Articles | Volume 12, issue 1
https://doi.org/10.5194/esd-12-353-2021
© 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/esd-12-353-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Mar 2021
Research article |
| 31 Mar 2021
| 31 Mar 2021
A climate network perspective on the intertropical convergence zone
Frederik Wolf
CORRESPONDING AUTHOR
Research Domain IV – Complexity Science, Potsdam Institute for Climate Impact Research (PIK) – Member of the Leibniz Association,
Potsdam, Germany
Department of Physics, Humboldt University,
Berlin, Germany
Aiko Voigt
Institute of Meteorology and Climate Research, Department Troposphere Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Lamont–Doherty Earth Observatory, Columbia University in the City of New York, NY, USA
Reik V. Donner
Research Domain IV – Complexity Science, Potsdam Institute for Climate Impact Research (PIK) – Member of the Leibniz Association,
Potsdam, Germany
Department of Water, Environment, Construction and Safety, Magdeburg–Stendal University of Applied Sciences,
Magdeburg, Germany
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Sylvia C. Sullivan, Aiko Voigt, Edgardo Sepúlveda Araya, Silvia Bucci, Annette Miltenberger, Meredith K. Kupinski, Christian Rolf, and Martina Krämer
Atmos. Chem. Phys., 26, 1685–1698, https://doi.org/10.5194/acp-26-1685-2026, https://doi.org/10.5194/acp-26-1685-2026, 2026
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We assess the temperature, moisture, and dynamics in the upper troposphere-lower stratosphere simulated over South Asia in a high-resolution model relative to aircraft data. The lower stratosphere tends to be too warm, too dry, and too quiescent in the model, and as a result, too few ice clouds are predicted to form there. These biases could affect radiative balance and circulation in other areas also, as significant upward transport of moisture and pollutants occurs during the Asian monsoon.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
Geosci. Model Dev., 18, 7735–7761, https://doi.org/10.5194/gmd-18-7735-2025, https://doi.org/10.5194/gmd-18-7735-2025, 2025
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The Next Generation of Earth Modeling Systems project (nextGEMS) developed two Earth system models that use horizontal grid spacing of 10 km and finer, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS simulated the Earth System climate over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Noémie Ehstand, Reik V. Donner, Cristóbal López, Marcelo Barreiro, and Emilio Hernández-García
Nonlin. Processes Geophys., 32, 367–382, https://doi.org/10.5194/npg-32-367-2025, https://doi.org/10.5194/npg-32-367-2025, 2025
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The Madden–Julian Oscillation (MJO) is a large-scale tropical wave of enhanced and suppressed rainfall, slowly moving eastward along the equator and influencing the weather and climate globally. We study the MJO using a simplified model designed to capture its large-scale features. We introduce new, more realistic model inputs, show that this enhanced model successfully replicates key characteristics of the MJO, and identify some of its limitations.
Blaž Gasparini, Rachel Atlas, Aiko Voigt, Martina Krämer, and Peter N. Blossey
Atmos. Chem. Phys., 25, 9957–9979, https://doi.org/10.5194/acp-25-9957-2025, https://doi.org/10.5194/acp-25-9957-2025, 2025
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The evolution of tropical cirrus clouds is poorly understood, which contributes to large uncertainties in climate projections. To address this issue, we use novel tracers in a cloud-resolving model to track the life cycle of cirrus clouds. This approach provides insights into cloud formation, ice crystal evolution, and radiative effects of cirrus clouds. Additionally, we improve the model's cloud microphysics using a simple, computationally efficient approach that can be applied to other models.
Edgardo I. Sepulveda Araya, Sylvia C. Sullivan, and Aiko Voigt
Atmos. Chem. Phys., 25, 8943–8958, https://doi.org/10.5194/acp-25-8943-2025, https://doi.org/10.5194/acp-25-8943-2025, 2025
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Clouds composed of ice crystals are key when evaluating atmospheric radiation. The morphology of the crystals found in clouds is not clear yet, and even less clear is the impact on the cloud heating rate, which is essential to describe precipitation and wind patterns. This motivated us to study how the heating rate behaves under a variety of ice complexity and environmental conditions, finding that increasing complexity in high and dense clouds weakens the heating rate.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Julianna Carvalho-Oliveira, Giorgia Di Capua, Leonard F. Borchert, Reik V. Donner, and Johanna Baehr
Weather Clim. Dynam., 5, 1561–1578, https://doi.org/10.5194/wcd-5-1561-2024, https://doi.org/10.5194/wcd-5-1561-2024, 2024
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We demonstrate with a causal analysis that an important recurrent summer atmospheric pattern, the so-called East Atlantic teleconnection, was influenced by the extratropical North Atlantic in spring during the second half of the 20th century. This causal link is, however, not well represented by our evaluated seasonal climate prediction system. We show that simulations able to reproduce this link show improved surface climate prediction credibility over those that do not.
Aiko Voigt, Stefanie North, Blaž Gasparini, and Seung-Hee Ham
Atmos. Chem. Phys., 24, 9749–9775, https://doi.org/10.5194/acp-24-9749-2024, https://doi.org/10.5194/acp-24-9749-2024, 2024
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Clouds shape weather and climate by interacting with photons, which changes temperatures within the atmosphere. We assess how well CMIP6 climate models capture this radiative heating by clouds within the atmosphere. While we find large differences among models, especially in cold regions of the atmosphere with abundant ice clouds, we also demonstrate that physical understanding allows us to predict the response of clouds and their radiative heating near the tropopause to climate change.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
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Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Behrooz Keshtgar, Aiko Voigt, Bernhard Mayer, and Corinna Hoose
Atmos. Chem. Phys., 24, 4751–4769, https://doi.org/10.5194/acp-24-4751-2024, https://doi.org/10.5194/acp-24-4751-2024, 2024
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Cloud-radiative heating (CRH) affects extratropical cyclones but is uncertain in weather and climate models. We provide a framework to quantify uncertainties in CRH within an extratropical cyclone due to four factors and show that the parameterization of ice optical properties contributes significantly to uncertainty in CRH. We also argue that ice optical properties, by affecting CRH on spatial scales of 100 km, are relevant for the large-scale dynamics of extratropical cyclones.
Johannes Hörner and Aiko Voigt
Earth Syst. Dynam., 15, 215–223, https://doi.org/10.5194/esd-15-215-2024, https://doi.org/10.5194/esd-15-215-2024, 2024
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Snowball Earth refers to a climate in the deep past of the Earth where the whole planet was covered in ice. Waterbelt states, where a narrow region of open water remains at the Equator, have been discussed as an alternative scenario, which might explain how life was able to survive these periods. Here, we demonstrate how waterbelt states are influenced by the thermodynamical sea-ice model used. The sea-ice model modulates snow on ice, ice albedo and ultimately the stability of waterbelt states.
David Docquier, Giorgia Di Capua, Reik V. Donner, Carlos A. L. Pires, Amélie Simon, and Stéphane Vannitsem
Nonlin. Processes Geophys., 31, 115–136, https://doi.org/10.5194/npg-31-115-2024, https://doi.org/10.5194/npg-31-115-2024, 2024
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Identifying causes of specific processes is crucial in order to better understand our climate system. Traditionally, correlation analyses have been used to identify cause–effect relationships in climate studies. However, correlation does not imply causation, which justifies the need to use causal methods. We compare two independent causal methods and show that these are superior to classical correlation analyses. We also find some interesting differences between the two methods.
Giorgia Di Capua, Dim Coumou, Bart van den Hurk, Antje Weisheimer, Andrew G. Turner, and Reik V. Donner
Weather Clim. Dynam., 4, 701–723, https://doi.org/10.5194/wcd-4-701-2023, https://doi.org/10.5194/wcd-4-701-2023, 2023
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Heavy rainfall in tropical regions interacts with mid-latitude circulation patterns, and this interaction can explain weather patterns in the Northern Hemisphere during summer. In this analysis we detect these tropical–extratropical interaction pattern both in observational datasets and data obtained by atmospheric models and assess how well atmospheric models can reproduce the observed patterns. We find a good agreement although these relationships are weaker in model data.
Sylvia Sullivan, Behrooz Keshtgar, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Hilke Lentink, Georgios Papavasileiou, and Aiko Voigt
Geosci. Model Dev., 16, 3535–3551, https://doi.org/10.5194/gmd-16-3535-2023, https://doi.org/10.5194/gmd-16-3535-2023, 2023
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Clouds absorb and re-emit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing; whether we describe convection approximately or exactly; and the level of detail used to describe small-scale processes, or microphysics, in clouds.
Behrooz Keshtgar, Aiko Voigt, Corinna Hoose, Michael Riemer, and Bernhard Mayer
Weather Clim. Dynam., 4, 115–132, https://doi.org/10.5194/wcd-4-115-2023, https://doi.org/10.5194/wcd-4-115-2023, 2023
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Forecasting extratropical cyclones is challenging due to many physical factors influencing their behavior. One such factor is the impact of heating and cooling of the atmosphere by the interaction between clouds and radiation. In this study, we show that cloud-radiative heating (CRH) increases the intensity of an idealized cyclone and affects its predictability. We find that CRH affects the cyclone mostly via increasing latent heat release and subsequent changes in the synoptic circulation.
Anubhav Choudhary and Aiko Voigt
Weather Clim. Dynam., 3, 1199–1214, https://doi.org/10.5194/wcd-3-1199-2022, https://doi.org/10.5194/wcd-3-1199-2022, 2022
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The warm conveyor belt (WCB), which is a stream of coherently rising air parcels, is an important feature of extratropical cyclones. This work presents the impact of model grid spacing on simulation of cloud diabatic processes in the WCB of a North Atlantic cyclone. We find that the refinement of the model grid systematically enhances the dynamical properties and heat releasing processes within the WCB. However, this pattern does not have a strong impact on the strength of associated cyclones.
Aiko Voigt, Petra Schwer, Noam von Rotberg, and Nicole Knopf
Geosci. Model Dev., 15, 7489–7504, https://doi.org/10.5194/gmd-15-7489-2022, https://doi.org/10.5194/gmd-15-7489-2022, 2022
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
Tommaso Alberti, Reik V. Donner, and Stéphane Vannitsem
Earth Syst. Dynam., 12, 837–855, https://doi.org/10.5194/esd-12-837-2021, https://doi.org/10.5194/esd-12-837-2021, 2021
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We provide a novel approach to diagnose the strength of the ocean–atmosphere coupling by using both a reduced order model and reanalysis data. Our findings suggest the ocean–atmosphere dynamics presents a rich variety of features, moving from a chaotic to a coherent coupled dynamics, mainly attributed to the atmosphere and only marginally to the ocean. Our observations suggest further investigations in characterizing the occurrence and spatial dependency of the ocean–atmosphere coupling.
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Short summary
In our work, we employ complex networks to study the relation between the time mean position of the intertropical convergence zone (ITCZ) and sea surface temperature (SST) variability. We show that the information hidden in different spatial SST correlation patterns, which we access utilizing complex networks, is strongly correlated with the time mean position of the ITCZ. This research contributes to the ongoing discussion on drivers of the annual migration of the ITCZ.
In our work, we employ complex networks to study the relation between the time mean position of...
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