Articles | Volume 4, issue 4
https://doi.org/10.5194/wcd-4-1001-2023
© Author(s) 2023. 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-4-1001-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Nov 2023
Research article |
| 21 Nov 2023
| 21 Nov 2023
Intrinsic predictability limits arising from Indian Ocean Madden–Julian oscillation (MJO) heating: effects on tropical and extratropical teleconnections
Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, VA, USA
Daniela I. V. Domeisen
Faculty of Geosciences and Environment, University of Lausanne, Lausanne, Switzerland
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sarah-Jane Lock
Research Department, European Centre for Medium-Range Forecasts, Reading, UK
Franco Molteni
Research Department, European Centre for Medium-Range Forecasts, Reading, UK
Priyanka Yadav
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
ESSIC, University of Maryland, College Park, College Park, MD, USA
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Chaim I. Garfinkel, Zachary D. Lawrence, Amy H. Butler, Etienne Dunn-Sigouin, Irina Statnaia, Alexey Yu. Karpechko, Gerbrand Koren, Marta Abalos, Blanca Ayarzaguena, David Barriopedro, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Judah Cohen, Daniela I. V. Domeisen, Javier García-Serrano, Neil P. Hindley, Martin Jucker, Hera Kim, Robert W. Lee, Simon H. Lee, Marisol Osman, Froila M. Palmeiro, Inna Polichtchouk, Jian Rao, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1762, https://doi.org/10.5194/egusphere-2024-1762, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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Variability in the extratropical stratosphere and troposphere are coupled, and because of the longer timescales characteristic of the stratosphere, this allows for a window of opportunity for surface prediction. This paper assesses whether models used for operational prediction capture these coupling processes accurately. We find that most processes are too-weak, however downward coupling from the lower stratosphere to the near surface is too strong.
Rachel W.-Y. Wu, Gabriel Chiodo, Inna Polichtchouk, and Daniela I. V. Domeisen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1652, https://doi.org/10.5194/egusphere-2024-1652, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Strong variations in the strength of the stratospheric polar vortex can profoundly affect surface weather extremes, therefore, accurately predicting the stratosphere can improve surface weather forecasts. The research reveals how uncertainty in the stratosphere is linked to the troposphere. The findings suggest that refining models to better represent the identified sources and impact regions in the troposphere is likely to improve the prediction of the stratosphere and its surface impacts.
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
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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.
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024, https://doi.org/10.5194/nhess-24-1555-2024, 2024
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We combine climate projections from 30 climate models with a climate risk model to project winter windstorm damages in Europe under climate change. We study the uncertainty and sensitivity factors related to the modelling of hazard, exposure and vulnerability. We emphasize high uncertainties in the damage projections, with climate models primarily driving the uncertainty. We find climate change reshapes future European windstorm risk by altering damage locations and intensity.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Franco Molteni, Fred Kucharski, and Riccardo Farneti
Weather Clim. Dynam., 5, 293–322, https://doi.org/10.5194/wcd-5-293-2024, https://doi.org/10.5194/wcd-5-293-2024, 2024
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We describe some new features of an intermediate-complexity coupled model, including a three-layer thermodynamic ocean model suitable to explore the extratropical response to tropical ocean variability. We present results on the model climatology and show that important features of interdecadal and interannual variability are realistically simulated in a
pacemakercoupled ensemble of 70-year runs, where portions of the tropical Indo-Pacific are constrained to follow the observed variability.
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
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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.
Maria Pyrina, Wolfgang Wicker, Andries Jan de Vries, Georgios Fragkoulidis, and Daniela I. V. Domeisen
EGUsphere, https://doi.org/10.5194/egusphere-2023-3088, https://doi.org/10.5194/egusphere-2023-3088, 2024
Preprint withdrawn
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We investigate the atmospheric dynamics behind heatwaves, specifically of those occurring simultaneously across regions, known as concurrent heatwaves. We find that heatwaves are strongly modulated by Rossby wave packets, being Rossby waves whose amplitude has a local maximum and decays at larger distances. High amplitude Rossby wave packets increase the occurrence probabilities of concurrent and non-concurrent heatwaves by a factor of 15 and 18, respectively, over several regions globally.
Gabriel Chiodo, Marina Friedel, Svenja Seeber, Daniela Domeisen, Andrea Stenke, Timofei Sukhodolov, and Franziska Zilker
Atmos. Chem. Phys., 23, 10451–10472, https://doi.org/10.5194/acp-23-10451-2023, https://doi.org/10.5194/acp-23-10451-2023, 2023
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Stratospheric ozone protects the biosphere from harmful UV radiation. Anthropogenic activity has led to a reduction in the ozone layer in the recent past, but thanks to the implementation of the Montreal Protocol, the ozone layer is projected to recover. In this study, we show that projected future changes in Arctic ozone abundances during springtime will influence stratospheric climate and thereby actively modulate large-scale circulation changes in the Northern Hemisphere.
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
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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.
Raphaël de Fondeville, Zheng Wu, Enikő Székely, Guillaume Obozinski, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 287–307, https://doi.org/10.5194/wcd-4-287-2023, https://doi.org/10.5194/wcd-4-287-2023, 2023
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We propose a fully data-driven, interpretable, and computationally scalable framework to characterize sudden stratospheric warmings (SSWs), extract statistically significant precursors, and produce machine learning (ML) forecasts. By successfully leveraging the long-lasting impact of SSWs, the ML predictions outperform sub-seasonal numerical forecasts for lead times beyond 25 d. Post-processing numerical predictions using their ML counterparts yields a performance increase of up to 20 %.
Wolfgang Wicker, Inna Polichtchouk, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 81–93, https://doi.org/10.5194/wcd-4-81-2023, https://doi.org/10.5194/wcd-4-81-2023, 2023
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Sudden stratospheric warmings are extreme weather events where the winter polar stratosphere warms by about 25 K. An improved representation of small-scale gravity waves in sub-seasonal prediction models can reduce forecast errors since their impact on the large-scale circulation is predictable multiple weeks ahead. After a sudden stratospheric warming, vertically propagating gravity waves break at a lower altitude than usual, which strengthens the long-lasting positive temperature anomalies.
Marina Friedel, Gabriel Chiodo, Andrea Stenke, Daniela I. V. Domeisen, and Thomas Peter
Atmos. Chem. Phys., 22, 13997–14017, https://doi.org/10.5194/acp-22-13997-2022, https://doi.org/10.5194/acp-22-13997-2022, 2022
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In spring, winds the Arctic stratosphere change direction – an event called final stratospheric warming (FSW). Here, we examine whether the interannual variability in Arctic stratospheric ozone impacts the timing of the FSW. We find that Arctic ozone shifts the FSW to earlier and later dates in years with high and low ozone via the absorption of UV light. The modulation of the FSW by ozone has consequences for surface climate in ozone-rich years, which may result in better seasonal predictions.
Nora Bergner, Marina Friedel, Daniela I. V. Domeisen, Darryn Waugh, and Gabriel Chiodo
Atmos. Chem. Phys., 22, 13915–13934, https://doi.org/10.5194/acp-22-13915-2022, https://doi.org/10.5194/acp-22-13915-2022, 2022
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Polar vortex extremes, particularly situations with an unusually weak cyclonic circulation in the stratosphere, can influence the surface climate in the spring–summer time in the Southern Hemisphere. Using chemistry-climate models and observations, we evaluate the robustness of the surface impacts. While models capture the general surface response, they do not show the observed climate patterns in midlatitude regions, which we trace back to biases in the models' circulations.
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
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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, Irina Statnaia, 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
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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.
Rachel Wai-Ying Wu, Zheng Wu, and Daniela I.V. Domeisen
Weather Clim. Dynam., 3, 755–776, https://doi.org/10.5194/wcd-3-755-2022, https://doi.org/10.5194/wcd-3-755-2022, 2022
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Accurate predictions of the stratospheric polar vortex can enhance surface weather predictability. Stratospheric events themselves are less predictable, with strong inter-event differences. We assess the predictability of stratospheric acceleration and deceleration events in a sub-seasonal prediction system, finding that the predictability of events is largely dependent on event magnitude, while extreme drivers of deceleration events are not fully represented in the model.
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022, https://doi.org/10.5194/gmd-15-5073-2022, 2022
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This paper describes an experimental protocol focused on sudden stratospheric warmings to be carried out by subseasonal forecast modeling centers. These will allow for inter-model comparisons of these major disruptions to the stratospheric polar vortex and their impacts on the near-surface flow. The protocol will lead to new insights into the contribution of the stratosphere to subseasonal forecast skill and new approaches to the dynamical attribution of extreme events.
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
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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.
Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
Atmos. Chem. Phys., 22, 2601–2623, https://doi.org/10.5194/acp-22-2601-2022, https://doi.org/10.5194/acp-22-2601-2022, 2022
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Great progress has been made in computer modelling and simulation of the whole climate system, including the stratosphere. Since the late 20th century we also gained a much clearer understanding of how the stratosphere interacts with the lower atmosphere. The latest generation of numerical prediction systems now explicitly represents the stratosphere and its interaction with surface climate, and here we review its role in long-range predictions and projections from weeks to decades ahead.
Zheng Wu, Bernat Jiménez-Esteve, Raphaël de Fondeville, Enikő Székely, Guillaume Obozinski, William T. Ball, and Daniela I. V. Domeisen
Weather Clim. Dynam., 2, 841–865, https://doi.org/10.5194/wcd-2-841-2021, https://doi.org/10.5194/wcd-2-841-2021, 2021
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We use an advanced statistical approach to investigate the dynamics of the development of sudden stratospheric warming (SSW) events in the winter Northern Hemisphere. We identify distinct signals that are representative of these events and their event type at lead times beyond currently predictable lead times. The results can be viewed as a promising step towards improving the predictability of SSWs in the future by using more advanced statistical methods in operational forecasting systems.
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
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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.
Hilla Afargan-Gerstman, Iuliia Polkova, Lukas Papritz, Paolo Ruggieri, Martin P. King, Panos J. Athanasiadis, Johanna Baehr, and Daniela I. V. Domeisen
Weather Clim. Dynam., 1, 541–553, https://doi.org/10.5194/wcd-1-541-2020, https://doi.org/10.5194/wcd-1-541-2020, 2020
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We investigate the stratospheric influence on marine cold air outbreaks (MCAOs) in the North Atlantic using ERA-Interim reanalysis data. MCAOs are associated with severe Arctic weather, such as polar lows and strong surface winds. Sudden stratospheric events are found to be associated with more frequent MCAOs in the Barents and the Norwegian seas, affected by the anomalous circulation over Greenland and Scandinavia. Identification of MCAO precursors is crucial for improved long-range prediction.
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
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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
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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.
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, https://doi.org/10.5194/gmd-12-4425-2019, 2019
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This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.
Matthias Fischer, Daniela I. V. Domeisen, Wolfgang A. Müller, and Johanna Baehr
Earth Syst. Dynam., 8, 129–146, https://doi.org/10.5194/esd-8-129-2017, https://doi.org/10.5194/esd-8-129-2017, 2017
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In a climate projection experiment with the Max Planck Institute Earth System Model (MPI-ESM), we find that a decline in the Atlantic Ocean meridional heat transport (OHT) is accompanied by a change in the seasonal cycle of the total OHT and its components. We found a northward shift of 5° and latitude-dependent shifts between 1 and 6 months in the seasonal cycle that are mainly associated with changes in the meridional velocity field rather than the temperature field.
Related subject area
Atmospheric predictability
Understanding winter windstorm predictability over Europe
Predictable decadal forcing of the North Atlantic jet speed by sub-polar North Atlantic sea surface temperatures
Exploiting the signal-to-noise ratio in multi-system predictions of boreal summer precipitation and temperature
Uncertainty growth and forecast reliability during extratropical cyclogenesis
Convection-parameterized and convection-permitting modelling of heavy precipitation in decadal simulations of the greater Alpine region with COSMO-CLM
Improved extended-range prediction of persistent stratospheric perturbations using machine learning
Increased vertical resolution in the stratosphere reveals role of gravity waves after sudden stratospheric warmings
The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control
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Predictability of a tornado environment index from El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation
Differences in the sub-seasonal predictability of extreme stratospheric events
Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20th century
Bimodality in ensemble forecasts of 2 m temperature: identification
Flow dependence of wintertime subseasonal prediction skill over Europe
Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment
Emergence of representative signals for sudden stratospheric warmings beyond current predictable lead times
The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6
Seasonal climate influences on the timing of the Australian monsoon onset
Subseasonal prediction of springtime Pacific–North American transport using upper-level wind forecasts
A dynamic and thermodynamic analysis of the 11 December 2017 tornadic supercell in the Highveld of South Africa
How an uncertain short-wave perturbation on the North Atlantic wave guide affects the forecast of an intense Mediterranean cyclone (Medicane Zorbas)
Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks
Subseasonal midlatitude prediction skill following Quasi-Biennial Oscillation and Madden–Julian Oscillation activity
Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany
Lisa Degenhardt, Gregor C. Leckebusch, and Adam A. Scaife
Weather Clim. Dynam., 5, 587–607, https://doi.org/10.5194/wcd-5-587-2024, https://doi.org/10.5194/wcd-5-587-2024, 2024
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This study investigates how dynamical factors that are known to influence cyclone or windstorm development and strengthening also influence the seasonal forecast skill of severe winter windstorms. This study shows which factors are well represented in the seasonal forecast model, the Global Seasonal forecasting system version 5 (GloSea5), and which might need improvement to refine the forecast of severe winter windstorms.
Kristian Strommen, Tim Woollings, Paolo Davini, Paolo Ruggieri, and Isla R. Simpson
Weather Clim. Dynam., 4, 853–874, https://doi.org/10.5194/wcd-4-853-2023, https://doi.org/10.5194/wcd-4-853-2023, 2023
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We present evidence which strongly suggests that decadal variations in the intensity of the North Atlantic winter jet stream can be predicted by current forecast models but that decadal variations in its position appear to be unpredictable. It is argued that this skill at predicting jet intensity originates from the slow, predictable variability in sea surface temperatures in the sub-polar North Atlantic.
Juan Camilo Acosta Navarro and Andrea Toreti
Weather Clim. Dynam., 4, 823–831, https://doi.org/10.5194/wcd-4-823-2023, https://doi.org/10.5194/wcd-4-823-2023, 2023
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Droughts and heatwaves have become some of the clearest manifestations of a changing climate. Near-term adaptation strategies can benefit from seasonal predictions, but these predictions still have limitations. We found that an intrinsic property of multi-system forecasts can serve to better anticipate extreme high-temperature and low-precipitation events during boreal summer in several regions of the Northern Hemisphere with different levels of predictability.
Mark J. Rodwell and Heini Wernli
Weather Clim. Dynam., 4, 591–615, https://doi.org/10.5194/wcd-4-591-2023, https://doi.org/10.5194/wcd-4-591-2023, 2023
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Midlatitude storms and their downstream impacts have a major impact on society, yet their prediction is especially prone to uncertainty. While this can never be fully eliminated, we find that the initial rate of growth of uncertainty varies for a range of forecast models. Examination of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) suggests ways in which uncertainty growth could be reduced, leading to sharper and more reliable forecasts over the first few days.
Alberto Caldas-Alvarez, Hendrik Feldmann, Etor Lucio-Eceiza, and Joaquim G. Pinto
Weather Clim. Dynam., 4, 543–565, https://doi.org/10.5194/wcd-4-543-2023, https://doi.org/10.5194/wcd-4-543-2023, 2023
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We evaluate convection-permitting modelling (CPM) simulations for the greater Alpine area to assess its added value compared to a 25 km resolution. A new method for severe precipitation detection is used, and the associated synoptic weather types are considered. Our results document the added value of CPM for precipitation representation with higher intensities, better rank correlation, better hit rates, and an improved amount and structure, but with an overestimation of the rates.
Raphaël de Fondeville, Zheng Wu, Enikő Székely, Guillaume Obozinski, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 287–307, https://doi.org/10.5194/wcd-4-287-2023, https://doi.org/10.5194/wcd-4-287-2023, 2023
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We propose a fully data-driven, interpretable, and computationally scalable framework to characterize sudden stratospheric warmings (SSWs), extract statistically significant precursors, and produce machine learning (ML) forecasts. By successfully leveraging the long-lasting impact of SSWs, the ML predictions outperform sub-seasonal numerical forecasts for lead times beyond 25 d. Post-processing numerical predictions using their ML counterparts yields a performance increase of up to 20 %.
Wolfgang Wicker, Inna Polichtchouk, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 81–93, https://doi.org/10.5194/wcd-4-81-2023, https://doi.org/10.5194/wcd-4-81-2023, 2023
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Sudden stratospheric warmings are extreme weather events where the winter polar stratosphere warms by about 25 K. An improved representation of small-scale gravity waves in sub-seasonal prediction models can reduce forecast errors since their impact on the large-scale circulation is predictable multiple weeks ahead. After a sudden stratospheric warming, vertically propagating gravity waves break at a lower altitude than usual, which strengthens the long-lasting positive temperature anomalies.
Takumi Matsunobu, Christian Keil, and Christian Barthlott
Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022, https://doi.org/10.5194/wcd-3-1273-2022, 2022
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This study quantifies the impact of poorly constrained parameters used to represent aerosol–cloud–precipitation interactions on precipitation and cloud forecasts associated with uncertainties in input atmospheric states. Uncertainties in these parameters have a non-negligible impact on daily precipitation amount and largely change the amount of cloud. The comparison between different weather situations reveals that the impact becomes more important when convection is triggered by local effects.
Melissa L. Breeden, John R. Albers, and Andrew Hoell
Weather Clim. Dynam., 3, 1183–1197, https://doi.org/10.5194/wcd-3-1183-2022, https://doi.org/10.5194/wcd-3-1183-2022, 2022
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We use a statistical dynamical model to generate precipitation forecasts for lead times of 2–6 weeks over southwest Asia, which are needed to support humanitarian food distribution. The model signal-to-noise ratio is used to identify a smaller subset of forecasts with particularly high skill, so-called subseasonal forecasts of opportunity (SFOs). Precipitation SFOs are often related to slowly evolving tropical phenomena, namely the El Niño–Southern Oscillation and Madden–Julian Oscillation.
Michael K. Tippett, Chiara Lepore, and Michelle L. L’Heureux
Weather Clim. Dynam., 3, 1063–1075, https://doi.org/10.5194/wcd-3-1063-2022, https://doi.org/10.5194/wcd-3-1063-2022, 2022
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The El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) are phenomena that affect the weather and climate of North America. Although ENSO hails from from the tropical Pacific and the AO high above the North Pole, the spatial patterns of their influence on a North American tornado environment index are remarkably similar in computer models. We find that when ENSO and the AO act in concert, their impact is large, and when they oppose each other, their impact is small.
Rachel Wai-Ying Wu, Zheng Wu, and Daniela I.V. Domeisen
Weather Clim. Dynam., 3, 755–776, https://doi.org/10.5194/wcd-3-755-2022, https://doi.org/10.5194/wcd-3-755-2022, 2022
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Accurate predictions of the stratospheric polar vortex can enhance surface weather predictability. Stratospheric events themselves are less predictable, with strong inter-event differences. We assess the predictability of stratospheric acceleration and deceleration events in a sub-seasonal prediction system, finding that the predictability of events is largely dependent on event magnitude, while extreme drivers of deceleration events are not fully represented in the model.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
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Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Cameron Bertossa, Peter Hitchcock, Arthur DeGaetano, and Riwal Plougonven
Weather Clim. Dynam., 2, 1209–1224, https://doi.org/10.5194/wcd-2-1209-2021, https://doi.org/10.5194/wcd-2-1209-2021, 2021
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While the assumption of Gaussianity leads to many simplifications, ensemble forecasts often exhibit non-Gaussian distributions. This work has systematically identified the presence of a specific case of
non-Gaussianity, bimodality. It has been found that bimodality occurs in a large portion of global 2 m temperature forecasts. This has drastic implications on forecast skill as the minimum probability in a bimodal distribution often lies at the maximum probability of a Gaussian distribution.
Constantin Ardilouze, Damien Specq, Lauriane Batté, and Christophe Cassou
Weather Clim. Dynam., 2, 1033–1049, https://doi.org/10.5194/wcd-2-1033-2021, https://doi.org/10.5194/wcd-2-1033-2021, 2021
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Forecasting temperature patterns beyond 2 weeks is very challenging, although occasionally, forecasts show more skill over Europe. Our study indicates that the level of skill varies concurrently for two distinct forecast systems. It also shows that higher skill occurs when forecasts are issued during specific patterns of atmospheric circulation that tend to be particularly persistent.
These results could help forecasters estimate a priori how trustworthy extended-range forecasts will be.
Cedric G. Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, Philippe Peyrillé, and Cyrille Flamant
Weather Clim. Dynam., 2, 893–912, https://doi.org/10.5194/wcd-2-893-2021, https://doi.org/10.5194/wcd-2-893-2021, 2021
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This work assesses the forecast of the temperature over the Sahara, a key driver of the West African Monsoon, at a seasonal timescale. The seasonal models are able to reproduce the climatological state and some characteristics of the temperature during the rainy season in the Sahel. But, because of errors in the timing, the forecast skill scores are significant only for the first 4 weeks.
Zheng Wu, Bernat Jiménez-Esteve, Raphaël de Fondeville, Enikő Székely, Guillaume Obozinski, William T. Ball, and Daniela I. V. Domeisen
Weather Clim. Dynam., 2, 841–865, https://doi.org/10.5194/wcd-2-841-2021, https://doi.org/10.5194/wcd-2-841-2021, 2021
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We use an advanced statistical approach to investigate the dynamics of the development of sudden stratospheric warming (SSW) events in the winter Northern Hemisphere. We identify distinct signals that are representative of these events and their event type at lead times beyond currently predictable lead times. The results can be viewed as a promising step towards improving the predictability of SSWs in the future by using more advanced statistical methods in operational forecasting systems.
Alberto Caldas-Alvarez, Samiro Khodayar, and Peter Knippertz
Weather Clim. Dynam., 2, 561–580, https://doi.org/10.5194/wcd-2-561-2021, https://doi.org/10.5194/wcd-2-561-2021, 2021
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The prediction capabilities of GPS, operational (low-resolution) and targeted (high-resolution) radiosondes for data assimilation in a Mediterranean heavy precipitation event at different model resolutions are investigated. The results show that even if GPS provides accurate observations, their lack of vertical information hampers the improvement, demonstrating the need for assimilating radiosondes, where the location and timing of release was more determinant than the vertical resolution.
Joel Lisonbee and Joachim Ribbe
Weather Clim. Dynam., 2, 489–506, https://doi.org/10.5194/wcd-2-489-2021, https://doi.org/10.5194/wcd-2-489-2021, 2021
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Why do some monsoon seasons start early, while others start late? For the Australian monsoon, some previous research suggested the El Niño–Southern Oscillation in the months before the onset influenced the monsoon timing. This research tests if this is still correct and if other large-scale climate patterns also influenced onset timing. We found that a strong La Niña pattern usually coincided with an early onset but weak La Niña and El Niño patterns did not show a consistent pattern.
John R. Albers, Amy H. Butler, Melissa L. Breeden, Andrew O. Langford, and George N. Kiladis
Weather Clim. Dynam., 2, 433–452, https://doi.org/10.5194/wcd-2-433-2021, https://doi.org/10.5194/wcd-2-433-2021, 2021
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Weather variability controls the transport of ozone from the stratosphere to the Earth’s surface and water vapor from oceanic source regions to continental land masses. Forecasting these types of transport has high societal value because of the negative impacts of ozone on human health and the role of water vapor in governing precipitation variability. We use upper-level wind forecasts to assess the potential for predicting ozone and water vapor transport 3–6 weeks ahead of time.
Lesetja E. Lekoloane, Mary-Jane M. Bopape, Tshifhiwa Gift Rambuwani, Thando Ndarana, Stephanie Landman, Puseletso Mofokeng, Morne Gijben, and Ngwako Mohale
Weather Clim. Dynam., 2, 373–393, https://doi.org/10.5194/wcd-2-373-2021, https://doi.org/10.5194/wcd-2-373-2021, 2021
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We analysed a tornadic supercell that tracked through the northern Highveld region of South Africa for 7 h. We found that atmospheric conditions were conducive for tornado-associated severe storms over the region. A 4.4 km resolution model run by the South African Weather Service was able to predict this supercell, including its timing. However, it underestimated its severity due to underestimations of other important factors necessary for real-world development of these kinds of storms.
Raphael Portmann, Juan Jesús González-Alemán, Michael Sprenger, and Heini Wernli
Weather Clim. Dynam., 1, 597–615, https://doi.org/10.5194/wcd-1-597-2020, https://doi.org/10.5194/wcd-1-597-2020, 2020
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In September 2018 an intense Mediterranean cyclone with structural similarities to a hurricane, a so-called medicane, caused severe damage in Greece. Its development was uncertain, even just a few days in advance. The reason for this was uncertainties in the jet stream over the North Atlantic 3 d prior to cyclogenesis that propagated into the Mediterranean. They led to an uncertain position of the upper-level disturbance and, as a result, of the position and thermal structure of the cyclone.
Peter Pfleiderer, Carl-Friedrich Schleussner, Tobias Geiger, and Marlene Kretschmer
Weather Clim. Dynam., 1, 313–324, https://doi.org/10.5194/wcd-1-313-2020, https://doi.org/10.5194/wcd-1-313-2020, 2020
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Seasonal outlooks of Atlantic hurricane activity are required to enable risk reduction measures and disaster preparedness. Many seasonal forecasts are based on a selection of climate signals from which a statistical model is constructed. The crucial step in this approach is to select the most relevant predictors without overfitting. Here we show that causal effect networks can be used to identify the most robust predictors. Based on these predictors we construct a competitive forecast model.
Kirsten J. Mayer and Elizabeth A. Barnes
Weather Clim. Dynam., 1, 247–259, https://doi.org/10.5194/wcd-1-247-2020, https://doi.org/10.5194/wcd-1-247-2020, 2020
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Tropical storms are key for harnessing midlatitude weather prediction skill 2–8 weeks into the future. Recently, stratospheric activity was shown to impact tropical storminess and thus may also be important for midlatitude prediction skill on these timescales. This work analyzes two forecast systems to assess whether they capture this additional skill. We find there is enhanced prediction out through week 4 when both the tropical and stratospheric phenomena are active.
Christian Barthlott and Andrew I. Barrett
Weather Clim. Dynam., 1, 207–224, https://doi.org/10.5194/wcd-1-207-2020, https://doi.org/10.5194/wcd-1-207-2020, 2020
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The mesoscale convective system (MCS) that affected Germany at Pentecost 2014 was one of the most severe for decades. However, the predictability of this system was very low. By moving the model domain by just one grid point changed whether the MCS was successfully simulated or not. The decisive factor seems to be small differences in the initial track of the convection: cooler air near the coast inhibited development there, but tracks slightly more inland found more favorable conditions.
Cited articles
Abid, M.-A., Kucharski, K., Molteni, F., Kang, I.-S., Tompkins, A. M., and Almazroui, M.: Separating the Indian an Pacific Ocean Impacts on the Euro-Atlantic Response to ENSO and Its Transition from Early to Late Winter, J. Climate, 34, 1531–1548, 2021. a
Baldwin, M. P. and Dunkerton, T. J.: Stratospheric harbingers of anomalous weather regimes, Science, 294, 581–584, 2001. a
Balwin, M. P. and Holton, J. R.: Climatology of the Stratospheric Polar Vortex and Planetary Wave Breaking, J. Atmos. Sci., 45, 1123–1142, 1988. a
Branstator, G. and Teng, H.: Tropospheric Waveguide Teleconnections and Their Seasonality, J. Atmos. Sci., 74, 1513–1532, https://doi.org/10.1175/JAS-D-16-0305.1, 2017. a
Buizza, R., Miller, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteor. Soc., 125, 2887–2908, https://doi.org/10.1002/qj.49712556006, 1999. a
Camargo, S. J., Wheeler, M. C., and Sobel, A. H.: Diagnosis of the MJO modulation of tropical cyclogenesis using an empirical index, J. Atmos. Sci., 66, 3061–3074, 2009. a
Camargo, S. J., Camp, J., Elsberry, R. L., Gregory, P. A., Klotzbach, P., Schreck, C. J., Sobel, A. H., Ventrice, M. J., Vitart, F., Wang, Z., Wheeler, M. C., Yamaguchi, M., and Zhan, R.: Tropical cyclone prediction on subseasonal time-scales, Trop. Cyclone Res. Rev., 8, 150–165, https://doi.org/10.1016/j.tcrr.2019.10.004, 2019. a
Cassou, C.: Intraseasonal interaction between the Madden-Julian Oscillation and the North Atlantic Oscillation, Nature, 455, 523–527, https://doi.org/10.1038/nature07286, 2008. a, b
Charney, J. G.: Geostrophic Turbulence, J. Atmos. Sci., 28, 1087–1095, 1971. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm,, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally,, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011. a
Domeisen, D. I., White, C. J., Afargan-Gerstman, H., Muñoz, Á. G., Janiga, M. A., Vitart, F., Wulff, C. O., Antoine, S., Ardilouze, C., Batté, L., Bloomfield, H. C., Brayshaw, D. J., Camargo, S. J., Charlton-Pérez, A., Collins, D., Cowan, T., del Mar Chaves, M., Ferranti, L., Gómez, R., Gonzalez, P. L. M., and Romero, C. G.: Advances in the subseasonal prediction of extreme events: Relevant case studies across the globe, B. Am. Meteorol. Soc., 103, E1473–E1501, https://doi.org/10.1175/BAMS-D-20-0221.1, 2022. a
Domeisen, D. I. V., Butler, A. H., Fröhlich, K., Bittner, M., Müller, W. A., and Baehr, J.: Seasonal predictability over Europe arising from El Niño and stratospheric variability in the MPI-ESM seasonal prediction system, J. Climate, 28, 256–271, 2015. a
Domeisen, D. I. V., Garfinkel, C. I., and Butler, A. H.: The Teleconnection of El Niõ Southern Oscillation to the Stratosphere, Rev. Geophys., 57, 5–47, 2019. a
Domeisen, D. I. V., Butler, A. H., Charlton-Perez, A. J., Ayarzaguena, B., Baldwin, M. P., Dunn Sigouin, E., Furtado, J. C., Garfinkel, C. I., Hitchcock, P., Karpechko, A. Y., Kim, H., Knight, J., Lang, A. L., Lim, E.-P., Marshall, A., Roff, G., Schwartz, C., Simpson, I. R., Son, S.-W., and Taguchi, M.: The Role of the Stratosphere in Subseasonal to Seasonal Prediction: 2. Predictability Arising From Stratosphere-Troposphere Coupling, J. Geophys. Res.-Atmos., 125, e2019JD030923, https://doi.org/10.1029/2019JD030923, 2020a. a
Domeisen, D. I. V., Grams, C. M., and Papritz, L.: The role of North Atlantic–European weather regimes in the surface impact of sudden stratospheric warming events, Weather Clim. Dynam., 1, 373–388, https://doi.org/10.5194/wcd-1-373-2020, 2020b. a
ECMWF: IFS Documentation CY43R3, chap. Part V: Ensemble Prediction System, ECMWF, https://doi.org/10.21957/vk7qosxn5, 2017a. a
ECMWF: IFS Documentation CY43R3, chap. Part VII: ECWMF wave model, ECMWF, https://doi.org/10.21957/mxz9z1gb, 2017b. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Nov starts 1981–2016, ECMWF [data set], https://doi.org/10.21957/ms6x-gk09, 2023a. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Jan starts 1981–2016, ECMWF [data set], https://doi.org/10.21957/qtqh-5r32, 2023b. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Nov starts 1981–2016 that include MJO in phases 2 or 3, ECMWF [data set], https://doi.org/10.21957/tzgp-tv45, 2023c. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Nov starts 1981–2016 that include MJO in phases 2 or 3, ECMWF [data set], https://doi.org/10.21957/cf3y-0343, 2023d. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Jan starts 1981–2016 that include MJO in phases 2 or 3, ECMWF [data set], https://doi.org/10.21957/ndqr-vs12, 2023e. a
ECMWF Research Department: Extended-range ensemble reforecasts for 1 Nov starts 1981–2016 that include MJO in phases 2 or 3, ECMWF [data set], https://doi.org/10.21957/kt7k-1r77, 2023f. a
Ferranti, L., Palmer, T. N., Molteni, F., and Klinker, E.: Tropical-Extratropical Interaction Associated with the 30–60 Day Oscillation and Its Impact on Medium and Extended Range Prediction, J. Atmos. Sci., 47, 2177–2199, https://doi.org/10.1175/1520-0469(1990)047<2177:TEIAWT>2.0.CO;2, 1990. a
Garfinkel, C. I. and Schwartz, C.: MJO-Related Tropical Convection Anomalies Lead to More Accurate Stratospheric Vortex Variability in Subseasonal Forecast Models, Geophys. Res. Lett., 44, 10054–10062, https://doi.org/10.1002/2017GL074470, 2017. a, b
Goosse, H. and Fichefet, T.: Importance of ice-ocean interactions for the global ocean circulation: A model study, J. Geophys. Res.-Oceans, 104, 23337–23355, https://doi.org/10.1029/1999JC900215, 1999. a
Hall, J. D., Matthews, A. J., and Karoli, D. J.: The modulation of tropical cyclone activity in the Australian region by the Madden-Julian Oscillation, Mon. Weather Rev., 129, 2970–2982, 2001. 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., Manuel. F., 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, 199 – 2049, https://doi.org/10.1002/qj.3803, 2020. a
Jones, C., Waliser, D. E., Lau, K. M., and Stern, W.: Global Occurrences of Extreme Precipitation and the Madden–Julian Oscillation: Observations and Predictability, J. Climate, 17, 4575–4589, https://doi.org/10.1175/3238.1, 2004. a
Kang, W. and Tziperman, E.: The MJO-SSW Teleconnection: Interaction Between MJO-Forced Waves and the Midlatitude Jet, Geophys. Res. Lett., 45, 4400–4409, https://doi.org/10.1029/2018GL077937, 2018. a
Lee, C.-Y., Camargo, S. J., Vitart, F., Sobel, A. H., and Tippett, M. K.: Subseasonal Tropical Cyclone Genesis Prediction and MJO in the S2S Dataset, Weather Forecast., 33, 967–988, https://doi.org/10.1175/WAF-D-17-0165.1, 2018. a
Lee, R. W., Woolnough, S. J., Charlton-Perez, A. J., and Vitart, F.: ENSO Modulation of MJO Teleconnections to the North Atlantic and Europe, Geophys. Res. Lett., 46, 13535–13545, https://doi.org/10.1029/2019GL084683, 2019. a
Lee, Y.-Y. and Lim, G.-H.: Dependency of the North Pacific winter storm tracks on the zonal distribution of MJO convection, J. Geophys. Res., 117, D14101, https://doi.org/10.1029/2011JD016417, 2012. a
Leroy, A. and Wheeler, M. C.: Statistical prediction of weekly tropical cyclone activity in the southern hemisphere, Mon. Weather Rev., 136, 3637–3654, 2008. a
Leutbecher, M., Lock, S.-J., Ollinaho, P., Lang, S. T. K., Balsamo, G., Bechtold, P., Bonavita, M., Christensen, H. M., Diamantakis, M., Dutra, E., English, S., Fisher, M., Forbes, R. M., Goddard, J., Haiden, T., Hogan, R. J., Juricke, S., Lawrence, H., MacLeod, D., Magnusson, L., Malardel, S., Massart, S., Sandu, I., Smolarkiewicz, P. K., Subramanian, A., Vitart, F., Wedi, N., and Weisheimer, A.: Stochastic representations of model uncertainties at ECMWF: state of the art and future vision, Q. J. Roy. Meteor. Soc., 143, 2315–2339, https://doi.org/10.1002/qj.3094, 2017. a, b, c
Li, Z., Peng, J., and Zhang, L.: Spectral budget of Rotational and Divergent Kinetic Energy in Global Analyses, J. Atmos. Sci., 80, 813–831, 2023. a
Lin, H. and Brunet, G.: The influence of the Madden–Julian oscillation on Canadian wintertime surface air temperature, Mon. Weather Rev., 137, 2250–2262, 2009. a
Lin, H., Brunet, G., and Derome, J.: An Observed Connection between the North Atlantic Oscillation and the Madden-Julian Oscillation, J. Climate, 22, 364–380, https://doi.org/10.1175/2008JCLI2515.1, 2009. a, b
Lin, H., Brunet, G., and Fontecilla, J. S.: Impact of the Madden-Julian Oscillation on the intraseasonal forecast skill of the North Atlantic Oscillation, Geophys. Res. Lett., 37, L19803, https://doi.org/10.1029/2010GL044315, 2010. a
Madden, R. A. and Julian, P. R.: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific, J. Atmos. Sci., 28, 702–708, 1971. a
Madden, R. A. and Julian, P. R.: Description of global-scale circulation cells in the tropics with a 40–50 day period, J. Atmos. Sci., 29, 1109–1123, 1972. a
Madec, G. and the NEMO team: NEMO ocean engine, Notes du Pôle de modẽlisation de l'Institut Pierre-Simon Laplace (IPSL), 915–934, https://doi.org/10.5281/zenodo.1475234, 2013. a
Maloney, E. D. and Hartmann, D. L.: Modulation of hurricane activity in the Gulf of Mexico by the Madden-Julian oscillation, Science, 287, 2002–2004, 2000. a
Matthews, A. J., Hoskins, B. J., and Masutani, M.: The global response to tropical heating in the Madden-Julian oscillation during the northern winter, Q. J. Roy. Meteor. Soc., 130, 1991–2011, https://doi.org/10.1256/qj.02.123, 2004. a, b
Merryfield, W. J., Baehr, J., Batté, L., Becker, E. J., Butler, A. H., Coelho, C. A. S., Danabasoglu, G., Dirmeyer, P. A., Doblas-Reyes, F. J., Domeisen, D. I. V., Ferranti, L., Ilynia, T., Kumar, A., Müller, W. A., Rixen, M., Robertson, A. W., Smith, D. M., Takaya, Y., Tuma, M., Vitart, F., White, C. J., Alvarez, M. S., Ardilouze, C., Attard, H., Baggett, C., Balmaseda, M. A., Beraki, A. F., Bhattacharjee, P. S., Bilbao, R., de Andrade, F. M., DeFlorio, M. J., Díaz, L. B., Ehsan, M. A., Fragkoulidis, G., Grainger, S., Green, B. W., Hell, M. C., Infanti, J. M., Isensee, K., Kataoka, T., Kirtman, B. P., Klingaman, N. P., Lee, J.-Y., Mayer, K., McKay, R., Mecking, J. V., Miller, D. E., Neddermann, N., Justin Ng, C. H., Osso, A., Pankatz, K., Peatman, S., Pegion, K., Perlwitz, J., Recalde-Coronel, G. C., Reintges, A., Renkl, C., Solaraju-Murali, B., Spring, A., Stan, C., Sun, Y. Q., Tozer, C. R., Vigaud, N., Woolnough, S., and Yeager, S.: Current and Emerging Developments in Subseasonal to Decadal Prediction, B. Am. Meteorol. Soc., 101, E869–E896, 2020. a
Muñoz, Á. G., Goddard, L., Mason, S. J., and Robertson, A. W.: Cross–time scale interactions and rainfall extreme events in southeastern South America for the austral summer. Part II: Predictive skill, J. Climate, 29, 5915–5934, 2016. a
Quinting, J., Grams, C. M., Chang, E. K.-M., Pfahl, S., and Wernli, H.: Warm conveyor belt activity over the Pacific: Modulation by the Madden-Julian Oscillation and impact on tropical-extratropical teleconnections, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-783, 2023. a
Rodney, M., Lin, H., and Derome, J.: Subseasonal Prediction of Wintertime North American Surface Air Temperature during Strong MJO Events, Mon. Weather Rev., 141, 2897–2909, 2013. a
Schwartz, C. and Garfinkel, C. I.: Troposphere-Stratosphere Coupling in Subseasonal-to-Seasonal Models and its Importance for a Realistic Extratropical Response to the Madden-Julian Oscillation, J. Geophys. Res.-Atmos., 125, e2019JD032043, https://doi.org/10.1029/2019JD032043, 2020. a, b, c, d
Schwartz, C., Garfinkel, C. I., Yadav, P., Chen, W., and Domeisen, D. I. V.: Stationary wave biases and their effect on upward troposphere– stratosphere coupling in sub-seasonal prediction models, Weather Clim. Dynam., 3, 679–692, https://doi.org/10.5194/wcd-3-679-2022, 2022. a
Selz, T.: Estimating the Intrinsic Limit of Predictability Using a Stochastic Convection Scheme, J. Atmos. Sci., 76, 757–765, 2019. a
Stan, C., Straus, D. M., Frederiksen, J. S., Lin, H., Maloney, E. D., and Schumacher, C.: Review of tropical-extratropical teleconnections on intraseasonal time scales, Rev. Geophys., 55, 902–937, 2017. a
Stan, C., Zheng, C., Chang, E. K.-M., Domeisen, D. I., Garfinkel, C. I., Jenney, A. M., Kim, H., Lim, Y.-K., Lin, H., Robertson, A., Schwartz, C., Vitart, F., Wang, J., and Yadav, P.: Advances in the prediction of MJO-Teleconnections in the S2S forecast systems, B. Am. Meteorol. Soc., 103, E1426–E1447, https://doi.org/10.1175/BAMS-D-21-0130.1, 2022. a, b, c, d
Straus, D. M.: On the role of the seasonal cycle, J. Atmos. Sci., 40, 303–313, 1983. a
Straus, D. M., Swenson, E., and Lappen, C.-L.: The MJO Cycle Forcing of the North Atlantic Circulation: Intervention Experiments with the Community Earth System Model, J. Atmos. Sci., 72, 660–681, https://doi.org/10.1175/JAS-D-14-0145.1, 2015. a
Sun, Y. Q., Rotunno, R., and Zhang., F.: Contributions of Moist Convection and Internal Gravity Waves to Building the Atmospheric
Swenson, E. T. and Straus, D. M.: A modelling framework for a better understanding of the tropically-forced component of the Indian monsoon variability, J. Earth Syst. Sci., 130, 7, https://doi.org/10.1007/s12040-020-01503-z, 2021. a
Valadão, C. E., Carvalho, L. M., Lucio, P. S., and Chaves, R. R.: Impacts of the Madden-Julian oscillation on intraseasonal precipitation over Northeast Brazil, Int. J. Climatol., 37, 1859–1884, 2017. a
Vitart, F.: Evolution of ECMWF sub-seasonal forecast skill scores, Q. J. Roy. Meteor. Soc., 140, 1889–1899, https://doi.org/10.1002/qj.2256, 2014. a
Vitart, F.: Madden-Julian Oscillation prediction and teleconnections in the S2S database, Q. J. Roy. Meteor. Soc., 143, 2210–2220, 2017. a
Vitart, F., Ardilouze, C., Bonet, A., Brookshaw, A., Chen, M., Codorean, C., Déqué, M., Ferranti, L., Fucile, E., Fuentes, M., Hendon, H., Hodgson, J., Kang, H.-S., Kumar, A., Lin, H., Liu, G., Liu, X., Malguzzi, P., Mallas, I., Manoussakis, M., Mastrangelo, D., MacLachlan, C., McLean, P., Minami, A., Mladek, R., Nakazawa, T., Najm, S, Nie, Y., Rixen, M., Robertson, A. W., Ruti, P., Sun, S., Takaya, Y., Tolstykh, M., Venuti, F., Waliser, D., Woolnough, S., Wu, T., Won, D.-J., Xiao, H., Zaripov, R., and Zhang, L.: The subseasonal to seasonal (S2S) prediction project database, B. Am. Meteorol. Soc., 98, 163–173, 2017. a, b, c
Wang, J., Kim, H., Kim, D., Henderson, S. A., Stan, C., and Maloney, E. D.: MJO teleconnections over the PNA region in climate models. Part II: Impacts of the MJO and basic state, J. Climate, 33, 5081–5101, 2020. a
Wang, J., DeFlorio, M. J., Guan, B., and Castellano, C. M.: Seasonality of MJO Impacts on Precipitation Extrems over the Western United States, J. Hydrometeorol., 24, 151–166, 2023. a
Yadav, P. and Straus, D. M.: Circulation Response to Fast and Slow MJO Episodes, Mon. Weather Rev., 145, 1577–1596, https://doi.org/10.1175/MWR-D-16-0352.1, 2017. a
Zagar, N., Jelic, D., Blaauw, M., and Bechtold, P.: Energy Spectra and Intertia-Gravity Waves in Global Analyses, J. Atmos. Sci., 74, 2447–2466, 2017. a
Zhao, Y.-B., Žagar, N., Lunkeit, F., and Blender, R.: Atmospheric bias teleconnections associated with systematic SST errors in the tropical Indian Ocean, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-917, 2023. a
Short summary
The global response to the Madden–Julian oscillation (MJO) is potentially predictable. Yet the diabatic heating is uncertain even within a particular episode of the MJO. Experiments with a global model probe the limitations imposed by this uncertainty. The large-scale tropical heating is predictable for 25 to 45 d, yet the associated Rossby wave source that links the heating to the midlatitude circulation is predictable for 15 to 20 d. This limitation has not been recognized in prior work.
The global response to the Madden–Julian oscillation (MJO) is potentially predictable. Yet the...
