Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-33-2025
© Author(s) 2025. 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-18-33-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
10 Jan 2025
Model evaluation paper |
| 10 Jan 2025
| 10 Jan 2025
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Xabier Pedruzo-Bagazgoitia
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Tobias Becker
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Sebastian Milinski
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Irina Sandu
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Razvan Aguridan
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Peter Bechtold
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Sebastian Beyer
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Jean Bidlot
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Souhail Boussetta
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Willem Deconinck
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Michail Diamantakis
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Peter Dueben
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Emanuel Dutra
Instituto Português do Mar e da Atmosfera, IPMA, Lisbon, Portugal
Instituto Dom Luiz, IDL, Faculty of Sciences, University of Lisbon, Lisbon, Portugal
Richard Forbes
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Rohit Ghosh
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Helge F. Goessling
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Ioan Hadade
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Jan Hegewald
Gauß-IT-Zentrum, Braunschweig University of Technology (GITZ), Braunschweig, Germany
Thomas Jung
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Department of Physics and Electrical Engineering, University of Bremen, Bremen, Germany
Sarah Keeley
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Lukas Kluft
Max Planck Institute for Meteorology (MPI-M), Hamburg, Germany
Nikolay Koldunov
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Aleksei Koldunov
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Tobias Kölling
Max Planck Institute for Meteorology (MPI-M), Hamburg, Germany
Josh Kousal
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Christian Kühnlein
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Pedro Maciel
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Kristian Mogensen
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Tiago Quintino
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Inna Polichtchouk
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Balthasar Reuter
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Domokos Sármány
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Patrick Scholz
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Dmitry Sidorenko
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Jan Streffing
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Birgit Sützl
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Daisuke Takasuka
Department of Geophysics, Tohoku University, Sendai, Japan
Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
Steffen Tietsche
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Mirco Valentini
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Benoît Vannière
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Nils Wedi
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Lorenzo Zampieri
European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany
Florian Ziemen
Deutsches Klimarechenzentrum (DKRZ), Hamburg, Germany
Related authors
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
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.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
Short summary
Short summary
We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
Short summary
Short summary
Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
Short summary
Short summary
We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Lukas Kluft, Bjorn Stevens, Manfred Brath, and Stefan A. Buehler
Atmos. Chem. Phys., 25, 9075–9084, https://doi.org/10.5194/acp-25-9075-2025, https://doi.org/10.5194/acp-25-9075-2025, 2025
Short summary
Short summary
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.
Blanca Ayarzagüena, Amy H. Butler, Peter Hitchcock, Chaim I. Garfinkel, Zac D. Lawrence, Wuhan Ning, Philip Rupp, Zheng Wu, Hilla Afargan-Gerstman, Natalia Calvo, Álvaro de la Cámara, Martin Jucker, Gerbrand Koren, Daniel De Maeseneire, Gloria L. Manney, Marisol Osman, Masakazu Taguchi, Cory Barton, Dong-Chang Hong, Yu-Kyung Hyun, Hera Kim, Jeff Knight, Piero Malguzzi, Daniele Mastrangelo, Jiyoung Oh, Inna Polichtchouk, Jadwiga H. Richter, Isla R. Simpson, Seok-Woo Son, Damien Specq, and Tim Stockdale
EGUsphere, https://doi.org/10.5194/egusphere-2025-3611, https://doi.org/10.5194/egusphere-2025-3611, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Sudden Stratospheric Warmings (SSWs) are known to follow a sustained wave dissipation in the stratosphere, which depends on both the tropospheric and stratospheric states. However, the relative role of each state is still unclear. Using a new set of subseasonal to seasonal forecasts, we show that the stratospheric state does not drastically affect the precursors of three recent SSWs, but modulates the stratospheric wave activity, with impacts depending on SSW features.
Paolo Andreozzi, Mark D. Fielding, Robin J. Hogan, Richard M. Forbes, Samuel Rémy, Birger Bohn, and Ulrich Löhnert
EGUsphere, https://doi.org/10.5194/egusphere-2025-3790, https://doi.org/10.5194/egusphere-2025-3790, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Aerosols significantly contribute to the Earth’s climate, but models still struggle at representing them. Here we use satellite observations of clouds to improve aerosols in our weather and air-quality model. We show that African wildfires induce too bright simulated clouds and that our model removes too much aerosol from ice-containing clouds. This showcases how our approach effectively targets poorly observed aerosol processes, potentially informing weather forecasting and climate models.
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian L. E. Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Dae-Won Kim, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana N. Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann
Earth Syst. Dynam., 16, 1103–1134, https://doi.org/10.5194/esd-16-1103-2025, https://doi.org/10.5194/esd-16-1103-2025, 2025
Short summary
Short summary
Based on a series of storm-resolving greenhouse warming simulations conducted with the AWI-CM3 model at 9 km global atmosphere and 4–25 km ocean resolution, we present new projections of regional climate change, modes of climate variability, and extreme events. The 10-year-long high-resolution simulations for the 2000s, 2030s, 2060s, and 2090s were initialized from a coarser-resolution transient run (31 km atmosphere) which follows the SSP5-8.5 greenhouse gas emission scenario from 1950–2100 CE.
Fernanda DI Alzira Oliveira Matos, Dmitry Sidorenko, Xiaoxu Shi, Lars Ackermann, Janini Pereira, Gerrit Lohmann, and Christian Stepanek
EGUsphere, https://doi.org/10.5194/egusphere-2025-2326, https://doi.org/10.5194/egusphere-2025-2326, 2025
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is responsible for about 25 % of the poleward ocean heat transport. Currently, the AMOC strength is mostly calculated in depth space (z-AMOC). However, we argue that, in warmer climates, the AMOC should be calculated in density space (ρ-AMOC). We performed simulations with CO2 forcing of 280 ppmv (PI) and 1120 ppmv of (4xCO2) and find that ρ-AMOC provides more physical and meaningful information about the AMOC in warmer climates.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Nicolai Krieger, Heini Wernli, Michael Sprenger, and Christian Kühnlein
Weather Clim. Dynam., 6, 447–469, https://doi.org/10.5194/wcd-6-447-2025, https://doi.org/10.5194/wcd-6-447-2025, 2025
Short summary
Short summary
This study investigates the Laseyer, a local windstorm in a narrow Swiss valley characterized by strong southeasterly winds during northwesterly ambient flow. Using large-eddy simulations (LESs) with 30 m grid spacing, this is the first study to reveal that the extreme gusts in the valley are caused by an amplifying interplay of two recirculation regions. Modifying terrain and ambient wind conditions affects the windstorm's intensity and highlights the importance of topographic details in LES.
Takashi Obase, Takanori Kodama, Takao Kawasaki, Sam Sherriff-Tadano, Daisuke Takasuka, Ayako Abe-Ouchi, and Masakazu Fujii
EGUsphere, https://doi.org/10.5194/egusphere-2025-1484, https://doi.org/10.5194/egusphere-2025-1484, 2025
Short summary
Short summary
In the past, Earth experienced its surface became completely covered with ice. Using an atmosphere-ocean climate model, we examined the evolution in the ocean circulation from modern to the snowball Earth. We found that the deep ocean ocean circulation experienced drastic weakening before the snowball onset by salinity changes, and after that the ocean circulation resumed. The ocean circulation changes have implications for understanding climate system feedback on the past snowball events.
Uwe Mikolajewicz, Marie-Luise Kapsch, Clemens Schannwell, Katharina D. Six, Florian A. Ziemen, Meike Bagge, Jean-Philippe Baudouin, Olga Erokhina, Veronika Gayler, Volker Klemann, Virna L. Meccia, Anne Mouchet, and Thomas Riddick
Clim. Past, 21, 719–751, https://doi.org/10.5194/cp-21-719-2025, https://doi.org/10.5194/cp-21-719-2025, 2025
Short summary
Short summary
A fully coupled atmosphere–ocean–ice-sheet–solid-earth model was applied to simulate the time from the Last Glacial Maximum (about 25 000 years before the present) to the pre-industrial period. The model simulations are compared to observational estimates. During this climate transition, the model simulates several abrupt changes in the North Atlantic region, which are initiated by different processes. The underlying mechanisms are analysed and described.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025, https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
Short summary
Vertical mixing is an important process, for example, for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes with different parameter settings in two different ocean models and show that most effects from mixing scheme parameter changes are model-dependent.
Ting-Chen Chen, Hugues Goosse, Matthias Aengenheyster, Kristian Strommen, Christopher Roberts, Malcolm Roberts, Rohit Ghosh, Jin-Song von Storch, and Stephy Libera
EGUsphere, https://doi.org/10.5194/egusphere-2025-666, https://doi.org/10.5194/egusphere-2025-666, 2025
Short summary
Short summary
The Southern Annular Mode (SAM) is a key driver of Southern Hemisphere climate variability, but global models often overestimate its persistence in summer. Using high-resolution models, we show this bias can be reduced, along with some improvements in jet latitude and likely a better-resolved eddy-mean flow feedback. Controlled experiments reveal the potential roles of sea surface temperature biases and ocean mesoscales, underscoring the complex mechanisms shaping SAM persistence.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
Geosci. Model Dev., 18, 921–937, https://doi.org/10.5194/gmd-18-921-2025, https://doi.org/10.5194/gmd-18-921-2025, 2025
Short summary
Short summary
We compared spatiotemporal forecasts of three machine learning models that learned water and energy
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
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.
Chaim I. Garfinkel, Zachary D. Lawrence, Amy H. Butler, Etienne Dunn-Sigouin, Irene Erner, Alexey Y. Karpechko, Gerbrand Koren, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Judah Cohen, Daniela I. V. Domeisen, Javier García-Serrano, Neil P. Hindley, Martin Jucker, Hera Kim, Robert W. Lee, Simon H. Lee, Marisol Osman, Froila M. Palmeiro, Inna Polichtchouk, Jian Rao, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
Weather Clim. Dynam., 6, 171–195, https://doi.org/10.5194/wcd-6-171-2025, https://doi.org/10.5194/wcd-6-171-2025, 2025
Short summary
Short summary
Variability in the extratropical stratosphere and troposphere is coupled, and because of the longer timescales characteristic of the stratosphere, this allows for a window of opportunity for surface prediction. This paper assesses whether models used for operational prediction capture these coupling processes accurately. We find that most processes are too weak; however downward coupling from the lower stratosphere to the near surface is too strong.
Tatiana Klimiuk, Patrick Ludwig, Antonio Sanchez-Benitez, Helge F. Goessling, Peter Braesicke, and Joaquim G. Pinto
Earth Syst. Dynam., 16, 239–255, https://doi.org/10.5194/esd-16-239-2025, https://doi.org/10.5194/esd-16-239-2025, 2025
Short summary
Short summary
Our study examines potential changes in heatwaves in central Europe due to global warming, using the 2019 summer heatwave as an example. By producing high-resolution storylines, we provide insights into how future heatwaves might spread, how they might persist for longer, and where stronger or weaker temperature increases may occur. This research helps us understand regional thermodynamic responses and highlights the importance of local strategies to protect communities from future heat events.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
Short summary
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Lea Volkmer, Tobias Kölling, Tobias Zinner, and Bernhard Mayer
Atmos. Meas. Tech., 17, 6807–6817, https://doi.org/10.5194/amt-17-6807-2024, https://doi.org/10.5194/amt-17-6807-2024, 2024
Short summary
Short summary
The importance of the consideration of cloud motion for the stereographic determination of cloud top height from aircraft observations is demonstrated using measurements of the airborne spectrometer of the Munich Aerosol Cloud Scanner (specMACS). A method for cloud motion correction using model winds from the European Centre for Medium-Range Weather Forecasts is presented and validated using both real measurements and realistic radiative transfer simulations.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Short summary
Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3051, https://doi.org/10.5194/egusphere-2024-3051, 2024
Short summary
Short summary
We investigated how the uncertainty in representing water vapour continuum absorption in the shortwave affects clear-sky shortwave radiative feedback. For current surface temperature, the impact is modest (<2 %). In a warmer world, continuum induced error in estimated shortwave feedback is up to ~5 %. Using the MT_CKD model in radiative transfer calculations may lead to an underestimation of the shortwave feedback. Constraining shortwave continuum will contribute to reducing these discrepancies.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Rachel W.-Y. Wu, Gabriel Chiodo, Inna Polichtchouk, and Daniela I. V. Domeisen
Atmos. Chem. Phys., 24, 12259–12275, https://doi.org/10.5194/acp-24-12259-2024, https://doi.org/10.5194/acp-24-12259-2024, 2024
Short summary
Short summary
Strong variations in the strength of the stratospheric polar vortex can profoundly affect surface weather extremes; therefore, accurately predicting the stratosphere can improve surface weather forecasts. The research reveals how uncertainty in the stratosphere is linked to the troposphere. The findings suggest that refining models to better represent the identified sources and impact regions in the troposphere is likely to improve the prediction of the stratosphere and its surface impacts.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Francesco Cocetta, Lorenzo Zampieri, Julia Selivanova, and Doroteaciro Iovino
The Cryosphere, 18, 4687–4702, https://doi.org/10.5194/tc-18-4687-2024, https://doi.org/10.5194/tc-18-4687-2024, 2024
Short summary
Short summary
Arctic sea ice is thinning and retreating because of global warming. Thus, the region is transitioning to a new state featuring an expansion of the marginal ice zone, a region where mobile ice interacts with waves from the open ocean. By analyzing 30 years of sea ice reconstructions that combine numerical models and observations, this paper proves that an ensemble of global ocean and sea ice reanalyses is an adequate tool for investigating the changing Arctic sea ice cover.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
Short summary
Short summary
We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
Short summary
Short summary
In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
Short summary
Short summary
We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024, https://doi.org/10.5194/nhess-24-1501-2024, 2024
Short summary
Short summary
Over Europe, 2022 was truly exceptional in terms of extreme heat conditions, both in terms of temperature anomalies and their temporal and spatial extent. The satellite all-sky land surface temperature (LST) is used to provide a climatological context to extreme heat events. Where drought conditions prevail, LST anomalies are higher than 2 m air temperature anomalies. ERA5-Land does not represent this effect correctly due to a misrepresentation of vegetation anomalies.
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
Short summary
Short summary
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.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
Short summary
Short summary
We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
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
Short summary
Short summary
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.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Anna Weber, Tobias Kölling, Veronika Pörtge, Andreas Baumgartner, Clemens Rammeloo, Tobias Zinner, and Bernhard Mayer
Atmos. Meas. Tech., 17, 1419–1439, https://doi.org/10.5194/amt-17-1419-2024, https://doi.org/10.5194/amt-17-1419-2024, 2024
Short summary
Short summary
In this work, we introduce the 2D RGB polarization-resolving cameras of the airborne hyperspectral and polarized imaging system specMACS. A full characterization and calibration of the cameras including a geometric calibration as well as a radiometric characterization is provided, allowing for the computation of absolute calibrated, georeferenced Stokes vectors rotated into the scattering plane. We validate the calibration by comparing sunglint measurements to radiative transfer simulations.
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
Short summary
Short summary
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.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
Short summary
Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
Short summary
Short summary
Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023, https://doi.org/10.5194/hess-27-4661-2023, 2023
Short summary
Short summary
Lakes play an important role when we try to explain and predict the weather. More accurate and up-to-date description of lakes all around the world for numerical models is a continuous task. However, it is difficult to assess the impact of updated lake description within a weather prediction system. In this work, we develop a method to quickly and automatically define how, where, and when updated lake description affects weather prediction.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Short summary
Short summary
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
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
Short summary
Short summary
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.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Earth Syst. Dynam., 14, 1239–1259, https://doi.org/10.5194/esd-14-1239-2023, https://doi.org/10.5194/esd-14-1239-2023, 2023
Short summary
Short summary
Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
Miriam Saraceni, Lorenzo Silvestri, Peter Bechtold, and Paolina Bongioannini Cerlini
Atmos. Chem. Phys., 23, 13883–13909, https://doi.org/10.5194/acp-23-13883-2023, https://doi.org/10.5194/acp-23-13883-2023, 2023
Short summary
Short summary
This study focuses on three medicanes, tropical-like cyclones that form in the Mediterranean Sea, studied by ensemble forecasting. This involved multiple simulations of the same event by varying initial conditions and model physics parameters, especially related to convection, which showed comparable results. It is found that medicane development is influenced by the model's ability to predict precursor events and the interaction between upper and lower atmosphere dynamics and thermodynamics.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hannah L. Croad, John Methven, Ben Harvey, Sarah P. E. Keeley, and Ambrogio Volonté
Weather Clim. Dynam., 4, 617–638, https://doi.org/10.5194/wcd-4-617-2023, https://doi.org/10.5194/wcd-4-617-2023, 2023
Short summary
Short summary
The interaction between Arctic cyclones and the sea ice surface in summer is investigated by analysing the friction and sensible heat flux processes acting in two cyclones with contrasting evolution. The major finding is that the effects of friction on cyclone strength are dependent on a particular feature of cyclone structure: whether they have a warm or cold core during growth. Friction leads to cooling within both cyclone types in the lower atmosphere, which may contribute to their longevity.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Guillaume Gastineau, Claude Frankignoul, Yongqi Gao, Yu-Chiao Liang, Young-Oh Kwon, Annalisa Cherchi, Rohit Ghosh, Elisa Manzini, Daniela Matei, Jennifer Mecking, Lingling Suo, Tian Tian, Shuting Yang, and Ying Zhang
The Cryosphere, 17, 2157–2184, https://doi.org/10.5194/tc-17-2157-2023, https://doi.org/10.5194/tc-17-2157-2023, 2023
Short summary
Short summary
Snow cover variability is important for many human activities. This study aims to understand the main drivers of snow cover in observations and models in order to better understand it and guide the improvement of climate models and forecasting systems. Analyses reveal a dominant role for sea surface temperature in the Pacific. Winter snow cover is also found to have important two-way interactions with the troposphere and stratosphere. No robust influence of the sea ice concentration is found.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
Short summary
Short summary
In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Nicola Maher, Robert C. Jnglin Wills, Pedro DiNezio, Jeremy Klavans, Sebastian Milinski, Sara C. Sanchez, Samantha Stevenson, Malte F. Stuecker, and Xian Wu
Earth Syst. Dynam., 14, 413–431, https://doi.org/10.5194/esd-14-413-2023, https://doi.org/10.5194/esd-14-413-2023, 2023
Short summary
Short summary
Understanding whether the El Niño–Southern Oscillation (ENSO) is likely to change in the future is important due to its widespread impacts. By using large ensembles, we can robustly isolate the time-evolving response of ENSO variability in 14 climate models. We find that ENSO variability evolves in a nonlinear fashion in many models and that there are large differences between models. These nonlinear changes imply that ENSO impacts may vary dramatically throughout the 21st century.
Felix Pithan, Marylou Athanase, Sandro Dahlke, Antonio Sánchez-Benítez, Matthew D. Shupe, Anne Sledd, Jan Streffing, Gunilla Svensson, and Thomas Jung
Geosci. Model Dev., 16, 1857–1873, https://doi.org/10.5194/gmd-16-1857-2023, https://doi.org/10.5194/gmd-16-1857-2023, 2023
Short summary
Short summary
Evaluating climate models usually requires long observational time series, but we present a method that also works for short field campaigns. We compare climate model output to observations from the MOSAiC expedition in the central Arctic Ocean. All models show how the arrival of a warm air mass warms the Arctic in April 2020, but two models do not show the response of snow temperature to the diurnal cycle. One model has too little liquid water and too much ice in clouds during cold days.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
Short summary
Short summary
We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
Short summary
Short summary
Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
Short summary
Short summary
In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
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
Short summary
Short summary
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.
Clemens Schannwell, Uwe Mikolajewicz, Florian Ziemen, and Marie-Luise Kapsch
Clim. Past, 19, 179–198, https://doi.org/10.5194/cp-19-179-2023, https://doi.org/10.5194/cp-19-179-2023, 2023
Short summary
Short summary
Heinrich-type ice-sheet surges are recurring events over the course of the last glacial cycle during which large numbers of icebergs are discharged from the Laurentide ice sheet into the ocean. These events alter the evolution of the global climate. Here, we use model simulations of the Laurentide ice sheet to identify and quantify the importance of various climate and ice-sheet parameters for the simulated surge cycle.
Wolfgang Wicker, Inna Polichtchouk, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 81–93, https://doi.org/10.5194/wcd-4-81-2023, https://doi.org/10.5194/wcd-4-81-2023, 2023
Short summary
Short summary
Sudden stratospheric warmings are extreme weather events where the winter polar stratosphere warms by about 25 K. An improved representation of small-scale gravity waves in sub-seasonal prediction models can reduce forecast errors since their impact on the large-scale circulation is predictable multiple weeks ahead. After a sudden stratospheric warming, vertically propagating gravity waves break at a lower altitude than usual, which strengthens the long-lasting positive temperature anomalies.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Sergei Kirillov, Igor Dmitrenko, David G. Babb, Jens K. Ehn, Nikolay Koldunov, Søren Rysgaard, David Jensen, and David G. Barber
Ocean Sci., 18, 1535–1557, https://doi.org/10.5194/os-18-1535-2022, https://doi.org/10.5194/os-18-1535-2022, 2022
Short summary
Short summary
The sea ice bridge usually forms during winter in Nares Strait and prevents ice drifting south. However, this bridge has recently become unstable, and in this study we investigate the role of oceanic heat flux in this decline. Using satellite data, we identify areas where sea ice is relatively thin and further attribute those areas to the heat fluxes from the warm subsurface water masses. We also discuss the potential role of such an impact on ice bridge instability and earlier ice break up.
Alessandro Carlo Maria Savazzi, Louise Nuijens, Irina Sandu, Geet George, and Peter Bechtold
Atmos. Chem. Phys., 22, 13049–13066, https://doi.org/10.5194/acp-22-13049-2022, https://doi.org/10.5194/acp-22-13049-2022, 2022
Short summary
Short summary
Winds are of great importance for the transport of energy and moisture in the atmosphere. In this study we use measurements from the EUREC4A field campaign and several model experiments to understand the wind bias in the forecasts produced by the European Centre for Medium-Range Weather Forecasts. We are able to link the model errors to heights above 2 km and to the representation of the diurnal cycle of winds: the model makes the winds too slow in the morning and too strong in the evening.
Nicola Maher, Thibault P. Tabarin, and Sebastian Milinski
Earth Syst. Dynam., 13, 1289–1304, https://doi.org/10.5194/esd-13-1289-2022, https://doi.org/10.5194/esd-13-1289-2022, 2022
Short summary
Short summary
El Niño events occur as two broad types: eastern Pacific (EP) and central Pacific (CP). EP and CP events differ in strength, evolution, and in their impacts. In this study we create a new machine learning classifier to identify the two types of El Niño events using observed sea surface temperature data. We apply our new classifier to climate models and show that CP events are unlikely to change in frequency or strength under a warming climate, with model disagreement for EP events.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
Short summary
Short summary
We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Zachary D. Lawrence, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Amy H. Butler, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Daniela I. V. Domeisen, Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel, Neil P. Hindley, Liwei Jia, Martin Jucker, Alexey Y. Karpechko, Hera Kim, Andrea L. Lang, Simon H. Lee, Pu Lin, Marisol Osman, Froila M. Palmeiro, Judith Perlwitz, Inna Polichtchouk, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Irene Erner, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu
Weather Clim. Dynam., 3, 977–1001, https://doi.org/10.5194/wcd-3-977-2022, https://doi.org/10.5194/wcd-3-977-2022, 2022
Short summary
Short summary
Forecast models that are used to predict weather often struggle to represent the Earth’s stratosphere. This may impact their ability to predict surface weather weeks in advance, on subseasonal-to-seasonal (S2S) timescales. We use data from many S2S forecast systems to characterize and compare the stratospheric biases present in such forecast models. These models have many similar stratospheric biases, but they tend to be worse in systems with low model tops located within the stratosphere.
Miguel Nogueira, Alexandra Hurduc, Sofia Ermida, Daniela C. A. Lima, Pedro M. M. Soares, Frederico Johannsen, and Emanuel Dutra
Geosci. Model Dev., 15, 5949–5965, https://doi.org/10.5194/gmd-15-5949-2022, https://doi.org/10.5194/gmd-15-5949-2022, 2022
Short summary
Short summary
We evaluated the quality of the ERA5 reanalysis representation of the urban heat island (UHI) over the city of Paris and performed a set of offline runs using the SURFEX land surface model. They were compared with observations (satellite and in situ). The SURFEX-TEB runs showed the best performance in representing the UHI, reducing its bias significantly. We demonstrate the ability of the SURFEX-TEB framework to simulate urban climate, which is crucial for studying climate change in cities.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Simon Felix Reifenberg and Helge Friedrich Goessling
The Cryosphere, 16, 2927–2946, https://doi.org/10.5194/tc-16-2927-2022, https://doi.org/10.5194/tc-16-2927-2022, 2022
Short summary
Short summary
Using model simulations, we analyze the impact of chaotic error growth on Arctic sea ice drift predictions. Regarding forecast uncertainty, our results suggest that it matters in which season and where ice drift forecasts are initialized and that both factors vary with the model in use. We find ice velocities to be slightly more predictable than near-surface wind, a main driver of ice drift. This is relevant for future developments of ice drift forecasting systems.
Ivo Suter, Tom Grylls, Birgit S. Sützl, Sam O. Owens, Chris E. Wilson, and Maarten van Reeuwijk
Geosci. Model Dev., 15, 5309–5335, https://doi.org/10.5194/gmd-15-5309-2022, https://doi.org/10.5194/gmd-15-5309-2022, 2022
Short summary
Short summary
Cities are increasingly moving to the fore of climate and air quality research due to their central role in the population’s health and well-being, while suitable models remain scarce. This article describes the development of a new urban LES model, which allows examining the effects of various processes, infrastructure and vegetation on the local climate and air quality. Possible applications are demonstrated and a comparison to an experiment is shown.
Jonathan J. Day, Sarah Keeley, Gabriele Arduini, Linus Magnusson, Kristian Mogensen, Mark Rodwell, Irina Sandu, and Steffen Tietsche
Weather Clim. Dynam., 3, 713–731, https://doi.org/10.5194/wcd-3-713-2022, https://doi.org/10.5194/wcd-3-713-2022, 2022
Short summary
Short summary
A recent drive to develop seamless forecasting systems has culminated in the development of weather forecasting systems that include a coupled representation of the atmosphere, ocean and sea ice. Before this, sea ice and sea surface temperature anomalies were typically fixed throughout a given forecast. We show that the dynamic coupling is most beneficial during periods of rapid ice advance, where persistence is a poor forecast of the sea ice and leads to large errors in the uncoupled system.
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John M. Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
Short summary
Short summary
This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
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
Short summary
Short summary
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.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
Short summary
Short summary
Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
Steve Delhaye, Thierry Fichefet, François Massonnet, David Docquier, Rym Msadek, Svenya Chripko, Christopher Roberts, Sarah Keeley, and Retish Senan
Weather Clim. Dynam., 3, 555–573, https://doi.org/10.5194/wcd-3-555-2022, https://doi.org/10.5194/wcd-3-555-2022, 2022
Short summary
Short summary
It is unclear how the atmosphere will respond to a retreat of summer Arctic sea ice. Much attention has been paid so far to weather extremes at mid-latitude and in winter. Here we focus on the changes in extremes in surface air temperature and precipitation over the Arctic regions in summer during and following abrupt sea ice retreats. We find that Arctic sea ice loss clearly shifts the extremes in surface air temperature and precipitation over terrestrial regions surrounding the Arctic Ocean.
Paolo Davini, Federico Fabiano, and Irina Sandu
Weather Clim. Dynam., 3, 535–553, https://doi.org/10.5194/wcd-3-535-2022, https://doi.org/10.5194/wcd-3-535-2022, 2022
Short summary
Short summary
In climate models, improvements obtained in the winter mid-latitude circulation following horizontal resolution increase are mainly caused by the more detailed representation of the mean orography. A high-resolution climate model with low-resolution orography might underperform compared to a low-resolution model with low-resolution orography. The absence of proper model tuning at high resolution is considered the potential reason behind such lack of improvements.
Stipo Sentić, Peter Bechtold, Željka Fuchs-Stone, Mark Rodwell, and David J. Raymond
Geosci. Model Dev., 15, 3371–3385, https://doi.org/10.5194/gmd-15-3371-2022, https://doi.org/10.5194/gmd-15-3371-2022, 2022
Short summary
Short summary
The Organization of Tropical East Pacific Convection (OTREC) field campaign focuses on studying convection in the eastern Pacific and Caribbean. Observations obtained from dropsondes have been assimilated into the ECMWF model and compared to a model run in which sondes have not been assimilated. The model performs well in both simulations, but the assimilation of sondes helps to reduce the departure for pre-tropical-storm conditions. Variables important to studying convection are also studied.
Viorica Nagavciuc, Patrick Scholz, and Monica Ionita
Nat. Hazards Earth Syst. Sci., 22, 1347–1369, https://doi.org/10.5194/nhess-22-1347-2022, https://doi.org/10.5194/nhess-22-1347-2022, 2022
Short summary
Short summary
Here we have assessed the variability and trends of hot and dry summers in Romania. The length, spatial extent, and frequency of heat waves in Romania have increased significantly over the last 70 years, while no significant changes have been observed in the drought conditions. The increased frequency of heat waves, especially after the 1990s, could be partially explained by an increase in the geopotential height over the eastern part of Europe.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
Short summary
The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
Short summary
Short summary
The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Sara Pasqualetto, Luisa Cristini, and Thomas Jung
Geosci. Commun., 5, 87–100, https://doi.org/10.5194/gc-5-87-2022, https://doi.org/10.5194/gc-5-87-2022, 2022
Short summary
Short summary
Many projects in their reporting phase are required to provide a clear plan for evaluating the results of those efforts aimed at translating scientific results to a broader audience. This paper illustrates methodologies and strategies used in the framework of a European research project to assess the impact of knowledge transfer activities, both quantitatively and qualitatively, and provides recommendations and hints for developing a useful impact plan for scientific projects.
Klaus Dethloff, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, Dörthe Handorf, Robert Ricker, Vladimir Bessonov, John J. Cassano, Jaclyn Clement Kinney, Robert Osinski, Markus Rex, Annette Rinke, Julia Sokolova, and Anja Sommerfeld
The Cryosphere, 16, 981–1005, https://doi.org/10.5194/tc-16-981-2022, https://doi.org/10.5194/tc-16-981-2022, 2022
Short summary
Short summary
Sea ice thickness anomalies during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) winter in January, February and March 2020 were simulated with the coupled Regional Arctic climate System Model (RASM) and compared with CryoSat-2/SMOS satellite data. Hindcast and ensemble simulations indicate that the sea ice anomalies are driven by nonlinear interactions between ice growth processes and wind-driven sea-ice transports, with dynamics playing a dominant role.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
Short summary
Short summary
Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
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
Short summary
Short summary
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.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
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
Short summary
Short summary
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.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
Short summary
Short summary
Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
Short summary
Short summary
The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
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
Short summary
Short summary
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.
Thomas Krumpen, Luisa von Albedyll, Helge F. Goessling, Stefan Hendricks, Bennet Juhls, Gunnar Spreen, Sascha Willmes, H. Jakob Belter, Klaus Dethloff, Christian Haas, Lars Kaleschke, Christian Katlein, Xiangshan Tian-Kunze, Robert Ricker, Philip Rostosky, Janna Rückert, Suman Singha, and Julia Sokolova
The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, https://doi.org/10.5194/tc-15-3897-2021, 2021
Short summary
Short summary
We use satellite data records collected along the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift to categorize ice conditions that shaped and characterized the floe and surroundings during the expedition. A comparison with previous years is made whenever possible. The aim of this analysis is to provide a basis and reference for subsequent research in the six main research areas of atmosphere, ocean, sea ice, biogeochemistry, remote sensing and ecology.
Christian Zeman, Nils P. Wedi, Peter D. Dueben, Nikolina Ban, and Christoph Schär
Geosci. Model Dev., 14, 4617–4639, https://doi.org/10.5194/gmd-14-4617-2021, https://doi.org/10.5194/gmd-14-4617-2021, 2021
Short summary
Short summary
Kilometer-scale atmospheric models allow us to partially resolve thunderstorms and thus improve their representation. We present an intercomparison between two distinct atmospheric models for 2 summer days with heavy thunderstorms over Europe. We show the dependence of precipitation and vertical wind speed on spatial and temporal resolution and also discuss the possible influence of the system of equations, numerical methods, and diffusion in the models.
Graeme Marlton, Andrew Charlton-Perez, Giles Harrison, Inna Polichtchouk, Alain Hauchecorne, Philippe Keckhut, Robin Wing, Thierry Leblanc, and Wolfgang Steinbrecht
Atmos. Chem. Phys., 21, 6079–6092, https://doi.org/10.5194/acp-21-6079-2021, https://doi.org/10.5194/acp-21-6079-2021, 2021
Short summary
Short summary
A network of Rayleigh lidars have been used to infer the upper-stratosphere temperature bias in ECMWF ERA-5 and ERA-Interim reanalyses during 1990–2017. Results show that ERA-Interim exhibits a cold bias of −3 to −4 K between 10 and 1 hPa. Comparisons with ERA-5 found a smaller bias of 1 K which varies between cold and warm between 10 and 3 hPa, indicating a good thermal representation of the atmosphere to 3 hPa. These biases must be accounted for in stratospheric studies using these reanalyses.
Nicola Maher, Sebastian Milinski, and Ralf Ludwig
Earth Syst. Dynam., 12, 401–418, https://doi.org/10.5194/esd-12-401-2021, https://doi.org/10.5194/esd-12-401-2021, 2021
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
Short summary
Short summary
This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Jun-Ichi Yano and Nils P. Wedi
Atmos. Chem. Phys., 21, 4759–4778, https://doi.org/10.5194/acp-21-4759-2021, https://doi.org/10.5194/acp-21-4759-2021, 2021
Short summary
Short summary
Sensitivities of forecasts of the Madden–Julian oscillation (MJO) to various different configurations of the physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear free wave. To emulate free dynamics in the IFS,
various momentum dissipation terms (
friction) as well as diabatic heating were selectively turned off over the tropics for the range of the latitudes from 20° S to 20° N.
Marie-Luise Kapsch, Uwe Mikolajewicz, Florian A. Ziemen, Christian B. Rodehacke, and Clemens Schannwell
The Cryosphere, 15, 1131–1156, https://doi.org/10.5194/tc-15-1131-2021, https://doi.org/10.5194/tc-15-1131-2021, 2021
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
Short summary
Short summary
This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Maurin Zouzoua, Fabienne Lohou, Paul Assamoi, Marie Lothon, Véronique Yoboue, Cheikh Dione, Norbert Kalthoff, Bianca Adler, Karmen Babić, Xabier Pedruzo-Bagazgoitia, and Solène Derrien
Atmos. Chem. Phys., 21, 2027–2051, https://doi.org/10.5194/acp-21-2027-2021, https://doi.org/10.5194/acp-21-2027-2021, 2021
Short summary
Short summary
Based on a field experiment conducted in June and July 2016, we analyzed the daytime breakup of continental low-level stratiform clouds over southern West Africa in order to provide complementary guidance for model evaluation during the monsoon season. Those clouds exhibit weaker temperature and moisture jumps at the top compared to marine stratiform clouds. Their lifetime and the transition towards shallow convective clouds during daytime hours depend on their coupling with the surface.
Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
Short summary
Short summary
Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Wolfgang Woiwode, Andreas Dörnbrack, Inna Polichtchouk, Sören Johansson, Ben Harvey, Michael Höpfner, Jörn Ungermann, and Felix Friedl-Vallon
Atmos. Chem. Phys., 20, 15379–15387, https://doi.org/10.5194/acp-20-15379-2020, https://doi.org/10.5194/acp-20-15379-2020, 2020
Short summary
Short summary
The lowermost-stratosphere moist bias in ECMWF analyses and 12 h forecasts is diagnosed for the Arctic winter-spring 2016 period by using two-dimensional GLORIA water vapor observations. The bias is already present in the initial conditions (i.e., the analyses), and sensitivity forecasts on time scales of < 12 h show hardly any sensitivity to modified spatial resolution and output frequency.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Sebastian Milinski, Nicola Maher, and Dirk Olonscheck
Earth Syst. Dynam., 11, 885–901, https://doi.org/10.5194/esd-11-885-2020, https://doi.org/10.5194/esd-11-885-2020, 2020
Short summary
Short summary
Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool to quantify the forced response and internal variability in various components of the climate system, but there is no established method to determine the required ensemble size for a given problem. We propose a new framework that can be used to estimate the required ensemble size from a model's control run or an existing large ensemble.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
Short summary
Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, and Emanuel Dutra
Geosci. Model Dev., 13, 3975–3993, https://doi.org/10.5194/gmd-13-3975-2020, https://doi.org/10.5194/gmd-13-3975-2020, 2020
Short summary
Short summary
We used earth observations to evaluate and improve the representation of land surface temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX land surface models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction in daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
Short summary
Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Guillaume Dodet, Jean-François Piolle, Yves Quilfen, Saleh Abdalla, Mickaël Accensi, Fabrice Ardhuin, Ellis Ash, Jean-Raymond Bidlot, Christine Gommenginger, Gwendal Marechal, Marcello Passaro, Graham Quartly, Justin Stopa, Ben Timmermans, Ian Young, Paolo Cipollini, and Craig Donlon
Earth Syst. Sci. Data, 12, 1929–1951, https://doi.org/10.5194/essd-12-1929-2020, https://doi.org/10.5194/essd-12-1929-2020, 2020
Short summary
Short summary
Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent. The CCI is a program of the European Space Agency, whose objective is to realize the full potential of global Earth Observation archives in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset.
Francesca Di Giuseppe, Claudia Vitolo, Blazej Krzeminski, Christopher Barnard, Pedro Maciel, and Jesús San-Miguel
Nat. Hazards Earth Syst. Sci., 20, 2365–2378, https://doi.org/10.5194/nhess-20-2365-2020, https://doi.org/10.5194/nhess-20-2365-2020, 2020
Short summary
Short summary
Forecasting of daily fire weather indices driven by the ECMWF ensemble prediction system is shown to have a good skill up to 10 d ahead in predicting flammable conditions in most regions of the world. The availability of these forecasts through the Copernicus Emergency Management Service can extend early warnings by up to 1–2 weeks, allowing for greater proactive coordination of resource-sharing and mobilization within and across countries.
Daniel Steinfeld, Maxi Boettcher, Richard Forbes, and Stephan Pfahl
Weather Clim. Dynam., 1, 405–426, https://doi.org/10.5194/wcd-1-405-2020, https://doi.org/10.5194/wcd-1-405-2020, 2020
Short summary
Short summary
The effect of latent heating on atmospheric blocking is investigated using numerical sensitivity experiments. The modification of latent heating in the upstream cyclone has substantial effects on the upper-tropospheric circulation, demonstrating that some blocking systems do not develop at all without upstream latent heating. The results highlight the importance of moist-diabatic processes for the dynamics of prolonged anticyclonic circulation anomalies.
Cited articles
Ahn, M.-S., Kim, D., Kang, D., Lee, J., Sperber, K. R., Gleckler, P. J., Jiang, X., Ham, Y.-G., and Kim, H.: MJO propagation across the Maritime Continent: Are CMIP6 models better than CMIP5 models?, Geophys. Res. Lett., 47, e2020GL087250, https://doi.org/10.1029/2020GL087250, 2020.
Arduini, G., Balsamo, G., Dutra, E., Day, J. J., Sandu, I., Boussetta, S., and Haiden, T.: Impact of a multi-layer snow scheme on near-surface weather forecasts, J. Adv. Model. Earth Sy., 11, 4687–4710, https://doi.org/10.1029/2019MS001725, 2019.
Baldwin, M. P., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P. H., Randel, W. J., Holton, J. R., Alexander, M. J., Hirota, I., Horinouchi, T., Jones, D. B. A., Kinnersley, J. S., Marquardt, C., Sato, K., and Takahashi, M.: The quasi-biennial oscillation, Rev. Geophys., 39, 179–229, https://doi.org/10.1029/1999RG000073, 2001.
Bauer, P., Quintino, T., Wedi, N., Bonanni, A., Chrust, M., Deconinck, W., Diamantakis, M., Düben, P., English, S., Flemming, J., Gillies, P., Hadade, I., Hawkes, J., Hawkins, M., Iffrig, O., Kühnlein, C., Lange, M., Lean, P., Marsden, O., Müller, A., Saarinen, S., Sarmany, D., Sleigh, M., Smart, S., Smolarkiewicz, P., Thiemert, D., Tumolo, G., Weihrauch, C., Zanna, C., and Maciel, P.: The ECMWF scalability programme: Progress and plans, European Centre for Medium Range Weather Forecasts, https://doi.org/10.21957/gdit22ulm, 2020.
Bauer, P., Dueben, P. D., Hoefler, T., Quintino, T., Schulthess, T., and Wedi, N. P.: The digital revolution of Earth-system science, Nat. Comput. Sci., 1, 104–113, https://doi.org/10.1038/s43588-021-00023-0, 2021.
Bauer, P., Quintino, T., and Wedi, N.P.: From the Scalability Programme to Destination Earth, ECMWF Newsletter, 171, 15–22, https://doi.org/10.21957/pb2vnp59ks, 2022.
Bechtold, P., Köhler, M., Jung, T., Leutbecher, M., Rodwell, M., Vitart, F., and Balsamo, G.: Advances in predicting atmospheric variability with the ECMWF model: From synoptic to decadal time-scales, Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008.
Bechtold, P., Semane, N., Lopez, P., Chaboureau, J.-P., Beljaars, A., and Bormann, N.: Representing equilibrium and non-equilibrium convection in large-scale models, J. Atmos. Sci., 134, 1337–1351, https://doi.org/10.1175/JAS-D-13-0163.1, 2014.
Becker, T., Bechtold, P., and Sandu, I.: Characteristics of convective precipitation over tropical Africa in storm-resolving global simulations, Q. J. Roy. Meteor. Soc., 147, 4388–4407, https://doi.org/10.1002/qj.4185, 2021.
Beljaars, A. C. M., Brown, A. R., and Wood, N.: A new parametrization of turbulent orographic form drag, Q. J. Roy. Meteor. Soc., 130, 1327–1347, https://doi.org/10.1256/qj.03.73, 2004.
Bengtsson, L, Dias, J., Gehne, M., Bechtold, P., Whitaker, J., Bao, J.-W., Magnusson, L., Michelson, S., Pegion, P., Tulich, S., and Kiladis, G.: Convectively coupled equatorial wave simulations using the ECMWF IFS and the NOAA GFS cumulus convection schemes in the NOAA GFS model, Mon. Weather Rev, 147, 4005–4025, https://doi.org/10.1175/MWR-D-19-0195.1, 2019.
Berthou, S., Rowell, D. P., Kendon, E. J., Roberts, M. J., Stratton, R. A., Crook, J. A., and Wilcox, C: Improved climatological precipitation characteristics over West Africa at convection-permitting scales, Clim. Dynam., 53, 1991–2011, https://doi.org/10.1007/s00382-019-04759-4, 2019.
Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus, R., Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H., Watanabe, M., and Webb, M. J.: Clouds, circulation and climate sensitivity, Nat. Geosci., 8, 261–268, https://doi.org/10.1038/ngeo2398, 2015.
Boussetta, S., Balsamo, G., Arduini, G., Dutra, E., McNorton, J., Choulga, M., Agustí-Panareda, A., Beljaars, A., Wedi, N., Munõz-Sabater, J., de Rosnay, P, Sandu, I., Hadade, I., Carver, G., Mazzetti, C., Prudhomme, C., Yamazaki, D., and Zsoter, E.: ECLand: The ECMWF Land Surface Modelling System, Atmosphere, 12, 723, https://doi.org/10.3390/atmos12060723, 2021.
Bozzo, A., Benedetti, A., Flemming, J., Kipling, Z., and Rémy, S.: An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF, Geosci. Model Dev., 13, 1007–1034, https://doi.org/10.5194/gmd-13-1007-2020, 2020.
Bryan, F. O., Gent, P. R., and Tomas, R.: Can Southern Ocean Eddy Effects Be Parameterized in Climate Models?, J. Climate, 27, 411–425, https://doi.org/10.1175/JCLI-D-12-00759.1, 2014.
Bushell, A. C., Anstey, J. A., Butchart, N., Kawatani, Y., Osprey, S. M., Richter, J. H., Serva, F., Braesicke, P., Cagnazzo, C., Chen, C.-C., Chun, H.-.-Y., Garcia, R. R., Gray, L. J., Hamilton, K., Kerzenmacher, T., Kim, Y.-.-H., Lott, F., McLandress, C., Naoe, H., Scinocca, J., Smith, A. K., Stockdale, T. N., Versick, S., Watanabe, S., Yoshida, K., and Yukimoto, S.: Evaluation of the Quasi-Biennial Oscillation in global climate models for the SPARC QBO-initiative, Q. J. Roy. Meteor. Soc., 148, 1459–1489, https://doi.org/10.1002/qj.3765, 2022.
Cao, B., Arduini, G., and Zsoter, E.: Brief communication: Improving ERA5-Land soil temperature in permafrost regions using an optimized multi-layer snow scheme, The Cryosphere, 16, 2701–2708, https://doi.org/10.5194/tc-16-2701-2022, 2022.
Chen, G., Ling, J., Zhang, R., Xiao, Z., and Li, C.: The MJO from CMIP5 to CMIP6: Perspectives from tracking MJO precipitation, Geophys. Res. Lett., 49, e2021GL095241, https://doi.org/10.1029/2021GL095241, 2022.
Copernicus Marine Data Store: Overview of products, http://marine.copernicus.eu/services-portfolio/access-to-products/, last access: 7 November 2024.
Crook, J., Klein, C., Folwell, S., Taylor, C. M., Parker, D. J., Stratton, R., and Stein, T.: Assessment of the representation of West African storm lifecycles in convection-permitting simulations, Earth Space Sci., 6, 818–835, https://doi.org/10.1029/2018EA000491, 2019.
Dai, A., Qian, T., Trenberth, K. E., and Milliman, J. D.: Changes in Continental Freshwater Discharge from 1948 to 2004, J. Climate, 22, 2773–2792, https://doi.org/10.1175/2008JCLI2592.1, 2009.
Danilov, S., Sidorenko, D., Wang, Q., and Jung, T.: The Finite-volumE Sea ice–Ocean Model (FESOM2), Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, 2017.
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Iudicone, D.: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res.-Oceans, 109 1–20, https://doi.org/10.1029/2004JC002378, 2004.
de Boyer Montégut, C.: Mixed layer depth climatology computed with a density threshold criterion of 0.03kg/m3 from 10 m depth value, SEANOE [data set], https://doi.org/10.17882/91774, 2023.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Diamantakis, M. and Agusti-Panareda, A.: A positive definite tracer mass fixer for high resolution weather and atmospheric composition forecasts, ECMWF Technical Memoranda, 819, https://doi.org/10.21957/qpogzoy, 2017.
Diamantakis, M. and Flemming, J.: Global mass fixer algorithms for conservative tracer transport in the ECMWF model, Geosci. Model Dev., 7, 965–979, https://doi.org/10.5194/gmd-7-965-2014, 2014.
Diamantakis, M. and Váňa, F.: A fast converging and concise algorithm for computing the departure points in semi-Lagrangian weather and climate models, Q. J. Roy. Meteor. Soc., 148, 670–684, https://doi.org/10.1002/qj.4224, 2021.
Dias, J., Gehne, M., Kiladis, G. N., Sakaeda, N., Bechtold, P., and Haiden, T.: Equatorial waves and the skill of NCEP and ECMWF forecast systems, Mon. Weather Rev., 146, 1763–1784, https://doi.org/10.1175/MWR-D-17-0362.1, 2018.
ECMWF: ECMWF IFS Documentation CY48R1 – Part III: Dynamics and Numerical Procedures, IFS Documentation CY48R1, https://doi.org/10.21957/26f0ad3473, 2023a.
ECMWF: ECMWF IFS documentation CY48R1 – Part IV Physical processes, IFS Documentation CY48R1, https://doi.org/10.21957/02054f0fbf, 2023b.
ECMWF: ECMWF IFS Documentation CY48R1 – Part VII: ECMWF Wave Model, IFS Documentation CY48R1, https://doi.org/10.21957/cd1936d846, 2023c.
ECMWF GitHub: Software to work with meteorological data and services, https://github.com/ecmwf, last access: 7 November 2024.
ECMWF News Item: nextGEMS probes km-scale resolutions in the Integrated Forecasting System, https://www.ecmwf.int/en/about/media-centre/news/2022/nextgems-probes-km-scale-resolutions-integrated-forecasting-system/ (last access: 4 January 2024), October 2022.
ECMWF Newsletter 172: Fixing water and energy budget imbalances in the Integrated Forecasting System, https://www.ecmwf.int/en/newsletter/172/ news/fixing-water-and-energy-budget-imbalances-integrated-forecasting-system/ (last access: 4 January 2024), Summer 2022.
Engwirda, D.: JIGSAW-GEO (1.0): locally orthogonal staggered unstructured grid generation for general circulation modelling on the sphere, Geosci. Model Dev., 10, 2117–2140, https://doi.org/10.5194/gmd-10-2117-2017, 2017.
EUMETSAT: Land Surface Analysis Satellite Application Facility (LSA SAF) data service, https://datalsasaf.lsasvcs.ipma.pt/PRODUCTS/MSG/MLST/, last access: 7 November 2024.
Faroux, S., Kaptué Tchuenté, A. T., Roujean, J.-L., Masson, V., Martin, E., and Le Moigne, P.: ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models, Geosci. Model Dev., 6, 563–582, https://doi.org/10.5194/gmd-6-563-2013, 2013.
FESOM2 GitHub: The Finite Element Sea Ice-Ocean Model (FESOM2), https://github.com/FESOM/fesom2, last access: 7 November 2024.
Fielding, M. D., Schäfer, S. A. K., Hogan, R. J., and Forbes, R. M.: Parametrizing cloud geometry and its application in a subgrid cloud-edge erosion scheme, Q. J. Roy. Meteor. Soc., 146, 1651–1667, https://doi.org/10.1002/qj.3758, 2020.
Forbes, R. M. and Ahlgrimm, M.: On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model, Mon. Weather Rev., 142, 3425–3445, https://doi.org/10.1175/MWR-D-13-00325.1, 2014.
Forbes, R. M., Tompkins, A. M., and Untch, A.: A new prognostic bulk microphysics scheme for the IFS, ECMWF Technical Memoranda, No. 649, https://doi.org/10.21957/bf6vjvxk, 2011.
Frenger, I., Gruber, N., Knutti, R., and Münnich, M.: Imprint of Southern Ocean eddies on winds, clouds and rainfall, Nat. Geosci., 6, 608–612, https://doi.org/10.1038/ngeo1863, 2013.
Gao, K., Harris, L., Bender, M., Chen, J.-H., Zhou, L., and Knutson, T.: Regulating fine-scale resolved convection in high-resolution models for better hurricane track prediction, Geophys. Res. Lett., 50, e2023GL103329, https://doi.org/10.1029/2023GL103329, 2023.
Garfinkel, C. I., Gerber, E. P., Shamir, O., Rao, J., Jucker, M., White, I., and Paldor, N.: A QBO cookbook: Sensitivity of the quasi-biennial oscillation to resolution, resolved waves, and parameterized gravity waves, J. Adv. Model. Earth Sy., 14, e2021MS002568, https://doi.org/10.1029/2021MS002568, 2022.
German Climate Computing Center (DKRZ): Registration on Levante supercomputer, https://luv.dkrz.de/register/, last access: 7 November 2024.
Goessling, H. F., Tietsche, S., Day, J. J., Hawkins, E., and Jung, T.: Predictability of the Arctic sea ice edge, Geophys. Res. Lett., 43, 1642–1650, https://doi.org/10.1002/2015GL067232, 2016.
Griffies, S. M., Winton, M., Anderson, W. G., Benson, R., Delworth, T. L., Dufour, C. O., Dunne, J. P., Goddard, P., Morrison, A. K., Rosati, A., Wittenberg, A.T., Yin, J., and Zhang, R.: Impacts on Ocean Heat from Transient Mesoscale Eddies in a Hierarchy of Climate Models, J. Climate, 28, 952–977, https://doi.org/10.1175/JCLI-D-14-00353.1, 2015.
Gutjahr, O., Jungclaus, J. H., Brüggemann, N., Haak, H., and Marotzke, J.: Air-sea interactions and water mass transformation during a katabatic storm in the Irminger Sea, J. Geophys. Res.-Oceans, 127, e2021JC018075, https://doi.org/10.1029/2021JC018075, 2022.
Hallberg, R.: Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects, Ocean Model., 72, 92–103, https://doi.org/10.1016/j.ocemod.2013.08.007, 2013.
Hannah, W. M. and Maloney, E. D.: The role of moisture–convection feedbacks in simulating the Madden–Julian oscillation, J. Climate, 24, 2754–2770, https://doi.org/10.1175/2011JCLI3803.1, 2011.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hewitt, H., Fox-Kemper, B., Pearson, B. Roberts, M., and Klocke, D.: The small scales of the ocean may hold the key to surprises, Nat. Clim. Change, 12, 496–499, https://doi.org/10.1038/s41558-022-01386-6, 2022.
Hogan, R. J. and Bozzo, A.: A flexible and efficient radiation scheme for the ECMWF model, J. Adv. Model. Earth Sy., 10, 1990–2008, https://doi.org/10.1029/2018MS001364, 2018.
Hogg, A. McC., Meredith, M. P., Chambers, D. P., Abrahamsen, E. P., Hughes, C. W., and Morrison, A. K.: Recent trends in the Southern Ocean eddy field, J. Geophys. Res.-Oceans, 120, 57–267, https://doi.org/10.1002/2014JC010470, 2015.
Hohenegger, C., Korn, P., Linardakis, L., Redler, R., Schnur, R., Adamidis, P., Bao, J., Bastin, S., Behravesh, M., Bergemann, M., Biercamp, J., Bockelmann, H., Brokopf, R., Brüggemann, N., Casaroli, L., Chegini, F., Datseris, G., Esch, M., George, G., Giorgetta, M., Gutjahr, O., Haak, H., Hanke, M., Ilyina, T., Jahns, T., Jungclaus, J., Kern, M., Klocke, D., Kluft, L., Kölling, T., Kornblueh, L., Kosukhin, S., Kroll, C., Lee, J., Mauritsen, T., Mehlmann, C., Mieslinger, T., Naumann, A. K., Paccini, L., Peinado, A., Praturi, D. S., Putrasahan, D., Rast, S., Riddick, T., Roeber, N., Schmidt, H., Schulzweida, U., Schütte, F., Segura, H., Shevchenko, R., Singh, V., Specht, M., Stephan, C. C., von Storch, J.-S., Vogel, R., Wengel, C., Winkler, M., Ziemen, F., Marotzke, J., and Stevens, B.: ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales, Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, 2023.
Hortal, M.: The development and testing of a new two-time-level semi-Lagrangian scheme (SETTLS) in the ECMWF forecast model, Q. J. Roy. Meteor. Soc., 128, 1671–1687, https://doi.org/10.1002/qj.200212858314, 2002.
Hutter, N., Bouchat, A., Dupont, F., Dukhovskoy, D., Koldunov, N., Lee, Y. J., Lemieux, J.-F., Lique, C., Losch, M., Maslowski, W., Myers, P. G., Ólason, E., Rampal, P., Rasmussen, T., Talandier, C., Tremblay, B., and Wang, Q.: Sea Ice Rheology Experiment (SIREx): 2. Evaluating linear kinematic features in high-resolution sea ice simulations, J. Geophys. Res.-Oceans, 127, e2021JC017666, https://doi.org/10.1029/2021JC017666, 2022.
Johnson, S. J., Stockdale, T. N., Ferranti, L., Balmaseda, M. A., Molteni, F., Magnusson, L., Tietsche, S., Decremer, D., Weisheimer, A., Balsamo, G., Keeley, S. P. E., Mogensen, K., Zuo, H., and Monge-Sanz, B. M.: SEAS5: the new ECMWF seasonal forecast system, Geosci. Model Dev., 12, 1087–1117, https://doi.org/10.5194/gmd-12-1087-2019, 2019.
Jones, P. W.: First- and second-order conservative remapping schemes for grids in spherical coordinates, Mon. Weather Rev., 127, 2204–2210, https://doi.org/10.1175/1520-0493(1999)127<2204:FASOCR>2.0.CO;2, 1999.
Judt, F. and Rios-Berrios, R: Resolved convection improves the representation of equatorial waves and tropical rainfall variability in a global nonhydrostatic model, Geophys. Res. Lett., 48, e2021GL093265, https://doi.org/10.1029/2021GL093265, 2021.
Judt, F., Klocke, D., Rios-Berrios, R. Vanniere, B., Ziemen, F., Auger, L., Biercamp, J., Bretherton, C., Chen, X., Düben, P., Hohenegger, C., Khairoutdinov, M., Kodama, C., Kornblueh, L., Lin, S.-J., Nakano, M., Neumann, P., Putman, W., Röber, N., Roberts, M., Satoh, M., Shibuya, R., Stevens, B., Vidale, P. L., Wedi, N., and Zhou, L.: Tropical Cyclones in Global Storm-Resolving Models, J. Meteorol. Soc. Jpn. Ser. II, 99, 579–602, https://doi.org/10.2151/jmsj.2021-029, 2021.
Jung, T., Miller, M. J., Palmer, T. N., Towers, P., Wedi, N., Achuthavarier, D., Adams, J. M., Altshuler, E. L., Cash, B. A., Kinter III, J. L., Marx, L., Stan, C., and Hodges, K. I.: High-Resolution Global Climate Simulations with the ECMWF Model in Project Athena: Experimental Design, Model Climate, and Seasonal Forecast Skill, J. Climate, 25, 3155–3172, https://doi.org/10.1175/JCLI-D-11-00265.1, 2012.
Keeley, S. P. E., Sutton, R. T., and Shaffrey, L. C.: The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate, Q. J. Roy. Meteor. Soc., 138, 1774–1783, https://doi.org/10.1002/qj.1912, 2012.
Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P., Avila, D., Abdalla, S., Willing, C., and Jupyter development team: Jupyter notebooks – a publishing format for reproducible computational workflows, in: Positioning and Power in Academic Publishing: Players, Agents and Agendas, edited by: Loizides, F. and Schmidt, B., IOS Press, 87–90, https://doi.org/10.3233/978-1-61499-649-1-87, 2016.
Kodama, C., Yamada, Y., Noda, A. T., Kikuchi, K., Kajikawa, Y., Nasuno, T., Tomita, T., Yamaura, T., Takahashi, H. G., Hara, M., Kawatani, Y., Satoh, M., and Sugi, M.: A 20-year climatology of a NICAM AMIP-type simulation, J. Meteorol. Soc. Jpn. Ser. II, 93, 393–424, https://doi.org/10.2151/jmsj.2015-024, 2015.
Kodama, C., Ohno, T., Seiki, T., Yashiro, H., Noda, A. T., Nakano, M., Yamada, Y., Roh, W., Satoh, M., Nitta, T., Goto, D., Miura, H., Nasuno, T., Miyakawa, T., Chen, Y.-W., and Sugi, M.: The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates, Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, 2021.
Köhler, M., Ahlgrimm, M. and Beljaars, A.: Unified treatment of dry convective and stratocumulus-topped boundary layers in the ECMWF model, Q. J. Roy. Meteor. Soc., 137, 43–57, https://doi.org/10.1002/qj.713, 2011.
Koldunov, N. V., Aizinger, V., Rakowsky, N., Scholz, P., Sidorenko, D., Danilov, S., and Jung, T.: Scalability and some optimization of the Finite-volumE Sea ice–Ocean Model, Version 2.0 (FESOM2), Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, 2019.
Koldunov, N., Kölling, T., Pedruzo-Bagazgoitia, X., Rackow, T., Redler, R., Sidorenko, D., Wieners, K.-H., Ziemen, F. A.: nextGEMS: output of the model development cycle 3 simulations for ICON and IFS, World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.26050/WDCC/nextGEMS_cyc3, 2023.
Kölling, T., Kluft, L., and Rackow, T.: gribscan (v0.0.10), Zenodo [code], https://doi.org/10.5281/zenodo.10625189, 2024.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air–sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2009.
Liebmann, B. and Smith, C. A.: Description of a Complete (Interpolated) Outgoing Longwave Radiation Dataset, B. Am. Meteorol. Soc., 77, 1275–1277, 1996.
Ling, J., Zhao, Y., and Chen, G.: Barrier effect on MJO propagation by the Maritime Continent in the MJO Task Force/GEWEX atmospheric system study models, J. Climate, 32, 5529–5547, https://doi.org/10.1175/JCLI-D-18-0870.1, 2019.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product, J. Climate, 31, 895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Youing, L., and Merchant, J. W.: Development of a global land cover characteristics database and IGB6 DISCover from the 1 km AVHRR data, Int. J. Remote Sens., 21, 1303–1330, https://doi.org/10.1080/014311600210191, 2000.
Lott, F. and Miller, M. J.: A new subgrid-scale orographic drag parametrization: Its formulation and testing, Q. J. Roy. Meteor. Soc., 123, 101–127, https://doi.org/10.1002/qj.49712353704, 1997.
Lüpkes, C., Vihma, T., Birnbaum, G., and Wacker, U.: Influence of leads in sea ice on the temperature of the atmospheric boundary layer during polar night, Geophys. Res. Lett., 35, L03805, https://doi.org/10.1029/2007GL032461, 2008.
Macdonald, R. W., Griffiths, R. F., and Hall, D. J.: An improved method for the estimation of surface roughness of obstacle arrays, Atmos. Environ., 32, 1857–1864, https://doi.org/10.1016/s1352-2310(97)00403-2, 1998.
Madden, R. A. and Julian, P. R.: Description of global-scale circulation cells in the tropics with a 40–50 day period, J. Atmos. Sci., 29, 1109–1123, https://doi.org/10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2, 1972.
Malardel, S., Wedi, N., Deconinck, W., Diamantakis, M., Kuehnlein, C., Mozdzynski, G., Hamrud, M., and Smolarkiewicz, P.: A new grid for the IFS, ECMWF Newsletter, 146, 23–28, https://doi.org/10.21957/zwdu9u5i, 2016.
Marti, O., Nguyen, S., Braconnot, P., Valcke, S., Lemarié, F., and Blayo, E.: A Schwarz iterative method to evaluate ocean–atmosphere coupling schemes: implementation and diagnostics in IPSL-CM6-SW-VLR, Geosci. Model Dev., 14, 2959–2975, https://doi.org/10.5194/gmd-14-2959-2021, 2021.
McNorton, J. R., Arduini, G., Bousserez, N., Agustí-Panareda, A., Balsamo, G., Boussetta, S., Choulga, M., Hadade, I., and Hogan, R. J.: An urban scheme for the ECMWF integrated forecasting system: Single-column and global offline application, J. Adv. Model. Earth Sy., 13, e2020MS002375, https://doi.org/10.1029/2020MS002375, 2021.
McNorton, J. R., Agustí-Panareda, A., Arduini, G., Balsamo, G., Bousserez, N., Boussetta, S., Chericoni, M., Choulga, M., Engelen, R., and Guevara, M.: An urban scheme for the ECMWF Integrated forecasting system: Global forecasts and residential CO2 emissions, J. Adv. Model. Earth Sy., 15, e2022MS003286, https://doi.org/10.1029/2022MS003286, 2023.
Miura, H., Satoh, M., Nasuno, T., Noda, A. T., and Oouchi, K.: A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model, Science, 318, 1763–1765, https://doi.org/10.1126/science.1148443, 2007.
Miyakawa, T., Yashiro, H., Suzuki, T., Tatebe, H., and Satoh, M.: A Madden-Julian Oscillation event remotely accelerates ocean upwelling to abruptly terminate the 1997/1998 super El Niño, Geophys. Res. Lett., 44, 9489–9495, https://doi.org/10.1002/2017GL074683, 2017.
Mogensen, K. S., Keeley, S., and Towers, P.: Coupling of the NEMO and IFS models in a single executable, ECMWF Technical Memoranda, 673, https://doi.org/10.21957/rfplwzuol, 2012.
Mogensen, K. S., Magnusson, L., and Bidlot, J.-R.: Tropical cyclone sensitivity to ocean coupling in the ECMWF coupled model, J. Geophys. Res.-Oceans, 122, 4392–4412, https://doi.org/10.1002/2017JC012753, 2017.
Morrison, A. K., Hogg, A. McC., England, M. H., and Spence, P.: Warm Circumpolar Deep Water transport toward Antarctica driven by local dense water export in canyons, Sci. Adv., 6, 85–101, https://doi.org/10.1126/sciadv.aav2516, 2020.
Mu, L., Nerger, L., Tang, Q., Loza, S. N., Sidorenko, D., Wang, Q., Semmler, T., Zampieri, L., Losch, M., and Goessling, H. F.: Toward a data assimilation system for seamless sea ice prediction based on the AWI Climate Model, J. Adv. Model. Earth Sy., 12, e2019MS001937, https://doi.org/10.1029/2019MS001937, 2020.
Mu, L., Nerger, L., Streffing, J., Tang, Q., Niraula, B., Zampieri, L., Loza, S. L., and Goessling, H. F.: Sea-ice forecasts with an upgraded AWI Coupled Prediction System, J. Adv. Model. Earth Sy., 14, e2022MS003176, https://doi.org/10.1029/2022MS003176, 2022.
Müller, A., Deconinck, W., Kühnlein, C., Mengaldo, G., Lange, M., Wedi, N., Bauer, P., Smolarkiewicz, P. K., Diamantakis, M., Lock, S.-J., Hamrud, M., Saarinen, S., Mozdzynski, G., Thiemert, D., Glinton, M., Bénard, P., Voitus, F., Colavolpe, C., Marguinaud, P., Zheng, Y., Van Bever, J., Degrauwe, D., Smet, G., Termonia, P., Nielsen, K. P., Sass, B. H., Poulsen, J. W., Berg, P., Osuna, C., Fuhrer, O., Clement, V., Baldauf, M., Gillard, M., Szmelter, J., O'Brien, E., McKinstry, A., Robinson, O., Shukla, P., Lysaght, M., Kulczewski, M., Ciznicki, M., Piątek, W., Ciesielski, S., Błażewicz, M., Kurowski, K., Procyk, M., Spychala, P., Bosak, B., Piotrowski, Z. P., Wyszogrodzki, A., Raffin, E., Mazauric, C., Guibert, D., Douriez, L., Vigouroux, X., Gray, A., Messmer, P., Macfaden, A. J., and New, N.: The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale, Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, 2019.
Nogueira, M., Boussetta, S., Balsamo, G., Albergel, C., Trigo, I. F., Johannsen, F., Miralles, D. G., and Dutra, E.: Upgrading land-cover and vegetation seasonality in the ECMWF coupled system: Verification with FLUXNET sites, METEOSAT satellite land surface temperatures, and ERA5 atmospheric reanalysis, J. Geophys. Res.-Atmos., 126, e2020JD034163, https://doi.org/10.1029/2020JD034163, 2021.
OpenIFS licence: Overview, Objectives, and Further Information, http://www.ecmwf.int/en/research/projects/openifs, last access: 7 November 2024.
Orr, A., Bechtold, P., Scinocca, J. F., Ern, M., and Janiskova, M.: Improved middle atmosphere climate and forecasts in the ECMWF model through a non-orographic gravity wave drag parametrization, J. Climate, 23, 5905–5926, https://doi.org/10.1175/2010JCLI3490.1, 2010.
OSI SAF: Global Sea Ice Concentration Climate Data Record v3.0 – Multimission, EUMETSAT SAF on Ocean and Sea Ice [data set], https://doi.org/10.15770/EUM_SAF_OSI_0013, 2022.
Overland, J. E., Curtin, T. B., and Smith Jr., W. O.: Preface [to special section on Leads and Polynyas], J. Geophys. Res., 100, 4267–4268, https://doi.org/10.1029/95JC00336, 1995.
Palmer, T.: Climate forecasting: Build high-resolution global climate models, Nature, 515, 338–339, https://doi.org/10.1038/515338a, 2014.
Palmer, T. and Stevens, B.: The scientific challenge of understanding and estimating climate change, P. Natl. Acad. Sci. USA, 116, 24390–24395, https://doi.org/10.1073/pnas.1906691116, 2019.
Paul, M. J. and Meyer, J. L.: Streams in the urban landscape, Annu. Rev. Ecol. Syst., 32, 333–365, https://doi.org/10.1146/annurev.ecolsys.32.081501.114040, 2001.
Pedruzo-Bagazgoitia, X., Rackow, T., and Hadade, I.: IFS-FESOM nextGEMS Cycle 2 4.4 km 1-year simulation, ECMWF [data set], https://doi.org/10.21957/1n36-qg55, 2022a.
Pedruzo-Bagazgoitia, X., Rackow, T., and Hadade, I.: IFS-NEMO nextGEMS Cycle 2 9 km baseline 2-year simulation, ECMWF [data set], https://doi.org/10.21957/x4vb-3b40, 2022b.
Polichtchouk, I., Wedi, N., and Kim, Y.-H.: Resolved gravity waves in the tropical stratosphere: Impact of horizontal resolution and deep convection parametrization, Q. J. Roy. Meteor. Soc., 148, 233–251, https://doi.org/10.1002/qj.4202, 2021.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., van Lipzig, N. P. M., and Leung, R.: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Pujol, M.-I., Faugère, Y., Taburet, G., Dupuy, S., Pelloquin, C., Ablain, M., and Picot, N.: DUACS DT2014: the new multi-mission altimeter data set reprocessed over 20 years, Ocean Sci., 12, 1067–1090, https://doi.org/10.5194/os-12-1067-2016, 2016.
Rackow, T., Sein, D. V., Semmler, T., Danilov, S., Koldunov, N. V., Sidorenko, D., Wang, Q., and Jung, T.: Sensitivity of deep ocean biases to horizontal resolution in prototype CMIP6 simulations with AWI-CM1.0, Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, 2019.
Rackow, T., Danilov, S., Goessling, H. F., Hellmer, H. H., Sein, D. V., Semmler, T., Sidorenko, D., and Jung, T.: Delayed Antarctic sea-ice decline in high-resolution climate change simulations, Nat. Commun., 13, 637, https://doi.org/10.1038/s41467-022-28259-y, 2022.
Rackow, T., Pedruzo-Bagazgoitia, X., and Becker, T.: Namelist files and settings for multi-year km-scale nextGEMS Cycle 3 simulations with IFS-FESOM/NEMO, Zenodo [data set], https://doi.org/10.5281/zenodo.10221652, 2023a.
Rackow, T., Becker, T., Forbes, R., and Fielding, M.: Source code changes to the Integrated Forecasting System (IFS) for nextGEMS simulations, Zenodo [code], https://doi.org/10.5281/zenodo.10223577, 2023b.
Rackow, T., Hegewald, J., Koldunov, N. V., Mogensen, K., Scholz, P., Sidorenko, D., and Streffing, J.: FESOM2.5 source code used in nextGEMS Cycle 3 simulations with IFS-FESOM, Zenodo [code], https://doi.org/10.5281/zenodo.10225420, 2023c.
Rackow, T., Kousal, J., Pedruzo-Bagazgoitia, X., and Zampieri, L.: trackow/nextGEMS-paper: Jupyter notebooks to reproduce the main figures of the nextGEMS overview paper, Zenodo [code], https://doi.org/10.5281/zenodo.13987877, 2024.
Randall, D. A. and Emanuel, K: The Weather–Climate Schism, B. Am. Meteorol. Soc., 105, E300–E305, https://doi.org/10.1175/BAMS-D-23-0124.1, 2024.
Saavedra Garfias, P., Kalesse-Los, H., von Albedyll, L., Griesche, H., and Spreen, G.: Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic, Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, 2023.
Sármány, D., Valentini, M., Maciel, P., Geier, P., Smart, S., Aguridan, R., Hawkes, J., and Quintino, T.: MultIO: A Framework for Message-Driven Data Routing For Weather and Climate Simulations, in: Proceedings of the Platform for Advanced Scientific Computing Conference (PASC '24), Association for Computing Machinery, New York, NY, USA, Article 24, 1–12, https://doi.org/10.1145/3659914.3659938, 2024.
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S.-J., Putman, W. M., and Düben, P.: Global Cloud-Resolving Models, Curr. Clim. Change Rep., 5, 172–184, https://doi.org/10.1007/s40641-019-00131-0, 2019.
Scaife, A. A., Baldwin, M. P., Butler, A. H., Charlton-Perez, A. J., Domeisen, D. I. V., Garfinkel, C. I., Hardiman, S. C., Haynes, P., Karpechko, A. Y., Lim, E.-P., Noguchi, S., Perlwitz, J., Polvani, L., Richter, J. H., Scinocca, J., Sigmond, M., Shepherd, T. G., Son, S.-W., and Thompson, D. W. J.: Long-range prediction and the stratosphere, Atmos. Chem. Phys., 22, 2601–2623, https://doi.org/10.5194/acp-22-2601-2022, 2022.
Schär, C., Fuhrer, O., Arteaga, A., Ban, N., Charpilloz, C., Di Girolamo, S., Hentgen, L., Hoefler, T., Lapillonne, X., Leutwyler, D., Osterried, K., Panosetti, D., Rüdisühli, S., Schlemmer, L., Schulthess, T. C., Sprenger, M., Ubbiali, S., and Wernli, H.: Kilometer-Scale Climate Models: Prospects and Challenges, B. Am. Meteorol. Soc., 101, E567–E587, https://doi.org/10.1175/BAMS-D-18-0167.1, 2020.
Scholz, P., Sidorenko, D., Gurses, O., Danilov, S., Koldunov, N., Wang, Q., Sein, D., Smolentseva, M., Rakowsky, N., and Jung, T.: Assessment of the Finite-volumE Sea ice-Ocean Model (FESOM2.0) – Part 1: Description of selected key model elements and comparison to its predecessor version, Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, 2019.
Schulthess, T. C., Bauer, P., Wedi, N., Fuhrer, O., Hoefler, T., and Schär, C.: Reflecting on the goal and baseline for exascale computing: A roadmap based on weather and climate simulations, Comput. Sci. Eng., 21, 30–41, https://doi.org/10.1109/MCSE.2018.2888788, 2019.
Sein, D. V., Koldunov, N. V., Danilov, S., Wang, Q., Sidorenko, D., Fast, I., Rackow, T., Cabos, W., and Jung, T.: Ocean modeling on a mesh with resolution following the local Rossby radius, J. Adv. Model. Earth Sy., 9, 2601–2614, https://doi.org/10.1002/2017MS001099, 2017.
Selivanova, J., Iovino, D., and Cocetta, F.: Past and future of the Arctic sea ice in High-Resolution Model Intercomparison Project (HighResMIP) climate models, The Cryosphere, 18, 2739–2763, https://doi.org/10.5194/tc-18-2739-2024, 2024.
Sidorenko, D., Goessling, H. F., Koldunov, N. V., Scholz, P., Danilov, S., Barbi, D., Cabos, W., Gurses, O., Harig, S., Hinrichs, C., Juricke, S., Lohmann, G., Losch, M., Mu, L., Rackow, T., Rakowsky, N., Sein, D., Semmler, T., Shi, X., Stepanek, C., Streffing, J., Wang, Q., Wekerle, C., Yang, H., and Jung, T.: Evaluation of FESOM2.0 coupled to ECHAM6.3: Pre-industrial and HighResMIP simulations, J. Adv. Model. Earth Sy., 11, 3794–3815, https://doi.org/10.1029/2019MS001696, 2019.
Siebesma, A. P., Soares, P. M., and Teixeira, J.: A combined eddy-diffusivity mass-flux approach for the convective boundary layer, J. Atmos. Sci., 64, 1230–1248, https://doi.org/10.1175/JAS3888.1, 2007.
Simmons, A. J. and Strüfing, R.: Numerical forecasts of stratospheric warming events using a model with a hybrid vertical coordinate, Q. J. Roy. Meteor. Soc., 109, 81–111, https://doi.org/10.1002/qj.49710945905, 1983.
Smart, S. D., Quintino, T., and Raoult, B.: A Scalable Object Store for Meteorological and Climate Data, in: Proceedings of the Platform for Advanced Scientific Computing Conference (PASC '17), Association for Computing Machinery, New York, NY, USA, Article 13, 1–8, https://doi.org/10.1145/3093172.3093238, 2017.
Stephan, C. C., Strube, C., Klocke, D., Ern, M., Hoffmann, L., Preusse, P., and Schmidt, H.: Gravity waves in global high-resolution simulations with explicit and parameterized convection, J. Geophys. Res.-Atmos., 124, 4446–4459, https://doi.org/10.1029/2018JD030073, 2019.
Stephan, C. C., Žagar, N., and Shepherd, T. G.: Waves and coherent flows in the tropical atmosphere: New opportunities, old challenges, Q. J. Roy. Meteor. Soc., 147, 2597–2624, https://doi.org/10.1002/qj.4109, 2021.
Stevens, B., Sherwood, S. C., Bony, S., and Webb, M. J.: Prospects for narrowing bounds on Earth's equilibrium climate sensitivity, Earth's Future, 4, 512–522, https://doi.org/10.1002/2016EF000376, 2016.
Stevens, B., Satoh, M., Auger, L., Biercamp, J., Bretherton, C.S., Chen, X., Düben, P., Judt, F., Khairoutdinov, M., Klocke, D., Kodama, C., Kornblueh, L., Lin, S.-L., Putman, W., Shibuya, R., Neumann, P., Röber, N., Vannier, B., Vidale, P.-L., Wedi, N., and Zhou, L.: DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains, Prog. Earth Planet. Sci., 6, 61, https://doi.org/10.1186/s40645-019-0304-z, 2019.
Stockdale, T. N., Kim, Y.-H., Anstey, J. A., Palmeiro, F. M., Butchart, N., Scaife, A. A., Andrews, M., Bushell, A. C., Dobrynin, M., Garcia-Serrano, J., Hamilton, K., Kawatani, Y., Lott, F., McLandress, C., Naoe, H., Osprey, S., Pohlmann, H., Scinocca, J., Watanabe, S., Yoshida, K., and Yukimoto, S.: Prediction of the quasi-biennial oscillation with a multi-model ensemble of QBO-resolving models, Q. J. Roy. Meteor. Soc., 148, 1519–1540, https://doi.org/10.1002/qj.3919, 2022.
Streffing, J., Sidorenko, D., Semmler, T., Zampieri, L., Scholz, P., Andrés-Martínez, M., Koldunov, N., Rackow, T., Kjellsson, J., Goessling, H., Athanase, M., Wang, Q., Hegewald, J., Sein, D. V., Mu, L., Fladrich, U., Barbi, D., Gierz, P., Danilov, S., Juricke, S., Lohmann, G., and Jung, T.: AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model, Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, 2022.
Suematsu, T. and Miura, H.: Zonal SST Difference as a Potential Environmental Factor Supporting the Longevity of the Madden–Julian Oscillation, J. Climate, 31, 7549–7564, https://doi.org/10.1175/JCLI-D-17-0822.1, 2018.
Takasuka, D. and Satoh, M.: Dynamical Roles of Mixed Rossby–Gravity Waves in Driving Convective Initiation and Propagation of the Madden–Julian Oscillation: General Views, J. Atmos. Sci., 77, 4211–4231, https://doi.org/10.1175/JAS-D-20-0050.1, 2020.
Takasuka, D., Kodama, C., Suematsu, T., Ohno, T., Yamada, Y., Seiki, T., Yashiro, H., Nakano, M., Miura, H., Noda, A. T., Nasuno, T., Miyakawa, T., and Masunaga, R.: How can we improve the seamless representation of climatological statistics and weather toward reliable global K-scale climate simulations?, J. Adv. Model. Earth Sy., 16, e2023MS003701, https://doi.org/10.1029/2023MS003701, 2024.
Takayabu, Y. N.: Large-scale cloud disturbances associated with equatorial waves Part I: Spectral features of the cloud disturbances, J. Meteorol. Soc. Jpn. Ser. II, 72, 433–449, https://doi.org/10.2151/jmsj1965.72.3_433, 1994.
Taylor, M., Caldwell, P. M., Bertagna, L., Clevenger, C., Donahue, A., Foucar, J., Guba, O., Hillman, B., Keen, N., Krishna, J., Norman, M., Sreepathi, S., Terai, C., White, J. B., Salinger, A. G., McCoy, R. B., Leung, L. R., Bader, D. C., and Wu, D.: The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System, in: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '23), Association for Computing Machinery, New York, NY, USA, Article 7, 1–11, https://dl.acm.org/doi/10.1145/3581784.3627044, 2023.
Temperton, C., Hortal, M., and Simmons, A. J.: A two-time-level semi-Lagrangian global spectral model, Q. J. Roy. Meteor. Soc., 127, 111–127, https://doi.org/10.1002/qj.49712757107, 2001.
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parametrization in large-scale models, Mon. Weather Rev., 117, 1779–1800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989.
Tiedtke, M.: Representation of clouds in large-scale models, Mon. Weather Rev., 121, 3040–3061, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2, 1993.
Tomita, H., Miura, H., Iga, S.-I., Nasuno, T., and Satoh, M.: A global cloud-resolving simulation: Preliminary results from an aqua planet experiment, Geophys. Res. Lett., 32, L08805, https://doi.org/10.1029/2005gl022459, 2005.
Treguier, A. M., de Boyer Montégut, C., Bozec, A., Chassignet, E. P., Fox-Kemper, B., McC. Hogg, A., Iovino, D., Kiss, A. E., Le Sommer, J., Li, Y., Lin, P., Lique, C., Liu, H., Serazin, G., Sidorenko, D., Wang, Q., Xu, X., and Yeager, S.: The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies, Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, 2023.
Trigo, I. F., Monteiro, I. T., Olesen, F., and Kabsch, E.: An assessment of remotely sensed land surface temperature, J. Geophys. Res., 113, 1–12, https://doi.org/10.1029/2008JD010035, 2008.
Untch, A. and Hortal, M.: A finite-element scheme for the vertical discretization of the semi-Lagrangian version of the ECMWF forecast model, Q. J. Roy. Meteor. Soc., 130, 1505–1530, https://doi.org/10.1256/qj.03.173, 2004.
van Westen, R. M. and Dijkstra, H. A.: Ocean eddies strongly affect global mean sea-level projections, Sci. Adv., 7, eabf1674, https://doi.org/10.1126/sciadv.abf1674, 2021.
Vivoda, J., Smolíková, P., and Simarro, J.: Finite Elements Used in the Vertical Discretization of the Fully Compressible Core of the ALADIN System, Mon. Weather Rev., 146, 3293–3310, https://doi.org/10.1175/MWR-D-18-0043.1, 2018.
von Albedyll, L., Hendricks, S., Hutter, N., Murashkin, D., Kaleschke, L., Willmes, S., Thielke, L., Tian-Kunze, X., Spreen, G., and Haas, C.: Lead fractions from SAR-derived sea ice divergence during MOSAiC, The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, 2024.
Wedi, N. P.: Increasing horizontal resolution in numerical weather prediction and climate simulations: Illusion or panacea?, Philos. T. Roy. Soc. A, 372, 20130289, https://doi.org/10.1098/rsta.2013.0289, 2014.
Wedi, N. P., Bauer, P., Denoninck, W., Diamantakis, M., Hamrud, M., Kuehnlein, C., Malardel, S., Mogensen, K., Mozdzynski, G., and Smolarkiewicz, P. K.: The modelling infrastructure of the Integrated Forecasting System: Recent advances and future challenges, ECMWF Technical Memoranda, 760, https://doi.org/10.21957/thtpwp67e, 2015.
Wedi, N. P., Polichtchouk, I., Dueben, P., Anantharaj, V.G., Bauer, P., Boussetta, S., Browne, P., Deconinck, W., Gaudin, W., Hadade, I., Hatfield, S., Iffrig, O., Lopez, P., Maciel, P., Mueller, A., Saarinen, S., Sandu, I., Quintino, T., and Vitart, F.: A baseline for global weather and climate simulations at 1 km resolution, J. Adv. Model. Earth Sy., 12, e2020MS002192, https://doi.org/10.1029/2020MS002192, 2020.
Wengel, C., Lee, S.-S., Stuecker, M. F., Timmermann, A., Chu, J.-E., and Schloesser, F.: Future high-resolution El Niño/Southern Oscillation dynamics, Nat. Clim. Change, 11, 758–765, https://doi.org/10.1038/s41558-021-01132-4, 2021.
Wheeler, M. and Kiladis, G. N: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain, J. Atmos. Sci., 56, 374–399, https://doi.org/10.1175/1520-0469(1999)056<0374:CCEWAO>2.0.CO;2, 1999.
Wieners, K.-H., Ziemen, F. A., Koldunov, N., Pedruzo-Bagazgoitia, X., Rackow, T., Redler, R., Sidorenko, D., and Kölling, T.: nextGEMS: output of the model development cycle 2 simulations for ICON and IFS, World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.26050/WDCC/nextGEMS_cyc2, 2023.
Yano, J.-I. and Wedi, N. P.: Sensitivities of the Madden–Julian oscillation forecasts to configurations of physics in the ECMWF global model, Atmos. Chem. Phys., 21, 4759–4778, https://doi.org/10.5194/acp-21-4759-2021, 2021.
Zampieri, L., Goessling, H. F., and Jung, T.: Bright prospects for Arctic sea ice prediction on subseasonal time scales, Geophys. Res. Lett., 45, 9731–9738, https://doi.org/10.1029/2018GL079394, 2018.
Zampieri, L., Goessling, H. F., and Jung, T.: Predictability of Antarctic sea ice edge on subseasonal time scales, Geophys. Res. Lett., 46, 9719–9727, https://doi.org/10.1029/2019GL084096, 2019.
Zhang, C.: Madden–Julian oscillation: Bridging weather and climate, B. Am. Meteorol. Soc., 94, 1849–1870, https://doi.org/10.1175/BAMS-D-12-00026.1, 2013.
Zsoter, E., Arduini, G., Prudhomme, C., Stephens, E., and Cloke, H.: Hydrological Impact of the New ECMWF Multi-Layer Snow Scheme, Atmosphere, 13, 727, https://doi.org/10.3390/atmos13050727, 2022.
Short summary
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.
Detailed global climate model simulations have been created based on a numerical weather...
