Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-6985-2022
© 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/gmd-15-6985-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
16 Sep 2022
Development and technical paper |
| 16 Sep 2022
| 16 Sep 2022
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
Marco A. Giorgetta
CORRESPONDING AUTHOR
Max-Planck-Institut für Meteorologie, Hamburg, Germany
William Sawyer
Centro Svizzero di Calcolo Scientifico, Lugano, Switzerland
Xavier Lapillonne
Bundesamt für Meteorologie und Klimatologie MeteoSchweiz, Zürich-Flughafen, Switzerland
Panagiotis Adamidis
Deutsches Klimarechenzentrum, Hamburg, Germany
Dmitry Alexeev
NVIDIA, Zürich, Switzerland
Valentin Clément
Center for Climate Systems Modeling, ETH, Zürich, Switzerland
Remo Dietlicher
Bundesamt für Meteorologie und Klimatologie MeteoSchweiz, Zürich-Flughafen, Switzerland
Jan Frederik Engels
Deutsches Klimarechenzentrum, Hamburg, Germany
Monika Esch
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Henning Franke
Max-Planck-Institut für Meteorologie, Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Hamburg, Germany
Claudia Frauen
Deutsches Klimarechenzentrum, Hamburg, Germany
Walter M. Hannah
Lawrence Livermore National Laboratory, Livermore, USA
Benjamin R. Hillman
Sandia National Laboratories, Albuquerque, USA
Luis Kornblueh
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Philippe Marti
Center for Climate Systems Modeling, ETH, Zürich, Switzerland
Matthew R. Norman
Oak Ridge National Laboratory, Oak Ridge, USA
Robert Pincus
Lamont-Doherty Earth Observatory, Columbia University, Palisades, USA
Sebastian Rast
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Daniel Reinert
Deutscher Wetterdienst, Offenbach, Germany
Reiner Schnur
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Uwe Schulzweida
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Bjorn Stevens
Max-Planck-Institut für Meteorologie, Hamburg, Germany
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
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Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
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Jennifer Schröter, Daniel Rieger, Christian Stassen, Heike Vogel, Michael Weimer, Sven Werchner, Jochen Förstner, Florian Prill, Daniel Reinert, Günther Zängl, Marco Giorgetta, Roland Ruhnke, Bernhard Vogel, and Peter Braesicke
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The flexible tracer framework within ICON-ART 2.1 suits the demands of a large variety of different applications ranging from numerical weather prediction to climate integrations.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
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Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
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H. Wan, M. A. Giorgetta, G. Zängl, M. Restelli, D. Majewski, L. Bonaventura, K. Fröhlich, D. Reinert, P. Rípodas, L. Kornblueh, and J. Förstner
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study examines the physical link between subtropical highs and stratocumulus variability. Using reanalysis data, we test two proposed pathways—one at the surface and one in the free troposphere—but find that neither is a dominant mechanism for stratocumulus variability on seasonal and interannual timescales. These results challenge the assumed influence of subtropical highs on stratocumulus and highlight the need for further research into lower tropospheric stability dynamics.
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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
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere 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.
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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Claudia Christine Stephan and Bjorn Stevens
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Tropical precipitation cluster area and intensity distributions follow power laws, but the physical processes responsible for this behavior remain unknown. We analyze global simulations that realistically represent precipitation processes. We consider Earth-like planets as well as virtual planets to realize different types of large-scale dynamics. Our finding is that power laws in Earth’s precipitation cluster statistics stem from the robust power laws in Earth’s atmospheric wind field.
John Patrick Dunne, Helene T. Hewitt, Julie Arblaster, Frédéric Bonou, Olivier Boucher, Tereza Cavazos, Paul J. Durack, Birgit Hassler, Martin Juckes, Tomoki Miyakawa, Matthew Mizielinski, Vaishali Naik, Zebedee Nicholls, Eleanor O’Rourke, Robert Pincus, Benjamin M. Sanderson, Isla R. Simpson, and Karl E. Taylor
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Lukas Kluft, Bjorn Stevens, Manfred Brath, and Stefan A. Buehler
EGUsphere, https://doi.org/10.5194/egusphere-2024-3829, https://doi.org/10.5194/egusphere-2024-3829, 2024
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Using a single column model, we investigate the effect of the vertical distribution of clouds on climate sensitivity. We show that, depending on their height, clouds can mask or unmask the radiative response of the clear-sky atmosphere. Our single column model yields an all-sky climate sensitivity of 2.2 K, slightly less than the clear-sky value. This value can be interpreted as a baseline to which changes in surface albedo and an assumed reduction in cloud albedo would add.
Pin-Hsin Hu, Christian H. Reick, Reiner Schnur, Axel Kleidon, and Martin Claussen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-111, https://doi.org/10.5194/gmd-2024-111, 2024
Preprint under review for GMD
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We introduce the new plant functional diversity model JeDi-BACH, a novel tool that integrates the Jena Diversity Model (JeDi) within the land component of the ICON Earth System Model. JeDi-BACH captures a richer set of plant trait variations based on environmental filtering and functional tradeoffs without a priori knowledge of the vegetation types. JeDi-BACH represents a significant advancement in modeling the complex interactions between plant functional diversity and climate.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco A. Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-2508, https://doi.org/10.5194/egusphere-2024-2508, 2024
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Ann Kristin Naumann, Monika Esch, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2024-2268, https://doi.org/10.5194/egusphere-2024-2268, 2024
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This study explores how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in the global storm-resolving model ICON. The results point to the importance of the fall speed of hydrometeor particles and to a simple relationship: the faster a condensate falls, the less there is of it. Implications for the energy balance and precipitation properties are discussed.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Bjorn Stevens and Lukas Kluft
Atmos. Chem. Phys., 23, 14673–14689, https://doi.org/10.5194/acp-23-14673-2023, https://doi.org/10.5194/acp-23-14673-2023, 2023
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A simple model is introduced to account for the spectral diversity of radiant energy transfer. It provides an improved basis for assessing the different ways in which clouds influence Earth’s climate sensitivity, demonstrating how many cloud effects depend on the existing cloud climatology. Given existing assessments of changes in cloud albedo with warming, it is determined that clouds reduce Earth's climate sensitivity as compared to what it would be in a counterfactual world without clouds.
Ruoyi Cui, Nikolina Ban, Marie-Estelle Demory, Raffael Aellig, Oliver Fuhrer, Jonas Jucker, Xavier Lapillonne, and Christoph Schär
Weather Clim. Dynam., 4, 905–926, https://doi.org/10.5194/wcd-4-905-2023, https://doi.org/10.5194/wcd-4-905-2023, 2023
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Our study focuses on severe convective storms that occur over the Alpine-Adriatic region. By running simulations for eight real cases and evaluating them against available observations, we found our models did a good job of simulating total precipitation, hail, and lightning. Overall, this research identified important meteorological factors for hail and lightning, and the results indicate that both HAILCAST and LPI diagnostics are promising candidates for future climate research.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
André Ehrlich, Martin Zöger, Andreas Giez, Vladyslav Nenakhov, Christian Mallaun, Rolf Maser, Timo Röschenthaler, Anna E. Luebke, Kevin Wolf, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 16, 1563–1581, https://doi.org/10.5194/amt-16-1563-2023, https://doi.org/10.5194/amt-16-1563-2023, 2023
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Measurements of the broadband radiative energy budget from aircraft are needed to study the effect of clouds, aerosol particles, and surface conditions on the Earth's energy budget. However, the moving aircraft introduces challenges to the instrument performance and post-processing of the data. This study introduces a new radiometer package, outlines a greatly simplifying method to correct thermal offsets, and provides exemplary measurements of solar and thermal–infrared irradiance.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023, https://doi.org/10.5194/essd-15-465-2023, 2023
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One of the novel ways EUREC4A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Ilaria Quaglia, Claudia Timmreck, Ulrike Niemeier, Daniele Visioni, Giovanni Pitari, Christina Brodowsky, Christoph Brühl, Sandip S. Dhomse, Henning Franke, Anton Laakso, Graham W. Mann, Eugene Rozanov, and Timofei Sukhodolov
Atmos. Chem. Phys., 23, 921–948, https://doi.org/10.5194/acp-23-921-2023, https://doi.org/10.5194/acp-23-921-2023, 2023
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The last very large explosive volcanic eruption we have measurements for is the eruption of Mt. Pinatubo in 1991. It is therefore often used as a benchmark for climate models' ability to reproduce these kinds of events. Here, we compare available measurements with the results from multiple experiments conducted with climate models interactively simulating the aerosol cloud formation.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
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A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
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This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
Walter Hannah, Kyle Pressel, Mikhail Ovchinnikov, and Gregory Elsaesser
Geosci. Model Dev., 15, 6243–6257, https://doi.org/10.5194/gmd-15-6243-2022, https://doi.org/10.5194/gmd-15-6243-2022, 2022
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An unphysical checkerboard signal is identified in two configurations of the atmospheric component of E3SM. The signal is very persistent and visible after averaging years of data. The signal is very difficult to study because it is often mixed with realistic weather. A method is presented to detect checkerboard patterns and compare the model with satellite observations. The causes of the signal are identified, and a solution for one configuration is discussed.
Theresa Mieslinger, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 6879–6898, https://doi.org/10.5194/acp-22-6879-2022, https://doi.org/10.5194/acp-22-6879-2022, 2022
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The trades are home to a plethora of small cumulus clouds that are often barely visible to the human eye and difficult to detect with active and passive remote sensing methods. With the help of a new method and by means of high-resolution data we can detect small and particularly thin clouds. We find that optically thin clouds are a common phenomenon in the trades, covering a large area and influencing the radiative effect of clouds if they are undetected and contaminate the cloud-free signal.
Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
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The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Michael Schäfer, Kevin Wolf, André Ehrlich, Christoph Hallbauer, Evelyn Jäkel, Friedhelm Jansen, Anna Elizabeth Luebke, Joshua Müller, Jakob Thoböll, Timo Röschenthaler, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 15, 1491–1509, https://doi.org/10.5194/amt-15-1491-2022, https://doi.org/10.5194/amt-15-1491-2022, 2022
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The new airborne thermal infrared imager VELOX is introduced. It measures two-dimensional fields of spectral thermal infrared radiance or brightness temperature within the large atmospheric window. The technical specifications as well as necessary calibration and correction procedures are presented. Example measurements from the first field deployment are analysed with respect to cloud coverage and cloud top altitude.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Debra K. Weisenstein, Daniele Visioni, Henning Franke, Ulrike Niemeier, Sandro Vattioni, Gabriel Chiodo, Thomas Peter, and David W. Keith
Atmos. Chem. Phys., 22, 2955–2973, https://doi.org/10.5194/acp-22-2955-2022, https://doi.org/10.5194/acp-22-2955-2022, 2022
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This paper explores a potential method of geoengineering that could be used to slow the rate of change of climate over decadal scales. We use three climate models to explore how injections of accumulation-mode sulfuric acid aerosol change the large-scale stratospheric particle size distribution and radiative forcing response for the chosen scenarios. Radiative forcing per unit sulfur injected and relative to the change in aerosol burden is larger with particulate than with SO2 injections.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Geet George, Bjorn Stevens, Sandrine Bony, Robert Pincus, Chris Fairall, Hauke Schulz, Tobias Kölling, Quinn T. Kalen, Marcus Klingebiel, Heike Konow, Ashley Lundry, Marc Prange, and Jule Radtke
Earth Syst. Sci. Data, 13, 5253–5272, https://doi.org/10.5194/essd-13-5253-2021, https://doi.org/10.5194/essd-13-5253-2021, 2021
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Dropsondes measure atmospheric parameters such as temperature, pressure, humidity and horizontal winds. The EUREC4A field campaign deployed 1215 dropsondes during January–February 2020 in the north Atlantic trade-wind region in order to characterize the thermodynamic and the dynamic structure of the atmosphere, primarily at horizontal scales of ~ 200 km. We present JOANNE, the dataset that provides these dropsonde measurements and thereby a rich characterization of the trade-wind atmosphere.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Hyunju Jung, Ann Kristin Naumann, and Bjorn Stevens
Atmos. Chem. Phys., 21, 10337–10345, https://doi.org/10.5194/acp-21-10337-2021, https://doi.org/10.5194/acp-21-10337-2021, 2021
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We analyze the behavior of organized convection in a large-scale flow by imposing a mean flow to idealized simulations. In the mean flow, organized convection initially propagates slower than the mean wind speed and becomes stationary. The initial upstream and downstream difference in surface fluxes becomes symmetric as the surface momentum flux acts as a drag, resulting in the stationarity. Meanwhile, the surface enthalpy flux has a minor role in the propagation of the convection.
Henning Franke, Ulrike Niemeier, and Daniele Visioni
Atmos. Chem. Phys., 21, 8615–8635, https://doi.org/10.5194/acp-21-8615-2021, https://doi.org/10.5194/acp-21-8615-2021, 2021
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Stratospheric aerosol modification (SAM) can alter the quasi-biennial oscillation (QBO). Our simulations with two different models show that the characteristics of the QBO response are primarily determined by the meridional structure of the aerosol-induced heating. Therefore, the QBO response to SAM depends primarily on the location of injection, while injection type and rate act to scale the specific response. Our results have important implications for evaluating adverse side effects of SAM.
Franziska Aemisegger, Raphaela Vogel, Pascal Graf, Fabienne Dahinden, Leonie Villiger, Friedhelm Jansen, Sandrine Bony, Bjorn Stevens, and Heini Wernli
Weather Clim. Dynam., 2, 281–309, https://doi.org/10.5194/wcd-2-281-2021, https://doi.org/10.5194/wcd-2-281-2021, 2021
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The interaction of clouds in the trade wind region with the atmospheric flow is complex and at the heart of uncertainties associated with climate projections. In this study, a natural tracer of atmospheric circulation is used to establish a link between air originating from dry regions of the midlatitudes and the occurrence of specific cloud patterns. Two pathways involving transport within midlatitude weather systems are identified, by which air is brought into the trades within 5–10 d.
Claudia Christine Stephan, Sabrina Schnitt, Hauke Schulz, Hugo Bellenger, Simon P. de Szoeke, Claudia Acquistapace, Katharina Baier, Thibaut Dauhut, Rémi Laxenaire, Yanmichel Morfa-Avalos, Renaud Person, Estefanía Quiñones Meléndez, Gholamhossein Bagheri, Tobias Böck, Alton Daley, Johannes Güttler, Kevin C. Helfer, Sebastian A. Los, Almuth Neuberger, Johannes Röttenbacher, Andreas Raeke, Maximilian Ringel, Markus Ritschel, Pauline Sadoulet, Imke Schirmacher, M. Katharina Stolla, Ethan Wright, Benjamin Charpentier, Alexis Doerenbecher, Richard Wilson, Friedhelm Jansen, Stefan Kinne, Gilles Reverdin, Sabrina Speich, Sandrine Bony, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 491–514, https://doi.org/10.5194/essd-13-491-2021, https://doi.org/10.5194/essd-13-491-2021, 2021
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The EUREC4A field campaign took place in the western tropical Atlantic during January and February 2020. A total of 811 radiosondes, launched regularly (usually 4-hourly) from Barbados, and 4 ships measured wind, temperature, and relative humidity. They sampled atmospheric variability associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. The methods of data collection and post-processing for the radiosonde data are described here.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
Earth Syst. Dynam., 11, 709–719, https://doi.org/10.5194/esd-11-709-2020, https://doi.org/10.5194/esd-11-709-2020, 2020
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In this paper we explore the potential of variability for constraining the equilibrium response of the climate system to external forcing. We show that the constraint is inherently skewed, with a long tail to high sensitivity, and that while the variability may contain some useful information, it is unlikely to generate a tight constraint.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
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To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Sebastian Borchert, Guidi Zhou, Michael Baldauf, Hauke Schmidt, Günther Zängl, and Daniel Reinert
Geosci. Model Dev., 12, 3541–3569, https://doi.org/10.5194/gmd-12-3541-2019, https://doi.org/10.5194/gmd-12-3541-2019, 2019
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We present an upper-atmosphere extension of the ICOsahedral Non-hydrostatic (ICON) model.
This includes an extension of the model dynamics from a shallow to a deep atmosphere
and the implementation of upper-atmosphere physics parameterizations.
Idealized test cases and climate simulations are performed in order to evaluate this new configuration, named UA-ICON.
Heike Konow, Marek Jacob, Felix Ament, Susanne Crewell, Florian Ewald, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Mario Mech, and Bjorn Stevens
Earth Syst. Sci. Data, 11, 921–934, https://doi.org/10.5194/essd-11-921-2019, https://doi.org/10.5194/essd-11-921-2019, 2019
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High-resolution measurements of maritime clouds are relatively scarce. Airborne cloud radar, microwave radiometer and dropsonde observations are used to expand these data. The measurements are unified into one data set to enable easy joint analyses of several or all instruments together to gain insight into cloud properties and atmospheric state. The data set contains measurements from four campaigns between December 2013 and October 2016 over the tropical and midlatitude Atlantic.
Ina Tegen, David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, Sebastian Rast, Harri Kokkola, Martin Schultz, Sabine Schroeder, Nikos Daskalakis, Stefan Barthel, Bernd Heinold, and Ulrike Lohmann
Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, https://doi.org/10.5194/gmd-12-1643-2019, 2019
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We describe a new version of the aerosol–climate model ECHAM–HAM and show tests of the model performance by comparing different aspects of the aerosol distribution with different datasets. The updated version of HAM contains improved descriptions of aerosol processes, including updated emission fields and cloud processes. While there are regional deviations between the model and observations, the model performs well overall.
Stephanie Fiedler, Bjorn Stevens, Matthew Gidden, Steven J. Smith, Keywan Riahi, and Detlef van Vuuren
Geosci. Model Dev., 12, 989–1007, https://doi.org/10.5194/gmd-12-989-2019, https://doi.org/10.5194/gmd-12-989-2019, 2019
Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
Geosci. Model Dev., 12, 879–892, https://doi.org/10.5194/gmd-12-879-2019, https://doi.org/10.5194/gmd-12-879-2019, 2019
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We summarize the results of the Dynamical Core Model Intercomparison Project's idealized supercell test case. Supercells are storm-scale weather phenomena that are a key target for next-generation, non-hydrostatic weather prediction models. We show that the dynamical cores of most global numerical models converge between approximately 1 and 0.5 km grid spacing for this test, although differences in final solution exist, particularly due to differing grid discretizations and numerical diffusion.
Johannes Eckstein, Roland Ruhnke, Stephan Pfahl, Emanuel Christner, Christopher Diekmann, Christoph Dyroff, Daniel Reinert, Daniel Rieger, Matthias Schneider, Jennifer Schröter, Andreas Zahn, and Peter Braesicke
Geosci. Model Dev., 11, 5113–5133, https://doi.org/10.5194/gmd-11-5113-2018, https://doi.org/10.5194/gmd-11-5113-2018, 2018
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We present ICON-ART-Iso, an extension to the global circulation model ICON, which allows for the simulation of the stable isotopologues of water. The main advantage over other isotope-enabled models is its flexible design with respect to the number of tracers simulated. We compare the results of several simulations to measurements of different scale. ICON-ART-Iso is able to reasonably reproduce the measurements. It is a promising tool to aid in the investigation of the atmospheric water cycle.
Uwe Mikolajewicz, Florian Ziemen, Guido Cioni, Martin Claussen, Klaus Fraedrich, Marvin Heidkamp, Cathy Hohenegger, Diego Jimenez de la Cuesta, Marie-Luise Kapsch, Alexander Lemburg, Thorsten Mauritsen, Katharina Meraner, Niklas Röber, Hauke Schmidt, Katharina D. Six, Irene Stemmler, Talia Tamarin-Brodsky, Alexander Winkler, Xiuhua Zhu, and Bjorn Stevens
Earth Syst. Dynam., 9, 1191–1215, https://doi.org/10.5194/esd-9-1191-2018, https://doi.org/10.5194/esd-9-1191-2018, 2018
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Model experiments show that changing the sense of Earth's rotation has relatively little impact on the globally and zonally averaged energy budgets but leads to large shifts in continental climates and patterns of precipitation. The retrograde world is greener as the desert area shrinks. Deep water formation shifts from the North Atlantic to the North Pacific with subsequent changes in ocean overturning. Over large areas of the Indian Ocean, cyanobacteria dominate over bulk phytoplankton.
Jennifer Schröter, Daniel Rieger, Christian Stassen, Heike Vogel, Michael Weimer, Sven Werchner, Jochen Förstner, Florian Prill, Daniel Reinert, Günther Zängl, Marco Giorgetta, Roland Ruhnke, Bernhard Vogel, and Peter Braesicke
Geosci. Model Dev., 11, 4043–4068, https://doi.org/10.5194/gmd-11-4043-2018, https://doi.org/10.5194/gmd-11-4043-2018, 2018
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In this paper, we introduce the most up-to-date version of the flexible tracer framework for the ICOsahedral Nonhydrostatic model with
Aerosols and Reactive Trace gases (ICON-ART).
We performed multiple simulations using different ICON physics configurations for weather and climate with ART.
The flexible tracer framework within ICON-ART 2.1 suits the demands of a large variety of different applications ranging from numerical weather prediction to climate integrations.
Martin G. Schultz, Scarlet Stadtler, Sabine Schröder, Domenico Taraborrelli, Bruno Franco, Jonathan Krefting, Alexandra Henrot, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Colombe Siegenthaler-Le Drian, Sebastian Wahl, Harri Kokkola, Thomas Kühn, Sebastian Rast, Hauke Schmidt, Philip Stier, Doug Kinnison, Geoffrey S. Tyndall, John J. Orlando, and Catherine Wespes
Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, https://doi.org/10.5194/gmd-11-1695-2018, 2018
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The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols. It thus allows for detailed investigations of chemical processes in the climate system. Evaluation of the model with various observational data yields good results, but the model has a tendency to produce too much OH in the tropics. This highlights the important interplay between atmospheric chemistry and dynamics.
Oliver Fuhrer, Tarun Chadha, Torsten Hoefler, Grzegorz Kwasniewski, Xavier Lapillonne, David Leutwyler, Daniel Lüthi, Carlos Osuna, Christoph Schär, Thomas C. Schulthess, and Hannes Vogt
Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, https://doi.org/10.5194/gmd-11-1665-2018, 2018
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The best hope for reducing long-standing uncertainties in climate projections is through increasing the horizontal resolution of climate models to the kilometer scale. We establish a baseline of what it would take to do such simulations using an atmospheric model that has been adapted to run on a supercomputer accelerated with graphics processing units. To our knowledge this represents the first production-ready atmospheric model being run entirely on accelerators on this scale.
Andrew E. Dessler, Thorsten Mauritsen, and Bjorn Stevens
Atmos. Chem. Phys., 18, 5147–5155, https://doi.org/10.5194/acp-18-5147-2018, https://doi.org/10.5194/acp-18-5147-2018, 2018
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One of the most important parameters in climate science is the equilibrium climate sensitivity (ECS). Estimates of this quantity based on 20th-century observations suggest low values of ECS (below 2 °C). We show that these calculations may be significantly in error. Together with other recent work on this problem, it seems probable that the ECS is larger than suggested by the 20th-century observations.
Allison A. Wing, Kevin A. Reed, Masaki Satoh, Bjorn Stevens, Sandrine Bony, and Tomoki Ohno
Geosci. Model Dev., 11, 793–813, https://doi.org/10.5194/gmd-11-793-2018, https://doi.org/10.5194/gmd-11-793-2018, 2018
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RCEMIP, an intercomparison of multiple types of numerical models, is proposed. In RCEMIP, the climate system is modeled in an idealized manner with no spatial dependence of boundary conditions (i.e., sea surface temperature) or forcing (i.e., incoming sunlight). This set of simulations will be used to investigate how the amount of cloudiness changes with warming, how the clustering of clouds changes with warming, and how the state of the atmosphere in this idealized setup varies between models.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
Geosci. Model Dev., 10, 4477–4509, https://doi.org/10.5194/gmd-10-4477-2017, https://doi.org/10.5194/gmd-10-4477-2017, 2017
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Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
Rieke Heinze, Christopher Moseley, Lennart Nils Böske, Shravan Kumar Muppa, Vera Maurer, Siegfried Raasch, and Bjorn Stevens
Atmos. Chem. Phys., 17, 7083–7109, https://doi.org/10.5194/acp-17-7083-2017, https://doi.org/10.5194/acp-17-7083-2017, 2017
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High-resolution multi-week simulations of a measurement campaign are evaluated with respect to mean boundary layer quantities and turbulence statistics. Two models are used in a semi-idealized setup through forcing, with output from a coarser-scale model to account for the larger-scale conditions. The boundary layer depth is in principal agreement with observations. Turbulence statistics like variance profiles agree satisfactorily with measurements.
Bjorn Stevens, Stephanie Fiedler, Stefan Kinne, Karsten Peters, Sebastian Rast, Jobst Müsse, Steven J. Smith, and Thorsten Mauritsen
Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, https://doi.org/10.5194/gmd-10-433-2017, 2017
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A simple analytic description of aerosol optical properties and their main effects on clouds is developed and described. The analytic description is easy to use and easy to modify and should aid experimentation to help understand how aerosol radiative and cloud interactions effect climate and circulation. The climatology is recommended for adoption by models participating in the sixth phase of the Coupled Model Intercomparison Project.
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
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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.
Matthew Toohey, Bjorn Stevens, Hauke Schmidt, and Claudia Timmreck
Geosci. Model Dev., 9, 4049–4070, https://doi.org/10.5194/gmd-9-4049-2016, https://doi.org/10.5194/gmd-9-4049-2016, 2016
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Stratospheric sulfate aerosols from volcanic eruptions have a significant impact on the Earth's climate. The Easy Volcanic Aerosol (EVA) volcanic forcing generator provides a tool whereby the optical properties of volcanic aerosols can be included in climate model simulations in a self-consistent, complete, and flexible manner. EVA is based on satellite observations of the 1991 Pinatubo eruption but can be applied to any real or hypothetical eruption of interest.
Robert Pincus, Piers M. Forster, and Bjorn Stevens
Geosci. Model Dev., 9, 3447–3460, https://doi.org/10.5194/gmd-9-3447-2016, https://doi.org/10.5194/gmd-9-3447-2016, 2016
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This paper describes an experimental protocol to understand the changes in energy balance (the "radiative forcing") that arise due to changes in atmospheric composition and why this value is not the same across climate models. The protocol includes a way to determine the total forcing to which each model is subjected, experiments designed at teasing out why certain errors occur, and experiments to identify any robust signals caused by atmospheric particles from human activities.
David Leutwyler, Oliver Fuhrer, Xavier Lapillonne, Daniel Lüthi, and Christoph Schär
Geosci. Model Dev., 9, 3393–3412, https://doi.org/10.5194/gmd-9-3393-2016, https://doi.org/10.5194/gmd-9-3393-2016, 2016
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The representation of moist convection (thunderstorms and rain showers) in climate models represents a major challenge, as this process is usually approximated due to the lack of appropriate computational resolution. Climate simulations using horizontal resolution of O(1 km) allow one to explicitly resolve deep convection and thus allow for an improved representation of the water cycle. We present a set of such simulations covering the European scale using a climate model enabled for GPUs.
Veronika Eyring, Sandrine Bony, Gerald A. Meehl, Catherine A. Senior, Bjorn Stevens, Ronald J. Stouffer, and Karl E. Taylor
Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, https://doi.org/10.5194/gmd-9-1937-2016, 2016
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The objective of CMIP is to better understand past, present, and future climate change in a multi-model context. CMIP's increasing importance and scope is a tremendous success story, but the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. In response to these challenges, we have adopted a more federated structure for the sixth phase of CMIP (i.e. CMIP6) and subsequent phases.
D. Rieger, M. Bangert, I. Bischoff-Gauss, J. Förstner, K. Lundgren, D. Reinert, J. Schröter, H. Vogel, G. Zängl, R. Ruhnke, and B. Vogel
Geosci. Model Dev., 8, 1659–1676, https://doi.org/10.5194/gmd-8-1659-2015, https://doi.org/10.5194/gmd-8-1659-2015, 2015
R. Hommel, C. Timmreck, M. A. Giorgetta, and H. F. Graf
Atmos. Chem. Phys., 15, 5557–5584, https://doi.org/10.5194/acp-15-5557-2015, https://doi.org/10.5194/acp-15-5557-2015, 2015
M. Mech, E. Orlandi, S. Crewell, F. Ament, L. Hirsch, M. Hagen, G. Peters, and B. Stevens
Atmos. Meas. Tech., 7, 4539–4553, https://doi.org/10.5194/amt-7-4539-2014, https://doi.org/10.5194/amt-7-4539-2014, 2014
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Here the High Altitude and LOng range research aircraft Microwave Package (HAMP) is introduced. The package consists
of three passive radiometer modules with 26 channels between 22
and 183 GHz and a 36 GHz Doppler cloud radar. The manuscript
describes the instrument specifications, the installation in the aircraft, and the operation. Furthermore, results from simulation
and retrieval studies, as well as measurements from a first test
campaign, are shown.
P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh
Geosci. Model Dev., 7, 105–145, https://doi.org/10.5194/gmd-7-105-2014, https://doi.org/10.5194/gmd-7-105-2014, 2014
H. Wan, M. A. Giorgetta, G. Zängl, M. Restelli, D. Majewski, L. Bonaventura, K. Fröhlich, D. Reinert, P. Rípodas, L. Kornblueh, and J. Förstner
Geosci. Model Dev., 6, 735–763, https://doi.org/10.5194/gmd-6-735-2013, https://doi.org/10.5194/gmd-6-735-2013, 2013
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Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
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Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2183, https://doi.org/10.5194/egusphere-2024-2183, 2024
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PaleoSTeHM v1.0-rc is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
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Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Thi Nhu Ngoc Do, Kengo Sudo, Akihiko Ito, Louisa Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2313, https://doi.org/10.5194/egusphere-2024-2313, 2024
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth System Models mainly due to partially incorporating CO2 effects and land cover changes rather than climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant-climate interactions.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
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Short summary
This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
This work presents a first version of the ICON atmosphere model that works not only on CPUs, but...
