Articles | Volume 9, issue 9
https://doi.org/10.5194/gmd-9-3393-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-3393-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19
David Leutwyler
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich,
Switzerland
Oliver Fuhrer
Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich,
Switzerland
Xavier Lapillonne
Center for Climate Systems Modeling C2SM, ETH Zurich, Zurich, Switzerland
Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich,
Switzerland
Daniel Lüthi
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich,
Switzerland
Christoph Schär
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich,
Switzerland
Related authors
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
EGUsphere, https://doi.org/10.5194/egusphere-2023-2263, https://doi.org/10.5194/egusphere-2023-2263, 2023
Short summary
Short summary
We investigate the effects of reduced precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced precision implementations of their model.
Stefan Rüdisühli, Michael Sprenger, David Leutwyler, Christoph Schär, and Heini Wernli
Weather Clim. Dynam., 1, 675–699, https://doi.org/10.5194/wcd-1-675-2020, https://doi.org/10.5194/wcd-1-675-2020, 2020
Short summary
Short summary
Most precipitation over Europe is linked to low-pressure systems, cold fronts, warm fronts, or high-pressure systems. Based on a massive computer simulation able to resolve thunderstorms, we quantify in detail how much precipitation these weather systems produced during 2000–2008. We find distinct seasonal and regional differences, such as fronts precipitating a lot in fall and winter over the North Atlantic but high-pressure systems mostly in summer over the continent by way of thunderstorms.
Oliver Fuhrer, Tarun Chadha, Torsten Hoefler, Grzegorz Kwasniewski, Xavier Lapillonne, David Leutwyler, Daniel Lüthi, Carlos Osuna, Christoph Schär, Thomas C. Schulthess, and Hannes Vogt
Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, https://doi.org/10.5194/gmd-11-1665-2018, 2018
Short summary
Short summary
The best hope for reducing long-standing uncertainties in climate projections is through increasing the horizontal resolution of climate models to the kilometer scale. We establish a baseline of what it would take to do such simulations using an atmospheric model that has been adapted to run on a supercomputer accelerated with graphics processing units. To our knowledge this represents the first production-ready atmospheric model being run entirely on accelerators on this scale.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
EGUsphere, https://doi.org/10.5194/egusphere-2023-2263, https://doi.org/10.5194/egusphere-2023-2263, 2023
Short summary
Short summary
We investigate the effects of reduced precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced precision implementations of their model.
Ruoyi Cui, Nikolina Ban, Marie-Estelle Demory, Raffael Aellig, Oliver Fuhrer, Jonas Jucker, Xavier Lapillonne, and Christoph Schär
Weather Clim. Dynam., 4, 905–926, https://doi.org/10.5194/wcd-4-905-2023, https://doi.org/10.5194/wcd-4-905-2023, 2023
Short summary
Short summary
Our study focuses on severe convective storms that occur over the Alpine-Adriatic region. By running simulations for eight real cases and evaluating them against available observations, we found our models did a good job of simulating total precipitation, hail, and lightning. Overall, this research identified important meteorological factors for hail and lightning, and the results indicate that both HAILCAST and LPI diagnostics are promising candidates for future climate research.
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, Veronique Bouchet, 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, Detlef Stammer, 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 Discuss., https://doi.org/10.5194/essd-2023-376, https://doi.org/10.5194/essd-2023-376, 2023
Revised manuscript accepted for ESSD
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 are proposed as international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Johann Dahm, Eddie Davis, Florian Deconinck, Oliver Elbert, Rhea George, Jeremy McGibbon, Tobias Wicky, Elynn Wu, Christopher Kung, Tal Ben-Nun, Lucas Harris, Linus Groner, and Oliver Fuhrer
Geosci. Model Dev., 16, 2719–2736, https://doi.org/10.5194/gmd-16-2719-2023, https://doi.org/10.5194/gmd-16-2719-2023, 2023
Short summary
Short summary
It is hard for scientists to write code which is efficient on different kinds of supercomputers. Python is popular for its user-friendliness. We converted a Fortran code, simulating Earth's atmosphere, into Python. This new code auto-converts to a faster language for processors or graphic cards. Our code runs 3.5–4 times faster on graphic cards than the original on processors in a specific supercomputer system.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
Short summary
Short summary
Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Roman Brogli, Christoph Heim, Jonas Mensch, Silje Lund Sørland, and Christoph Schär
Geosci. Model Dev., 16, 907–926, https://doi.org/10.5194/gmd-16-907-2023, https://doi.org/10.5194/gmd-16-907-2023, 2023
Short summary
Short summary
The pseudo-global-warming (PGW) approach is a downscaling methodology that imposes the large-scale GCM-based climate change signal on the boundary conditions of a regional climate simulation. It offers several benefits in comparison to conventional downscaling. We present a detailed description of the methodology, provide companion software to facilitate the preparation of PGW simulations, and present validation and sensitivity studies.
Qinggang Gao, Christian Zeman, Jesus Vergara-Temprado, Daniela C. A. Lima, Peter Molnar, and Christoph Schär
Weather Clim. Dynam., 4, 189–211, https://doi.org/10.5194/wcd-4-189-2023, https://doi.org/10.5194/wcd-4-189-2023, 2023
Short summary
Short summary
We developed a vortex identification algorithm for realistic atmospheric simulations. The algorithm enabled us to obtain a climatology of vortex shedding from Madeira Island for a 10-year simulation period. This first objective climatological analysis of vortex streets shows consistency with observed atmospheric conditions. The analysis shows a pronounced annual cycle with an increasing vortex shedding rate from April to August and a sudden decrease in September.
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, https://doi.org/10.5194/gmd-15-6985-2022, 2022
Short summary
Short summary
This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
Christian R. Steger, Benjamin Steger, and Christoph Schär
Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022, https://doi.org/10.5194/gmd-15-6817-2022, 2022
Short summary
Short summary
Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.
Christian Zeman and Christoph Schär
Geosci. Model Dev., 15, 3183–3203, https://doi.org/10.5194/gmd-15-3183-2022, https://doi.org/10.5194/gmd-15-3183-2022, 2022
Short summary
Short summary
Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.
Roman Brogli, Silje Lund Sørland, Nico Kröner, and Christoph Schär
Weather Clim. Dynam., 2, 1093–1110, https://doi.org/10.5194/wcd-2-1093-2021, https://doi.org/10.5194/wcd-2-1093-2021, 2021
Short summary
Short summary
In a warmer future climate, climate simulations predict that some land areas will experience excessive warming during summer. We show that the excessive summer warming is related to the vertical distribution of warming within the atmosphere. In regions characterized by excessive warming, much of the warming occurs close to the surface. In other regions, most of the warming is redistributed to higher levels in the atmosphere, which weakens the surface warming.
Daniel Regenass, Linda Schlemmer, Elena Jahr, and Christoph Schär
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-426, https://doi.org/10.5194/hess-2021-426, 2021
Manuscript not accepted for further review
Short summary
Short summary
Weather and climate models need to represent the water cycle on land in order to provide accurate estimates of moisture and energy exchange between the land and the atmosphere. Infiltration of water into the soil is often modeled with an equation describing water transport in porous media. Here, we point out some challenges arising in the numerical solution of this equation and show the consequences for the representation of the water cycle in modern weather and climate models.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Panitz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev., 14, 5125–5154, https://doi.org/10.5194/gmd-14-5125-2021, https://doi.org/10.5194/gmd-14-5125-2021, 2021
Short summary
Short summary
We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia, and Africa. How the model configuration, horizontal and vertical resolutions, and choice of driving data influence the model results for the five domains is assessed, with the purpose of aiding the planning and design of regional climate simulations in the future.
Christian Zeman, Nils P. Wedi, Peter D. Dueben, Nikolina Ban, and Christoph Schär
Geosci. Model Dev., 14, 4617–4639, https://doi.org/10.5194/gmd-14-4617-2021, https://doi.org/10.5194/gmd-14-4617-2021, 2021
Short summary
Short summary
Kilometer-scale atmospheric models allow us to partially resolve thunderstorms and thus improve their representation. We present an intercomparison between two distinct atmospheric models for 2 summer days with heavy thunderstorms over Europe. We show the dependence of precipitation and vertical wind speed on spatial and temporal resolution and also discuss the possible influence of the system of equations, numerical methods, and diffusion in the models.
Jeremy McGibbon, Noah D. Brenowitz, Mark Cheeseman, Spencer K. Clark, Johann P. S. Dahm, Eddie C. Davis, Oliver D. Elbert, Rhea C. George, Lucas M. Harris, Brian Henn, Anna Kwa, W. Andre Perkins, Oliver Watt-Meyer, Tobias F. Wicky, Christopher S. Bretherton, and Oliver Fuhrer
Geosci. Model Dev., 14, 4401–4409, https://doi.org/10.5194/gmd-14-4401-2021, https://doi.org/10.5194/gmd-14-4401-2021, 2021
Short summary
Short summary
FV3GFS is a weather and climate model written in Fortran. It uses Fortran so that it can run fast, but this makes it hard to add features if you do not (or even if you do) know Fortran. We have written a Python interface to FV3GFS that lets you import the Fortran model as a Python package. We show examples of how this is used to write
modelscripts, which reproduce or build on what the Fortran model can do. You could do this same wrapping for any compiled model, not just FV3GFS.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
Short summary
Short summary
Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
Stefan Rüdisühli, Michael Sprenger, David Leutwyler, Christoph Schär, and Heini Wernli
Weather Clim. Dynam., 1, 675–699, https://doi.org/10.5194/wcd-1-675-2020, https://doi.org/10.5194/wcd-1-675-2020, 2020
Short summary
Short summary
Most precipitation over Europe is linked to low-pressure systems, cold fronts, warm fronts, or high-pressure systems. Based on a massive computer simulation able to resolve thunderstorms, we quantify in detail how much precipitation these weather systems produced during 2000–2008. We find distinct seasonal and regional differences, such as fronts precipitating a lot in fall and winter over the North Atlantic but high-pressure systems mostly in summer over the continent by way of thunderstorms.
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, https://doi.org/10.5194/gmd-12-4425-2019, 2019
Short summary
Short summary
This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.
Dominik Brunner, Gerrit Kuhlmann, Julia Marshall, Valentin Clément, Oliver Fuhrer, Grégoire Broquet, Armin Löscher, and Yasjka Meijer
Atmos. Chem. Phys., 19, 4541–4559, https://doi.org/10.5194/acp-19-4541-2019, https://doi.org/10.5194/acp-19-4541-2019, 2019
Short summary
Short summary
Atmospheric transport models are increasingly being used to estimate CO2 emissions from atmospheric CO2 measurements. This study demonstrates the importance of distributing CO2 emissions vertically in the model according to realistic profiles, since a major proportion of CO2 is emitted through tall stacks from power plants and industrial sources. With the traditional approach of emitting all CO2 at the surface, models may significantly overestimate the atmospheric CO2 levels.
Samuel Monhart, Massimiliano Zappa, Christoph Spirig, Christoph Schär, and Konrad Bogner
Hydrol. Earth Syst. Sci., 23, 493–513, https://doi.org/10.5194/hess-23-493-2019, https://doi.org/10.5194/hess-23-493-2019, 2019
Short summary
Short summary
Subseasonal streamflow forecasts have received increasing attention during the past decade, but their performance in alpine catchments is still largely unknown. We analyse the effect of a statistical correction technique applied to the driving meteorological forecasts on the performance of the resulting streamflow forecasts. The study shows the benefits of such hydrometeorological ensemble prediction systems and highlights the importance of snow-related processes for subseasonal predictions.
Stefan Brönnimann, Jan Rajczak, Erich M. Fischer, Christoph C. Raible, Marco Rohrer, and Christoph Schär
Nat. Hazards Earth Syst. Sci., 18, 2047–2056, https://doi.org/10.5194/nhess-18-2047-2018, https://doi.org/10.5194/nhess-18-2047-2018, 2018
Short summary
Short summary
Heavy precipitation events in Switzerland are expected to become more intense, but the seasonality also changes. Analysing a large set of model simulations, we find that annual maximum rainfall events become less frequent in late summer and more frequent in early summer and early autumn. The seasonality shift is arguably related to summer drying. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events.
Erik Kjellström, Grigory Nikulin, Gustav Strandberg, Ole Bøssing Christensen, Daniela Jacob, Klaus Keuler, Geert Lenderink, Erik van Meijgaard, Christoph Schär, Samuel Somot, Silje Lund Sørland, Claas Teichmann, and Robert Vautard
Earth Syst. Dynam., 9, 459–478, https://doi.org/10.5194/esd-9-459-2018, https://doi.org/10.5194/esd-9-459-2018, 2018
Short summary
Short summary
Based on high-resolution regional climate models we investigate European climate change at 1.5 and 2 °C of global warming compared to pre-industrial levels. Considerable near-surface warming exceeding that of the global mean is found for most of Europe, already at the lower 1.5 °C of warming level. Changes in precipitation and near-surface wind speed are identified. The 1.5 °C of warming level shows significantly less change compared to the 2 °C level, indicating the importance of mitigation.
Oliver Fuhrer, Tarun Chadha, Torsten Hoefler, Grzegorz Kwasniewski, Xavier Lapillonne, David Leutwyler, Daniel Lüthi, Carlos Osuna, Christoph Schär, Thomas C. Schulthess, and Hannes Vogt
Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, https://doi.org/10.5194/gmd-11-1665-2018, 2018
Short summary
Short summary
The best hope for reducing long-standing uncertainties in climate projections is through increasing the horizontal resolution of climate models to the kilometer scale. We establish a baseline of what it would take to do such simulations using an atmospheric model that has been adapted to run on a supercomputer accelerated with graphics processing units. To our knowledge this represents the first production-ready atmospheric model being run entirely on accelerators on this scale.
Michael Keller, Nico Kröner, Oliver Fuhrer, Daniel Lüthi, Juerg Schmidli, Martin Stengel, Reto Stöckli, and Christoph Schär
Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, https://doi.org/10.5194/acp-18-5253-2018, 2018
Short summary
Short summary
Deep convection is often associated with thunderstorms and heavy rain events. In this study, the sensitivity of Alpine deep convective events to environmental parameters and climate warming is investigated. To this end, simulations are conducted at resolutions of 12 and 2 km. The results show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences are found in terms of the radiative feedbacks.
Prisco Frei, Sven Kotlarski, Mark A. Liniger, and Christoph Schär
The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, https://doi.org/10.5194/tc-12-1-2018, 2018
Short summary
Short summary
Snowfall is central to Alpine environments, and its future changes will be associated with pronounced impacts. We here assess future snowfall changes in the European Alps based on an ensemble of state-of-the-art regional climate model experiments and on two different greenhouse gas emission scenarios. The results reveal pronounced changes in the Alpine snowfall climate with considerable snowfall reductions at low and mid-elevations but also snowfall increases at high elevations in midwinter.
Martin Wild, Atsumu Ohmura, Christoph Schär, Guido Müller, Doris Folini, Matthias Schwarz, Maria Zyta Hakuba, and Arturo Sanchez-Lorenzo
Earth Syst. Sci. Data, 9, 601–613, https://doi.org/10.5194/essd-9-601-2017, https://doi.org/10.5194/essd-9-601-2017, 2017
Short summary
Short summary
The Global Energy Balance Archive (GEBA) is a database for the central storage of worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 database, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and to date contains around 500 000 monthly mean entries from 2500 locations.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
Related subject area
Climate and Earth system modeling
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
The Regional Climate-Chemistry-Ecology Coupling Model RegCM-Chem (v4.6)-YIBs (v1.0): Development and Application
Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections
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.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
Short summary
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary
Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
Short summary
Short summary
We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
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.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
Short summary
Short summary
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
Short summary
Short summary
The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
Short summary
Short summary
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
Short summary
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
Short summary
Short summary
By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
Short summary
Short summary
We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
Short summary
Short summary
Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
Short summary
Short summary
We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
Short summary
Short summary
We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
Short summary
Short summary
Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
Short summary
Short summary
This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
Short summary
Short summary
This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
Short summary
Short summary
The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
Short summary
Short summary
The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
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.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
Short summary
Short summary
Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
Short summary
Short summary
This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
Short summary
Short summary
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
Short summary
Short summary
The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
Short summary
Short summary
We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
Short summary
Short summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
Short summary
Short summary
This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Short summary
Short summary
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
Short summary
Short summary
Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
Short summary
Short summary
For the first time, we coupled a regional climate chemistry model RegCM-Chem with a dynamic vegetation model YIBs to create a regional climate-chemistry-ecology model RegCM-Chem-YIBs. We applied it to simulate climatic, chemical and ecological parameters in East Asia and fully validated it on a variety of observational data. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
Short summary
Short summary
We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Cited articles
Attema, J. J., Loriaux, J. M., and Lenderink, G.: Extreme precipitation response to climate perturbations in an atmospheric mesoscale model, Environ. Res. Lett., 9, 014003, https://doi.org/10.1088/1748-9326/9/1/014003, 2014.
Baldauf, M., Seifert, A., Foerstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905, 2011.
Ban, N., Schmidli, J., and Schär, C.: Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations, J. Geophys. Res.-Atmos., 119, 7889–7907, https://doi.org/10.1002/2014JD021478, 2014.
Ban, N., Schmidli, J., and Schär, C.: Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?, Geophys. Res. Lett., 42, 1165–1172, https://doi.org/10.1002/2014GL062588, 2015.
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015.
Bellprat, O., Kotlarski, S., Lüthi, D., De Elia, R., Frigon, A. Laprise, R., and Schär, C.: Objective Calibration of Regional Climate Models: Application over Europe and North America, J. Climate, 29, 819–838, https://doi.org/10.1175/JCLI-D-15-0302.1, 2016.
Benoit, R., Schär, C., Binder, P., Chamberland, S., Davies, H. C., Desgagne, M., Girard, C., Keil, C., Kouwen, N., Luthi, D., Maric, D., Muller, E., Pellerin, P., Schmidli, J., Schubiger, F., Schwierz, C., Sprenger, M., Walser, A., Willemse, S., Yu, W., and Zala, E.: The real-time ultrafinescale forecast support during the special observing period of the MAP, B. Am. Meteorol. Soc., 83, 85–10, https://doi.org/10.1175/1520-0477(2002)083<0085:TRTUFS>2.3.CO;2, 2002.
Bianco, M.: An interface for halo exchange pattern, 2012.
Boing, S. J., Jonker, H. J. J., Siebesma, A. P., and Grabowski, W. W.: Influence of the Subcloud Layer on the Development of a Deep Convective Ensemble, J. Atmos. Sci., 69, 2682–2698, https://doi.org/10.1175/JAS-D-11-0317.1, 2012.
Bony, S., Stevens, B., , Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus, R., Shepherd, T. G., Sherwood, S. C., Siebesma, P., Sobel, A. H., Watanabe, M., and Webb, M. J.: Clouds, circulation and climate sensitivity, Nature, 8, 261–268, https://doi.org/10.1038/ngeo2398, 2015.
Bott, A.: A positive definite advection scheme obtained by nonlinear renormalization of the advective fluxes., Mon. Weather Rev., 117, 1006–1015, https://doi.org/10.1175/1520-0493(1989)117<1006:APDASO>2.0.CO;2, 1989.
Bretherton, C. S. and Khairoutdinov, M. F.: Convective self-aggregation feedbacks in near-global cloud-resolving simulations of an aquaplanet, J. Adv. Model Earth Sy., 7, 1765–1787, https://doi.org/10.1002/2015MS000499, 2015.
Brisson, E., Demuzere, M., and van Lipzig, N. P.: Modelling strategies for performing convection-permitting climate simulations, Meteorol. Z., 25, 149–163, https://doi.org/10.1127/metz/2015/0598, 2016.
Bryan, G., Wyngaard, J., and Fritsch, J.: Resolution Requirements for the Simulation of Deep Moist Convection, Mon. Weather Rev., 131, 2394–2416, https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2, 2003.
Bryan, G. H. and Morrison, H.: Sensitivity of a Simulated Squall Line to Horizontal Resolution and Parameterization of Microphysics, Mon. Weather Rev., 140, 202–225, https://doi.org/10.1175/MWR-D-11-00046.1, 2012.
Christen, M., Schenk, O., Messmer, P., Neufeld, E., and Burkhart, H.: Accelerating Stencil-Based Computations by Increased Temporal Locality on Modern Multi- and Many-Core Architectures, in: First International Workshop on New Frontiers in High-performance and Hardware-aware Computing (HipHaC'08) held in conjunction with the 41st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-41), 8 November 2008, Lake Como, Italy, 2008.
Clark, P., Roberts, N., Lean, H., Ballard, S. P., and Charlton-Perez, C.: Convection-permitting models: a step-change in rainfall forecasting, Meteorol. Appl., 23, 165–181, https://doi.org/10.1002/met.1538, 2016.
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.
Deest, G., Estibals, N., Yuki, T., Derrien, S., and Rajopadhye, S.: Towards Scalable and Efficient FPGA Stencil Accelerators, in: 6th International Workshop on Polyhedral Compilation Techniques (IMPACT'16), held with HIPEAC'16, Proceedings of the IMPACT series, available at: http://impact.gforge.inria.fr/ (last access: 16 September 2016), Prague, Czech Republic, 2016.
Demeshko, I., Maruyama, N., Tomita, H., and Satoshi, M.: Multi-GPU Implementation of the NICAM Atmospheric Model, in: Euro-Par 2012: Parallel Processing Workshops, edited by: Caragiannis, I., Alexander, M., Badia, R., Cannataro, M., Costan, A., Danelutto, M., Desprez, F., Krammer, B., Sahuquillo, J., Scott, S., and Weidendorfer, J., vol. 7640 of Lecture Notes in Computer Science, Springer, 175–184, 2013.
Dione, C., Lothon, M., Badiane, D., Campistron, B., Couvreux, F., Guichard, F., and Sall, S. M.: Phenomenology of Sahelian convection observed in Niamey during the early monsoon, Q. J. Roy. Meteor. Soc., 140, 500–516, https://doi.org/10.1002/qj.2149, 2014.
Donofrio, D., Oliker, L., Shalf, J., Wehner, M. F., Rowen, C., Krueger, J., Kamil, S., and Mohiyuddin, M.: Energy-efficient computing for extreme-scale science, Computer, 42, 62–71, 2009.
Düben, P. D., Joven, J., Lingamneni, A., McNamara, H., De Micheli, G., Palem, K. V., and Palmer, T. N.: On the use of inexact, pruned hardware in atmospheric modelling, Philos. T. Roy. Soc. A, 372, https://doi.org/10.1098/rsta.2013.0276, 2014.
Fink, A. H., Brücher, T., Ermert, V., Krüger, A., and Pinto, J. G.: The European storm Kyrill in January 2007: synoptic evolution, meteorological impacts and some considerations with respect to climate change, Nat. Hazards Earth Syst. Sci., 9, 405–423, https://doi.org/10.5194/nhess-9-405-2009, 2009.
Förstner, J. and Doms, G.: Runge-Kutta time integration and high-order spatial discretization of advection – A new dynamical core for the LMK, COSMO, 168–176, 2004.
Fuhrer, O., Osuna, C., Lapillonne, X., Gysi, T., Cumming, B., Arteaga, A., and Schulthess, T. C.: Towards a performance portable, architecture agnostic implementation strategy for weather and climate models, Supercomp. Front. Innov., 1, https://doi.org/10.14529/jsfi140103, 2014.
Govett, M., Middlecoff, J., and Henderson, T.: Directive-Based Parallelization of the NIM Weather Model for GPUs, in: Accelerator Programming using Directives (WACCPD), 2014 First Workshop, 55–61, https://doi.org/10.1109/WACCPD.2014.9, 2014.
Grabowski, W., Bechtold, P., Cheng, A., Forbes, R., Halliwell, C., Khairoutdinov, M., Lang, S., Nasuno, T., Petch, J., Tao, W., Wong, R., Wu, X., and Xu, K.: Daytime convective development over land: A model intercomparison based on LBA observations, Q. J. Roy. Meteor. Soc., 132, 317–344, https://doi.org/10.1256/qj.04.147, 2006.
Gysi, T., Osuna, C., Fuhrer, O., Bianco, M., and Schulthess, T. C.: STELLA: A Domain-specific Tool for Structured Grid Methods in Weather and Climate Models, in: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC '15, 41:1–41:12, https://doi.org/10.1145/2807591.2807627, 2015.
Gysi, T., Baer, J., and Hoefler, T.: dCUDA: Hardware Supported Overlap of Computation and Communication, The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), accepted, 2016.
Haylock, M., Hofstra, N., Klein Tank, A., Klok, E., Jones, P., and New, M.: A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008.
Heise, E., Ritter, B., and Schrodin, R.: Operational implementation of the multilayer soil model, COSMO Tech. Rep., No. 9, Tech. rep., COSMO, 2006.
Henderson, T., Middlecoff, J., Rosinski, J., Govett, M., and Madden, P.: Experience Applying Fortran GPU Compilers to Numerical Weather Prediction, in: Proceedings of the 2011 Symposium on Application Accelerators in High-Performance Computing, SAAHPC '11, IEEE Computer Society, Washington, DC, USA, 34–41, https://doi.org/10.1109/SAAHPC.2011.9, 2011.
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European high-resolution gridded data set of daily precipitation and surface temperature, J. Geophys. Res.-Atmos., 114, D21, https://doi.org/10.1029/2009JD011799, 2009.
Hohenegger, C., Brockhaus, P., Bretherton, C. S., and Schär, C.: The Soil Moisture-Precipitation Feedback in Simulations with Explicit and Parameterized Convection, J. Climate, 22, 5003–5020, https://doi.org/10.1175/2009JCLI2604.1, 2009.
Houze, R.: Cloud Dynamics, Elsevier Science, 2014.
Isotta, F. A., Vogel, R., and Frei, C.: Evaluation of European regional reanalyses and downscalings for precipitation in the Alpine region, Meteorol. Z., 24, 15–37, https://doi.org/10.1127/metz/2014/0584, 2015.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014.
Jorgensen, D. P., Pu, Z., Persson, P. O. G., and Tao, W.-K.: Variations Associated with Cores and Gaps of a Pacific Narrow Cold Frontal Rainband, Mon. Weather Rev., 131, 2705–2729, https://doi.org/10.1175/1520-0493(2003)131<2705:VAWCAG>2.0.CO;2, 2003.
Keil, C.and Tafferner, A. and Reinhardt, T.: Synthetic satellite imagery in the Lokal-Modell, Atmos. Res., 82, 19–25, https://doi.org/10.1016/j.atmosres.2005.01.008, 2006.
Kendon, E. J., Roberts, N. M., Senior, C. A., and Roberts, M. J.: Realism of Rainfall in a Very High-Resolution Regional Climate Model, J. Climate, 25, 5791–5806, https://doi.org/10.1175/JCLI-D-11-00562.1, 2012.
Kendon, E. J., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan, S. C., and Senior, C. A.: Heavier summer downpours with climate change revealed by weather forecast resolution model, Nat. Clim. Change, 4, 570–576, https://doi.org/10.1038/NCLIMATE2258, 2014.
Khairoutdinov, M. and Randall, D.: High-resolution simulation of shallow-to-deep convection transition over land, J. Atmos. Sci, 63, 3421–3436, https://doi.org/10.1175/JAS3810.1, 2006.
Knote, C., Heinemann, G., and Rockel, B.: Changes in weather extremes: Assessment of return values using high resolution climate simulations at convection-resolving scale, Meteorol. Z., 19, 11–23, https://doi.org/10.1127/0941-2948/2010/0424, 2010.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Langhans, W., Schmidli, J., and Schär, C.: Bulk Convergence of Cloud-Resolving Simulations of Moist Convection over Complex Terrain, J. Atmos. Sci., 69, 2207–2228, 2012.
Lapillonne, X. and Fuhrer, O.: Using Compiler Directives to Port Large Scientific Applications to GPUs: An Example from Atmospheric Science, Parallel Process. Lett., 24, 1450003, https://doi.org/10.1142/S0129626414500030, 2014.
Lean, H. W., Clark, P. A., Dixon, M., Roberts, N. M., Fitch, A., Forbes, R., and Halliwell, C.: Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom, Mon. Weather Rev., 136, 3408–3424, https://doi.org/10.1175/2008MWR2332.1, 2008.
Leduc, M. and Laprise, R.: Regional climate model sensitivity to domain size, Clim. Dynam., 32, 833–854, https://doi.org/10.1007/s00382-008-0400-z, 2009.
Leutwyler, D., Fuhrer, O., Lapillonne, X., Lüthi, D., and Schär, C.: Convection-Resolving Simulations of Winter strom Kyrill, https://doi.org/10.3929/ethz-a-010483662, available at: https://vimeo.com/136588266 (last access: 1 March 2016), 2015a.
Leutwyler, D., Fuhrer, O., Lapillonne, X., Lüthi, D., and Schär, C.: Diurnal Cycle of Convection, https://doi.org/10.3929/ethz-a-010483656, available at: http://vimeo.com/136588806 (last access: 1 March 2016), 2015b.
Leutwyler, D., Fuhrer, O., Lapillonne, X., Lüthi, D., and Schär, C.: Cold Pools in a Convection-Resolving Model, https://doi.org/10.3929/ethz-a-010619320, 2016.
Little, J. D. C.: A Proof for the Queuing Formula: L = lambda*W, Oper. Res., 9, 383–387, https://doi.org/10.1287/opre.9.3.383, 1961.
Lothon, M., Campistron, B., Chong, M., Couvreux, F., Guichard, F., Rio, C., and Williams, E.: Life Cycle of a Mesoscale Circular Gust Front Observed by a C-Band Doppler Radar in West Africa, Mon. Weather Rev., 139, 1370–1388, https://doi.org/10.1175/2010MWR3480.1, 2011.
Ludwig, P., Pinto, J. G., Hoepp, S. A., Fink, A. H., and Gray, S. L.: Secondary Cyclogenesis along an Occluded Front Leading to Damaging Wind Gusts: Windstorm Kyrill, January 2007, Mon. Weather Rev., 143, 1417–1437, https://doi.org/10.1175/MWR-D-14-00304.1, 2015.
Mass, C., Ovens, D., Westrick, K., and Colle, B.: Does Increasing Horizontal Resolution Produce More Skillful Forecasts?, B. Am. Meteorol. Soc., 83, 407–430, https://doi.org/10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2, 2002.
McInnes, H., Kristiansen, J., Kristjansson, J. E., and Schyberg, H.: The role of horizontal resolution for polar low simulations, Q. J. Roy. Meteor. Soc., 137, 1674–1687, https://doi.org/10.1002/qj.849, 2011.
Mellor, G. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Michalakes, J. and Vachharajani, M.: GPU acceleration of numerical weather prediction, in: Parallel and Distributed Processing, 2008. IPDPS 2008, IEEE International Symposium, 1–7, https://doi.org/10.1109/IPDPS.2008.4536351, 2008.
Mielikainen, J., Huang, B., Huang, H. A., and Goldberg, M.: Improved GPU/CUDA Based Parallel Weather and Research Forecast (WRF) Single Moment 5-Class (WSM5) Cloud Microphysics, IEEE J. Selel. Top. Appl., 5, 1256–1265, 2012.
Miura, H., Satoh, M., Nasuno, T., Noda, A. T., and Oouchi, K.: A Madden-Julian Oscillation Event Realistically Simulated by a Global Cloud-Resolving Model, Science, 318, 1763–1765, https://doi.org/10.1126/science.1148443, 2007.
Miyamoto, Y., Kajikawa, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita, H.: Deep moist atmospheric convection in a subkilometer global simulation, Geophys. Res. Lett., 40, 4922–4926, https://doi.org/10.1002/grl.50944, 2013.
MPI Forum: MPI: A Message-Passing Interface Standard, Version 3.1, available at: http://www.mpi-forum.org (last access: August 2016), 2015.
OpenACC: The OpenACC Application Programing Interface, 2011, available at: http://www.openacc-standard.org/ (last access: 10 July 2015), 2011.
Owens, J., Houston, M., Luebke, D., Green, S., Stone, J., and Phillips, J.: GPU Computing, Proc. IEEE, 96, 879–899, https://doi.org/10.1109/JPROC.2008.917757, 2008.
Palmer, T.: Build high-resolution global climate models, Nature, 515, 338–339, 2014.
Panitz, H.-J., Dosio, A., Büchner, M., Lüthi, D., and Keuler, K.: COSMO-CLM (CCLM) climate simulations over CORDEX-Africa domain: analysis of the ERA-Interim driven simulations at 0.44° and 0.2° resolution, Clim. Dynam., 42, 3015–3038, https://doi.org/10.1007/s00382-013-1834-5, 2014.
Prein, A. F. and Gobiet, A.: Impacts of uncertainties in European gridded precipitation observations on regional climate analysis, Int. J. Climatol., https://doi.org/10.1002/joc.4706, online first, 2016.
Prein, A. F., Gobiet, A., Suklitsch, M., Truhetz, H., Awan, N. K., Keuler, K., and Georgievski, G.: Added value of convection permitting seasonal simulations, Clim. Dynam., 41, 2655–2677, https://doi.org/10.1007/s00382-013-1744-6, 2013.
Randall, D., Khairoutdinov, M., Arakawa, A., and Grabowski, W.: Breaking the cloud parameterization deadlock, B. Am. Meteorol. Soc., 84, 1547+, https://doi.org/10.1175/BAMS-84-11-1547, 2003.
Raschendorfer, M.: The new turbulence parameterization of LM, COSMO, 90–98, 2001.
Rebetez, M., Dupont, O., and Giroud, M.: An analysis of the July 2006 heatwave extent in Europe compared to the record year of 2003, Theor. Appl. Climatol., 95, 1–7, https://doi.org/10.1007/s00704-007-0370-9, 2009.
Reinhardt, T. and Seifert, A.: A three-category ice-scheme for LMK, COSMO, 115–120, 2005.
Richard, E., Buzzi, A., and Zängl, G.: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme, Q. J. Roy. Meteor. Soc., 133, 831–846, https://doi.org/10.1002/qj.65, 2007.
Ritter, B. and Geleyn, J. F.: A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, 303–325, 1992.
Schalkwijk, J., Jonker, H. J. J., Siebesma, A. P., and Van Meijgaard, E.: Weather Forecasting Using GPU-Based Large-Eddy Simulations, B. Am. Meteorol. Soc., 96, 715–724, https://doi.org/10.1175/BAMS-D-14-00114.1, 2015.
Schlemmer, L. and Hohenegger, C.: The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics, J. Atmos Sci., 71, 2842–2858, https://doi.org/10.1175/JAS-D-13-0170.1, 2014.
Schneider, W. and Bott, A.: On the time-splitting errors of one-dimensional advection schemes in numerical weather prediction models; a comparative study, Q. J. Roy. Meteor. Soc., 140, 2321–2329, https://doi.org/10.1002/qj.2301, 2014.
Schulthess, T. C.: Programming revisited, Nature Phys., 11, 369–373, https://doi.org/10.1038/nphys3294, 2015.
Shimokawabe, T., Aoki, T., Muroi, C., Ishida, J., Kawano, K., Endo, T., Nukada, A., Maruyama, N., and Matsuoka, S.: An 80-Fold Speedup, 15.0 TFlops Full GPU Acceleration of Non-Hydrostatic Weather Model ASUCA Production Code, in: 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 11 pp., 2010.
Skamarock, W. C., Park, S.-H., Klemp, J. B., and Snyder, C.: Atmospheric Kinetic Energy Spectra from Global High-Resolution Nonhydrostatic Simulations, J. Atmos. Sci., 71, 4369–4381, https://doi.org/10.1175/JAS-D-14-0114.1, 2014.
Steppeler, J., Doms, G., Schättler, U., Bitzer, H. W., Gassmann, A., Damrath, U., and Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic model LM, Meteorol. Atmos. Phys., 82, 75–96, 2003.
Stevens, B. and Bony, S.: What Are Climate Models Missing?, Science, 340, 1053–1054, https://doi.org/10.1126/science.1237554, 2013.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parametrization in Large-Scale Models, Mon. Weather Rev., 117, 1779–1800, 1989.
Tompkins, A. M.: Organization of Tropical Convection in Low Vertical Wind Shears: The Role of Cold Pools, J. Atmos. Sci., 58, 1650–1672, https://doi.org/10.1175/1520-0469(2001)058<1650:OOTCIL>2.0.CO;2, 2001.
Wehner, M., Oliker, L., and Shalf, J.: Towards Ultra-High Resolution Models of Climate and Weather, Int. J. High Perform. Comput. Appl., 22, 149–165, https://doi.org/10.1177/1094342007085023, 2008.
Wehner, M. F., Oliker, L., Shalf, J., Donofrio, D., Drummond, L. A., Heikes, R., Kamil, S., Kono, C., Miller, N., Miura, H., Mohiyuddin, M., Randall, D., and Yang, W.-S.: Hardware/software co-design of global cloud system resolving models, J. Adv. Model. Earth Sys., 3, 4, https://doi.org/10.1029/2011MS000073, 2011.
Weisman, M., Skamarock, W., and Klemp, J.: The resolution dependence of explicitly modeled convective systems, Mon. Weather Rev., 125, 527–548, 1997.
Wicker, L. and Skamarock, W.: Time-splitting methods for elastic models using forward time schemes, Mon. Weather Rev., 130, 2088–2097, 2002.
Wyngaard, J. C.: Toward numerical modeling in the “terra incognita”, J. Atmos. Sci., 61, 1816–1826, 2004.
Zhou, B., Simon, J. S., and Chow, F. K.: The Convective Boundary Layer in the Terra Incognita, J. Atmos. Sci., 71, 2545–2563, https://doi.org/10.1175/JAS-D-13-0356.1, 2014.
Short summary
The representation of moist convection (thunderstorms and rain showers) in climate models represents a major challenge, as this process is usually approximated due to the lack of appropriate computational resolution. Climate simulations using horizontal resolution of O(1 km) allow one to explicitly resolve deep convection and thus allow for an improved representation of the water cycle. We present a set of such simulations covering the European scale using a climate model enabled for GPUs.
The representation of moist convection (thunderstorms and rain showers) in climate models...