Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7439-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7439-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Concurrent calculation of radiative transfer in the atmospheric simulation in ECHAM-6.3.05p2
Mohammad Reza Heidari
CORRESPONDING AUTHOR
Department of Informatics, Universität Hamburg, Hamburg, Germany
Zhaoyang Song
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, 510275, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 519082, Zhuhai, China
Enrico Degregori
German Climate Computing Center (DKRZ), Hamburg, Germany
Jörg Behrens
German Climate Computing Center (DKRZ), Hamburg, Germany
Hendryk Bockelmann
German Climate Computing Center (DKRZ), Hamburg, Germany
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Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
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
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The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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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.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeor., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a, b
Balaji, V.: The Flexible Modeling System, in: Earth system modelling, edited by: Valcke, S., Redler, R., and Budich, R., Volume 3, Springer briefs in earth system sciences, Springer, Berlin, Germany, 33–41, 2012. a
Balaji, V., Benson, R., Wyman, B., and Held, I.: Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework, Geosci. Model Dev., 9, 3605–3616, https://doi.org/10.5194/gmd-9-3605-2016, 2016. a, b, c, d, e, f, g, h, i, j, k
Bayr, T., Dommenget, D., Martin, T., and Power, S. B.: The eastward shift of
the Walker Circulation in response to global warming and its relationship to
ENSO variability, Clim. Dynam., 43, 2747–2763, 2014. a
Behrens, J., Hanke, M., and Jahns, T.: How to use MPI communication in highly parallel climate simulations more easily and more efficiently, in: EGU General Assembly Conference Abstracts, 27 April–2 May 2014, Vienna, Austria, p. 13569, 2014. a
Cess, R. D., Potter, G., Blanchet, G., Boer, J., Del Genio, A., Déqué, M., Dymnikov, V., Galin, V., Gates, W., Ghan, S., Kiehl, J., Lacis, A., Le Treut, H., Li, Z., Liang, X., McAvaney, B., Meleshko, V., Mitchell, J., Morcrette, J., Randall, D., Rikus, L., Roeckner, E., Royer, J., Schlese, U., Sheinin, D., Slingo, A., Sokolov, A., Taylor, E., Washington, W., Wetherald, R., Yagai, I., and Zhang, M.: Intercomparison and
interpretation of climate feedback processes in 19 atmospheric general
circulation models, J. Geophys. Rese.-Atmos., 95,
16601–16615, 1990. a
Cotronei, A. and Slawig, T.: Single-precision arithmetic in ECHAM radiation reduces runtime and energy consumption, Geosci. Model Dev., 13, 2783–2804, https://doi.org/10.5194/gmd-13-2783-2020, 2020. a, b
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a, b, c
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Giorgetta, M. A., Jungclaus, J. H., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., V., Brovkin, T., Crueger, M., Esch, K., Fieg, K., Glushak, V., Gayler, H., Haak, H., Hollweg, T., Ilyina, S., Kinne, L., Kornblueh, D., Matei, T., Mauritsen, U., Mikolajewicz, W., Mueller, D., Notz, F., Pithan, T., Raddatz, S., Rast, R., Redler, E., Roeckner, H., Schmidt, R., Schnur, J., Segschneider, K., D. Six, M., Stockhause, C., Timmreck, J., Wegner, H.,
Widmann, K. H., Wieners, M., Claussen, J., Marotzke, B., and Stevens, B.:
Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for
the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Syst., 5, 572–597, 2013. a
Guilyardi, E.: El Niño–mean state–seasonal cycle interactions in a
multi-model ensemble, Clim. Dynam., 26, 329–348, 2006. a
Guilyardi, E., Gualdi, S., Slingo, J., Navarra, A., Delécluse, P., Cole,
J., Madec, G., Roberts, M., Latif, M., and Terray, L.: Representing El Nino
in coupled ocean–atmosphere GCMs: the dominant role of the atmospheric
component, J. Climate, 17, 4623–4629, 2004. a
Guilyardi, E., Braconnot, P., Jin, F.-F., Kim, S. T., Kolasinski, M., Li, T.,
and Musat, I.: Atmosphere feedbacks during ENSO in a coupled GCM with a
modified atmospheric convection scheme, J. Climate, 22, 5698–5718,
2009. a
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014. a
Heidari, M. R., Song, Z., and Degregori, E.: Outputs of AMIP experiments using ECHAM-6.3.05p2 with the concurrent radiation scheme, Zenodo [data set], https://doi.org/10.5281/zenodo.4589140, 2021. a
Hogan, R. J. and Bozzo, A.: Mitigating errors in surface temperature forecasts using approximate radiation updates, J. Adv. Model. Earth Syst., 7, 836–853, 2015. a
Hogan, R. J. and Hirahara, S.: Effect of solar zenith angle specification in
models on mean shortwave fluxes and stratospheric temperatures, Geophys.
Res. Lett., 43, 482–488, 2016. a
Jin, F.-F., Kim, S. T., and Bejarano, L.: A coupled-stability index for ENSO,
Geophys. Res. Lett., 33, L23708, https://doi.org/10.1029/2006GL027221, 2006. a
Jones, P. D., Lister, D. H., Osborn, T. J., Harpham, C., Salmon, M., and Morice, C. P.: Hemispheric and large-scale land surface air temperature variations: an extensive revision and an update to 2010, J. Geophys. Res., 117, D05127, https://doi.org/10.1029/2011JD017139, 2012. a
Kidston, J., Renwick, J., and McGregor, J.: Hemispheric-scale seasonality of
the Southern Annular Mode and impacts on the climate of New Zealand, J. Climate, 22, 4759–4770, 2009. a
Loeb, N. G., Lyman, J. M., Johnson, G. C., Allan, R. P., Doelling, D. R., Wong, T., Soden, B. J., and Stephens, G. L.: Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty, Nat. Geosci., 5, 110–113, https://doi.org/10.1038/NGEO1375, 2012. a, b
Mauritsen, T. and Roeckner, E.: Tuning the MPI-ESM1. 2 global climate model to improve the match with instrumental record warming by lowering its climate
sensitivity, J. Adv. Model. Earth Syst., 12,
e2019MS002037, https://doi.org/10.1029/2019MS002037, 2020. a
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S., Fläschner, D., Gayler, V., Giorgetta, M., Goll, D., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T., Jimenéz-de-la-Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S., Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B., Müller, W., Nabel, J., Nam, C., Notz, D., Nyawira, S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M., Raddatz, T., Rast, S., Redler, R., Reick, C., Rohrschneider, T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt, A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the
MPI-M Earth System Model version 1.2 (MPI-ESM1. 2) and its response to
increasing CO2, J. Adv. Model. Earth Syst., 11, 998–1038,
2019. a
McAfee, S. A. and Russell, J. L.: Northern annular mode impact on spring
climate in the western United States, Geophys. Res. Lett., 35, L17701, https://doi.org/10.1029/2008GL034828, 2008. a
Morcrette, J.-J.: On the effects of the temporal and spatial sampling of
radiation fields on the ECMWF forecasts and analyses, Mon. Weather Rev.,
128, 876–887, 2000. a
Morcrette, J.-J., Mozdzynski, G., and Leutbecher, M.: A reduced radiation grid for the ECMWF Integrated Forecasting System, Mon. Weather Rev., 136,
4760–4772, 2008. a
Mozdzynski, G. and Morcrette, J.-J.: Reorganization of the radiation transfer
calculations in the ECMWF IFS, European Centre for Medium-Range Weather Forecasts, https://doi.org/10.21957/pxjpl93ov, 2014. a
MPI-M and DKRZ: Source code of the Max Planck Institute atmospheric general circulation model (ECHAM6) adopted to the project PalMod, World Data Center for Climate (WDCC) at DKRZ [code], https://doi.org/10.35089/WDCC/SC_PalMod_ECHAM6, 2021. a
Neelin, J. D., Battisti, D. S., Hirst, A. C., Jin, F.-F., Wakata, Y., Yamagata, T., and Zebiak, S. E.: ENSO theory, J. Geophys. Res., 103, 14261–14290, 1998. a
Pincus, R. and Stevens, B.: Paths to accuracy for radiation parameterizations
in atmospheric models, J. Adv. Model. Earth Syst., 5, 225–233, 2013. a
Rasp, S.: Statistical methods and machine learning in weather and climate
modeling, PhD thesis, Faculty of Physics, Ludwig-Maximilians-Universität, available at: https://edoc.ub.uni-muenchen.de/23867/1/Rasp_Stephan.pdf (last access: 30 November 2021), 2019. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth system model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, 2013. a, b, c, d, e
Short summary
To improve our understanding of climate system dynamics and their variability, the numerical atmospheric model ECHAM6 is used to simulate a complete glacial cycle over the past 120 000 years. However, performing such simulations takes a long time even on state-of-the-art supercomputers. To accelerate the model simulation, we propose calculating radiative transfer processes in parallel with adiabatic processes in the atmosphere, which reduces the simulation time by nearly half.
To improve our understanding of climate system dynamics and their variability, the numerical...