Articles | Volume 2, issue 3
https://doi.org/10.5194/wcd-2-841-2021
© Author(s) 2021. 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-2-841-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2021
Research article |
| 07 Sep 2021
| 07 Sep 2021
Emergence of representative signals for sudden stratospheric warmings beyond current predictable lead times
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
Bernat Jiménez-Esteve
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
Raphaël de Fondeville
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
Enikő Székely
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
Guillaume Obozinski
Swiss Data Science Center, ETH Zürich and EPFL, Zurich, Switzerland
William T. Ball
Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, TU Delft, Delft, the Netherlands
Daniela I. V. Domeisen
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
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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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Marina Friedel, Gabriel Chiodo, Andrea Stenke, Daniela I. V. Domeisen, and Thomas Peter
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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.
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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, Irene Erner, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
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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
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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.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
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A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
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.
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021, https://doi.org/10.5194/gmd-14-5525-2021, 2021
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This paper features the new atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0 and its validation. The model performance is evaluated against reanalysis products and observations of atmospheric circulation and trace gas distribution, with a focus on stratospheric processes. Although we identified some problems to be addressed in further model upgrades, we demonstrated that SOCOLv4.0 is already well suited for studies related to chemistry–climate–aerosol interactions.
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.
Simone Dietmüller, Hella Garny, Roland Eichinger, and William T. Ball
Atmos. Chem. Phys., 21, 6811–6837, https://doi.org/10.5194/acp-21-6811-2021, https://doi.org/10.5194/acp-21-6811-2021, 2021
Margot Clyne, Jean-Francois Lamarque, Michael J. Mills, Myriam Khodri, William Ball, Slimane Bekki, Sandip S. Dhomse, Nicolas Lebas, Graham Mann, Lauren Marshall, Ulrike Niemeier, Virginie Poulain, Alan Robock, Eugene Rozanov, Anja Schmidt, Andrea Stenke, Timofei Sukhodolov, Claudia Timmreck, Matthew Toohey, Fiona Tummon, Davide Zanchettin, Yunqian Zhu, and Owen B. Toon
Atmos. Chem. Phys., 21, 3317–3343, https://doi.org/10.5194/acp-21-3317-2021, https://doi.org/10.5194/acp-21-3317-2021, 2021
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This study finds how and why five state-of-the-art global climate models with interactive stratospheric aerosols differ when simulating the aftermath of large volcanic injections as part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP). We identify and explain the consequences of significant disparities in the underlying physics and chemistry currently in some of the models, which are problems likely not unique to the models participating in this study.
Arseniy Karagodin-Doyennel, Eugene Rozanov, Ales Kuchar, William Ball, Pavle Arsenovic, Ellis Remsberg, Patrick Jöckel, Markus Kunze, David A. Plummer, Andrea Stenke, Daniel Marsh, Doug Kinnison, and Thomas Peter
Atmos. Chem. Phys., 21, 201–216, https://doi.org/10.5194/acp-21-201-2021, https://doi.org/10.5194/acp-21-201-2021, 2021
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The solar signal in the mesospheric H2O and CO was extracted from the CCMI-1 model simulations and satellite observations using multiple linear regression (MLR) analysis. MLR analysis shows a pronounced and statistically robust solar signal in both H2O and CO. The model results show a general agreement with observations reproducing a negative/positive solar signal in H2O/CO. The pattern of the solar signal varies among the considered models, reflecting some differences in the model setup.
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.
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Short summary
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.
We use an advanced statistical approach to investigate the dynamics of the development of sudden...
