2157-2017, https://doi.org/10.5194/gmd-10-2157-2017, 2017
Short summary
Short summary
The Quasi-Biennial Oscillation (QBO) is a pattern of winds in the equatorial stratosphere that has been observed for the past 60 years. It is thought to have long-range influences, e.g. on the Northern Hemisphere winter polar vortex and therefore Europe's winter weather. Since its period is about 2 years, being able to predict the QBO might also improve weather forecasting. Using a set of characteristic metrics, this paper examines how reliable current climate models are in simulating the QBO.
Masatomo Fujiwara, Jonathon S. Wright, Gloria L. Manney, Lesley J. Gray, James Anstey, Thomas Birner, Sean Davis, Edwin P. Gerber, V. Lynn Harvey, Michaela I. Hegglin, Cameron R. Homeyer, John A. Knox, Kirstin Krüger, Alyn Lambert, Craig S. Long, Patrick Martineau, Andrea Molod, Beatriz M. Monge-Sanz, Michelle L. Santee, Susann Tegtmeier, Simon Chabrillat, David G. H. Tan, David R. Jackson, Saroja Polavarapu, Gilbert P. Compo, Rossana Dragani, Wesley Ebisuzaki, Yayoi Harada, Chiaki Kobayashi, Will McCarty, Kazutoshi Onogi, Steven Pawson, Adrian Simmons, Krzysztof Wargan, Jeffrey S. Whitaker, and Cheng-Zhi Zou
Atmos. Chem. Phys., 17, 1417–1452, https://doi.org/10.5194/acp-17-1417-2017, https://doi.org/10.5194/acp-17-1417-2017, 2017
Short summary
Short summary
We introduce the SPARC Reanalysis Intercomparison Project (S-RIP), review key concepts and elements of atmospheric reanalysis systems, and summarize the technical details of and differences among 11 of these systems. This work supports scientific studies and intercomparisons of reanalysis products by collecting these background materials and technical details into a single reference. We also address several common misunderstandings and points of confusion regarding reanalyses.
Mark J. Webb, Timothy Andrews, Alejandro Bodas-Salcedo, Sandrine Bony, Christopher S. Bretherton, Robin Chadwick, Hélène Chepfer, Hervé Douville, Peter Good, Jennifer E. Kay, Stephen A. Klein, Roger Marchand, Brian Medeiros, A. Pier Siebesma, Christopher B. Skinner, Bjorn Stevens, George Tselioudis, Yoko Tsushima, and Masahiro Watanabe
Geosci. Model Dev., 10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, https://doi.org/10.5194/gmd-10-359-2017, 2017
Short summary
Short summary
The Cloud Feedback Model Intercomparison Project (CFMIP) aims to improve understanding of cloud-climate feedback mechanisms and evaluation of cloud processes and cloud feedbacks in climate models. CFMIP also aims to improve understanding of circulation, regional-scale precipitation and non-linear changes. CFMIP is contributing to the 6th phase of the Coupled Model Intercomparison Project (CMIP6) by coordinating a hierarchy of targeted experiments with cloud-related model outputs.
Peter Good, Timothy Andrews, Robin Chadwick, Jean-Louis Dufresne, Jonathan M. Gregory, Jason A. Lowe, Nathalie Schaller, and Hideo Shiogama
Geosci. Model Dev., 9, 4019–4028, https://doi.org/10.5194/gmd-9-4019-2016, https://doi.org/10.5194/gmd-9-4019-2016, 2016
Short summary
Short summary
The nonlinMIP model intercomparison project is described. nonlinMIP provides experiments that account for state-dependent regional and global climate responses. The experiments have two main applications: 1) to focus understanding of responses to CO2 forcing on states relevant to specific policy or scientific questions (e.g.
change under low-forcing scenarios, the benefits of mitigation, or from past cold climates to
the present day), or 2) to understand state dependence of climate responses.
C. J. Wright, S. M. Osprey, and J. C. Gille
Atmos. Chem. Phys., 15, 8459–8477, https://doi.org/10.5194/acp-15-8459-2015, https://doi.org/10.5194/acp-15-8459-2015, 2015
Short summary
Short summary
Data from the HIRDLS instrument are used to study the numerical variability of gravity waves. Observed distributions are dominated by long-vertical-short-horizontal-wavelength waves, with a similar spectral form at all locations. We further divide our data into subspecies by wavelength, and investigate variation in these subspecies in time and space. We show that the variations associated with particular phenomena arise due to changes in specific parts of the spectrum.
Related subject area
Atmospheric teleconnections incl. stratosphere–troposphere coupling
Model spread in multidecadal North Atlantic Oscillation variability connected to stratosphere–troposphere coupling
The role of the Indian Ocean Dipole in modulating the Austral Spring ENSO teleconnection into the Southern Hemisphere
Opposite spectral properties of Rossby waves during weak and strong stratospheric polar vortex events
Stratospheric influence on the winter North Atlantic storm track in subseasonal reforecasts
How do different pathways connect the stratospheric polar vortex to its tropospheric precursors?
A critical evaluation of decadal solar cycle imprints in the MiKlip historical ensemble simulations
The teleconnection of extreme El Niño–Southern Oscillation (ENSO) events to the tropical North Atlantic in coupled climate models
Using large ensembles to quantify the impact of sudden stratospheric warmings and their precursors on the North Atlantic Oscillation
The stratosphere: a review of the dynamics and variability
Stratospheric downward wave reflection events modulate North American weather regimes and cold spells
Modulation of the El Niño teleconnection to the North Atlantic by the tropical North Atlantic during boreal spring and summer
Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems
Stratospheric modulation of Arctic Oscillation extremes as represented by extended-range ensemble forecasts
Decline in Etesian winds after large volcanic eruptions in the last millennium
Stationary wave biases and their effect on upward troposphere– stratosphere coupling in sub-seasonal prediction models
Stratospheric wave driving events as an alternative to sudden stratospheric warmings
Tropical influence on heat-generating atmospheric circulation over Australia strengthens through spring
Sudden stratospheric warmings during El Niño and La Niña: sensitivity to atmospheric model biases
Minimal impact of model biases on Northern Hemisphere El Niño–Southern Oscillation teleconnections
Resampling of ENSO teleconnections: accounting for cold-season evolution reduces uncertainty in the North Atlantic
The wave geometry of final stratospheric warming events
Origins of multi-decadal variability in sudden stratospheric warmings
Tropospheric eddy feedback to different stratospheric conditions in idealised baroclinic life cycles
Impacts of the North Atlantic Oscillation on winter precipitations and storm track variability in southeast Canada and the northeast United States
The role of Barents–Kara sea ice loss in projected polar vortex changes
Mechanisms and predictability of sudden stratospheric warming in winter 2018
On the intermittency of orographic gravity wave hotspots and its importance for middle atmosphere dynamics
The role of North Atlantic–European weather regimes in the surface impact of sudden stratospheric warming events
Nonlinearity in the tropospheric pathway of ENSO to the North Atlantic
Rémy Bonnet, Christine M. McKenna, and Amanda C. Maycock
Weather Clim. Dynam., 5, 913–926, https://doi.org/10.5194/wcd-5-913-2024, https://doi.org/10.5194/wcd-5-913-2024, 2024
Short summary
Short summary
Climate models underestimate multidecadal winter North Atlantic Oscillation (NAO) variability. Understanding the origin of this weak variability is important for making reliable climate projections. We use multi-model climate simulations to explore statistical relationships with drivers that may contribute to NAO variability. We find a relationship between modelled stratosphere–troposphere coupling and multidecadal NAO variability, offering an avenue to improve the simulation of NAO variability.
Luciano Gustavo Andrian, Marisol Osman, and Carolina Susana Vera
EGUsphere, https://doi.org/10.5194/egusphere-2024-1812, https://doi.org/10.5194/egusphere-2024-1812, 2024
Short summary
Short summary
The interplay between El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) is well-researched in the tropical Indian Ocean, but their effects on the Southern Hemisphere's extratropical regions during spring are less studied. Our results show that the positive phase of the IOD can strengthen the El Niño circulation anomalies, heightening its continental impacts. On the other hand, negative IOD combined with La Niña shows less consistent changes among the different methodologies.
Michael Schutte, Daniela I. V. Domeisen, and Jacopo Riboldi
Weather Clim. Dynam., 5, 733–752, https://doi.org/10.5194/wcd-5-733-2024, https://doi.org/10.5194/wcd-5-733-2024, 2024
Short summary
Short summary
The winter circulation in the stratosphere, a layer of the Earth’s atmosphere between 10 and 50 km height, is tightly linked to the circulation in the lower atmosphere determining our daily weather. This interconnection happens in the form of waves propagating in and between these two layers. Here, we use space–time spectral analysis to show that disruptions and enhancements of the stratospheric circulation modify the shape and propagation of waves in both layers.
Hilla Afargan-Gerstman, Dominik Büeler, C. Ole Wulff, Michael Sprenger, and Daniela I. V. Domeisen
Weather Clim. Dynam., 5, 231–249, https://doi.org/10.5194/wcd-5-231-2024, https://doi.org/10.5194/wcd-5-231-2024, 2024
Short summary
Short summary
The stratosphere is a layer of Earth's atmosphere found above the weather systems. Changes in the stratosphere can affect the winds and the storm tracks in the North Atlantic region for a relatively long time, lasting for several weeks and even months. We show that the stratosphere can be important for weather forecasts beyond 1 week, but more work is needed to improve the accuracy of these forecasts for 3–4 weeks.
Raphael Harry Köhler, Ralf Jaiser, and Dörthe Handorf
Weather Clim. Dynam., 4, 1071–1086, https://doi.org/10.5194/wcd-4-1071-2023, https://doi.org/10.5194/wcd-4-1071-2023, 2023
Short summary
Short summary
This study explores the local mechanisms of troposphere–stratosphere coupling on seasonal timescales during extended winter in the Northern Hemisphere. The detected tropospheric precursor regions exhibit very distinct mechanisms of coupling to the stratosphere, thus highlighting the importance of the time- and zonally resolved picture. Moreover, this study demonstrates that the ICOsahedral Non-hydrostatic atmosphere model (ICON) can realistically reproduce troposphere–stratosphere coupling.
Tobias C. Spiegl, Ulrike Langematz, Holger Pohlmann, and Jürgen Kröger
Weather Clim. Dynam., 4, 789–807, https://doi.org/10.5194/wcd-4-789-2023, https://doi.org/10.5194/wcd-4-789-2023, 2023
Short summary
Short summary
We investigate the role of the solar cycle in atmospheric domains with the Max Plank Institute Earth System Model in high resolution (MPI-ESM-HR). We focus on the tropical upper stratosphere, Northern Hemisphere (NH) winter dynamics and potential surface imprints. We found robust solar signals at the tropical stratopause and a weak dynamical response in the NH during winter. However, we cannot confirm the importance of the 11-year solar cycle for decadal variability in the troposphere.
Jake W. Casselman, Joke F. Lübbecke, Tobias Bayr, Wenjuan Huo, Sebastian Wahl, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 471–487, https://doi.org/10.5194/wcd-4-471-2023, https://doi.org/10.5194/wcd-4-471-2023, 2023
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) has remote effects on the tropical North Atlantic (TNA), but the connections' nonlinearity (strength of response to an increasing ENSO signal) is not always well represented in models. Using the Community Earth System Model version 1 – Whole Atmosphere Community Climate Mode (CESM-WACCM) and the Flexible Ocean and Climate Infrastructure version 1, we find that the TNA responds linearly to extreme El Niño but nonlinearly to extreme La Niña for CESM-WACCM.
Philip E. Bett, Adam A. Scaife, Steven C. Hardiman, Hazel E. Thornton, Xiaocen Shen, Lin Wang, and Bo Pang
Weather Clim. Dynam., 4, 213–228, https://doi.org/10.5194/wcd-4-213-2023, https://doi.org/10.5194/wcd-4-213-2023, 2023
Short summary
Short summary
Sudden-stratospheric-warming (SSW) events can severely affect the subsequent weather at the surface. We use a large ensemble of climate model hindcasts to investigate features of the climate that make strong impacts more likely through negative NAO conditions. This allows a more robust assessment than using observations alone. Air pressure over the Arctic prior to an SSW and the zonal-mean zonal wind in the lower stratosphere have the strongest relationship with the subsequent NAO response.
Neal Butchart
Weather Clim. Dynam., 3, 1237–1272, https://doi.org/10.5194/wcd-3-1237-2022, https://doi.org/10.5194/wcd-3-1237-2022, 2022
Short summary
Short summary
In recent years, it has emerged that there is an affinity between stratospheric variability and surface events. Waves from the troposphere interacting with the mean flow drive much of the variability in the polar vortex, sudden stratospheric warmings and tropical quasi-biennial oscillation. Here we review the historical evolution of established knowledge of the stratosphere's global structure and dynamical variability, along with recent advances and theories, and identify outstanding challenges.
Gabriele Messori, Marlene Kretschmer, Simon H. Lee, and Vivien Wendt
Weather Clim. Dynam., 3, 1215–1236, https://doi.org/10.5194/wcd-3-1215-2022, https://doi.org/10.5194/wcd-3-1215-2022, 2022
Short summary
Short summary
Over 10 km above the ground, there is a region of the atmosphere called the stratosphere. While there is very little air in the stratosphere itself, its interactions with the lower parts of the atmosphere – where we live – can affect the weather. Here we study a specific example of such an interaction, whereby processes occurring at the boundary of the stratosphere can lead to a continent-wide drop in temperatures in North America during winter.
Jake W. Casselman, Bernat Jiménez-Esteve, and Daniela I. V. Domeisen
Weather Clim. Dynam., 3, 1077–1096, https://doi.org/10.5194/wcd-3-1077-2022, https://doi.org/10.5194/wcd-3-1077-2022, 2022
Short summary
Short summary
Using an atmospheric general circulation model, we analyze how the tropical North Atlantic influences the El Niño–Southern Oscillation connection towards the North Atlantic European region. We also focus on the lesser-known boreal spring and summer response following an El Niño–Southern Oscillation event. Our results show that altered tropical Atlantic sea surface temperatures may cause different responses over the Caribbean region, consequently influencing the North Atlantic European region.
Zachary D. Lawrence, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Amy H. Butler, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Daniela I. V. Domeisen, Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel, Neil P. Hindley, Liwei Jia, Martin Jucker, Alexey Y. Karpechko, Hera Kim, Andrea L. Lang, Simon H. Lee, Pu Lin, Marisol Osman, Froila M. Palmeiro, Judith Perlwitz, Inna Polichtchouk, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Irene Erner, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
Weather Clim. Dynam., 3, 977–1001, https://doi.org/10.5194/wcd-3-977-2022, https://doi.org/10.5194/wcd-3-977-2022, 2022
Short summary
Short summary
Forecast models that are used to predict weather often struggle to represent the Earth’s stratosphere. This may impact their ability to predict surface weather weeks in advance, on subseasonal-to-seasonal (S2S) timescales. We use data from many S2S forecast systems to characterize and compare the stratospheric biases present in such forecast models. These models have many similar stratospheric biases, but they tend to be worse in systems with low model tops located within the stratosphere.
Jonas Spaeth and Thomas Birner
Weather Clim. Dynam., 3, 883–903, https://doi.org/10.5194/wcd-3-883-2022, https://doi.org/10.5194/wcd-3-883-2022, 2022
Short summary
Short summary
Past research has demonstrated robust stratosphere–troposphere dynamical coupling following stratospheric circulation extremes. Here, we use a large set of extended-range ensemble forecasts to robustly quantify the increased risk for tropospheric circulation extremes following stratospheric extreme events. In particular, we provide estimates of the fraction of tropospheric extremes that may be attributable to preceding stratospheric extremes.
Stergios Misios, Ioannis Logothetis, Mads F. Knudsen, Christoffer Karoff, Vassilis Amiridis, and Kleareti Tourpali
Weather Clim. Dynam., 3, 811–823, https://doi.org/10.5194/wcd-3-811-2022, https://doi.org/10.5194/wcd-3-811-2022, 2022
Short summary
Short summary
We investigate the impact of strong volcanic eruptions on the northerly Etesian winds blowing in the eastern Mediterranean. Μodel simulations of the last millennium demonstrate a robust reduction in the total number of days with Etesian winds in the post-eruption summers. The decline in the Etesian winds is attributed to a weakened Indian summer monsoon in the post-eruption summer. These findings could improve seasonal predictions of the wind circulation in the eastern Mediterranean.
Chen Schwartz, Chaim I. Garfinkel, Priyanka Yadav, Wen Chen, and Daniela I. V. Domeisen
Weather Clim. Dynam., 3, 679–692, https://doi.org/10.5194/wcd-3-679-2022, https://doi.org/10.5194/wcd-3-679-2022, 2022
Short summary
Short summary
Eleven operational forecast models that run on subseasonal timescales (up to 2 months) are examined to assess errors in their simulated large-scale stationary waves in the Northern Hemisphere winter. We found that models with a more finely resolved stratosphere generally do better in simulating the waves in both the stratosphere (10–50 km) and troposphere below. Moreover, a connection exists between errors in simulated time-mean convection in tropical regions and errors in the simulated waves.
Thomas Reichler and Martin Jucker
Weather Clim. Dynam., 3, 659–677, https://doi.org/10.5194/wcd-3-659-2022, https://doi.org/10.5194/wcd-3-659-2022, 2022
Short summary
Short summary
Variations in the stratospheric polar vortex, so-called vortex events, can improve predictions of surface weather and climate. There are various ways to detect such events, and here we use the amount of wave energy that propagates into the stratosphere. The new definition is tested against so-called stratospheric sudden warmings (SSWs). We find that the wave definition has advantages over SSWs, for example in terms of a stronger surface response that follows the events.
Roseanna C. McKay, Julie M. Arblaster, and Pandora Hope
Weather Clim. Dynam., 3, 413–428, https://doi.org/10.5194/wcd-3-413-2022, https://doi.org/10.5194/wcd-3-413-2022, 2022
Short summary
Short summary
Understanding what makes it hot in Australia in spring helps us better prepare for harmful impacts. We look at how the higher latitudes and tropics change the atmospheric circulation from early to late spring and how that changes maximum temperatures in Australia. We find that the relationship between maximum temperatures and the tropics is stronger in late spring than early spring. These findings could help improve forecasts of hot months in Australia in spring.
Nicholas L. Tyrrell, Juho M. Koskentausta, and Alexey Yu. Karpechko
Weather Clim. Dynam., 3, 45–58, https://doi.org/10.5194/wcd-3-45-2022, https://doi.org/10.5194/wcd-3-45-2022, 2022
Short summary
Short summary
El Niño events are known to effect the variability of the wintertime stratospheric polar vortex. The observed relationship differs from what is seen in climate models. Climate models have errors in their average winds and temperature, and in this work we artificially reduce those errors to see how that changes the communication of El Niño events to the polar stratosphere. We find reducing errors improves stratospheric variability, but does not explain the differences with observations.
Nicholas L. Tyrrell and Alexey Yu. Karpechko
Weather Clim. Dynam., 2, 913–925, https://doi.org/10.5194/wcd-2-913-2021, https://doi.org/10.5194/wcd-2-913-2021, 2021
Short summary
Short summary
Tropical Pacific sea surface temperatures (El Niño) affect the global climate. The Pacific-to-Europe connection relies on interactions of large atmospheric waves with winds and surface pressure. We looked at how mean errors in a climate model affect its ability to simulate the Pacific-to-Europe connection. We found that even large errors in the seasonal winds did not affect the response of the model to an El Niño event, which is good news for seasonal forecasts which rely on these connections.
Martin P. King, Camille Li, and Stefan Sobolowski
Weather Clim. Dynam., 2, 759–776, https://doi.org/10.5194/wcd-2-759-2021, https://doi.org/10.5194/wcd-2-759-2021, 2021
Short summary
Short summary
We re-examine the uncertainty of ENSO teleconnection to the North Atlantic by considering the November–December and January–February months in the cold season, in addition to the conventional DJF months. This is motivated by previous studies reporting varying teleconnected atmospheric anomalies and the mechanisms concerned. Our results indicate an improved confidence in the patterns of the teleconnection. The finding may also have implications on research in predictability and climate impact.
Amy H. Butler and Daniela I. V. Domeisen
Weather Clim. Dynam., 2, 453–474, https://doi.org/10.5194/wcd-2-453-2021, https://doi.org/10.5194/wcd-2-453-2021, 2021
Short summary
Short summary
We classify by wave geometry the stratospheric polar vortex during the final warming that occurs every spring in both hemispheres due to a combination of radiative and dynamical processes. We show that the shape of the vortex, as well as the timing of the seasonal transition, is linked to total column ozone prior to and surface weather following the final warming. These results have implications for prediction and our understanding of stratosphere–troposphere coupling processes in springtime.
Oscar Dimdore-Miles, Lesley Gray, and Scott Osprey
Weather Clim. Dynam., 2, 205–231, https://doi.org/10.5194/wcd-2-205-2021, https://doi.org/10.5194/wcd-2-205-2021, 2021
Short summary
Short summary
Observations of the stratosphere span roughly half a century, preventing analysis of multi-decadal variability in circulation using these data. Instead, we rely on long simulations of climate models. Here, we use a model to examine variations in northern polar stratospheric winds and find they vary with a period of around 90 years. We show that this is possibly due to variations in the size of winds over the Equator. This result may improve understanding of Equator–polar stratospheric coupling.
Philip Rupp and Thomas Birner
Weather Clim. Dynam., 2, 111–128, https://doi.org/10.5194/wcd-2-111-2021, https://doi.org/10.5194/wcd-2-111-2021, 2021
Short summary
Short summary
We use the simple framework of an idealised baroclinic life cycle to study the tropospheric eddy feedback to different stratospheric conditions and, hence, obtain insights into the fundamental processes of stratosphere–troposphere coupling – in particular, the processes involved in creating the robust equatorward shift in the tropospheric mid-latitude jet that has been observed following sudden stratospheric warming events.
Julien Chartrand and Francesco S. R. Pausata
Weather Clim. Dynam., 1, 731–744, https://doi.org/10.5194/wcd-1-731-2020, https://doi.org/10.5194/wcd-1-731-2020, 2020
Short summary
Short summary
This study explores the relationship between the North Atlantic Oscillation and the winter climate of eastern North America using reanalysis data. Results show that negative phases are linked with an increase in frequency of winter storms developing on the east coast of the United States, resulting in much heavier snowfall over the eastern United States. On the contrary, an increase in cyclone activity over southeastern Canada results in slightly heavier precipitation during positive phases.
Marlene Kretschmer, Giuseppe Zappa, and Theodore G. Shepherd
Weather Clim. Dynam., 1, 715–730, https://doi.org/10.5194/wcd-1-715-2020, https://doi.org/10.5194/wcd-1-715-2020, 2020
Short summary
Short summary
The winds in the polar stratosphere affect the weather in the mid-latitudes, making it important to understand potential changes in response to global warming. However, climate model projections disagree on how this so-called polar vortex will change in the future. Here we show that sea ice loss in the Barents and Kara (BK) seas plays a central role in this. The time when the BK seas become ice-free differs between models, which explains some of the disagreement regarding vortex projections.
Irene Erner, Alexey Y. Karpechko, and Heikki J. Järvinen
Weather Clim. Dynam., 1, 657–674, https://doi.org/10.5194/wcd-1-657-2020, https://doi.org/10.5194/wcd-1-657-2020, 2020
Short summary
Short summary
In this paper we investigate the role of the tropospheric forcing in the occurrence of the sudden stratospheric warming (SSW) that took place in February 2018, its predictability and teleconnection with the Madden–Julian oscillation (MJO) by analysing the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecast. The purpose of the paper is to present the results of the analysis of the atmospheric circulation before and during the SSW and clarify the driving mechanisms.
Ales Kuchar, Petr Sacha, Roland Eichinger, Christoph Jacobi, Petr Pisoft, and Harald E. Rieder
Weather Clim. Dynam., 1, 481–495, https://doi.org/10.5194/wcd-1-481-2020, https://doi.org/10.5194/wcd-1-481-2020, 2020
Short summary
Short summary
Our study focuses on the impact of topographic structures such as the Himalayas and Rocky Mountains, so-called orographic gravity-wave hotspots. These hotspots play an important role in the dynamics of the middle atmosphere, in particular in the lower stratosphere. We study intermittency and zonally asymmetric character of these hotspots and their effects on the upper stratosphere and mesosphere using a new detection method in various modeling and observational datasets.
Daniela I. V. Domeisen, Christian M. Grams, and Lukas Papritz
Weather Clim. Dynam., 1, 373–388, https://doi.org/10.5194/wcd-1-373-2020, https://doi.org/10.5194/wcd-1-373-2020, 2020
Short summary
Short summary
We cannot currently predict the weather over Europe beyond 2 weeks. The stratosphere provides a promising opportunity to go beyond that limit by providing a change in probability of certain weather regimes at the surface. However, not all stratospheric extreme events are followed by the same surface weather evolution. We show that this weather evolution is related to the tropospheric weather regime around the onset of the stratospheric extreme event for many stratospheric events.
Bernat Jiménez-Esteve and Daniela I. V. Domeisen
Weather Clim. Dynam., 1, 225–245, https://doi.org/10.5194/wcd-1-225-2020, https://doi.org/10.5194/wcd-1-225-2020, 2020
Short summary
Short summary
Atmospheric predictability over Europe on subseasonal to seasonal timescales remains limited. However, the remote impact from the El Niño–Southern Oscillation (ENSO) can help to improve predictability. Research has suggested that the ENSO impact in the North Atlantic region is affected by nonlinearities. Here, we isolate the nonlinearities in the tropospheric pathway through the North Pacific, finding that a strong El Niño leads to a stronger and distinct impact compared to a strong La Niña.
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)...
