Articles | Volume 15, issue 16
https://doi.org/10.5194/gmd-15-6399-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6399-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
29 Aug 2022
Model evaluation paper |
| 29 Aug 2022
| 29 Aug 2022
AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Department of Mathematics & Logistics, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Tido Semmler
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Lorenzo Zampieri
National Center for Atmospheric Research, 1850 Table Mesa Dr, Boulder, CO 80305, United States of America
Patrick Scholz
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Miguel Andrés-Martínez
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Nikolay Koldunov
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Thomas Rackow
European Centre for Medium-Range Weather Forecasts, Robert-Schuman-Platz 3, 53175 Bonn, Germany
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Joakim Kjellsson
GEOMAR Helmholtz Centre for Ocean Research Kiel, Wischhofstraße 1–3, 24148 Kiel, Germany
Helge Goessling
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Marylou Athanase
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Qiang Wang
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Jan Hegewald
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Dmitry V. Sein
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Shirshov Institute of Oceanology, RAS, Moscow, Russia
Longjiang Mu
Pilot National Laboratory for Marine Science and Technology, Qingdao, China
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Uwe Fladrich
Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 60176 Norrköping, Sweden
Dirk Barbi
University IT and Data Center, Rhenish Friedrich Wilhelm University of Bonn, Regina-Pacis-Weg 3, 53113 Bonn, Germany
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Paul Gierz
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Sergey Danilov
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Department of Mathematics & Logistics, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
Stephan Juricke
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Department of Mathematics & Logistics, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
Gerrit Lohmann
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Department of Physics, University of Bremen, Bibliothekstraße 1, 28359 Bremen, Germany
Thomas Jung
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Department of Physics, University of Bremen, Bibliothekstraße 1, 28359 Bremen, Germany
Related authors
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
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.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2491, https://doi.org/10.5194/egusphere-2024-2491, 2024
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, 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, 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.
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.
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.
Xiaoyu Wang, Longjiang Mu, and Xianyao Chen
Ocean Sci., 21, 577–586, https://doi.org/10.5194/os-21-577-2025, https://doi.org/10.5194/os-21-577-2025, 2025
Short summary
Short summary
The East Siberian Sea has nearly 80 % of the subsea permafrost worldwide. The cold layer with a temperature around −1.5 ºC above the seafloor prevents heat transporting from above to melt permafrost and release methane from sediments. However, we observed a warming trend at the seafloor caused by wave-induced vertical mixing in the shelf. The intensified mixing can transport enormous heat downward, leading to warming of more than 3 °C at the bottom, putting the subsea permafrost at high risk.
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.
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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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.
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.
Wee Wei Khoo, Juliane Müller, Oliver Esper, Wenshen Xiao, Christian Stepanek, Paul Gierz, Gerrit Lohmann, Walter Geibert, Jens Hefter, and Gesine Mollenhauer
Clim. Past, 21, 299–326, https://doi.org/10.5194/cp-21-299-2025, https://doi.org/10.5194/cp-21-299-2025, 2025
Short summary
Short summary
Using a multiproxy approach, we analyzed biomarkers and diatom assemblages from a marine sediment core from the Powell Basin, Weddell Sea. The results reveal the first continuous coastal Antarctic sea ice record since the Last Penultimate Glacial. Our findings contribute valuable insights into past glacial–interglacial sea ice responses to a changing climate and enhance our understanding of ocean–sea ice–ice shelf interactions and dynamics.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
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.
Lutz Schirrmeister, Margret C. Fuchs, Thomas Opel, Andrei Andreev, Frank Kienast, Andrea Schneider, Larisa Nazarova, Larisa Frolova, Svetlana Kuzmina, Tatiana Kuznetsova, Vladimir Tumskoy, Heidrun Matthes, Gerit Lohmann, Guido Grosse, Viktor Kunitsky, Hanno Meyer, Heike H. Zimmermann, Ulrike Herzschuh, Thomas Boehmer, Stuart Umbo, Sevi Modestou, Sebastian F. M. Breitenbach, Anfisa Pismeniuk, Georg Schwamborn, Stephanie Kusch, and Sebastian Wetterich
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-74, https://doi.org/10.5194/cp-2024-74, 2024
Revised manuscript accepted for CP
Short summary
Short summary
The strong ecosystem response to the Last Interglacial warming, reflected in the high diversity of proxies, shows the sensitivity of permafrost regions to rising temperatures. In particular, the development of thermokarst landscapes created a mosaic of terrestrial, wetland, and aquatic habitats, fostering an increase in biodiversity. This biodiversity is evident in the rich variety of terrestrial insects, vegetation, and aquatic invertebrates preserved in these deposits.
Shunya Koseki, Rubén Vázquez, William Cabos, Claudia Gutiérrez, Dmitry V. Sein, and Marie-Lou Bachèlery
Earth Syst. Dynam., 15, 1401–1416, https://doi.org/10.5194/esd-15-1401-2024, https://doi.org/10.5194/esd-15-1401-2024, 2024
Short summary
Short summary
Using a high-resolution regionally coupled model, we suggest that Dakar Niño variability will be reinforced under the Representative Concentration Pathway (RCP) 8.5 scenario. This may be induced by intensified surface heat flux anomalies and, secondarily, by anomalies in horizontal and vertical advection. Increased sea surface temperature (SST) variability can be associated with stronger wind variability, attributed to amplified surface temperature anomalies between ocean and land.
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.
Hu Yang, Xiaoxu Shi, Xulong Wang, Qingsong Liu, Yi Zhong, Xiaodong Liu, Youbin Sun, Yanjun Cai, Fei Liu, Gerrit Lohmann, Martin Werner, Zhimin Jian, Tainã M. L. Pinho, Hai Cheng, Lijuan Lu, Jiping Liu, Chao-Yuan Yang, Qinghua Yang, Yongyun Hu, Xing Cheng, Jingyu Zhang, and Dake Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2778, https://doi.org/10.5194/egusphere-2024-2778, 2024
Short summary
Short summary
The precession driven low-latitude hydrological cycle is not paced by hemispheric summer insolation, but shifting perihelion.
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.
Yugeng Chen, Pengyang Song, Xianyao Chen, and Gerrit Lohmann
Clim. Past, 20, 2001–2015, https://doi.org/10.5194/cp-20-2001-2024, https://doi.org/10.5194/cp-20-2001-2024, 2024
Short summary
Short summary
Our study examines the Atlantic Meridional Overturning Circulation (AMOC) during the Last Glacial Maximum (LGM), a period with higher tidal dissipation. Despite increased tidal mixing, our model simulations show that the AMOC remained relatively shallow, consistent with paleoproxy data and resolving previous inconsistencies between proxy data and model simulations. This research highlights the importance of strong ocean stratification during the LGM and its interaction with tidal mixing.
Shreya Trivedi, Imke Sievers, Marylou Athanase, Antonio Sánchez Benítez, and Tido Semmler
EGUsphere, https://doi.org/10.5194/egusphere-2024-2214, https://doi.org/10.5194/egusphere-2024-2214, 2024
Short summary
Short summary
Our study introduces a new method to compare CMIP6 models' sea ice and snow simulations with in-situ (MOSAiC) measurements. We assessed models for their accuracy in replicating Arctic sea ice and snow thicknesses, using two sea-ice and atmosphere-based methods to select "proxy years." We show that the models often overestimate snow thickness and mistime sea ice cycles. Despite limitations, this approach provides a valuable tool for evaluating climate models in localized time and space.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2491, https://doi.org/10.5194/egusphere-2024-2491, 2024
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, 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, 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.
Kacper Nowak, Sergey Danilov, Vasco Müller, and Caili Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1119, https://doi.org/10.5194/egusphere-2024-1119, 2024
Short summary
Short summary
A new method called coarse-graining scale analysis is gaining traction as an alternative to Fourier analysis. However, it requires data to be on a regular grid. To address this, we present a high-performance Python package of coarse-graining technique using discrete Laplacians. This method can handle any mesh type and is ideal for processing output directly from unstructured-mesh models. Computation is split into preparation and solving phases, with GPU acceleration ensuring fast processing.
Yingxue Liu, Joakim Kjellsson, Abhishek Savita, and Wonsun Park
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-66, https://doi.org/10.5194/gmd-2024-66, 2024
Revised manuscript under review for GMD
Short summary
Short summary
The impact of horizontal resolution and model time step on extreme precipitation over Europe is examined in OpenIFS. We find that the biases are reduced with increasing horizontal resolution, but not with reducing time step. The large-scale precipitation is more sensitive to the horizontal resolution, however, the convective precipitation is more sensitive to the model time step. Increasing horizontal resolution is more important for extreme precipitation simulation that reducing time step.
Holly C. Ayres, David Ferreira, Wonsun Park, Joakim Kjellsson, and Malin Ödalen
Weather Clim. Dynam., 5, 805–820, https://doi.org/10.5194/wcd-5-805-2024, https://doi.org/10.5194/wcd-5-805-2024, 2024
Short summary
Short summary
The Weddell Sea Polynya (WSP) is a large, closed-off opening in winter sea ice that has opened only a couple of times since we started using satellites to observe sea ice. The aim of this study is to determine the impact of the WSP on the atmosphere. We use three numerical models of the atmosphere, and for each, we use two levels of detail. We find that the WSP causes warming but only locally, alongside an increase in precipitation, and shows some dependence on the large-scale background winds.
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.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
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.
Viorica Nagavciuc, Simon L. L. Michel, Daniel F. Balting, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David N. Steger, Gerrit Lohmann, and Monica Ionita
Clim. Past, 20, 573–595, https://doi.org/10.5194/cp-20-573-2024, https://doi.org/10.5194/cp-20-573-2024, 2024
Short summary
Short summary
The main aim of this paper is to present the summer vapor pressure deficit (VPD) reconstruction dataset for the last 400 years over Europe based on δ18O records by using a random forest approach. We provide both a spatial and a temporal long-term perspective on the past summer VPD and new insights into the relationship between summer VPD and large-scale atmospheric circulation. This is the first gridded reconstruction of the European summer VPD over the past 400 years.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
Short summary
Short summary
The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
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.
Uta Krebs-Kanzow, Christian B. Rodehacke, and Gerrit Lohmann
The Cryosphere, 17, 5131–5136, https://doi.org/10.5194/tc-17-5131-2023, https://doi.org/10.5194/tc-17-5131-2023, 2023
Short summary
Short summary
We compare components of the surface energy balance from two datasets, ERA5 and ERA-Interim, which can be used to estimate the surface mass balance (SMB) on the Greenland Ice Sheet (GrIS). ERA5 differs significantly from ERA-Interim, especially in the melt regions with lower temperatures and stronger shortwave radiation. Consequently, methods that previously estimated the GrIS SMB from ERA-Interim need to be carefully recalibrated before conversion to ERA5 forcing.
Xiaoxu Shi, Martin Werner, Hu Yang, Roberta D'Agostino, Jiping Liu, Chaoyuan Yang, and Gerrit Lohmann
Clim. Past, 19, 2157–2175, https://doi.org/10.5194/cp-19-2157-2023, https://doi.org/10.5194/cp-19-2157-2023, 2023
Short summary
Short summary
The Last Glacial Maximum (LGM) marks the most recent extremely cold and dry time period of our planet. Using AWI-ESM, we quantify the relative importance of Earth's orbit, greenhouse gases (GHG) and ice sheets (IS) in determining the LGM climate. Our results suggest that both GHG and IS play important roles in shaping the LGM temperature. Continental ice sheets exert a major control on precipitation, atmospheric dynamics, and the intensity of El Niño–Southern Oscillation.
Xin Ren, Daniel J. Lunt, Erica Hendy, Anna von der Heydt, Ayako Abe-Ouchi, Bette Otto-Bliesner, Charles J. R. Williams, Christian Stepanek, Chuncheng Guo, Deepak Chandan, Gerrit Lohmann, Julia C. Tindall, Linda E. Sohl, Mark A. Chandler, Masa Kageyama, Michiel L. J. Baatsen, Ning Tan, Qiong Zhang, Ran Feng, Stephen Hunter, Wing-Le Chan, W. Richard Peltier, Xiangyu Li, Youichi Kamae, Zhongshi Zhang, and Alan M. Haywood
Clim. Past, 19, 2053–2077, https://doi.org/10.5194/cp-19-2053-2023, https://doi.org/10.5194/cp-19-2053-2023, 2023
Short summary
Short summary
We investigate the Maritime Continent climate in the mid-Piacenzian warm period and find it is warmer and wetter and the sea surface salinity is lower compared with preindustrial period. Besides, the fresh and warm water transfer through the Maritime Continent was stronger. In order to avoid undue influence from closely related models in the multimodel results, we introduce a new metric, the multi-cluster mean, which could reveal spatial signals that are not captured by the multimodel mean.
Ryan Love, Lev Tarasov, Heather Andres, Alan Condron, Xu Zhang, and Gerrit Lohmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2225, https://doi.org/10.5194/egusphere-2023-2225, 2023
Preprint archived
Short summary
Short summary
Freshwater injection into bands across the North Atlantic are a mainstay of climate modelling when investigating topics such as climate change or the role of glacial runoff in the glacial climate system. However, this approach is unrealistic and results in a systematic bias in the climate response to a given flux of freshwater. We evaluate the magnitude of this bias by comparison to two other approaches for introducing freshwater into a coupled climate model setup for glacial conditions.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
Short summary
Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
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.
Nicolas Stoll, Matthias Wietz, Stephan Juricke, Franziska Pausch, Corina Peter, Miriam Seifert, Jana C. Massing, Moritz Zeising, Rebecca A. McPherson, Melissa Käß, and Björn Suckow
Polarforschung, 91, 31–43, https://doi.org/10.5194/polf-91-31-2023, https://doi.org/10.5194/polf-91-31-2023, 2023
Short summary
Short summary
Global crises, such as climate change and the COVID-19 pandemic, show the importance of communicating science to the public. We introduce the YouTube channel "Wissenschaft fürs Wohnzimmer", which livestreams presentations on climate-related topics weekly and is accessible to all. The project encourages interaction between scientists and the public and has been running successfully for over 2 years. We present the concept, what we have learnt, and the challenges after 100 streamed episodes.
Di Cai, Gerrit Lohmann, Xianyao Chen, and Monica Ionita
EGUsphere, https://doi.org/10.5194/egusphere-2023-1646, https://doi.org/10.5194/egusphere-2023-1646, 2023
Preprint archived
Short summary
Short summary
Our study reveals how a decline in autumn sea ice in the Barents-Kara Seas leads to severe winters in Europe. Using observational data, we illustrate that Arctic sea ice loss isn't just a local issue – it impacts harsh winter conditions globally. Current climate models struggle to reflect these effects accurately, indicating a need for more research. Gaining a more nuanced understanding of this relationship will enhance our climate predictions and preparation for future extremes.
Johannes Riebold, Andy Richling, Uwe Ulbrich, Henning Rust, Tido Semmler, and Dörthe Handorf
Weather Clim. Dynam., 4, 663–682, https://doi.org/10.5194/wcd-4-663-2023, https://doi.org/10.5194/wcd-4-663-2023, 2023
Short summary
Short summary
Arctic sea ice loss might impact the atmospheric circulation outside the Arctic and therefore extremes over mid-latitudes. Here, we analyze model experiments to initially assess the influence of sea ice loss on occurrence frequencies of large-scale circulation patterns. Some of these detected circulation changes can be linked to changes in occurrences of European temperature extremes. Compared to future global temperature increases, the sea-ice-related impacts are however of secondary relevance.
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.
Iván M. Parras-Berrocal, Rubén Vázquez, William Cabos, Dimitry V. Sein, Oscar Álvarez, Miguel Bruno, and Alfredo Izquierdo
Ocean Sci., 19, 941–952, https://doi.org/10.5194/os-19-941-2023, https://doi.org/10.5194/os-19-941-2023, 2023
Short summary
Short summary
Global warming may strongly affect dense water formation in the eastern Mediterranean, potentially impacting basin circulation and water properties. We find that at the end of the century dense water formation is reduced by 75 % for the Adriatic, 84 % for the Aegean, and 83 % for the Levantine Sea. This reduction is caused by changes in the temperature and salinity of surface and intermediate waters, which strengthen the vertical stratification, hampering deep convection.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
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.
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.
Julia E. Weiffenbach, Michiel L. J. Baatsen, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Zixuan Han, Alan M. Haywood, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Julia C. Tindall, Charles J. R. Williams, Qiong Zhang, and Zhongshi Zhang
Clim. Past, 19, 61–85, https://doi.org/10.5194/cp-19-61-2023, https://doi.org/10.5194/cp-19-61-2023, 2023
Short summary
Short summary
We study the behavior of the Atlantic Meridional Overturning Circulation (AMOC) in the mid-Pliocene. The mid-Pliocene was about 3 million years ago and had a similar CO2 concentration to today. We show that the stronger AMOC during this period relates to changes in geography and that this has a significant influence on ocean temperatures and heat transported northwards by the Atlantic Ocean. Understanding the behavior of the mid-Pliocene AMOC can help us to learn more about our future climate.
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.
Kristian Strommen, Stephan Juricke, and Fenwick Cooper
Weather Clim. Dynam., 3, 951–975, https://doi.org/10.5194/wcd-3-951-2022, https://doi.org/10.5194/wcd-3-951-2022, 2022
Short summary
Short summary
Observational data suggest that the extent of Arctic sea ice influences mid-latitude winter weather. However, climate models generally fail to reproduce this link, making it unclear if models are missing something or if the observed link is just a coincidence. We show that if one explicitly represents the effect of unresolved sea ice variability in a climate model, then it is able to reproduce this link. This implies that the link may be real but that many models simply fail to simulate it.
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.
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.
Ryan A. Green, Laurie Menviel, Katrin J. Meissner, Xavier Crosta, Deepak Chandan, Gerrit Lohmann, W. Richard Peltier, Xiaoxu Shi, and Jiang Zhu
Clim. Past, 18, 845–862, https://doi.org/10.5194/cp-18-845-2022, https://doi.org/10.5194/cp-18-845-2022, 2022
Short summary
Short summary
Climate models are used to predict future climate changes and as such, it is important to assess their performance in simulating past climate changes. We analyze seasonal sea-ice cover over the Southern Ocean simulated from numerical PMIP3, PMIP4 and LOVECLIM simulations during the Last Glacial Maximum (LGM). Comparing these simulations to proxy data, we provide improved estimates of LGM seasonal sea-ice cover. Our estimate of summer sea-ice extent is 20 %–30 % larger than previous estimates.
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.
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022, https://doi.org/10.5194/esd-13-809-2022, 2022
Short summary
Short summary
The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. When the biogeochemical coupling is included, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.
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.
Matthias Gröger, Christian Dieterich, Cyril Dutheil, H. E. Markus Meier, and Dmitry V. Sein
Earth Syst. Dynam., 13, 613–631, https://doi.org/10.5194/esd-13-613-2022, https://doi.org/10.5194/esd-13-613-2022, 2022
Short summary
Short summary
Atmospheric rivers transport high amounts of water from subtropical regions to Europe. They are an important driver of heavy precipitation and flooding. Their response to a warmer future climate in Europe has so far been assessed only by global climate models. In this study, we apply for the first time a high-resolution regional climate model that allow to better resolve and understand the fate of atmospheric rivers over Europe.
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.
Sebastian Hinck, Evan J. Gowan, Xu Zhang, and Gerrit Lohmann
The Cryosphere, 16, 941–965, https://doi.org/10.5194/tc-16-941-2022, https://doi.org/10.5194/tc-16-941-2022, 2022
Short summary
Short summary
Proglacial lakes were pervasive along the retreating continental ice margins after the Last Glacial Maximum. Similarly to the marine ice boundary, interactions at the ice-lake interface impact ice sheet dynamics and mass balance. Previous numerical ice sheet modeling studies did not include a dynamical lake boundary. We describe the implementation of an adaptive lake boundary condition in PISM and apply the model to the glacial retreat of the Laurentide Ice Sheet.
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.
Justus Contzen, Thorsten Dickhaus, and Gerrit Lohmann
Geosci. Model Dev., 15, 1803–1820, https://doi.org/10.5194/gmd-15-1803-2022, https://doi.org/10.5194/gmd-15-1803-2022, 2022
Short summary
Short summary
Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Daniel Balting, Simon Michel, Viorica Nagavciuc, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David Steger, Gerrit Lohmann, and Monica Ionita
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-47, https://doi.org/10.5194/essd-2022-47, 2022
Preprint withdrawn
Short summary
Short summary
Vapor pressure deficit is a key component of vegetation dynamics, soil science, meteorology, and soil science. In this study, we reconstruct the variability of the vapor pressure deficit in the past and examine the changes in future scenarios using climate models. In this way, past, present and future changes of the vapor pressure deficit can be detected locally, regionally, and continentally with higher statistical significance.
Alba de la Vara, Iván M. Parras-Berrocal, Alfredo Izquierdo, Dmitry V. Sein, and William Cabos
Earth Syst. Dynam., 13, 303–319, https://doi.org/10.5194/esd-13-303-2022, https://doi.org/10.5194/esd-13-303-2022, 2022
Short summary
Short summary
We study with the regionally coupled climate model ROM the impact of climate change on the Tyrrhenian Sea circulation, as well as the possible mechanisms and consequences in the NW Mediterranean Sea. Our results show a shift towards the summer circulation pattern by the end of the century. Also, water flowing via the Corsica Channel is more stratified and smaller in volume. Both factors may contribute to the interruption of deep water formation in the Gulf of Lions in the future.
Stephan Krätschmer, Michèlle van der Does, Frank Lamy, Gerrit Lohmann, Christoph Völker, and Martin Werner
Clim. Past, 18, 67–87, https://doi.org/10.5194/cp-18-67-2022, https://doi.org/10.5194/cp-18-67-2022, 2022
Short summary
Short summary
We use an atmospheric model coupled to an aerosol model to investigate the global mineral dust cycle with a focus on the Southern Hemisphere for warmer and colder climate states and compare our results to observational data. Our findings suggest that Australia is the predominant source of dust deposited over Antarctica during the last glacial maximum. In addition, we find that the southward transport of dust from all sources to Antarctica happens at lower altitudes in colder climates.
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.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
Short summary
Short summary
Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Kim H. Stadelmaier, Patrick Ludwig, Pascal Bertran, Pierre Antoine, Xiaoxu Shi, Gerrit Lohmann, and Joaquim G. Pinto
Clim. Past, 17, 2559–2576, https://doi.org/10.5194/cp-17-2559-2021, https://doi.org/10.5194/cp-17-2559-2021, 2021
Short summary
Short summary
We use regional climate simulations for the Last Glacial Maximum to reconstruct permafrost and to identify areas of thermal contraction cracking of the ground in western Europe. We find ground cracking, a precondition for the development of permafrost proxies, south of the probable permafrost border, implying that permafrost was not the limiting factor for proxy development. A good agreement with permafrost and climate proxy data is achieved when easterly winds are modelled more frequently.
Zixuan Han, Qiong Zhang, Qiang Li, Ran Feng, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Bette L. Otto-Bliesner, Esther C. Brady, Nan Rosenbloom, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Charles J. R. Williams, Daniel J. Lunt, Jianbo Cheng, Qin Wen, and Natalie J. Burls
Clim. Past, 17, 2537–2558, https://doi.org/10.5194/cp-17-2537-2021, https://doi.org/10.5194/cp-17-2537-2021, 2021
Short summary
Short summary
Understanding the potential processes responsible for large-scale hydrological cycle changes in a warmer climate is of great importance. Our study implies that an imbalance in interhemispheric atmospheric energy during the mid-Pliocene could have led to changes in the dynamic effect, offsetting the thermodynamic effect and, hence, altering mid-Pliocene hydroclimate cycling. Moreover, a robust westward shift in the Pacific Walker circulation can moisten the northern Indian Ocean.
Arthur M. Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Henk A. Dijkstra, Julia C. Tindall, Ayako Abe-Ouchi, Alice R. Booth, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Alan M. Haywood, Stephen J. Hunter, Youichi Kamae, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gabriel M. Pontes, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Qiong Zhang, Zhongshi Zhang, Ilana Wainer, and Charles J. R. Williams
Clim. Past, 17, 2427–2450, https://doi.org/10.5194/cp-17-2427-2021, https://doi.org/10.5194/cp-17-2427-2021, 2021
Short summary
Short summary
In this work, we have studied the behaviour of El Niño events in the mid-Pliocene, a period of around 3 million years ago, using a collection of 17 climate models. It is an interesting period to study, as it saw similar atmospheric carbon dioxide levels to the present day. We find that the El Niño events were less strong in the mid-Pliocene simulations, when compared to pre-industrial climate. Our results could help to interpret El Niño behaviour in future climate projections.
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.
Nele Lamping, Juliane Müller, Jens Hefter, Gesine Mollenhauer, Christian Haas, Xiaoxu Shi, Maria-Elena Vorrath, Gerrit Lohmann, and Claus-Dieter Hillenbrand
Clim. Past, 17, 2305–2326, https://doi.org/10.5194/cp-17-2305-2021, https://doi.org/10.5194/cp-17-2305-2021, 2021
Short summary
Short summary
We analysed biomarker concentrations on surface sediment samples from the Antarctic continental margin. Highly branched isoprenoids and GDGTs are used for reconstructing recent sea-ice distribution patterns and ocean temperatures respectively. We compared our biomarker-based results with data obtained from satellite observations and estimated from a numerical model and find reasonable agreements. Further, we address caveats and provide recommendations for future investigations.
Saeid Bagheri Dastgerdi, Melanie Behrens, Jean-Louis Bonne, Maria Hörhold, Gerrit Lohmann, Elisabeth Schlosser, and Martin Werner
The Cryosphere, 15, 4745–4767, https://doi.org/10.5194/tc-15-4745-2021, https://doi.org/10.5194/tc-15-4745-2021, 2021
Short summary
Short summary
In this study, for the first time, water vapour isotope measurements in Antarctica for all seasons of a year are performed. Local temperature is identified as the main driver of δ18O and δD variability. A similar slope of the temperature–δ18O relationship in vapour and surface snow points to the water vapour isotope content as a potential key driver. This dataset can be used as a new dataset to evaluate the capability of isotope-enhanced climate models.
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.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 5637–5668, https://doi.org/10.5194/gmd-14-5637-2021, https://doi.org/10.5194/gmd-14-5637-2021, 2021
Short summary
Short summary
This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in CMIP6. We give an overview of the model and describe in detail how it differs from its predecessor and the other EC-Earth3 configurations. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Ellen Berntell, Qiong Zhang, Qiang Li, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, William Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, Charles J. R. Williams, Daniel J. Lunt, Ran Feng, Bette L. Otto-Bliesner, and Esther C. Brady
Clim. Past, 17, 1777–1794, https://doi.org/10.5194/cp-17-1777-2021, https://doi.org/10.5194/cp-17-1777-2021, 2021
Short summary
Short summary
The mid-Pliocene Warm Period (~ 3.2 Ma) is often considered an analogue for near-future climate projections, and model results from the PlioMIP2 ensemble show an increase of rainfall over West Africa and the Sahara region compared to pre-industrial conditions. Though previous studies of future projections show a west–east drying–wetting contrast over the Sahel, these results indicate a uniform rainfall increase over the Sahel in warm climates characterized by increased greenhouse gas forcing.
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.
Xiaoxu Shi, Dirk Notz, Jiping Liu, Hu Yang, and Gerrit Lohmann
Geosci. Model Dev., 14, 4891–4908, https://doi.org/10.5194/gmd-14-4891-2021, https://doi.org/10.5194/gmd-14-4891-2021, 2021
Short summary
Short summary
The ice–ocean heat flux is one of the key elements controlling sea ice changes. It motivates our study, which aims to examine the responses of modeled climate to three ice–ocean heat flux parameterizations, including two old approaches that assume one-way heat transport and a new one describing a double-diffusive ice–ocean heat exchange. The results show pronounced differences in the modeled sea ice, ocean, and atmosphere states for the latter as compared to the former two parameterizations.
Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev., 14, 4781–4796, https://doi.org/10.5194/gmd-14-4781-2021, https://doi.org/10.5194/gmd-14-4781-2021, 2021
Short summary
Short summary
This paper describes the large ensemble done by SMHI with the EC-Earth3 climate model. The ensemble comprises 50 realizations for each of the historical experiments after 1970 and four different future projections for CMIP6. We describe the creation of the initial states for the ensemble and the reduced set of output variables. A first look at the results illustrates the changes in the climate during this century and puts them in relation to the uncertainty from the model's internal variability.
Dirk Barbi, Nadine Wieters, Paul Gierz, Miguel Andrés-Martínez, Deniz Ural, Fatemeh Chegini, Sara Khosravi, and Luisa Cristini
Geosci. Model Dev., 14, 4051–4067, https://doi.org/10.5194/gmd-14-4051-2021, https://doi.org/10.5194/gmd-14-4051-2021, 2021
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
Short summary
Short summary
The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
Uta Krebs-Kanzow, Paul Gierz, Christian B. Rodehacke, Shan Xu, Hu Yang, and Gerrit Lohmann
The Cryosphere, 15, 2295–2313, https://doi.org/10.5194/tc-15-2295-2021, https://doi.org/10.5194/tc-15-2295-2021, 2021
Short summary
Short summary
The surface mass balance scheme dEBM (diurnal Energy Balance Model) provides a novel, computationally inexpensive interface between the atmosphere and land ice for Earth system modeling. The dEBM is particularly suitable for Earth system modeling on multi-millennial timescales as it accounts for changes in the Earth's orbit and atmospheric greenhouse gas concentration.
Daniel F. Balting, Monica Ionita, Martin Wegmann, Gerhard Helle, Gerhard H. Schleser, Norel Rimbu, Mandy B. Freund, Ingo Heinrich, Diana Caldarescu, and Gerrit Lohmann
Clim. Past, 17, 1005–1023, https://doi.org/10.5194/cp-17-1005-2021, https://doi.org/10.5194/cp-17-1005-2021, 2021
Short summary
Short summary
To extend climate information back in time, we investigate the climate sensitivity of a δ18O network from tree rings, consisting of 26 European sites and covering the last 400 years. Our results suggest that the δ18O variability is associated with large-scale anomaly patterns that resemble those observed for the El Niño–Southern Oscillation. We conclude that the investigation of large-scale climate signals far beyond instrumental records can be done with a δ18O network derived from tree rings.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
Short summary
Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Odd Helge Otterå, Kerim H. Nisancioglu, Ning Tan, Camille Contoux, Gilles Ramstein, Ran Feng, Bette L. Otto-Bliesner, Esther Brady, Deepak Chandan, W. Richard Peltier, Michiel L. J. Baatsen, Anna S. von der Heydt, Julia E. Weiffenbach, Christian Stepanek, Gerrit Lohmann, Qiong Zhang, Qiang Li, Mark A. Chandler, Linda E. Sohl, Alan M. Haywood, Stephen J. Hunter, Julia C. Tindall, Charles Williams, Daniel J. Lunt, Wing-Le Chan, and Ayako Abe-Ouchi
Clim. Past, 17, 529–543, https://doi.org/10.5194/cp-17-529-2021, https://doi.org/10.5194/cp-17-529-2021, 2021
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is an important topic in the Pliocene Model Intercomparison Project. Previous studies have suggested a much stronger AMOC during the Pliocene than today. However, our current multi-model intercomparison shows large model spreads and model–data discrepancies, which can not support the previous hypothesis. Our study shows good consistency with future projections of the AMOC.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
Short summary
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227, https://doi.org/10.5194/cp-17-203-2021, https://doi.org/10.5194/cp-17-203-2021, 2021
Short summary
Short summary
This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
Xuewei Li, Qinghua Yang, Lejiang Yu, Paul R. Holland, Chao Min, Longjiang Mu, and Dake Chen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-359, https://doi.org/10.5194/tc-2020-359, 2021
Preprint withdrawn
Short summary
Short summary
The Arctic sea ice thickness record minimum is confirmed occurring in autumn 2011. The dynamic and thermodynamic processes leading to the minimum thickness is analyzed based on a daily sea ice thickness reanalysis data covering the melting season. The results demonstrate that the dynamic transport of multiyear ice and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice thickness in 2011.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
Short summary
Short summary
The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
Short summary
Short summary
The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
Short summary
Short summary
An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
Short summary
Short summary
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Gerrit Lohmann
Earth Syst. Dynam., 11, 1195–1208, https://doi.org/10.5194/esd-11-1195-2020, https://doi.org/10.5194/esd-11-1195-2020, 2020
Short summary
Short summary
With the development of computer capacities, simpler models like energy balance models have not disappeared, and a stronger emphasis has been given to the concept of a hierarchy of models. The global temperature is calculated by the radiation budget through the incoming energy from the Sun and the outgoing energy from the Earth. The argument that the temperature can be calculated by a simple radiation budget is revisited, and it is found that the effective heat capacity matters.
Christian B. Rodehacke, Madlene Pfeiffer, Tido Semmler, Özgür Gurses, and Thomas Kleiner
Earth Syst. Dynam., 11, 1153–1194, https://doi.org/10.5194/esd-11-1153-2020, https://doi.org/10.5194/esd-11-1153-2020, 2020
Short summary
Short summary
In the warmer future, Antarctica's ice sheet will lose more ice due to enhanced iceberg calving and a warming ocean that melts more floating ice from below. However, the hydrological cycle is also stronger in a warmer world. Hence, more snowfall will precipitate on Antarctica and may balance the amplified ice loss. We have used future climate scenarios from various global climate models to perform numerous ice sheet simulations to show that precipitation may counteract mass loss.
Maria-Elena Vorrath, Juliane Müller, Lorena Rebolledo, Paola Cárdenas, Xiaoxu Shi, Oliver Esper, Thomas Opel, Walter Geibert, Práxedes Muñoz, Christian Haas, Gerhard Kuhn, Carina B. Lange, Gerrit Lohmann, and Gesine Mollenhauer
Clim. Past, 16, 2459–2483, https://doi.org/10.5194/cp-16-2459-2020, https://doi.org/10.5194/cp-16-2459-2020, 2020
Short summary
Short summary
We tested the applicability of the organic biomarker IPSO25 for sea ice reconstructions in the industrial era at the western Antarctic Peninsula. We successfully evaluated our data with satellite sea ice observations. The comparison with marine and ice core records revealed that sea ice interpretations must consider climatic and sea ice dynamics. Sea ice biomarker production is mainly influenced by the Southern Annular Mode, while the El Niño–Southern Oscillation seems to have a minor impact.
Wesley de Nooijer, Qiong Zhang, Qiang Li, Qiang Zhang, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Harry J. Dowsett, Christian Stepanek, Gerrit Lohmann, Bette L. Otto-Bliesner, Ran Feng, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, and Chris M. Brierley
Clim. Past, 16, 2325–2341, https://doi.org/10.5194/cp-16-2325-2020, https://doi.org/10.5194/cp-16-2325-2020, 2020
Short summary
Short summary
The simulations for the past climate can inform us about the performance of climate models in different climate scenarios. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), when the CO2 level was comparable to today. The results highlight the importance of slow feedbacks in the model simulations and imply that we must be careful when using simulations of the mPWP as an analogue for future climate change.
Christian Stepanek, Eric Samakinwa, Gregor Knorr, and Gerrit Lohmann
Clim. Past, 16, 2275–2323, https://doi.org/10.5194/cp-16-2275-2020, https://doi.org/10.5194/cp-16-2275-2020, 2020
Short summary
Short summary
Future climate is expected to be warmer than today. We study climate based on simulations of the mid-Pliocene (about 3 million years ago), which was a time of elevated temperatures, and discuss implications for the future. Our results are provided towards a comparison to both proxy evidence and output of other climate models. We simulate a mid-Pliocene climate that is both warmer and wetter than today. Some climate characteristics can be more directly transferred to the near future than others.
Florian Fuhrmann, Benedikt Diensberg, Xun Gong, Gerrit Lohmann, and Frank Sirocko
Clim. Past, 16, 2221–2238, https://doi.org/10.5194/cp-16-2221-2020, https://doi.org/10.5194/cp-16-2221-2020, 2020
Short summary
Short summary
Proxy data of sediment cores, speleothem, pollen and isotope data were used to reconstruct past aridity of eight regions of the world over the last 60 000 years. These regions show humid conditions during the early MIS3 (60 to 45 ka). Also the early Holocene (14 to 6 ka) was humid throughout the regions. In contrast, MIS2 and the LGM were arid in Northern Nemisphere records. On- and offsets of aridity/humidity differ between the regions. All this is in good agreement with recent model results.
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.
Alan M. Haywood, Julia C. Tindall, Harry J. Dowsett, Aisling M. Dolan, Kevin M. Foley, Stephen J. Hunter, Daniel J. Hill, Wing-Le Chan, Ayako Abe-Ouchi, Christian Stepanek, Gerrit Lohmann, Deepak Chandan, W. Richard Peltier, Ning Tan, Camille Contoux, Gilles Ramstein, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Qiong Zhang, Qiang Li, Youichi Kamae, Mark A. Chandler, Linda E. Sohl, Bette L. Otto-Bliesner, Ran Feng, Esther C. Brady, Anna S. von der Heydt, Michiel L. J. Baatsen, and Daniel J. Lunt
Clim. Past, 16, 2095–2123, https://doi.org/10.5194/cp-16-2095-2020, https://doi.org/10.5194/cp-16-2095-2020, 2020
Short summary
Short summary
The large-scale features of middle Pliocene climate from the 16 models of PlioMIP Phase 2 are presented. The PlioMIP2 ensemble average was ~ 3.2 °C warmer and experienced ~ 7 % more precipitation than the pre-industrial era, although there are large regional variations. PlioMIP2 broadly agrees with a new proxy dataset of Pliocene sea surface temperatures. Combining PlioMIP2 and proxy data suggests that a doubling of atmospheric CO2 would increase globally averaged temperature by 2.6–4.8 °C.
Claudia Wekerle, Tore Hattermann, Qiang Wang, Laura Crews, Wilken-Jon von Appen, and Sergey Danilov
Ocean Sci., 16, 1225–1246, https://doi.org/10.5194/os-16-1225-2020, https://doi.org/10.5194/os-16-1225-2020, 2020
Short summary
Short summary
The high-resolution ocean models ROMS and FESOM configured for the Fram Strait reveal very energetic ocean conditions there. The two main currents meander strongly and shed circular currents of water, called eddies. Our analysis shows that this region is characterised by small and short-lived eddies (on average around a 5 km radius and 10 d lifetime). Both models agree on eddy properties and show similar patterns of baroclinic and barotropic instability of the West Spitsbergen Current.
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, https://doi.org/10.5194/cp-16-1847-2020, 2020
Short summary
Short summary
This paper provides an initial exploration and comparison to climate reconstructions of the new climate model simulations of the mid-Holocene (6000 years ago). These use state-of-the-art models developed for CMIP6 and apply the same experimental set-up. The models capture several key aspects of the climate, but some persistent issues remain.
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.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Lars Nerger, Qi Tang, and Longjiang Mu
Geosci. Model Dev., 13, 4305–4321, https://doi.org/10.5194/gmd-13-4305-2020, https://doi.org/10.5194/gmd-13-4305-2020, 2020
Short summary
Short summary
Data assimilation combines observations with numerical models to get an improved estimate of the model state. This work discusses the technical aspects of how a coupled model that simulates the ocean and the atmosphere can be augmented by data assimilation functionality provided in generic form by the open-source software PDAF (Parallel Data Assimilation Framework). A very efficient program is obtained that can be executed on high-performance computers.
Jesper Sjolte, Florian Adolphi, Bo M. Vinther, Raimund Muscheler, Christophe Sturm, Martin Werner, and Gerrit Lohmann
Clim. Past, 16, 1737–1758, https://doi.org/10.5194/cp-16-1737-2020, https://doi.org/10.5194/cp-16-1737-2020, 2020
Short summary
Short summary
In this study we investigate seasonal climate reconstructions produced by matching climate model output to ice core and tree-ring data, and we evaluate the model–data reconstructions against meteorological observations. The reconstructions capture the main patterns of variability in sea level pressure and temperature in summer and winter. The performance of the reconstructions depends on seasonal climate variability itself, and definitions of seasons can be optimized to capture this variability.
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020, https://doi.org/10.5194/cp-16-1715-2020, 2020
Short summary
Short summary
Interest in past climates as sources of information for the climate system has grown in recent years. In particular, studies of the warm mid-Pliocene and cold Last Glacial Maximum showed relationships between the tropical surface temperature of the Earth and its sensitivity to an abrupt doubling of atmospheric CO2. In this study, we develop a new and promising statistical method and obtain similar results as previously observed, wherein the sensitivity does not seem to exceed extreme values.
Erin L. McClymont, Heather L. Ford, Sze Ling Ho, Julia C. Tindall, Alan M. Haywood, Montserrat Alonso-Garcia, Ian Bailey, Melissa A. Berke, Kate Littler, Molly O. Patterson, Benjamin Petrick, Francien Peterse, A. Christina Ravelo, Bjørg Risebrobakken, Stijn De Schepper, George E. A. Swann, Kaustubh Thirumalai, Jessica E. Tierney, Carolien van der Weijst, Sarah White, Ayako Abe-Ouchi, Michiel L. J. Baatsen, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Ran Feng, Chuncheng Guo, Anna S. von der Heydt, Stephen Hunter, Xiangyi Li, Gerrit Lohmann, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 16, 1599–1615, https://doi.org/10.5194/cp-16-1599-2020, https://doi.org/10.5194/cp-16-1599-2020, 2020
Short summary
Short summary
We examine the sea-surface temperature response to an interval of climate ~ 3.2 million years ago, when CO2 concentrations were similar to today and the near future. Our geological data and climate models show that global mean sea-surface temperatures were 2.3 to 3.2 ºC warmer than pre-industrial climate, that the mid-latitudes and high latitudes warmed more than the tropics, and that the warming was particularly enhanced in the North Atlantic Ocean.
Eric Samakinwa, Christian Stepanek, and Gerrit Lohmann
Clim. Past, 16, 1643–1665, https://doi.org/10.5194/cp-16-1643-2020, https://doi.org/10.5194/cp-16-1643-2020, 2020
Short summary
Short summary
Boundary conditions, forcing, and methodology for the two phases of PlioMIP differ considerably. We compare results from PlioMIP1 and PlioMIP2 simulations. We also carry out sensitivity experiments to infer the relative contribution of different boundary conditions to mid-Pliocene warmth. Our results show dominant effects of mid-Pliocene geography on the climate state and also that prescribing orbital forcing for different time slices within the mid-Pliocene could lead to pronounced variations.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
Short summary
Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
Short summary
Short summary
HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Paul Gierz, Lars Ackermann, Christian B. Rodehacke, Uta Krebs-Kanzow, Christian Stepanek, Dirk Barbi, and Gerrit Lohmann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-159, https://doi.org/10.5194/gmd-2020-159, 2020
Publication in GMD not foreseen
Short summary
Short summary
In this study, we describe the SCOPE coupler, which is used connect the ECHAM6/JSBACH/FESOM1.4 climate model to the PISM 1.1.4 ice sheet model. This system is used to simulate IPCC scenarios projected for the future, and several warm periods in the past; the mid Holocene and the Last Interglacial. Our new model allows us to simulate the ice sheet’s response to changes in the climatic conditions, providing a new avenue of investigation over the previous models, which keep the cryosphere fixed.
Dmitry Sidorenko, Sergey Danilov, Nikolay Koldunov, Patrick Scholz, and Qiang Wang
Geosci. Model Dev., 13, 3337–3345, https://doi.org/10.5194/gmd-13-3337-2020, https://doi.org/10.5194/gmd-13-3337-2020, 2020
Short summary
Short summary
Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then be artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
Short summary
Short summary
In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Ivan M. Parras-Berrocal, Ruben Vazquez, William Cabos, Dmitry Sein, Rafael Mañanes, Juan Perez-Sanz, and Alfredo Izquierdo
Ocean Sci., 16, 743–765, https://doi.org/10.5194/os-16-743-2020, https://doi.org/10.5194/os-16-743-2020, 2020
Short summary
Short summary
This work presents high-resolution simulations of a coupled regional model in the Mediterranean basin. The approach allows us to assess the role of ocean feedbacks in the downscaled climate. Our results show good skills in simulating present climate; the model's robustness introduces improvements in reproducing physical processes at local scales. Our climate projections reveal that by the end of the 21st century the Mediterranean Sea will be warmer and saltier although not in a homogeneous way.
Reinhard Schiemann, Panos Athanasiadis, David Barriopedro, Francisco Doblas-Reyes, Katja Lohmann, Malcolm J. Roberts, Dmitry V. Sein, Christopher D. Roberts, Laurent Terray, and Pier Luigi Vidale
Weather Clim. Dynam., 1, 277–292, https://doi.org/10.5194/wcd-1-277-2020, https://doi.org/10.5194/wcd-1-277-2020, 2020
Short summary
Short summary
In blocking situations the westerly atmospheric flow in the midlatitudes is blocked by near-stationary high-pressure systems. Blocking can be associated with extremes such as cold spells and heat waves. Climate models are known to underestimate blocking occurrence. Here, we assess the latest generation of models and find improvements in simulated blocking, partly due to increases in model resolution. These new models are therefore more suitable for studying climate extremes related to blocking.
Martin Wegmann, Marco Rohrer, María Santolaria-Otín, and Gerrit Lohmann
Earth Syst. Dynam., 11, 509–524, https://doi.org/10.5194/esd-11-509-2020, https://doi.org/10.5194/esd-11-509-2020, 2020
Short summary
Short summary
Predicting the climate of the upcoming season is of big societal benefit, but finding out which component of the climate system can act as a predictor is difficult. In this study, we focus on Eurasian snow cover as such a component and show that knowing the snow cover in November is very helpful in predicting the state of winter over Europe. However, this mechanism was questioned in the past. Using snow data that go back 150 years into the past, we are now very confident in this relationship.
Torben Koenigk, Ramon Fuentes-Franco, Virna Meccia, Oliver Gutjahr, Laura C. Jackson, Adrian L. New, Pablo Ortega, Christopher Roberts, Malcolm Roberts, Thomas Arsouze, Doroteaciro Iovino, Marie-Pierre Moine, and Dmitry V. Sein
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-41, https://doi.org/10.5194/os-2020-41, 2020
Revised manuscript not accepted
Short summary
Short summary
The mixing of water masses into the deep ocean in the North Atlantic is important for the entire global ocean circulation. We use seven global climate models to investigate the effect of increasing the model resolution on this deep ocean mixing. The main result is that increased model resolution leads to a deeper mixing of water masses in the Labrador Sea but has less effect in the Greenland Sea. However, most of the models overestimate the deep ocean mixing compared to observations.
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
Short summary
Short summary
This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Jianjun Zou, Xuefa Shi, Aimei Zhu, Selvaraj Kandasamy, Xun Gong, Lester Lembke-Jene, Min-Te Chen, Yonghua Wu, Shulan Ge, Yanguang Liu, Xinru Xue, Gerrit Lohmann, and Ralf Tiedemann
Clim. Past, 16, 387–407, https://doi.org/10.5194/cp-16-387-2020, https://doi.org/10.5194/cp-16-387-2020, 2020
Short summary
Short summary
Large-scale reorganization of global ocean circulation has been documented in a variety of marine archives, including the enhanced North Pacific Intermediate Water NPIW. Our data support both the model- and data-based ideas that the enhanced NPIW mainly developed during cold spells, while an expansion of oxygen-poor zones occurred at warming intervals (Bölling-Alleröd).
Xingxing Liu, Youbin Sun, Jef Vandenberghe, Peng Cheng, Xu Zhang, Evan J. Gowan, Gerrit Lohmann, and Zhisheng An
Clim. Past, 16, 315–324, https://doi.org/10.5194/cp-16-315-2020, https://doi.org/10.5194/cp-16-315-2020, 2020
Short summary
Short summary
The East Asian summer monsoon and winter monsoon are anticorrelated on a centennial timescale during 16–1 ka. The centennial monsoon variability is connected to changes of both solar activity and North Atlantic cooling events during the Early Holocene. Then, North Atlantic cooling became the major forcing of events during the Late Holocene. This work presents the great challenge and potential to understand the response of the monsoon system to global climate changes in the past and the future.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
Short summary
Short summary
Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
Short summary
Short summary
This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice-Ocean Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor, FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases but with a remarkable performance speedup with a 3 times higher throughput.
Alexandre Cauquoin, Martin Werner, and Gerrit Lohmann
Clim. Past, 15, 1913–1937, https://doi.org/10.5194/cp-15-1913-2019, https://doi.org/10.5194/cp-15-1913-2019, 2019
Short summary
Short summary
We present here the first model results of a newly developed isotope-enhanced version of the Earth system model MPI-ESM. Our model setup has a finer spatial resolution compared to other isotope-enabled fully coupled models. We evaluate the model for preindustrial and mid-Holocene climate conditions. Our analyses show a good to very good agreement with various isotopic data. The spatial and temporal links between isotopes and climate variables under warm climatic conditions are also analyzed.
Ivan Kuznetsov, Alexey Androsov, Vera Fofonova, Sergey Danilov, Natalja Rakowsky, Sven Harig, and Karen Helen Wiltshire
Ocean Sci. Discuss., https://doi.org/10.5194/os-2019-103, https://doi.org/10.5194/os-2019-103, 2019
Revised manuscript not accepted
Short summary
Short summary
Coastal regions play a significant role in global processes. Numerical models are one of the major instruments in understanding ocean dynamics. The main objective of this article is to demonstrate the representativeness of the simulations with the new FESOM-C model by comparing the results with observational data for the southeastern part of the North Sea. An equally important objective is to present the application of convergence analysis of solutions for grids of different spatial resolutions.
Nikolay V. Koldunov, Vadym Aizinger, Natalja Rakowsky, Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, and Thomas Jung
Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, https://doi.org/10.5194/gmd-12-3991-2019, 2019
Short summary
Short summary
We measure how computational performance of the global FESOM2 ocean model (formulated on an unstructured mesh) changes with the increase in the number of computational cores. We find that for many components of the model the performance increases linearly but we also identify two bottlenecks: sea ice and ssh submodules. We show that FESOM2 is on par with the state-of-the-art ocean models in terms of throughput that reach 16 simulated years per day for eddy resolving configuration (1/10°).
Özgür Gürses, Vanessa Kolatschek, Qiang Wang, and Christian Bernd Rodehacke
The Cryosphere, 13, 2317–2324, https://doi.org/10.5194/tc-13-2317-2019, https://doi.org/10.5194/tc-13-2317-2019, 2019
Short summary
Short summary
The warming of the Earth's climate system causes sea level rise. In Antarctica, ice streams flow into the sea and develop ice shelves. These are floating extensions of the ice streams. Ocean water melts these ice shelves. It has been proposed that a submarine wall could shield these ice shelves from the warm water. Our model simulation shows that the wall protects ice shelves. However, the warm water flows to neighboring ice shelves. There, enhanced melting reduces the effectiveness of the wall.
Kristian Strommen, Hannah M. Christensen, Dave MacLeod, Stephan Juricke, and Tim N. Palmer
Geosci. Model Dev., 12, 3099–3118, https://doi.org/10.5194/gmd-12-3099-2019, https://doi.org/10.5194/gmd-12-3099-2019, 2019
Short summary
Short summary
Due to computational limitations, climate models cannot fully resolve the laws of physics below a certain scale – a large source of errors and uncertainty. Stochastic schemes aim to account for this by randomly sampling the possible unresolved states. We develop new stochastic schemes for the EC-Earth climate model and evaluate their impact on model performance. While several benefits are found, the impact is sometimes too strong, suggesting such schemes must be carefully calibrated before use.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
Short summary
Short summary
Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Lennert B. Stap, Peter Köhler, and Gerrit Lohmann
Earth Syst. Dynam., 10, 333–345, https://doi.org/10.5194/esd-10-333-2019, https://doi.org/10.5194/esd-10-333-2019, 2019
Short summary
Short summary
Processes causing the same global-average radiative forcing might lead to different global temperature changes. We expand the theoretical framework by which we calculate paleoclimate sensitivity with an efficacy factor. Applying the revised approach to radiative forcing caused by CO2 and land ice albedo perturbations, inferred from data of the past 800 000 years, gives a new paleo-based estimate of climate sensitivity.
Doug M. Smith, James A. Screen, Clara Deser, Judah Cohen, John C. Fyfe, Javier García-Serrano, Thomas Jung, Vladimir Kattsov, Daniela Matei, Rym Msadek, Yannick Peings, Michael Sigmond, Jinro Ukita, Jin-Ho Yoon, and Xiangdong Zhang
Geosci. Model Dev., 12, 1139–1164, https://doi.org/10.5194/gmd-12-1139-2019, https://doi.org/10.5194/gmd-12-1139-2019, 2019
Short summary
Short summary
The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the sixth Coupled Model Intercomparison Project (CMIP6). It will investigate the causes and global consequences of polar amplification through coordinated multi-model numerical experiments. This paper documents the experimental protocol.
Alexey Androsov, Vera Fofonova, Ivan Kuznetsov, Sergey Danilov, Natalja Rakowsky, Sven Harig, Holger Brix, and Karen Helen Wiltshire
Geosci. Model Dev., 12, 1009–1028, https://doi.org/10.5194/gmd-12-1009-2019, https://doi.org/10.5194/gmd-12-1009-2019, 2019
Short summary
Short summary
We present a description of a coastal ocean circulation model designed to work on variable-resolution meshes made of triangular and quadrilateral cells. This hybrid mesh functionality allows for higher numerical performance and less dissipative solutions.
Monica Ionita, Klaus Grosfeld, Patrick Scholz, Renate Treffeisen, and Gerrit Lohmann
Earth Syst. Dynam., 10, 189–203, https://doi.org/10.5194/esd-10-189-2019, https://doi.org/10.5194/esd-10-189-2019, 2019
Short summary
Short summary
Based on a simple statistical model we show that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the September sea ice extent and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic.
Evan J. Gowan, Lu Niu, Gregor Knorr, and Gerrit Lohmann
Earth Syst. Sci. Data, 11, 375–391, https://doi.org/10.5194/essd-11-375-2019, https://doi.org/10.5194/essd-11-375-2019, 2019
Short summary
Short summary
The speed of ice sheet flow is largely controlled by the strength of the ice–bed interface. We present three datasets on the geological properties of regions in North America, Greenland and Iceland that were covered by Quaternary ice sheets. These include the grain size of glacial sediments, the continuity of sediment cover and bedrock geology. Simple ice modelling experiments show that altering the basal strength of the ice sheet on the basis of these datasets impacts ice thickness.
Nils Hutter, Lorenzo Zampieri, and Martin Losch
The Cryosphere, 13, 627–645, https://doi.org/10.5194/tc-13-627-2019, https://doi.org/10.5194/tc-13-627-2019, 2019
Short summary
Short summary
Arctic sea ice is an aggregate of ice floes with various sizes. The different sizes result from constant deformation of the ice pack. If a floe breaks, open ocean is exposed in a lead. Collision of floes forms pressure ridges. Here, we present algorithms that detect and track these deformation features in satellite observations and model output. The tracked features are used to provide a comprehensive description of localized deformation of sea ice and help to understand its material properties.
Uta Krebs-Kanzow, Paul Gierz, and Gerrit Lohmann
The Cryosphere, 12, 3923–3930, https://doi.org/10.5194/tc-12-3923-2018, https://doi.org/10.5194/tc-12-3923-2018, 2018
Short summary
Short summary
We present a new surface melt scheme for land ice. Derived from the energy balance of melting surfaces, the scheme may be particularly suitable for long ice-sheet simulations of past and future climates. It is computationally inexpensive and can be adapted to changes in the Earth's orbit and atmospheric composition. The scheme yields a better spatial representation of surface melt than common empirical schemes when applied to the Greenland Ice Sheet under present-day climate conditions.
Gerrit Lohmann
Earth Syst. Dynam., 9, 1279–1281, https://doi.org/10.5194/esd-9-1279-2018, https://doi.org/10.5194/esd-9-1279-2018, 2018
Short summary
Short summary
Long-term sea surface temperature trends and variability are underestimated in models compared to paleoclimate data. The idea is presented that the trends and variability are related, which is elaborated in a conceptual model framework. The temperature spectrum can be used to estimate the timescale-dependent climate sensitivity.
Nikolay V. Koldunov and Luisa Cristini
Adv. Geosci., 45, 295–303, https://doi.org/10.5194/adgeo-45-295-2018, https://doi.org/10.5194/adgeo-45-295-2018, 2018
Short summary
Short summary
We believe that project managers can benefit from using programming languages in their work. In this paper we show several simple examples of how python programming language can be used for some of the basic text manipulation tasks, as well as describe more complicated test cases using a HORIZON 2020 type European project as an example.
Axel Wagner, Gerrit Lohmann, and Matthias Prange
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-172, https://doi.org/10.5194/gmd-2018-172, 2018
Publication in GMD not foreseen
Short summary
Short summary
This study demonstrates the dependence of simulated surface air temperatures on variations in grid resolution and resolution-dependent orography in simulations of the Mid-Holocene. A set of Mid-Holocene sensitivity experiments is carried out. The simulated Mid-Holocene temperature differences (low versus high resolution) reveal a response that regionally exceeds the Mid-Holocene to preindustrial modelled temperature anomalies, and show partly reversed signs across the same geographical regions.
Jesper Sjolte, Christophe Sturm, Florian Adolphi, Bo M. Vinther, Martin Werner, Gerrit Lohmann, and Raimund Muscheler
Clim. Past, 14, 1179–1194, https://doi.org/10.5194/cp-14-1179-2018, https://doi.org/10.5194/cp-14-1179-2018, 2018
Short summary
Short summary
Tropical volcanic eruptions and variations in solar activity have been suggested to influence the strength of westerly winds across the North Atlantic. We use Greenland ice core records together with a climate model simulation, and find stronger westerly winds for five winters following tropical volcanic eruptions. We see a delayed response to solar activity of 5 years, and the response to solar minima corresponds well to the cooling pattern during the period known as the Little Ice Age.
Monica Ionita, Patrick Scholz, Klaus Grosfeld, and Renate Treffeisen
Earth Syst. Dynam., 9, 939–954, https://doi.org/10.5194/esd-9-939-2018, https://doi.org/10.5194/esd-9-939-2018, 2018
Short summary
Short summary
In austral spring 2016 the Antarctic region experienced anomalous sea ice retreat in all sectors, with sea ice extent in October and November 2016 being the lowest in the Southern Hemisphere over the observational record (1979–present). The extreme sea ice retreat was accompanied by the wettest and warmest spring on record, over large areas covering the Indian ocean, the Ross Sea, and the Weddell Sea.
Sebastian G. Mutz, Todd A. Ehlers, Martin Werner, Gerrit Lohmann, Christian Stepanek, and Jingmin Li
Earth Surf. Dynam., 6, 271–301, https://doi.org/10.5194/esurf-6-271-2018, https://doi.org/10.5194/esurf-6-271-2018, 2018
Short summary
Short summary
We use a climate model and statistics to provide an overview of regional climates from different times in the late Cenozoic. We focus on tectonically active mountain ranges in particular. Our results highlight significant changes in climates throughout the late Cenozoic, which should be taken into consideration when interpreting erosion rates. We also document the differences between model- and proxy-based estimates for late Cenozoic climate change in South America and Tibet.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
Short summary
Short summary
For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Akil Hossain, Xu Zhang, and Gerrit Lohmann
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-9, https://doi.org/10.5194/cp-2018-9, 2018
Revised manuscript not accepted
Norel Rimbu, Monica Ionita, Markus Czymzik, Achim Brauer, and Gerrit Lohmann
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-137, https://doi.org/10.5194/cp-2017-137, 2017
Manuscript not accepted for further review
Short summary
Short summary
Multi-decadal to millennial flood frequency variations in the Mid- to Late Holocene in a flood layer record from Lake Ammersee is strongly related to the occurrence of extreme precipitation and temperatures in the northeastern Europe.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. LeGrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Francesco S. R. Pausata, Jean-Yves Peterschmitt, Steven J. Phipps, Hans Renssen, and Qiong Zhang
Geosci. Model Dev., 10, 3979–4003, https://doi.org/10.5194/gmd-10-3979-2017, https://doi.org/10.5194/gmd-10-3979-2017, 2017
Short summary
Short summary
The PMIP4 and CMIP6 mid-Holocene and Last Interglacial simulations provide an opportunity to examine the impact of two different changes in insolation forcing on climate at times when other forcings were relatively similar to present. This will allow exploration of the role of feedbacks relevant to future projections. Evaluating these simulations using paleoenvironmental data will provide direct out-of-sample tests of the reliability of state-of-the-art models to simulate climate changes.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, https://doi.org/10.5194/gmd-10-4035-2017, 2017
Short summary
Short summary
The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Nikolay V. Koldunov, Armin Köhl, Nuno Serra, and Detlef Stammer
The Cryosphere, 11, 2265–2281, https://doi.org/10.5194/tc-11-2265-2017, https://doi.org/10.5194/tc-11-2265-2017, 2017
Short summary
Short summary
The paper describes one of the first attempts to use the so-called adjoint data assimilation method to bring Arctic Ocean model simulations closer to observation, especially in terms of the sea ice. It is shown that after assimilation the model bias in simulating the Arctic sea ice is considerably reduced. There is also additional improvement in the sea ice thickens representation that is not assimilated directly.
Lu Niu, Gerrit Lohmann, Sebastian Hinck, and Evan J. Gowan
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-105, https://doi.org/10.5194/cp-2017-105, 2017
Revised manuscript not accepted
Short summary
Short summary
The sensitivity of Northern Hemisphere ice sheets to atmospheric forcing during the last glacial-interglacial cycle is investigated by using output from PMIP3 models. The results show large diversity in simulated ice sheets between different models. We found that summer surface air temperature pattern resembles the ice sheet extent pattern at the LGM. This study implies careful constrains on climate output is essential for simulating reliable glacial-interglacial Northern Hemisphere ice sheets.
Kristofer Döös, Bror Jönsson, and Joakim Kjellsson
Geosci. Model Dev., 10, 1733–1749, https://doi.org/10.5194/gmd-10-1733-2017, https://doi.org/10.5194/gmd-10-1733-2017, 2017
Short summary
Short summary
The TRACMASS trajectory code with corresponding schemes has been improved and become more accurate and user friendly over the years. An outcome of the present study is that we strongly recommend the use of the
time-dependentTRACMASS scheme. We would also like to dissuade the use of the more primitive
stepwise-stationaryscheme, since the velocity fields remain stationary for longer periods, creating abrupt discontinuities in the velocity fields and yielding inaccurate solutions.
Vera D. Meyer, Jens Hefter, Gerrit Lohmann, Lars Max, Ralf Tiedemann, and Gesine Mollenhauer
Clim. Past, 13, 359–377, https://doi.org/10.5194/cp-13-359-2017, https://doi.org/10.5194/cp-13-359-2017, 2017
Anton Y. Dvornikov, Stanislav D. Martyanov, Vladimir A. Ryabchenko, Tatjana R. Eremina, Alexey V. Isaev, and Dmitry V. Sein
Earth Syst. Dynam., 8, 265–282, https://doi.org/10.5194/esd-8-265-2017, https://doi.org/10.5194/esd-8-265-2017, 2017
Paolo Davini, Jost von Hardenberg, Susanna Corti, Hannah M. Christensen, Stephan Juricke, Aneesh Subramanian, Peter A. G. Watson, Antje Weisheimer, and Tim N. Palmer
Geosci. Model Dev., 10, 1383–1402, https://doi.org/10.5194/gmd-10-1383-2017, https://doi.org/10.5194/gmd-10-1383-2017, 2017
Short summary
Short summary
The Climate SPHINX project is a large set of more than 120 climate simulations run with the EC-Earth global climate. It explores the sensitivity of present-day and future climate to the model horizontal resolution (from 150 km up to 16 km) and to the introduction of two stochastic physics parameterisations. Results shows that the the stochastic schemes can represent a cheaper alternative to a resolution increase, especially for the representation of the tropical climate variability.
Monica Ionita, Lena M. Tallaksen, Daniel G. Kingston, James H. Stagge, Gregor Laaha, Henny A. J. Van Lanen, Patrick Scholz, Silvia M. Chelcea, and Klaus Haslinger
Hydrol. Earth Syst. Sci., 21, 1397–1419, https://doi.org/10.5194/hess-21-1397-2017, https://doi.org/10.5194/hess-21-1397-2017, 2017
Short summary
Short summary
This paper analyses the European summer drought of 2015 from a climatological perspective, including its origin and spatial and temporal development, and how it compares with the 2003 event. It discusses the main contributing factors controlling the occurrence and persistence of the event: temperature and precipitation anomalies, blocking episodes and sea surface temperatures. The results represent the outcome of a collaborative initiative of members of UNESCO’s FRIEND-Water program.
Sergey Danilov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, https://doi.org/10.5194/gmd-10-765-2017, 2017
Short summary
Short summary
Numerical models of global ocean circulation are used to learn about future climate. The ocean circulation is characterized by processes on different spatial scales which are still beyond the reach of present computers. We describe a new model setup that allows one to vary a model's spatial resolution and hence focus the computational power on regional dynamics, reaching a better description of local processes in areas of interest.
Venkatramani Balaji, Eric Maisonnave, Niki Zadeh, Bryan N. Lawrence, Joachim Biercamp, Uwe Fladrich, Giovanni Aloisio, Rusty Benson, Arnaud Caubel, Jeffrey Durachta, Marie-Alice Foujols, Grenville Lister, Silvia Mocavero, Seth Underwood, and Garrett Wright
Geosci. Model Dev., 10, 19–34, https://doi.org/10.5194/gmd-10-19-2017, https://doi.org/10.5194/gmd-10-19-2017, 2017
Short summary
Short summary
Climate models are among the most computationally expensive scientific applications in the world. We present a set of measures of computational performance that can be used to compare models that are independent of underlying hardware and the model formulation. They are easy to collect and reflect performance actually achieved in practice. We are preparing a systematic effort to collect these metrics for the world's climate models during CMIP6, the next Climate Model Intercomparison Project.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. Legrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Jean-Yves Peterschmidt, Francesco S.-R. Pausata, Steven Phipps, and Hans Renssen
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-106, https://doi.org/10.5194/cp-2016-106, 2016
Preprint retracted
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Helge F. Goessling and Sebastian Bathiany
Earth Syst. Dynam., 7, 697–715, https://doi.org/10.5194/esd-7-697-2016, https://doi.org/10.5194/esd-7-697-2016, 2016
Short summary
Short summary
Carbon dioxide, while warming the Earth's surface, cools the atmosphere beyond about 15 km (the middle atmosphere). This cooling is considered a fingerprint of anthropogenic global warming, yet the physical reason behind it remains prone to misconceptions. Here we use a simple radiation model to illustrate the physical essence of stratospheric cooling, and a complex climate model to quantify how strongly different mechanisms contribute.
Jonathan J. Day, Steffen Tietsche, Mat Collins, Helge F. Goessling, Virginie Guemas, Anabelle Guillory, William J. Hurlin, Masayoshi Ishii, Sarah P. E. Keeley, Daniela Matei, Rym Msadek, Michael Sigmond, Hiroaki Tatebe, and Ed Hawkins
Geosci. Model Dev., 9, 2255–2270, https://doi.org/10.5194/gmd-9-2255-2016, https://doi.org/10.5194/gmd-9-2255-2016, 2016
Short summary
Short summary
Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable.
Madlene Pfeiffer and Gerrit Lohmann
Clim. Past, 12, 1313–1338, https://doi.org/10.5194/cp-12-1313-2016, https://doi.org/10.5194/cp-12-1313-2016, 2016
Short summary
Short summary
The Last Interglacial was warmer, with a reduced Greenland Ice Sheet (GIS), compared to the late Holocene. We analyse – through climate model simulations – the impact of a reduced GIS on the global surface air temperature and find a relatively strong warming especially in the Northern Hemisphere. These results are then compared to temperature reconstructions, indicating good agreement with respect to the pattern. However, the simulated temperatures underestimate the proxy-based temperatures.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
Short summary
Short summary
We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
Norel Rimbu, Markus Czymzik, Monica Ionita, Gerrit Lohmann, and Achim Brauer
Clim. Past, 12, 377–385, https://doi.org/10.5194/cp-12-377-2016, https://doi.org/10.5194/cp-12-377-2016, 2016
M. Werner, B. Haese, X. Xu, X. Zhang, M. Butzin, and G. Lohmann
Geosci. Model Dev., 9, 647–670, https://doi.org/10.5194/gmd-9-647-2016, https://doi.org/10.5194/gmd-9-647-2016, 2016
Short summary
Short summary
This paper presents the first results of a new isotope-enabled GCM set-up, based on the ECHAM5/MPI-OM fully coupled atmosphere-ocean model. Results of two equilibrium simulations under pre-industrial and Last Glacial Maximum conditions reveal a good to very good agreement with many delta O-18 and delta D observational records, and a remarkable improvement for the modelling of the deuterium excess signal in Antarctic ice cores.
M. Stärz, G. Lohmann, and G. Knorr
Clim. Past, 12, 151–170, https://doi.org/10.5194/cp-12-151-2016, https://doi.org/10.5194/cp-12-151-2016, 2016
Short summary
Short summary
In order to account for coupled climate-soil processes, we developed a soil scheme which is asynchronously coupled to an earth system model. We tested the scheme and found additional warming for a relatively warm climate (mid-Holocene), and extra cooling for a colder (Last Glacial Maximum) than preindustrial climate. These findings indicate a relatively strong positive soil feedback to climate, which may help to reduce model-data discrepancies for the climate of the geological past.
M. Forrest, J. T. Eronen, T. Utescher, G. Knorr, C. Stepanek, G. Lohmann, and T. Hickler
Clim. Past, 11, 1701–1732, https://doi.org/10.5194/cp-11-1701-2015, https://doi.org/10.5194/cp-11-1701-2015, 2015
Short summary
Short summary
We simulated Late Miocene (11-7 Million years ago) vegetation using two plausible CO2 concentrations: 280ppm CO2 and 450ppm CO2. We compared the simulated vegetation to existing plant fossil data for the whole Northern Hemisphere. Our results suggest that during the Late Miocene the CO2 levels have been relatively low, or that other factors that are not included in the models maintained the seasonal temperate forests and open vegetation.
X. Shi and G. Lohmann
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-6-2137-2015, https://doi.org/10.5194/esdd-6-2137-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
Our work is to investigate to what degree the open water ice formation affects the ice and ocean properties.
Our results show a positive feedback among the Arctic sea ice, the AMOC, and the surface air temperature in the Arctic.
The sea ice transport affects the freshwater budget in regions of deep water formation.
A link between the climate of Northern Hemisphere continents and the lead closing rate during ice formation period is also shown by the model.
S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter
Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, https://doi.org/10.5194/gmd-8-1747-2015, 2015
Short summary
Short summary
Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.
N. Sudarchikova, U. Mikolajewicz, C. Timmreck, D. O'Donnell, G. Schurgers, D. Sein, and K. Zhang
Clim. Past, 11, 765–779, https://doi.org/10.5194/cp-11-765-2015, https://doi.org/10.5194/cp-11-765-2015, 2015
B. de Boer, A. M. Dolan, J. Bernales, E. Gasson, H. Goelzer, N. R. Golledge, J. Sutter, P. Huybrechts, G. Lohmann, I. Rogozhina, A. Abe-Ouchi, F. Saito, and R. S. W. van de Wal
The Cryosphere, 9, 881–903, https://doi.org/10.5194/tc-9-881-2015, https://doi.org/10.5194/tc-9-881-2015, 2015
Short summary
Short summary
We present results from simulations of the Antarctic ice sheet by means of an intercomparison project with six ice-sheet models. Our results demonstrate the difficulty of all models used here to simulate a significant retreat or re-advance of the East Antarctic ice grounding line. Improved grounding-line physics could be essential for a correct representation of the migration of the grounding line of the Antarctic ice sheet during the Pliocene.
A. M. Dolan, S. J. Hunter, D. J. Hill, A. M. Haywood, S. J. Koenig, B. L. Otto-Bliesner, A. Abe-Ouchi, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, G. Ramstein, N. A. Rosenbloom, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 11, 403–424, https://doi.org/10.5194/cp-11-403-2015, https://doi.org/10.5194/cp-11-403-2015, 2015
Short summary
Short summary
Climate and ice sheet models are often used to predict the nature of ice sheets in Earth history. It is important to understand whether such predictions are consistent among different models, especially in warm periods of relevance to the future. We use input from 15 different climate models to run one ice sheet model and compare the predictions over Greenland. We find that there are large differences between the predicted ice sheets for the warm Pliocene (c. 3 million years ago).
V. Schourup-Kristensen, D. Sidorenko, D. A. Wolf-Gladrow, and C. Völker
Geosci. Model Dev., 7, 2769–2802, https://doi.org/10.5194/gmd-7-2769-2014, https://doi.org/10.5194/gmd-7-2769-2014, 2014
D. Barbi, G. Lohmann, K. Grosfeld, and M. Thoma
Geosci. Model Dev., 7, 2003–2013, https://doi.org/10.5194/gmd-7-2003-2014, https://doi.org/10.5194/gmd-7-2003-2014, 2014
I. A. Dmitrenko, S. A. Kirillov, N. Serra, N. V. Koldunov, V. V. Ivanov, U. Schauer, I. V. Polyakov, D. Barber, M. Janout, V. S. Lien, M. Makhotin, and Y. Aksenov
Ocean Sci., 10, 719–730, https://doi.org/10.5194/os-10-719-2014, https://doi.org/10.5194/os-10-719-2014, 2014
T. Goelles, K. Grosfeld, and G. Lohmann
Geosci. Model Dev., 7, 1395–1408, https://doi.org/10.5194/gmd-7-1395-2014, https://doi.org/10.5194/gmd-7-1395-2014, 2014
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
A. Basu, M. G. Schultz, S. Schröder, L. Francois, X. Zhang, G. Lohmann, and T. Laepple
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-3193-2014, https://doi.org/10.5194/acpd-14-3193-2014, 2014
Revised manuscript not accepted
D. J. Hill, A. M. Haywood, D. J. Lunt, S. J. Hunter, F. J. Bragg, C. Contoux, C. Stepanek, L. Sohl, N. A. Rosenbloom, W.-L. Chan, Y. Kamae, Z. Zhang, A. Abe-Ouchi, M. A. Chandler, A. Jost, G. Lohmann, B. L. Otto-Bliesner, G. Ramstein, and H. Ueda
Clim. Past, 10, 79–90, https://doi.org/10.5194/cp-10-79-2014, https://doi.org/10.5194/cp-10-79-2014, 2014
M. Thoma, K. Grosfeld, D. Barbi, J. Determann, S. Goeller, C. Mayer, and F. Pattyn
Geosci. Model Dev., 7, 1–21, https://doi.org/10.5194/gmd-7-1-2014, https://doi.org/10.5194/gmd-7-1-2014, 2014
X. Zhang, G. Lohmann, G. Knorr, and X. Xu
Clim. Past, 9, 2319–2333, https://doi.org/10.5194/cp-9-2319-2013, https://doi.org/10.5194/cp-9-2319-2013, 2013
B. Haese, M. Werner, and G. Lohmann
Geosci. Model Dev., 6, 1463–1480, https://doi.org/10.5194/gmd-6-1463-2013, https://doi.org/10.5194/gmd-6-1463-2013, 2013
R. Zhang, Q. Yan, Z. S. Zhang, D. Jiang, B. L. Otto-Bliesner, A. M. Haywood, D. J. Hill, A. M. Dolan, C. Stepanek, G. Lohmann, C. Contoux, F. Bragg, W.-L. Chan, M. A. Chandler, A. Jost, Y. Kamae, A. Abe-Ouchi, G. Ramstein, N. A. Rosenbloom, L. Sohl, and H. Ueda
Clim. Past, 9, 2085–2099, https://doi.org/10.5194/cp-9-2085-2013, https://doi.org/10.5194/cp-9-2085-2013, 2013
Z.-S. Zhang, K. H. Nisancioglu, M. A. Chandler, A. M. Haywood, B. L. Otto-Bliesner, G. Ramstein, C. Stepanek, A. Abe-Ouchi, W.-L. Chan, F. J. Bragg, C. Contoux, A. M. Dolan, D. J. Hill, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, N. A. Rosenbloom, L. E. Sohl, and H. Ueda
Clim. Past, 9, 1495–1504, https://doi.org/10.5194/cp-9-1495-2013, https://doi.org/10.5194/cp-9-1495-2013, 2013
N. Rakowsky, A. Androsov, A. Fuchs, S. Harig, A. Immerz, S. Danilov, W. Hiller, and J. Schröter
Nat. Hazards Earth Syst. Sci., 13, 1629–1642, https://doi.org/10.5194/nhess-13-1629-2013, https://doi.org/10.5194/nhess-13-1629-2013, 2013
H. F. Goessling and C. H. Reick
Atmos. Chem. Phys., 13, 5567–5585, https://doi.org/10.5194/acp-13-5567-2013, https://doi.org/10.5194/acp-13-5567-2013, 2013
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
C. Giry, T. Felis, M. Kölling, W. Wei, G. Lohmann, and S. Scheffers
Clim. Past, 9, 841–858, https://doi.org/10.5194/cp-9-841-2013, https://doi.org/10.5194/cp-9-841-2013, 2013
A. M. Haywood, D. J. Hill, A. M. Dolan, B. L. Otto-Bliesner, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, H. J. Dowsett, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, A. Abe-Ouchi, S. J. Pickering, G. Ramstein, N. A. Rosenbloom, U. Salzmann, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 9, 191–209, https://doi.org/10.5194/cp-9-191-2013, https://doi.org/10.5194/cp-9-191-2013, 2013
G. Lohmann, A. Wackerbarth, P. M. Langebroek, M. Werner, J. Fohlmeister, D. Scholz, and A. Mangini
Clim. Past, 9, 89–98, https://doi.org/10.5194/cp-9-89-2013, https://doi.org/10.5194/cp-9-89-2013, 2013
S. Dietrich, M. Werner, T. Spangehl, and G. Lohmann
Clim. Past, 9, 13–26, https://doi.org/10.5194/cp-9-13-2013, https://doi.org/10.5194/cp-9-13-2013, 2013
Related subject area
Climate and Earth system modeling
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Process-based modeling framework for sustainable irrigation management at the regional scale: Integrating rice production, water use, and greenhouse gas emissions
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
ICON-HAM-lite: simulating the Earth system with interactive aerosols at kilometer scales
Reducing Time and Computing Costs in EC-Earth: An Automatic Load-Balancing Approach for Coupled ESMs
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
Short summary
Short summary
Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
Short summary
Short summary
Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
Short summary
Short summary
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
Short summary
Short summary
We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
Short summary
Short summary
The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
Short summary
Short summary
HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
Short summary
Short summary
We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
Short summary
Short summary
This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
Short summary
Short summary
Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
Short summary
Short summary
The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
Short summary
Short summary
CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
Short summary
Short summary
The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
Short summary
Short summary
A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
Short summary
Short summary
In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
Short summary
Short summary
We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Short summary
In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
Short summary
Short summary
We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
Short summary
Short summary
The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
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.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
Short summary
Short summary
Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
Short summary
Short summary
A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Preprint under review for GMD
Short summary
Short summary
This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
Short summary
Short summary
Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
Short summary
Short summary
We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
Short summary
Short summary
We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
Short summary
Short summary
We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
Short summary
Short summary
The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
Short summary
Short summary
We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
Short summary
Short summary
The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
Short summary
Short summary
In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Philipp Weiss, Ross Herbert, and Philip Stier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3325, https://doi.org/10.5194/egusphere-2024-3325, 2024
Short summary
Short summary
Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of log-normal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of five kilometers. It captures key aerosol processes like dust storms or tropical cyclones.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-155, https://doi.org/10.5194/gmd-2024-155, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This work presents an automatic tool to enhance the performance of climate models by optimizing how computer resources are allocated. Traditional methods are time-consuming and error-prone, often resulting in inefficient simulations. Our tool improves speed and reduces computational costs without needing expert knowledge. The tool has been tested on European climate models, making simulations up to 34 % faster while using fewer resources, helping to make climate simulations more efficient.
Cited articles
Adcroft, A. and Campin, J.-M.: Rescaled height coordinates for accurate
representation of free-surface flows in ocean circulation models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003,
2004. a
Adler, R. F., Sapiano, M. R. P., Huffman, G. J., Wang, J.-J., Gu, G., Bolvin,
D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R.,
and Shin, D.-B.: The Global Precipitation Climatology Project (GPCP) Monthly
Analysis (New Version 2.3) and a Review of 2017 Global Precipitation,
Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138, 2018. a
Ali, A., Christensen, K. H., Øyvind Breivik, Malila, M., Raj, R. P., Bertino,
L., Chassignet, E. P., and Bakhoday-Paskyabi, M.: A comparison of Langmuir
turbulence parameterizations and key wave effects in a numerical model of the
North Atlantic and Arctic Oceans, Ocean Model., 137, 76–97,
https://doi.org/10.1016/j.ocemod.2019.02.005, 2019. a
Baker, A. J., Schiemann, R., Hodges, K. I., Demory, M.-E., Mizielinski, M. S.,
Roberts, M. J., Shaffrey, L. C., Strachan, J., and Vidale, P. L.: Enhanced
Climate Change Response of Wintertime North Atlantic Circulation, Cyclonic
Activity, and Precipitation in a 25-km-Resolution Global Atmospheric Model,
J. Climate, 32, 7763–7781, https://doi.org/10.1175/JCLI-D-19-0054.1, 2019. a
Balaji, V., Maisonnave, E., Zadeh, N., Lawrence, B. N., Biercamp, J., Fladrich, U., Aloisio, G., Benson, R., Caubel, A., Durachta, J., Foujols, M.-A., Lister, G., Mocavero, S., Underwood, S., and Wright, G.: CPMIP: measurements of real computational performance of Earth system models in CMIP6, Geosci. Model Dev., 10, 19–34, https://doi.org/10.5194/gmd-10-19-2017, 2017. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi,
M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification
from Field Site to Terrestrial Water Storage and Impact in the Integrated
Forecast System, J. Hydrometeorol., 10, 623–643,
https://doi.org/10.1175/2008JHM1068.1, 2009. a
Barbi, D., Wieters, N., Gierz, P., Andrés-Martínez, M., Ural, D., Chegini, F., Khosravi, S., and Cristini, L.: ESM-Tools version 5.0: a modular infrastructure for stand-alone and coupled Earth system modelling (ESM), Geosci. Model Dev., 14, 4051–4067, https://doi.org/10.5194/gmd-14-4051-2021, 2021. a
Barbi, D., Gierz, P., Andrés-Martínez, M., Ural, D., and Cristini, L.: esm_tools_release3_as_used_by_AWI-CM3_paper (3.1), Zenodo [code], https://doi.org/10.5281/zenodo.6335309, 2022. a
Batrak, Y. and Müller, M.: On the warm bias in atmospheric reanalyses
induced by the missing snow over Arctic sea-ice, Nat. Commun., 10,
4170, https://doi.org/10.1038/s41467-019-11975-3, 2019. a
Beadling, R. L., Russell, J. L., Stouffer, R. J., Mazloff, M., Talley, L. D.,
Goodman, P. J., Sallée, J. B., Hewitt, H. T., Hyder, P., and Pandde, A.:
Representation of Southern Ocean Properties across Coupled Model
Intercomparison Project Generations: CMIP3 to CMIP6, J. Climate, 33,
6555–6581, https://doi.org/10.1175/JCLI-D-19-0970.1, 2020. a
Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., Meehl,
G. A., Predoi, V., Roberts, M. J., and Eyring, V.: Quantifying Progress
Across Different CMIP Phases With the ESMValTool, J. Geophys.
Res.-Atmos., 125, e2019JD032321,
https://doi.org/10.1029/2019JD032321, 2020. a, b
Buizza, R., Milleer, M., and Palmer, T. N.: Stochastic representation of model
uncertainties in the ECMWF ensemble prediction system, Q. J.
Roy. Meteor. Soc., 125, 2887–2908,
https://doi.org/10.1002/qj.49712556006, 1999. a
Caesar, L., McCarthy, G. D., Thornalley, D. J. R., Cahill, N., and Rahmstorf,
S.: Reply to: Atlantic circulation change still uncertain, Nat. Geosci., 15, 168–170,
https://doi.org/10.1038/s41561-022-00897-3, 2022. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a
Curry, B., Lee, C. M., Petrie, B., Moritz, R. E., and Kwok, R.: Multiyear
Volume, Liquid Freshwater, and Sea Ice Transports through Davis Strait,
2004–10, J. Phys. Oceanogr., 44, 1244–1266,
https://doi.org/10.1175/JPO-D-13-0177.1, 2014. a
Danek, C., Shi, X., Stepanek, C., Yang, H., Barbi, D., Hegewald, J., and
Lohmann, G.: AWI AWI-ESM1.1LR model output prepared for CMIP6 CMIP, Earth System Grid Federation,
https://doi.org/10.22033/ESGF/CMIP6.9301, 2020. a
Danilov, S., Wang, Q., Timmermann, R., Iakovlev, N., Sidorenko, D., Kimmritz, M., Jung, T., and Schröter, J.: Finite-Element Sea Ice Model (FESIM), version 2, Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, 2015. a
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. a, b
Davini, P., Corti, S., D'Andrea, F., Rivière, G., and von Hardenberg, J.:
Improved Winter European Atmospheric Blocking Frequencies in High-Resolution
Global Climate Simulations, J. Adv. Model. Earth Sy., 9,
2615–2634, https://doi.org/10.1002/2017MS001082, 2017. a
Davy, R., Chen, L., and Hanna, E.: Arctic amplification metrics, International
J. Climatol., 38, 4384–4394,
https://doi.org/10.1002/joc.5675, 2018. a
Dawson, A.: EOFs: A library for EOF analysis of meteorological, oceanographic,
and climate data, J. Open Res. Softw., 4, e14,
https://doi.org/10.5334/jors.122, 2016. a, b
Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J., Balaji, V.,
Beesley, J. A., Cooke, W. F., Dixon, K. W., Dunne, J., Dunne, K. A.,
Durachta, J. W., Findell, K. L., Ginoux, P., Gnanadesikan, A., Gordon, C. T.,
Griffies, S. M., Gudgel, R., Harrison, M. J., Held, I. M., Hemler, R. S.,
Horowitz, L. W., Klein, S. A., Knutson, T. R., Kushner, P. J., Langenhorst,
A. R., Lee, H.-C., Lin, S.-J., Lu, J., Malyshev, S. L., Milly, P. C. D.,
Ramaswamy, V., Russell, J., Schwarzkopf, M. D., Shevliakova, E., Sirutis,
J. J., Spelman, M. J., Stern, W. F., Winton, M., Wittenberg, A. T., Wyman,
B., Zeng, F., and Zhang, R.: GFDL's CM2 global coupled climate models. Part
I: Formulation and simulation characteristics, J. Climate, 19,
643–674, https://doi.org/10.1175/JCLI3629.1, 2006. a
Delworth, T. L., Rosati, A., Anderson, W., Adcroft, A. J., Balaji, V., Benson,
R., Dixon, K., Griffies, S. M., Lee, H.-C., Pacanowski, R. C., Vecchi, G. A.,
Wittenberg, A. T., Zeng, F., and Zhang, R.: Simulated Climate and Climate
Change in the GFDL CM2.5 High-Resolution Coupled Climate Model, J. Climate, 25, 2755–2781, https://doi.org/10.1175/JCLI-D-11-00316.1, 2012. a, b
Donohue, K. A., Tracey, K. L., Watts, D. R., Chidichimo, M. P., and Chereskin,
T. K.: Mean Antarctic Circumpolar Current transport measured in Drake
Passage, Geophys. Res. Lett., 43, 11760–11767,
https://doi.org/10.1002/2016GL070319, 2016. a, b
Döscher, R., Acosta, M., Alessandri, A., Anthoni, P., Arsouze, T., Bergman, T., Bernardello, R., Boussetta, S., Caron, L.-P., Carver, G., Castrillo, M., Catalano, F., Cvijanovic, I., Davini, P., Dekker, E., Doblas-Reyes, F. J., Docquier, D., Echevarria, P., Fladrich, U., Fuentes-Franco, R., Gröger, M., v. Hardenberg, J., Hieronymus, J., Karami, M. P., Keskinen, J.-P., Koenigk, T., Makkonen, R., Massonnet, F., Ménégoz, M., Miller, P. A., Moreno-Chamarro, E., Nieradzik, L., van Noije, T., Nolan, P., O'Donnell, D., Ollinaho, P., van den Oord, G., Ortega, P., Prims, O. T., Ramos, A., Reerink, T., Rousset, C., Ruprich-Robert, Y., Le Sager, P., Schmith, T., Schrödner, R., Serva, F., Sicardi, V., Sloth Madsen, M., Smith, B., Tian, T., Tourigny, E., Uotila, P., Vancoppenolle, M., Wang, S., Wårlind, D., Willén, U., Wyser, K., Yang, S., Yepes-Arbós, X., and Zhang, Q.: The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6, Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, 2022. a, b
ECMWF: IFS Documentation CY43R3 – Part III: Dynamics and numerical procedures,
no. 3 in IFS Documentation, ECMWF, https://doi.org/10.21957/8l7miod5m,
2017a. a
ECMWF: IFS Documentation CY43R3 – Part IV: Physical processes, no. 4 in IFS
Documentation, ECMWF, https://doi.org/10.21957/efyk72kl, 2017b. a
ECMWF: IFS Documentation CY43R3 – Part VII: ECMWF wave model, no. 7 in IFS
Documentation, ECMWF, https://doi.org/10.21957/mxz9z1gb, 2017c. a
Forbes, R., Geer, A., Lonitz, K., and Ahlgrimm, M.: Reducing systematic errors
in cold-air outbreaks, ECMWF newsletter, 146, 17–22, 2016. a
Gent, P. R. and Mcwilliams, J. C.: Isopycnal mixing in ocean circulation
models, J. Phys. Oceanogr., 20, 150–155, 1990. a
Gregory, J. M., Ingram, W. J., Palmer, M. A., Jones, G. S., Stott, P. A.,
Thorpe, R. B., Lowe, J. A., Johns, T. C., and Williams, K. D.: A new method
for diagnosing radiative forcing and climate sensitivity, Geophys.
Res. Lett., 31, https://doi.org/10.1029/2003GL018747, 2004. a
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016. a
Hazeleger, W., Severijns, C., Semmler, T., Ştefănescu, S., Yang,
S., Wang, X., Wyser, K., Dutra, E., Baldasano, J. M., Bintanja, R., Bougeault, P., Caballero, R., Ekman, A. M. L., Christensen, J. H., van den Hurk, B., Jimenez, P., Jones, C., Kållberg, P., Koenigk, T., McGrath, R., Miranda, P., van Noije, T., Palmer, T., Parodi, J. A., Schmith, T., Selten, F., Storelvmo, T., Sterl, A., Tapamo, H., Vancoppenolle, M., Viterbo, P., and Willén, U.:
EC-Earth: a seamless earth-system prediction approach in action, B. Am. Meteorol. Soc., 91, 1357–1364,
https://doi.org/10.1175/2010BAMS2877.1, 2010. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., 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, 2020. a
Hertwig, E., von Storch, J.-S., Handorf, D., Dethloff, K., Fast, I., and
Krismer, T.: Effect of horizontal resolution on ECHAM6-AMIP performance,
Clim. Dynam., 45, 185–211, https://doi.org/10.1007/s00382-014-2396-x, 2015. a
Hortal, M. and Simmons, A. J.: Use of Reduced Gaussian Grids in Spectral
Models, Mon. Weather Rev., 119, 1057–1074,
https://doi.org/10.1175/1520-0493(1991)119<1057:UORGGI>2.0.CO;2, 1991. a
Hunke, E., Allard, R., Bailey, D. A., Blain, P., Craig, A., Dupont, F.,
DuVivier, A., Grumbine, R., Hebert, D., Holland, M., Jeffery, N., Lemieux,
J.-F., Osinski, R., Rasmussen, T., Ribergaard, M., Roach, L., Roberts, A.,
Turner, M., and Winton, M.: CICE-Consortium/Icepack: Icepack 1.2.1, Zenodo [code],
https://doi.org/10.5281/zenodo.3712299, 2020. a
Johannessen, O. M., Kuzmina, S. I., Bobylev, L. P., and Miles, M. W.: Surface
air temperature variability and trends in the Arctic: new amplification
assessment and regionalisation, Tellus A, 68, 28234, https://doi.org/10.3402/tellusa.v68.28234, 2016. a
Jung, T., Miller, M. J., Palmer, T. N., Towers, P., Wedi, N., Achuthavarier,
D., Adams, J. M., Altshuler, E. L., Cash, B. A., Kinter, 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. a
Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., Matei, D.,
Mikolajewicz, U., Notz, D., and von Storch, J. S.: Characteristics of the
ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean
component of the MPI-Earth system model, J. Adv. Model. Earth Sy., 5, 422–446, https://doi.org/10.1002/jame.20023, 2013. a, b
Juricke, S., Danilov, S., Koldunov, N., Oliver, M., Sein, D. V., Sidorenko, D.,
and Wang, Q.: A kinematic kinetic energy backscatter parametrization: From
implementation to global ocean simulations, J. Adv. Model. Earth Sy., 12, e2020MS002175, https://doi.org/10.1029/2020MS002175, 2020. a
Keil, P., Mauritsen, T., Jungclaus, J., Hedemann, C., Olonscheck, D., and
Ghosh, R.: Multiple drivers of the North Atlantic warming hole, Nat.
Clim. Change, 10, 667–671, https://doi.org/10.1038/s41558-020-0819-8, 2020. a
Kimmritz, M., Danilov, S., and Losch, M.: The adaptive EVP method for solving
the sea ice momentum equation, Ocean Model., 101, 59–67,
https://doi.org/10.1016/j.ocemod.2016.03.004, 2016. a
Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G., Woollen, J.,
Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., van den Dool, H.,
Jenne, R., and Fiorino, M.: The NCEP–NCAR 50-Year Reanalysis: Monthly Means
CD-ROM and Documentation, B. Am. Meteorol. Soc.,
82, 247–268, https://doi.org/10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2, 2001. a, b
Kjellsson, J., Streffing, J., Carver, G., and Köhler, M.: From weather
forecasting to climate modelling using OpenIFS, ECMWF Newsletter, 164,
38–41, 2020. a
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, 2019a. a, b
Koldunov, N. V., Danilov, S., Sidorenko, D., Hutter, N., Losch, M., Goessling,
H., Rakowsky, N., Scholz, P., Sein, D., Wang, Q., and Jung, T.: Fast EVP
Solutions in a High-Resolution Sea Ice Model, J. Adv. Model.
Earth Sy., 11, 1269–1284, https://doi.org/10.1029/2018MS001485,
2019b. a
Komen, G., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., and
Janssen, P.: Dynamics and modelling of ocean waves, Cambridge University
Press, UK, 554, 1271–1285, 1996. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: A
review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994. a, b
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49–78, https://doi.org/10.5194/tc-13-49-2019, 2019. a
Lemarié, F., Blayo, E., and Debreu, L.: Analysis of Ocean-atmosphere Coupling
Algorithms: Consistency and Stability, Procedia Computer Science, 51,
2066–2075, https://doi.org/10.1016/j.procs.2015.05.473, 2015. a
Lemke, P.: A coupled one-dimensional sea ice-ocean model, J.
Geophys. Res.-Oceans, 92, 13164–13172,
https://doi.org/10.1029/JC092iC12p13164, 1987. a
Ma, X., Jing, Z., Chang, P., Liu, X., Montuoro, R., Small, R. J., Bryan, F. O.,
Greatbatch, R. J., Brandt, P., Wu, D., Lin, X., and Wu, L.: Western boundary
currents regulated by interaction between ocean eddies and the atmosphere,
Nature, 535, 533–537, https://doi.org/10.1038/nature18640, 2016. a
Maisonnave, E., Coquart, L., and Piacentini, A.: A better diagnostic of the
load imbalance in OASIS based coupled systems, Tech. rep., Technical Report,
TR/CMGC/20/176, CECI, UMR CERFACS/CNRS No5318, France, 2020. a
Malardel, S., Diamantakis, M., Agusti-Panareda, A., and Flemming, J.: Dry mass
versus total mass conservation in the IFS, ECMWF, https://doi.org/10.21957/s3ho2aq29, 2019. a
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. a, b
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S., Péan, C., Berger, S.,
Caud, N., Chen, Y., Goldfarb, L., Gomis, M., Huang, M., Leitzell, K., Lonnoy,
E., Matthews, J., Maycock, T., Waterfield, T., Yelekçi, O., Yu, R., and
Zhou, B. (Eds.): Summary for Policymakers, in: Climate Change 2021: The
Physical Science Basis. Contribution of Working Group I to the Sixth
Assessment Report of the Intergovernmental Panel on Climate Change, Tech.
rep., Intergovernmental Panel on Climate Change, https://doi.org/10.1017/9781009157896,
2021. a, b
McGregor, J. L.: C-CAM: Geometric aspects and dynamical formulation, CSIRO
Atmospheric Research Dickson ACT, 2005. a
Meehl, G. A., Senior, C. A., Eyring, V., Flato, G., Lamarque, J.-F., Stouffer,
R. J., Taylor, K. E., and Schlund, M.: Context for interpreting equilibrium
climate sensitivity and transient climate response from the CMIP6 Earth
system models, Sci. Adv., 6, eaba1981, https://doi.org/10.1126/sciadv.aba1981,
2020. a
Meredith, M. P., Woodworth, P. L., Chereskin, T. K., Marshall, D. P., Allison,
L. C., Bigg, G. R., Donohue, K., Heywood, K. J., Hughes, C. W., Hibbert, A.,
Hogg, A. M., Johnson, H. L., Jullion, L., King, B. A., Leach, H., Lenn,
Y.-D., Morales Maqueda, M. A., Munday, D. R., Naveira Garabato, A. C.,
Provost, C., Sallée, J.-B., and Sprintall, J.: Sustained Monitoring of the
Southern Ocean at Drake Passage: Past Achievements and Future Priorities,
Rev. Geophys., 49, RG4005, https://doi.org/10.1029/2010RG000348, 2011. a
Meurdesoif, Y.: XIOS 2.0 (Revision 1297), Zenodo [code], https://doi.org/10.5281/zenodo.4905653, 2017. a
Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick,
R. E., Dunn, R. J. H., Osborn, T. J., Jones, P. D., and Simpson, I. R.: An
Updated Assessment of Near-Surface Temperature Change From 1850: The HadCRUT5
Data Set, J. Geophys. Res.-Atmos., 126, e2019JD032361,
https://doi.org/10.1029/2019JD032361, 2021. a, b
Münchow, A. and Melling, H.: Ocean current observations from Nares Strait
to the west of Greenland: Interannual to tidal variability and forcing,
J. Marine Res., 66, 801–833,
https://doi.org/10.1357/002224008788064612, 2008. a
Münchow, A., Melling, H., and Falkner, K. K.: An Observational Estimate of
Volume and Freshwater Flux Leaving the Arctic Ocean through Nares Strait,
J. Phys. Oceanogr., 36, 2025–2041, https://doi.org/10.1175/JPO2962.1,
2006. a
Ollinaho, P., Lock, S.-J., Leutbecher, M., Bechtold, P., Beljaars, A., Bozzo,
A., Forbes, R. M., Haiden, T., Hogan, R. J., and Sandu, I.: Towards
process-level representation of model uncertainties: stochastically perturbed
parametrizations in the ECMWF ensemble, Q. J. Roy.
Meteor. Soc., 143, 408–422, https://doi.org/10.1002/qj.2931,
2017. a, b
Parkinson, C. L. and Washington, W. M.: A large-scale numerical model of sea
ice, J. Geophys. Res.-Oceans, 84, 311–337,
https://doi.org/10.1029/JC084iC01p00311, 1979. a
Petersen, M. R., Jacobsen, D. W., Ringler, T. D., Hecht, M. W., and Maltrud,
M. E.: Evaluation of the arbitrary Lagrangian–Eulerian vertical coordinate
method in the MPAS-Ocean model, Ocean Model., 86, 93–113,
https://doi.org/10.1016/j.ocemod.2014.12.004, 2015. a
Pithan, F., Shepherd, T. G., Zappa, G., and Sandu, I.: Climate model biases in
jet streams, blocking and storm tracks resulting from missing orographic
drag, Geophys. Res. Lett., 43, 7231–7240,
https://doi.org/10.1002/2016GL069551, 2016. a
Platnick, S., Ackerman, S., King, M., Meyer, K., Menzel, W., Holz, R., Baum,
B., and Yang, P.: MODIS atmosphere L2 cloud product (06_L2), NASA MODIS
Adaptive Processing System, Goddard Space Flight Center, https://doi.org/10.5067/MODIS/MOD06_L2.006, 2015. a
Rackow, T. and Juricke, S.: Flow-dependent stochastic coupling for climate
models with high ocean-to-atmosphere resolution ratio, Q. J. Roy. Meteor. Soc., 146, 284–300,
https://doi.org/10.1002/qj.3674, 2020. a
Rackow, T., Goessling, H. F., Jung, T., Sidorenko, D., Semmler, T., Barbi, D.,
and Handorf, D.: Towards multi-resolution global climate modeling with
ECHAM6-FESOM. Part II: climate variability, Clim. Dynam., 50, 2369–2394,
https://doi.org/10.1007/s00382-016-3192-6, 2018. a
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. a, b
Reichler, T. and Kim, J.: How Well Do Coupled Models Simulate Today's Climate?,
B. Am. Meteorol. Soc., 89, 303–312,
https://doi.org/10.1175/BAMS-89-3-303, 2008. a, b
Renault, L., Molemaker, M. J., Gula, J., Masson, S., and McWilliams, J. C.:
Control and Stabilization of the Gulf Stream by Oceanic Current Interaction
with the Atmosphere, J. Phys. Oceanogr., 46, 3439–3453,
https://doi.org/10.1175/JPO-D-16-0115.1, 2016. a
Ridderinkhof, H., van der Werf, P. M., Ullgren, J. E., van Aken, H. M., van
Leeuwen, P. J., and de Ruijter, W. P. M.: Seasonal and interannual
variability in the Mozambique Channel from moored current observations,
J. Geophys. Res.-Oceans, 115, C6,
https://doi.org/10.1029/2009JC005619, 2010. a
Ritchie, H.: Semi-Lagrangian Advection on a Gaussian Grid, Mon. Weather
Rev., 115, 608–619, https://doi.org/10.1175/1520-0493(1987)115<0608:SLAOAG>2.0.CO;2,
1987. a
Ritchie, H., Temperton, C., Simmons, A., Hortal, M., Davies, T., Dent, D., and
Hamrud, M.: Implementation of the Semi-Lagrangian Method in a
High-Resolution Version of the ECMWF Forecast Model, Mon. Weather Rev.,
123, 489–514, https://doi.org/10.1175/1520-0493(1995)123<0489:IOTSLM>2.0.CO;2, 1995. a, b
Roach, A. T., Aagaard, K., Pease, C. H., Salo, S. A., Weingartner, T., Pavlov,
V., and Kulakov, M.: Direct measurements of transport and water properties
through the Bering Strait, J. Geophys. Res.-Oceans, 100,
18443–18457, https://doi.org/10.1029/95JC01673, 1995. a
Robert, A., Henderson, J., and Turnbull, C.: An Implicit Time Integration
Scheme for Baroclinic Models of the Atmosphere, Mon. Weather Rev., 100,
329–335, https://doi.org/10.1175/1520-0493(1972)100<0329:AITISF>2.3.CO;2, 1972. a
Roberts, C. D., Senan, R., Molteni, F., Boussetta, S., Mayer, M., and Keeley, S. P. E.: Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP, Geosci. Model Dev., 11, 3681–3712, https://doi.org/10.5194/gmd-11-3681-2018, 2018. a, b
Saarinen, S., Hamrud, M., Salmond, D., and Hague, J.: Dr. Hook instrumentation
tool, Tech. rep., European Centre for Medium-Range Weather Forecasts, 2005. a
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter
regionalization ofhttps://doi.org/10.1029/2008WR007327, 2010. a
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S.-J., Putman, W. M.,
and Düben, P.: Global Cloud-Resolving Models, Current Climate Change
Reports, 5, 172–184, https://doi.org/10.1007/s40641-019-00131-0, 2019. a
Scafetta, N.: Testing the CMIP6 GCM Simulations versus Surface Temperature
Records from 1980–1990 to 2011–2021: High ECS Is Not Supported, Climate,
9, 161, https://doi.org/10.3390/cli9110161, 2021. a, b
Schauer, U., Beszczynska-Möller, A., Walczowski, W., Fahrbach, E.,
Piechura, J., and Hansen, E.: Variation of Measured Heat Flow Through the
Fram Strait Between 1997 and 2006, pp. 65–85, Springer Netherlands,
Dordrecht, https://doi.org/10.1007/978-1-4020-6774-7_4, 2008. a
Schiemann, R., Demory, M.-E., Shaffrey, L. C., Strachan, J., Vidale, P. L.,
Mizielinski, M. S., Roberts, M. J., Matsueda, M., Wehner, M. F., and Jung,
T.: The Resolution Sensitivity of Northern Hemisphere Blocking in Four 25-km
Atmospheric Global Circulation Models, J. Climate, 30, 337–358,
https://doi.org/10.1175/JCLI-D-16-0100.1, 2017. a
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. a, b
Scholz, P., Sidorenko, D., Danilov, S., Wang, Q., Koldunov, N., Sein, D., and Jung, T.: Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix, Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, 2022a. a
Scholz, P., Sidorenko, D., Gurses, O., Danilov, S., Koldunov, N., Wang, Q., Sein, D., Smolentseva, M., Rakowsky, N., and Jung, T.: FESOM 2.0 AWI-CM3 version 3.0 (AWI-CM3 version 3.0), Zenodo [code], https://doi.org/10.5281/zenodo.6335383, 2022b. a
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. a, b
Semmler, T., Danilov, S., Gierz, P., Goessling, H. F., Hegewald, J., Hinrichs,
C., Koldunov, N., Khosravi, N., Mu, L., Rackow, T., Sein, D. V., Sidorenko,
D., Wang, Q., and Jung, T.: Simulations for CMIP6 With the AWI Climate Model
AWI-CM-1-1, J. Adv. Model. Earth Sy., 12,
e2019MS002009, https://doi.org/10.1029/2019MS002009, 2020. a, b
Sidorenko, D., Rackow, T., Jung, T., Semmler, T., Barbi, D., Danilov, S.,
Dethloff, K., Dorn, W., Fieg, K., Goessling, H. F., Handorf, D., Harig, S.,
Hiller, W., Juricke, S., Losch, M., Schröter, J., Sein, D. V., and Wang,
Q.: Towards multi-resolution global climate modeling with ECHAM6–FESOM. Part
I: model formulation and mean climate, Clim. Dynam., 44, 757–780,
https://doi.org/10.1007/s00382-014-2290-6, 2015. a, b
Sidorenko, D., Goessling, H., Koldunov, N., 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: Preindustrial and HighResMIP
Simulations, J. Adv. Model. Earth Sy., 11, 3794–3815,
https://doi.org/10.1029/2019MS001696, 2019. a, b, c
Sidorenko, D., Danilov, S., Streffing, J., Fofonova, V., Goessling, H. F.,
Scholz, P., Wang, Q., Androsov, A., Cabos, W., Juricke, S., Koldunov, N.,
Rackow, T., Sein, D. V., and Jung, T.: AMOC Variability and Watermass
Transformations in the AWI Climate Model, J. Adv. Model. Earth Sy., 13, e2021MS002582,
https://doi.org/10.1029/2021MS002582, 2021. a, b, c
Smedsrud, L. H., Ingvaldsen, R., Nilsen, J. E. Ø., and Skagseth, Ø.: Heat in the Barents Sea: transport, storage, and surface fluxes, Ocean Sci., 6, 219–234, https://doi.org/10.5194/os-6-219-2010, 2010. a
Steele, M., Morley, R., and Ermold, W.: PHC: A global ocean hydrography with a
high-quality Arctic Ocean, J. Climate, 14, 2079–2087,
https://doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2, 2001. a, b, c
Sterl, A., Bintanja, R., Brodeau, L., Gleeson, E., Koenigk, T., Schmith, T.,
Semmler, T., Severijns, C., Wyser, K., and Yang, S.: A look at the ocean in
the EC-Earth climate model, Clim. Dynam., 39, 2631–2657,
https://doi.org/10.1007/s00382-011-1239-2, 2012. a, b
Storto, A., Masina, S., and Navarra, A.: Evaluation of the CMCC eddy-permitting
global ocean physical reanalysis system (C-GLORS, 1982–2012) and its
assimilation components, Q. J. Roy. Meteorol.
Soc., 142, 738–758, https://doi.org/10.1002/qj.2673, 2016. a
Streffing, J.: AWI-CM3 version 3.0 historic, 4XCO2, 1 % CO2 data, Zenodo [data set], https://doi.org/10.5281/zenodo.6337593, 2022a. a
Streffing, J.: AWI-CM3 version 3.0 pre-industrial control data, Zenodo [data set], https://doi.org/10.5281/zenodo.6337571, 2022b. a
Streffing, J.: AWI-CM3 version 3.0 spinup simulation data, Zenodo [data set], https://doi.org/10.5281/zenodo.6337627, 2022c. a
Streffing, J.: JanStreffing/2020_AWICM3_GMD_PAPER: Revision 1 (1.1), Zenodo [code], https://doi.org/10.5281/zenodo.6653826, 2022d. a
Streffing, J. and Fladich, U.: Modifications to use OpenIFS CY43R3V1 for AWI-CM3 version 3.0, Zenodo [code], https://doi.org/10.5281/zenodo.6335498, 2022. a
Timmermann, R. and Beckmann, A.: Parameterization of vertical mixing in the
Weddell Sea, Ocean Model., 6, 83–100, https://doi.org/10.1016/S1463-5003(02)00061-6,
2004. a
Titchner, H. A. and Rayner, N. A.: The Met Office Hadley Centre sea ice and sea
surface temperature data set, version 2: 1. Sea ice concentrations, J. Geophys. Res.-Atmos., 119, 2864–2889,
https://doi.org/10.1002/2013JD020316, 2014. a
van Haren, R., Haarsma, R. J., Van Oldenborgh, G. J., and Hazeleger, W.:
Resolution Dependence of European Precipitation in a State-of-the-Art
Atmospheric General Circulation Model, J. Climate, 28, 5134–5149,
https://doi.org/10.1175/JCLI-D-14-00279.1, 2015. a
Vignati, E., Wilson, J., and Stier, P.: M7: An efficient size-resolved aerosol
microphysics module for large-scale aerosol transport models, J.
Geophys. Res.-Atmos., 109,
https://doi.org/10.1029/2003JD004485, 2004. a
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A.,
Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P., Nabat,
P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke, S., Beau, I.,
Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes, J., Douville,
H., Ethé, C., Franchistéguy, L., Geoffroy, O., Lévy, C., Madec, G.,
Meurdesoif, Y., Msadek, R., Ribes, A., Sanchez-Gomez, E., Terray, L., and
Waldman, R.: Evaluation of CMIP6 DECK Experiments With CNRM-CM6-1, J.
Adv. Model. Earth Sy., 11, 2177–2213,
https://doi.org/10.1029/2019MS001683, 2019. a
Walsh, J., Chapman, W., Fetterer, F., and Stewart, J.: Gridded monthly sea ice
extent and concentration, 1850 onward, Version 2, Boulder, Colorado USA,
NSIDC: National Snow and Ice Data Center,
https://doi.org/10.7265/jj4s-tq79, 2019. a
Wang, S., Wang, Q., Shu, Q., Scholz, P., Lohmann, G., and Qiao, F.: Improving
the Upper-Ocean Temperature in an Ocean Climate Model (FESOM 1.4): Shortwave
Penetration Versus Mixing Induced by Nonbreaking Surface Waves, J. Adv. Model. Earth Sy., 11, 545–557,
https://doi.org/10.1029/2018MS001494, 2019.
a
Watts, M., Maslowski, W., Lee, Y. J., Kinney, J. C., and Osinski, R.: A Spatial
Evaluation of Arctic Sea Ice and Regional Limitations in CMIP6 Historical
Simulations, J. Climate, 34, 6399–6420,
https://doi.org/10.1175/JCLI-D-20-0491.1, 2021. a
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee, R. B., Smith, G. L.,
and Cooper, J. E.: Clouds and the Earth's Radiant Energy System (CERES): An
Earth Observing System Experiment, B. Am. Meteorol.
Soc., 77, 853–868,
https://doi.org/10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2, 1996. a
Wild, M.: The global energy balance as represented in CMIP6 climate models,
Clim. Dynam., 55, 553–577, 2020. a
Willison, J., Robinson, W. A., and Lackmann, G. M.: North Atlantic Storm-Track
Sensitivity to Warming Increases with Model Resolution, J. Climate,
28, 4513–4524, https://doi.org/10.1175/JCLI-D-14-00715.1, 2015. a
Woodgate, R. A.: Increases in the Pacific inflow to the Arctic from 1990 to
2015, and insights into seasonal trends and driving mechanisms from
year-round Bering Strait mooring data, Prog. Oceanogr., 160,
124–154, https://doi.org/10.1016/j.pocean.2017.12.007, 2018. a
Wyser, K.: EC-Earth community runoff-mapper scheme, Zenodo [code], https://doi.org/10.5281/zenodo.6335474, 2022. a
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description
of floodplain inundation dynamics in a global river routing model, Water
Resour. Res., 47, https://doi.org/10.1029/2010WR009726, 2011. a
Yang, C., Christensen, H. M., Corti, S., von Hardenberg, J., and Davini, P.:
The impact of stochastic physics on the El Niño Southern Oscillation in
the EC-Earth coupled model, Clim. Dynam., 53, 2843–2859,
https://doi.org/10.1007/s00382-019-04660-0, 2019. a
Yepes-Arbós, X., van den Oord, G., Acosta, M. C., and Carver, G. D.: Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study, Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, 2022. a
Zampieri, L., Kauker, F., Fröhle, J., Sumata, H., Hunke, E. C., and Goessling,
H. F.: Impact of Sea-Ice Model Complexity on the Performance of an
Unstructured-Mesh Sea-Ice/Ocean Model under Different Atmospheric Forcings,
J. Adv. Model. Earth Sy., 13, e2020MS002438,
https://doi.org/10.1029/2020MS002438, 2021. a
Zeman, C., Wedi, N. P., Dueben, P. D., Ban, N., and Schär, C.: Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing, Geosci. Model Dev., 14, 4617–4639, https://doi.org/10.5194/gmd-14-4617-2021, 2021. a
Zhang, J. and Rothrock, D. A.: Modeling Global Sea Ice with a Thickness and
Enthalpy Distribution Model in Generalized Curvilinear Coordinates, Mon.
Weather Rev., 131, 845–861,
https://doi.org/10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2, 2003. a
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.
We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly...
