Articles | Volume 15, issue 1
https://doi.org/10.5194/gmd-15-269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| Highlight paper
| 
13 Jan 2022
Model evaluation paper | Highlight paper |
| 13 Jan 2022
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
Eduardo Moreno-Chamarro
CORRESPONDING AUTHOR
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Louis-Philippe Caron
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
now at: Ouranos, Montréal, H3A 1B9, Canada
Saskia Loosveldt Tomas
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Javier Vegas-Regidor
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Oliver Gutjahr
Max Planck Institute for Meteorology, 20146 Hamburg, Germany
now at: Institut für Meereskunde, Universität Hamburg, 20146 Hamburg, Germany
Marie-Pierre Moine
CECI, Université de Toulouse, CERFACS/CNRS, 31100, Toulouse, France
Dian Putrasahan
Max Planck Institute for Meteorology, 20146 Hamburg, Germany
Christopher D. Roberts
ECMWF European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, United Kingdom
Malcolm J. Roberts
Met Office, Exeter, CE2 EX1 3PB, United Kingdom
Retish Senan
ECMWF European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, United Kingdom
Laurent Terray
CECI, Université de Toulouse, CERFACS/CNRS, 31100, Toulouse, France
Etienne Tourigny
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Pier Luigi Vidale
NCAS-Climate, Department of Meteorology, University of Reading, Reading, RG6 6BB, United Kingdom
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Guillian Van Achter, Thierry Fichefet, Hugues Goosse, and Eduardo Moreno-Chamarro
The Cryosphere, 16, 4745–4761, https://doi.org/10.5194/tc-16-4745-2022, https://doi.org/10.5194/tc-16-4745-2022, 2022
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We investigate the changes in ocean–ice interactions in the Totten Glacier area between the last decades (1995–2014) and the end of the 21st century (2081–2100) under warmer climate conditions. By the end of the 21st century, the sea ice is strongly reduced, and the ocean circulation close to the coast is accelerated. Our research highlights the importance of including representations of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.
Sam White, Eduardo Moreno-Chamarro, Davide Zanchettin, Heli Huhtamaa, Dagomar Degroot, Markus Stoffel, and Christophe Corona
Clim. Past, 18, 739–757, https://doi.org/10.5194/cp-18-739-2022, https://doi.org/10.5194/cp-18-739-2022, 2022
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This study examines whether the 1600 Huaynaputina volcano eruption triggered persistent cooling in the North Atlantic. It compares previous paleoclimate simulations with new climate reconstructions from natural proxies and historical documents and finds that the reconstructions are consistent with, but do not support, an eruption trigger for persistent cooling. The study also analyzes societal impacts of climatic change in ca. 1600 and the use of historical observations in model–data comparison.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
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This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Eduardo Moreno-Chamarro, Pablo Ortega, and François Massonnet
Geosci. Model Dev., 13, 4773–4787, https://doi.org/10.5194/gmd-13-4773-2020, https://doi.org/10.5194/gmd-13-4773-2020, 2020
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Climate models need to capture sea ice complexity to represent it realistically. Here we assess how distributing sea ice in discrete thickness categories impacts how sea ice variability is simulated in the NEMO3.6–LIM3 model. Simulations and satellite observations are compared by using k-means clustering of sea ice concentration in winter and summer between 1979 and 2014 at both poles. Little improvements in the modeled sea ice lead us to recommend using the standard number of five categories.
Maria Pyrina, Eduardo Moreno-Chamarro, Sebastian Wagner, and Eduardo Zorita
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-50, https://doi.org/10.5194/esd-2019-50, 2019
Revised manuscript not accepted
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
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Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
Jenny Hieronymus, Magnus Hieronymus, Matthias Gröger, Jörg Schwinger, Raffaele Bernadello, Etienne Tourigny, Valentina Sicardi, Itzel Ruvalcaba Baroni, and Klaus Wyser
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-54, https://doi.org/10.5194/bg-2023-54, 2023
Preprint under review for BG
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Changes in the seasonality of primary production has been examined using daily data from two earth system models covering the period 1750–2100. The daily data made it possible to detect shifts in the day of the year during which the net primary production reaches its peak value. It was found that the day of peak primary production occurs earlier and earlier during the 21st century and that a major change in the time series occurs in the beginning of the 21st century.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Emmanouil Flaounas, Leonardo Aragão, Lisa Bernini, Stavros Dafis, Benjamin Doiteau, Helena Flocas, Suzanne L. Gray, Alexia Karwat, John Kouroutzoglou, Piero Lionello, Florian Pantillon, Claudia Pasquero, Platon Patlakas, Maria Angels Picornell, Federico Porcù, Matthew D. K. Priestley, Marco Reale, Malcolm Roberts, Hadas Saaroni, Dor Sandler, Enrico Scoccimarro, Michael Sprenger, and Baruch Ziv
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-63, https://doi.org/10.5194/wcd-2022-63, 2023
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Cyclone detection and tracking methods (CDTMs) have different approaches in defining and tracking cyclone centers. This leads to disagreements on extratropical cyclone climatologies. We present a new approach that combines tracks from indiviudal CDTMs to produce new composite tracks. These new tracks are shown to correspond to physically meaningful systems with distinctive life stages.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Wei Li, Jie Chen, Lu Li, Yvan J. Orsolini, Yiheng Xiang, Retish Senan, and Patricia de Rosnay
The Cryosphere, 16, 4985–5000, https://doi.org/10.5194/tc-16-4985-2022, https://doi.org/10.5194/tc-16-4985-2022, 2022
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Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Guillian Van Achter, Thierry Fichefet, Hugues Goosse, and Eduardo Moreno-Chamarro
The Cryosphere, 16, 4745–4761, https://doi.org/10.5194/tc-16-4745-2022, https://doi.org/10.5194/tc-16-4745-2022, 2022
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We investigate the changes in ocean–ice interactions in the Totten Glacier area between the last decades (1995–2014) and the end of the 21st century (2081–2100) under warmer climate conditions. By the end of the 21st century, the sea ice is strongly reduced, and the ocean circulation close to the coast is accelerated. Our research highlights the importance of including representations of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.
Julia F. Lockwood, Galina S. Guentchev, Alexander Alabaster, Simon J. Brown, Erika J. Palin, Malcolm J. Roberts, and Hazel E. Thornton
Nat. Hazards Earth Syst. Sci., 22, 3585–3606, https://doi.org/10.5194/nhess-22-3585-2022, https://doi.org/10.5194/nhess-22-3585-2022, 2022
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We describe how we developed a set of 1300 years' worth of European winter windstorm footprints, using a multi-model ensemble of high-resolution global climate models, for use by the insurance industry to analyse windstorm risk. The large amount of data greatly reduces uncertainty on risk estimates compared to using shorter observational data sets and also allows the relationship between windstorm risk and predictable large-scale climate indices to be quantified.
Rafaela Jane Delfino, Gerry Bagtasa, Kevin Hodges, and Pier Luigi Vidale
Nat. Hazards Earth Syst. Sci., 22, 3285–3307, https://doi.org/10.5194/nhess-22-3285-2022, https://doi.org/10.5194/nhess-22-3285-2022, 2022
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We showed the effects of altering the choice of cumulus schemes, surface flux options, and spectral nudging with a high level of sensitivity to cumulus schemes in simulating an intense typhoon. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in simulating typhoons such as Haiyan in 2013. This study is useful in addressing the growing need to plan and prepare for as well as reduce the impacts of intense typhoons in the Philippines.
Aurélien Ribes, Julien Boé, Saïd Qasmi, Brigitte Dubuisson, Hervé Douville, and Laurent Terray
Earth Syst. Dynam., 13, 1397–1415, https://doi.org/10.5194/esd-13-1397-2022, https://doi.org/10.5194/esd-13-1397-2022, 2022
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We use a novel statistical method to combine climate simulations and observations, and we deliver an updated assessment of past and future warming over France. As a key result, we find that the warming over that region was underestimated in previous multi-model ensembles by up to 50 %. We also assess the contribution of greenhouse gases, aerosols, and other factors to the observed warming, as well as the impact on the seasonal temperature cycle, and we discuss implications for climate services.
Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, https://doi.org/10.5194/gmd-15-6115-2022, 2022
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CSTools (short for Climate Service Tools) is an R package that contains process-based methods for climate forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to describing the structure and methods in the package, we also present three use cases to illustrate the seasonal climate forecast post-processing for specific purposes.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Tim Rohrschneider, Johanna Baehr, Veit Lüschow, Dian Putrasahan, and Jochem Marotzke
Ocean Sci., 18, 979–996, https://doi.org/10.5194/os-18-979-2022, https://doi.org/10.5194/os-18-979-2022, 2022
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This paper presents an analysis of wind sensitivity experiments in order to provide insight into the wind forcing dependence of the AMOC by understanding the behavior of its depth scale(s).
Ambrogio Volonté, Andrew G. Turner, Reinhard Schiemann, Pier Luigi Vidale, and Nicholas P. Klingaman
Weather Clim. Dynam., 3, 575–599, https://doi.org/10.5194/wcd-3-575-2022, https://doi.org/10.5194/wcd-3-575-2022, 2022
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In this study we analyse the complex seasonal evolution of the East Asian summer monsoon. Using reanalysis data, we show the importance of the interaction between tropical and extratropical air masses converging at the monsoon front, particularly during its northward progression. The upper-level flow pattern (e.g. the westerly jet) controls the balance between the airstreams and thus the associated rainfall. This framework provides a basis for studies of extreme events and climate variability.
Steve Delhaye, Thierry Fichefet, François Massonnet, David Docquier, Rym Msadek, Svenya Chripko, Christopher Roberts, Sarah Keeley, and Retish Senan
Weather Clim. Dynam., 3, 555–573, https://doi.org/10.5194/wcd-3-555-2022, https://doi.org/10.5194/wcd-3-555-2022, 2022
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It is unclear how the atmosphere will respond to a retreat of summer Arctic sea ice. Much attention has been paid so far to weather extremes at mid-latitude and in winter. Here we focus on the changes in extremes in surface air temperature and precipitation over the Arctic regions in summer during and following abrupt sea ice retreats. We find that Arctic sea ice loss clearly shifts the extremes in surface air temperature and precipitation over terrestrial regions surrounding the Arctic Ocean.
Sam White, Eduardo Moreno-Chamarro, Davide Zanchettin, Heli Huhtamaa, Dagomar Degroot, Markus Stoffel, and Christophe Corona
Clim. Past, 18, 739–757, https://doi.org/10.5194/cp-18-739-2022, https://doi.org/10.5194/cp-18-739-2022, 2022
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This study examines whether the 1600 Huaynaputina volcano eruption triggered persistent cooling in the North Atlantic. It compares previous paleoclimate simulations with new climate reconstructions from natural proxies and historical documents and finds that the reconstructions are consistent with, but do not support, an eruption trigger for persistent cooling. The study also analyzes societal impacts of climatic change in ca. 1600 and the use of historical observations in model–data comparison.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Mark R. Muetzelfeldt, Reinhard Schiemann, Andrew G. Turner, Nicholas P. Klingaman, Pier Luigi Vidale, and Malcolm J. Roberts
Hydrol. Earth Syst. Sci., 25, 6381–6405, https://doi.org/10.5194/hess-25-6381-2021, https://doi.org/10.5194/hess-25-6381-2021, 2021
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Simulating East Asian Summer Monsoon (EASM) rainfall poses many challenges because of its multi-scale nature. We evaluate three setups of a 14 km global climate model against observations to see if they improve simulated rainfall. We do this over catchment basins of different sizes to estimate how model performance depends on spatial scale. Using explicit convection improves rainfall diurnal cycle, yet more model tuning is needed to improve mean and intensity biases in simulated summer rainfall.
Laurent Terray
Weather Clim. Dynam., 2, 971–989, https://doi.org/10.5194/wcd-2-971-2021, https://doi.org/10.5194/wcd-2-971-2021, 2021
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Attribution of the causes of extreme temperature events has become active research due to the wide-ranging impacts of recent heat waves and cold spells. Here we show that a purely observational approach based on atmospheric circulation analogues and resampling provides a robust quantification of the various dynamic and thermodynamic contributions to specific extreme temperature events. The approach can easily be integrated in the toolbox of any real-time extreme event attribution system.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Gabriel M. P. Perez, Pier Luigi Vidale, Nicholas P. Klingaman, and Thomas C. M. Martin
Weather Clim. Dynam., 2, 475–488, https://doi.org/10.5194/wcd-2-475-2021, https://doi.org/10.5194/wcd-2-475-2021, 2021
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Much of the rainfall in tropical regions comes from organised cloud bands called convergence zones (CZs). These bands have hundreds of kilometers. In South America (SA), they cause intense rain for long periods of time. To study these systems, we need to define and identify them with computer code. We propose a definition of CZs based on the the pathways of air, selecting regions where air masses originated in separated regions meet. This method identifies important mechanisms of rain in SA.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev., 14, 2317–2349, https://doi.org/10.5194/gmd-14-2317-2021, https://doi.org/10.5194/gmd-14-2317-2021, 2021
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We compare four ocean vertical mixing schemes in 100-year coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable but produce a similar global bias pattern. We therefore cannot classify any scheme as superior but conclude that the chosen mixing scheme may be important for regional biases.
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
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This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Liang Guo, Ruud J. van der Ent, Nicholas P. Klingaman, Marie-Estelle Demory, Pier Luigi Vidale, Andrew G. Turner, Claudia C. Stephan, and Amulya Chevuturi
Geosci. Model Dev., 13, 6011–6028, https://doi.org/10.5194/gmd-13-6011-2020, https://doi.org/10.5194/gmd-13-6011-2020, 2020
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Precipitation over East Asia simulated in the Met Office Unified Model is compared with observations. Moisture sources of EA precipitation are traced using a moisture tracking model. Biases in moisture sources are linked to biases in precipitation. Using the tracking model, changes in moisture sources can be attributed to changes in SST, circulation and associated evaporation. This proves that the method used in this study is useful to identify the causes of biases in regional precipitation.
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
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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.
Eduardo Moreno-Chamarro, Pablo Ortega, and François Massonnet
Geosci. Model Dev., 13, 4773–4787, https://doi.org/10.5194/gmd-13-4773-2020, https://doi.org/10.5194/gmd-13-4773-2020, 2020
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Climate models need to capture sea ice complexity to represent it realistically. Here we assess how distributing sea ice in discrete thickness categories impacts how sea ice variability is simulated in the NEMO3.6–LIM3 model. Simulations and satellite observations are compared by using k-means clustering of sea ice concentration in winter and summer between 1979 and 2014 at both poles. Little improvements in the modeled sea ice lead us to recommend using the standard number of five categories.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
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HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Reinhard Schiemann, Panos Athanasiadis, David Barriopedro, Francisco Doblas-Reyes, Katja Lohmann, Malcolm J. Roberts, Dmitry V. Sein, Christopher D. Roberts, Laurent Terray, and Pier Luigi Vidale
Weather Clim. Dynam., 1, 277–292, https://doi.org/10.5194/wcd-1-277-2020, https://doi.org/10.5194/wcd-1-277-2020, 2020
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In blocking situations the westerly atmospheric flow in the midlatitudes is blocked by near-stationary high-pressure systems. Blocking can be associated with extremes such as cold spells and heat waves. Climate models are known to underestimate blocking occurrence. Here, we assess the latest generation of models and find improvements in simulated blocking, partly due to increases in model resolution. These new models are therefore more suitable for studying climate extremes related to blocking.
Torben Koenigk, Ramon Fuentes-Franco, Virna Meccia, Oliver Gutjahr, Laura C. Jackson, Adrian L. New, Pablo Ortega, Christopher Roberts, Malcolm Roberts, Thomas Arsouze, Doroteaciro Iovino, Marie-Pierre Moine, and Dmitry V. Sein
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-41, https://doi.org/10.5194/os-2020-41, 2020
Revised manuscript not accepted
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The mixing of water masses into the deep ocean in the North Atlantic is important for the entire global ocean circulation. We use seven global climate models to investigate the effect of increasing the model resolution on this deep ocean mixing. The main result is that increased model resolution leads to a deeper mixing of water masses in the Labrador Sea but has less effect in the Greenland Sea. However, most of the models overestimate the deep ocean mixing compared to observations.
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
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This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Malcolm J. Roberts, Alex Baker, Ed W. Blockley, Daley Calvert, Andrew Coward, Helene T. Hewitt, Laura C. Jackson, Till Kuhlbrodt, Pierre Mathiot, Christopher D. Roberts, Reinhard Schiemann, Jon Seddon, Benoît Vannière, and Pier Luigi Vidale
Geosci. Model Dev., 12, 4999–5028, https://doi.org/10.5194/gmd-12-4999-2019, https://doi.org/10.5194/gmd-12-4999-2019, 2019
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We investigate the role that horizontal grid spacing plays in global coupled climate model simulations, together with examining the efficacy of a new design of simulation experiments that is being used by the community for multi-model comparison. We found that finer grid spacing in both atmosphere and ocean–sea ice models leads to a general reduction in bias compared to observations, and that once eddies in the ocean are resolved, several key climate processes are greatly improved.
Maria Pyrina, Eduardo Moreno-Chamarro, Sebastian Wagner, and Eduardo Zorita
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-50, https://doi.org/10.5194/esd-2019-50, 2019
Revised manuscript not accepted
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
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Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
Yvan Orsolini, Martin Wegmann, Emanuel Dutra, Boqi Liu, Gianpaolo Balsamo, Kun Yang, Patricia de Rosnay, Congwen Zhu, Wenli Wang, Retish Senan, and Gabriele Arduini
The Cryosphere, 13, 2221–2239, https://doi.org/10.5194/tc-13-2221-2019, https://doi.org/10.5194/tc-13-2221-2019, 2019
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The Tibetan Plateau region exerts a considerable influence on regional climate, yet the snowpack over that region is poorly represented in both climate and forecast models due a large precipitation and snowfall bias. We evaluate the snowpack in state-of-the-art atmospheric reanalyses against in situ observations and satellite remote sensing products. Improved snow initialisation through better use of snow observations in reanalyses may improve medium-range to seasonal weather forecasts.
Oliver Gutjahr, Dian Putrasahan, Katja Lohmann, Johann H. Jungclaus, Jin-Song von Storch, Nils Brüggemann, Helmuth Haak, and Achim Stössel
Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, https://doi.org/10.5194/gmd-12-3241-2019, 2019
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We analyse how climatic mean states of the atmosphere and ocean change with increasing the horizontal model resolution of the Max Planck Institute Earth System Model (MPI-ESM1.2) and how they are affected by the representation of vertical mixing in the ocean. It is in particular a high-resolution ocean that reduces biases not only in the ocean but also in the atmosphere. The vertical mixing scheme affects the strength and stability of the Atlantic meridional overturning circulation (AMOC).
Manu Anna Thomas, Abhay Devasthale, Torben Koenigk, Klaus Wyser, Malcolm Roberts, Christopher Roberts, and Katja Lohmann
Geosci. Model Dev., 12, 1679–1702, https://doi.org/10.5194/gmd-12-1679-2019, https://doi.org/10.5194/gmd-12-1679-2019, 2019
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Cloud processes occur at scales ranging from few micrometres to hundreds of kilometres. Their representation in global climate models and their fidelity are thus sensitive to the choice of spatial resolution. Here, cloud radiative effects simulated by models are evaluated using a satellite dataset, with a focus on investigating the sensitivity to spatial resolution. The evaluations are carried out using two approaches: the traditional statistical comparisons and the process-oriented evaluation.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
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The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Christopher D. Roberts, Retish Senan, Franco Molteni, Souhail Boussetta, Michael Mayer, and Sarah P. E. Keeley
Geosci. Model Dev., 11, 3681–3712, https://doi.org/10.5194/gmd-11-3681-2018, https://doi.org/10.5194/gmd-11-3681-2018, 2018
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This paper presents climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6).
Claudia Christine Stephan, Nicholas P. Klingaman, Pier Luigi Vidale, Andrew G. Turner, Marie-Estelle Demory, and Liang Guo
Geosci. Model Dev., 11, 3215–3233, https://doi.org/10.5194/gmd-11-3215-2018, https://doi.org/10.5194/gmd-11-3215-2018, 2018
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Summer precipitation over China in the MetUM reaches twice its observed values. Increasing the horizontal resolution of the model and adding air–sea coupling have little effect on these biases. Nevertheless, MetUM correctly simulates spatial patterns of temporally coherent precipitation and the associated large-scale processes. This suggests that the model may provide useful predictions of summer intraseasonal variability despite the substantial biases in overall intraseasonal variance.
Reinhard Schiemann, Pier Luigi Vidale, Len C. Shaffrey, Stephanie J. Johnson, Malcolm J. Roberts, Marie-Estelle Demory, Matthew S. Mizielinski, and Jane Strachan
Hydrol. Earth Syst. Sci., 22, 3933–3950, https://doi.org/10.5194/hess-22-3933-2018, https://doi.org/10.5194/hess-22-3933-2018, 2018
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A new generation of global climate models with resolutions between 50 and 10 km is becoming available. Here, we assess how well one such model simulates European precipitation. We find clear improvements in the mean precipitation pattern, and importantly also for extreme daily precipitation over 30 major European river basins. Despite remaining limitations, new high-resolution global models hold great promise for improved climate predictions of European precipitation at impact-relevant scales.
Claudia Christine Stephan, Nicholas P. Klingaman, Pier Luigi Vidale, Andrew G. Turner, Marie-Estelle Demory, and Liang Guo
Geosci. Model Dev., 11, 1823–1847, https://doi.org/10.5194/gmd-11-1823-2018, https://doi.org/10.5194/gmd-11-1823-2018, 2018
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Climate simulations are evaluated for their ability to reproduce year-to-year variability of precipitation over China. Mean precipitation and variability are too high in all simulations but improve with finer resolution and coupling. Simulations reproduce the observed spatial patterns of rainfall variability. However, not all of these patterns are associated with observed mechanisms. For example, simulations do not reproduce summer rainfall along the Yangtze valley in response to El Niño.
Elisângela Broedel, Celso Von Randow, Luz Adriana Cuartas, Antonio Donato Nobre, Alessandro Carioca de Araújo, Bart Kruijt, Etienne Tourigny, Luiz Antônio Cândido, Martin Hodnett, and Javier Tomasella
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-203, https://doi.org/10.5194/hess-2017-203, 2017
Revised manuscript not accepted
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This work describes the simulation of surface fluxes in two distinct environments along a topographic gradient in a central Amazonian forest using the INLAND Model. The results show that a surface model can capture the small differences related to energy, water and carbon balance between both sites. These confirms the importance to incorporate subgrid scale variability by including relief attributes of topography, soil and vegetation to better representing Terra Firme forests in these models.
Rafael Abel, Claus W. Böning, Richard J. Greatbatch, Helene T. Hewitt, and Malcolm J. Roberts
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-24, https://doi.org/10.5194/os-2017-24, 2017
Revised manuscript not accepted
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In coupled global atmosphere ocean models a feedback from ocean surface currents to atmospheric winds was found. Surface winds are energized by about 30 % of the ocean currents. We were able to implement this feedback in uncoupled ocean models which results in a realistic surface flux coupling. Due to changes in the dissipation the kinetic energy of the time-variable flow is increased up to 10 % when this feedback is implemented. Implementation in other models should be straightforward.
David Walters, Ian Boutle, Malcolm Brooks, Thomas Melvin, Rachel Stratton, Simon Vosper, Helen Wells, Keith Williams, Nigel Wood, Thomas Allen, Andrew Bushell, Dan Copsey, Paul Earnshaw, John Edwards, Markus Gross, Steven Hardiman, Chris Harris, Julian Heming, Nicholas Klingaman, Richard Levine, James Manners, Gill Martin, Sean Milton, Marion Mittermaier, Cyril Morcrette, Thomas Riddick, Malcolm Roberts, Claudio Sanchez, Paul Selwood, Alison Stirling, Chris Smith, Dan Suri, Warren Tennant, Pier Luigi Vidale, Jonathan Wilkinson, Martin Willett, Steve Woolnough, and Prince Xavier
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, https://doi.org/10.5194/gmd-10-1487-2017, 2017
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
Laurent Bessières, Stéphanie Leroux, Jean-Michel Brankart, Jean-Marc Molines, Marie-Pierre Moine, Pierre-Antoine Bouttier, Thierry Penduff, Laurent Terray, Bernard Barnier, and Guillaume Sérazin
Geosci. Model Dev., 10, 1091–1106, https://doi.org/10.5194/gmd-10-1091-2017, https://doi.org/10.5194/gmd-10-1091-2017, 2017
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A new, probabilistic version of an ocean modelling system has been implemented in order to simulate the chaotic and the atmospherically forced contributions to the ocean variability. For that purpose, a large ensemble of global hindcasts has been performed. Results illustrate the importance of the oceanic chaos on climate-related oceanic indices, and the relevance of such probabilistic ocean modelling approaches to anticipating the behaviour of the next generation of coupled climate models.
Oliver Gutjahr, Günther Heinemann, Andreas Preußer, Sascha Willmes, and Clemens Drüe
The Cryosphere, 10, 2999–3019, https://doi.org/10.5194/tc-10-2999-2016, https://doi.org/10.5194/tc-10-2999-2016, 2016
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We estimated the formation of new sea ice within polynyas in the Laptev Sea (Siberia) with the regional climate model COSMO-CLM at 5 km horizontal resolution. Fractional sea ice and the representation of thin ice is often neglected in atmospheric models. Our study demonstrates, however, that the way thin ice in polynyas is represented in the model considerably affects the amount of newly formed sea-ice and the air–ice–ocean heat flux. Both processes impact the Arctic sea-ice budget.
Reindert J. Haarsma, Malcolm J. Roberts, Pier Luigi Vidale, Catherine A. Senior, Alessio Bellucci, Qing Bao, Ping Chang, Susanna Corti, Neven S. Fučkar, Virginie Guemas, Jost von Hardenberg, Wilco Hazeleger, Chihiro Kodama, Torben Koenigk, L. Ruby Leung, Jian Lu, Jing-Jia Luo, Jiafu Mao, Matthew S. Mizielinski, Ryo Mizuta, Paulo Nobre, Masaki Satoh, Enrico Scoccimarro, Tido Semmler, Justin Small, and Jin-Song von Storch
Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, https://doi.org/10.5194/gmd-9-4185-2016, 2016
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Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.
Rasmus E. Benestad, Retish Senan, and Yvan Orsolini
Earth Syst. Dynam., 7, 851–861, https://doi.org/10.5194/esd-7-851-2016, https://doi.org/10.5194/esd-7-851-2016, 2016
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Seasonal predictions have been challenging for mid-latitude regions such as Europe, and we suspect that one reason may be due to subjective choices in how the forecast models are configured. We tested how (1) the inclusion and omission of the representation of the stratosphere affect the predictions and (2) the degree of detail in the sea-ice description. The test was carried out with a set of simulations (experiments) using a technique known as "factorial regression".
Helene T. Hewitt, Malcolm J. Roberts, Pat Hyder, Tim Graham, Jamie Rae, Stephen E. Belcher, Romain Bourdallé-Badie, Dan Copsey, Andrew Coward, Catherine Guiavarch, Chris Harris, Richard Hill, Joël J.-M. Hirschi, Gurvan Madec, Matthew S. Mizielinski, Erica Neininger, Adrian L. New, Jean-Christophe Rioual, Bablu Sinha, David Storkey, Ann Shelly, Livia Thorpe, and Richard A. Wood
Geosci. Model Dev., 9, 3655–3670, https://doi.org/10.5194/gmd-9-3655-2016, https://doi.org/10.5194/gmd-9-3655-2016, 2016
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We examine the impact in a coupled model of increasing atmosphere and ocean horizontal resolution and the frequency of coupling between the atmosphere and ocean. We demonstrate that increasing the ocean resolution from 1/4 degree to 1/12 degree has a major impact on ocean circulation and global heat transports. The results add to the body of evidence suggesting that ocean resolution is an important consideration when developing coupled models for weather and climate applications.
K. D. Williams, C. M. Harris, A. Bodas-Salcedo, J. Camp, R. E. Comer, D. Copsey, D. Fereday, T. Graham, R. Hill, T. Hinton, P. Hyder, S. Ineson, G. Masato, S. F. Milton, M. J. Roberts, D. P. Rowell, C. Sanchez, A. Shelly, B. Sinha, D. N. Walters, A. West, T. Woollings, and P. K. Xavier
Geosci. Model Dev., 8, 1509–1524, https://doi.org/10.5194/gmd-8-1509-2015, https://doi.org/10.5194/gmd-8-1509-2015, 2015
M. S. Mizielinski, M. J. Roberts, P. L. Vidale, R. Schiemann, M.-E. Demory, J. Strachan, T. Edwards, A. Stephens, B. N. Lawrence, M. Pritchard, P. Chiu, A. Iwi, J. Churchill, C. del Cano Novales, J. Kettleborough, W. Roseblade, P. Selwood, M. Foster, M. Glover, and A. Malcolm
Geosci. Model Dev., 7, 1629–1640, https://doi.org/10.5194/gmd-7-1629-2014, https://doi.org/10.5194/gmd-7-1629-2014, 2014
M.-P. Moine, S. Valcke, B. N. Lawrence, C. Pascoe, R. W. Ford, A. Alias, V. Balaji, P. Bentley, G. Devine, S. A. Callaghan, and E. Guilyardi
Geosci. Model Dev., 7, 479–493, https://doi.org/10.5194/gmd-7-479-2014, https://doi.org/10.5194/gmd-7-479-2014, 2014
D. N. Walters, K. D. Williams, I. A. Boutle, A. C. Bushell, J. M. Edwards, P. R. Field, A. P. Lock, C. J. Morcrette, R. A. Stratton, J. M. Wilkinson, M. R. Willett, N. Bellouin, A. Bodas-Salcedo, M. E. Brooks, D. Copsey, P. D. Earnshaw, S. C. Hardiman, C. M. Harris, R. C. Levine, C. MacLachlan, J. C. Manners, G. M. Martin, S. F. Milton, M. D. Palmer, M. J. Roberts, J. M. Rodríguez, W. J. Tennant, and P. L. Vidale
Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, https://doi.org/10.5194/gmd-7-361-2014, 2014
Related subject area
Climate and Earth system modeling
Importance of ice nucleation and precipitation on climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)
UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model
Porting the WAVEWATCH III (v6.07) wave action source terms to GPU
Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions
Analysis of systematic biases in tropospheric hydrostatic delay models and construction of a correction model
A new precipitation emulator (PREMU v1.0) for lower-complexity models
Simulating marine neodymium isotope distributions using Nd v1.0 coupled to the ocean component of the FAMOUS–MOSES1 climate model: sensitivities to reversible scavenging efficiency and benthic source distributions
CMIP6 simulations with the compact Earth system model OSCAR v3.1
Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1
The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses
AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales
Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) – refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN – Part 1: Adaptive grid refinement in an idealized double-gyre case
Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean
stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1
Evaluation of native Earth system model output with ESMValTool v2.6.0
The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Temperature forecasting by deep learning methods
Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios
Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro
Climate change projections of wet and dry extreme events in the Upper Jhelum Basin using a multivariate drought index: Evaluation of bias correction
Implementation and evaluation of the GEOS-Chem chemistry module version 13.1.2 within the Community Earth System Model v2.1
Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project
Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2
Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)
Impact of increased resolution on the representation of the Canary upwelling system in climate models
Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations
Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at planetary boundary layer gray-zone resolution: a case study over the coastal regions of North China
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise
A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)
A modeling framework to understand historical and projected ocean climate change in large coupled ensembles
TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids
Estimation of missing building height in OpenStreetMap data: a French case study using GeoClimate 0.0.1
The Moist Quasi-Geostrophic Coupled Model: MQ-GCM 2.0
Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53
Pace v0.1: A Python-based Performance-Portable Implementation of the FV3 Dynamical Core
Transport parameterization of the Polar SWIFT model (version 2)
Effects of complex terrain on the shortwave radiative balance: A sub–grid scale parameterization for the GFDL Land Model version 4.2
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
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Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Olawale James Ikuyajolu, Luke Van Roekel, Steven R. Brus, Erin E. Thomas, Yi Deng, and Sarat Sreepathi
Geosci. Model Dev., 16, 1445–1458, https://doi.org/10.5194/gmd-16-1445-2023, https://doi.org/10.5194/gmd-16-1445-2023, 2023
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Wind-generated waves play an important role in modifying physical processes at the air–sea interface, but they have been traditionally excluded from climate models due to the high computational cost of running spectral wave models for climate simulations. To address this, our work identified and accelerated the computationally intensive section of WAVEWATCH III on GPU using OpenACC. This allows for high-resolution modeling of atmosphere–wave–ocean feedbacks in century-scale climate integrations.
Edward C. Chan, Joana Leitão, Andreas Kerschbaumer, and Timothy M. Butler
Geosci. Model Dev., 16, 1427–1444, https://doi.org/10.5194/gmd-16-1427-2023, https://doi.org/10.5194/gmd-16-1427-2023, 2023
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Yeti is a Handbook Emission Factors for Road Transport-based traffic emission inventory written in the Python 3 scripting language, which adopts a generalized treatment for activity data using traffic information of varying levels of detail introduced in a systematic and consistent manner, with the ability to maximize reusability. Thus, Yeti has been conceived and implemented with a high degree of data and process symmetry, allowing scalable and flexible execution while affording ease of use.
Haopeng Fan, Siran Li, Zhongmiao Sun, Guorui Xiao, Xinxing Li, and Xiaogang Liu
Geosci. Model Dev., 16, 1345–1358, https://doi.org/10.5194/gmd-16-1345-2023, https://doi.org/10.5194/gmd-16-1345-2023, 2023
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The traditional tropospheric zenith hydrostatic delay (ZHD) model's bias is usually thought negligible, yet it still reaches 10 mm sometimes and would lead to millimeter-level position errors for space geodetic observations. Therefore, we analyzed the bias’ characteristics and present a grid model to correct the traditional ZHD formula. When verifying the efficiency based on data from the ECMWF (European Centre for Medium-Range Weather Forecasts), ZHD biases were rectified by ~50 %.
Gang Liu, Shushi Peng, Chris Huntingford, and Yi Xi
Geosci. Model Dev., 16, 1277–1296, https://doi.org/10.5194/gmd-16-1277-2023, https://doi.org/10.5194/gmd-16-1277-2023, 2023
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Due to computational limits, lower-complexity models (LCMs) were developed as a complementary tool for accelerating comprehensive Earth system models (ESMs) but still lack a good precipitation emulator for LCMs. Here, we developed a data-calibrated precipitation emulator (PREMU), a computationally effective way to better estimate historical and simulated precipitation by current ESMs. PREMU has potential applications related to land surface processes and their interactions with climate change.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
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We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Yann Quilcaille, Thomas Gasser, Philippe Ciais, and Olivier Boucher
Geosci. Model Dev., 16, 1129–1161, https://doi.org/10.5194/gmd-16-1129-2023, https://doi.org/10.5194/gmd-16-1129-2023, 2023
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The model OSCAR is a simple climate model, meaning its representation of the Earth system is simplified but calibrated on models of higher complexity. Here, we diagnose its latest version using a total of 99 experiments in a probabilistic framework and under observational constraints. OSCAR v3.1 shows good agreement with observations, complex Earth system models and emerging properties. Some points for improvements are identified, such as the ocean carbon cycle.
Sandra L. LeGrand, Theodore W. Letcher, Gregory S. Okin, Nicholas P. Webb, Alex R. Gallagher, Saroj Dhital, Taylor S. Hodgdon, Nancy P. Ziegler, and Michelle L. Michaels
Geosci. Model Dev., 16, 1009–1038, https://doi.org/10.5194/gmd-16-1009-2023, https://doi.org/10.5194/gmd-16-1009-2023, 2023
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Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
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
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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.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev., 16, 851–867, https://doi.org/10.5194/gmd-16-851-2023, https://doi.org/10.5194/gmd-16-851-2023, 2023
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Cell-tracking algorithms allow for the study of properties of a convective cell across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm's criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Yan Zhang, Xuantong Wang, Yuhao Sun, Chenhui Ning, Shiming Xu, Hengbin An, Dehong Tang, Hong Guo, Hao Yang, Ye Pu, Bo Jiang, and Bin Wang
Geosci. Model Dev., 16, 679–704, https://doi.org/10.5194/gmd-16-679-2023, https://doi.org/10.5194/gmd-16-679-2023, 2023
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We construct a new ocean model, OMARE, that can carry out multi-scale ocean simulation with adaptive mesh refinement. OMARE is based on the refactorization of NEMO with a third-party, high-performance piece of middleware. We report the porting process and experiments of an idealized western-boundary current system. The new model simulates turbulent and temporally varying mesoscale and submesoscale processes via adaptive refinement. Related topics and future work with OMARE are also discussed.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717, https://doi.org/10.5194/gmd-16-705-2023, https://doi.org/10.5194/gmd-16-705-2023, 2023
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To improve the numerical model predictability of monthly extended-range scales, we use the simplified slab ocean model (SOM) to restrict the complicated sea surface temperature (SST) bias from a 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have better performance than the WRF-ROMS, which has a significant impact on the atmosphere. For extreme weather events such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Dagmawi Teklu Asfaw, Michael Bliss Singer, Rafael Rosolem, David MacLeod, Mark Cuthbert, Edisson Quichimbo Miguitama, Manuel F. Rios Gaona, and Katerina Michaelides
Geosci. Model Dev., 16, 557–571, https://doi.org/10.5194/gmd-16-557-2023, https://doi.org/10.5194/gmd-16-557-2023, 2023
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stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
Markus Köhli, Martin Schrön, Steffen Zacharias, and Ulrich Schmidt
Geosci. Model Dev., 16, 449–477, https://doi.org/10.5194/gmd-16-449-2023, https://doi.org/10.5194/gmd-16-449-2023, 2023
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In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Magnus Hieronymus
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-295, https://doi.org/10.5194/gmd-2022-295, 2023
Revised manuscript accepted for GMD
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A statistical model called the sea level simulator is presented and made freely available. The sea level simulator integrates mean sea level rise and sea level extremes into a joint framework that is useful for flood risk estimation. These flood risk estimates are contingent on probabilities given to different emission scenarios and the length of the planning period. The model is also useful for uncertainty quantifications and in decision and adaptation problems.
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
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More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
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All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Geosci. Model Dev., 15, 8931–8956, https://doi.org/10.5194/gmd-15-8931-2022, https://doi.org/10.5194/gmd-15-8931-2022, 2022
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Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.
Thomas Bossy, Thomas Gasser, and Philippe Ciais
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022, https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Rubina Ansari, Ana Casanueva, Muhammad Usman Liaqat, and Giovanna Grossi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-237, https://doi.org/10.5194/gmd-2022-237, 2022
Revised manuscript accepted for GMD
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Bias correction has become indispensable to climate model output as a post-processing step to render climate model output more useful for impact assessment studies. The current work presents a comparison of different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) for climate model simulations from three initiatives (CMIP6, CORDEX and CORDEX-CORE) for a multivariate drought index (i.e., Standardized Precipitation Evapotranspiration Index).
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Laura Claire Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-277, https://doi.org/10.5194/gmd-2022-277, 2022
Revised manuscript accepted for GMD
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The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult, however it is unclear whether TP exist in global climate models. Here we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic hosing model intercomparison project (NAHosMIP).
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, and Jorge López-Parages
Geosci. Model Dev., 15, 8245–8267, https://doi.org/10.5194/gmd-15-8245-2022, https://doi.org/10.5194/gmd-15-8245-2022, 2022
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Increasing model resolution depends on the subdomain of the Canary upwelling considered. In the Iberian Peninsula, the high-resolution (HR) models do not seem to better simulate the upwelling indices, while in Morocco to the Senegalese coast, the HR models show a clear improvement. Thus increasing the resolution of a global climate model does not necessarily have to be the only way to better represent the climate system. There is still much work to be done in terms of physical parameterizations.
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243, https://doi.org/10.5194/gmd-15-8221-2022, https://doi.org/10.5194/gmd-15-8221-2022, 2022
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Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI).
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Entao Yu, Rui Bai, Xia Chen, and Lifang Shao
Geosci. Model Dev., 15, 8111–8134, https://doi.org/10.5194/gmd-15-8111-2022, https://doi.org/10.5194/gmd-15-8111-2022, 2022
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A large number of simulations are conducted to investigate how different physical parameterization schemes impact surface wind simulations under stable weather conditions over the coastal regions of North China using the Weather Research and Forecasting model with a horizontal grid spacing of 0.5 km. Results indicate that the simulated wind speed is most sensitive to the planetary boundary layer schemes, followed by short-wave/long-wave radiation schemes and microphysics schemes.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Marina Martínez Montero, Michel Crucifix, Victor Couplet, Nuria Brede, and Nicola Botta
Geosci. Model Dev., 15, 8059–8084, https://doi.org/10.5194/gmd-15-8059-2022, https://doi.org/10.5194/gmd-15-8059-2022, 2022
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We present SURFER, a lightweight model that links CO2 emissions and geoengineering to ocean acidification and sea level rise from glaciers, ocean thermal expansion and Greenland and Antarctic ice sheets. The ice sheet module adequately describes the tipping points of both Greenland and Antarctica. SURFER is understandable, fast, accurate up to several thousands of years, capable of emulating results obtained by state of the art models and well suited for policy analyses.
Francisco José Cuesta-Valero, Hugo Beltrami, Stephan Gruber, Almudena García-García, and J. Fidel González-Rouco
Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, https://doi.org/10.5194/gmd-15-7913-2022, 2022
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Inversions of subsurface temperature profiles provide past long-term estimates of ground surface temperature histories and ground heat flux histories at timescales of decades to millennia. Theses estimates complement high-frequency proxy temperature reconstructions and are the basis for studying continental heat storage. We develop and release a new bootstrap method to derive meaningful confidence intervals for the average surface temperature and heat flux histories from any number of profiles.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Wentao Zhang, Xiangjun Shi, and Chunsong Lu
Geosci. Model Dev., 15, 7751–7766, https://doi.org/10.5194/gmd-15-7751-2022, https://doi.org/10.5194/gmd-15-7751-2022, 2022
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The two-moment bulk cloud microphysics scheme used in CAM6 was modified to consider the impacts of the ice-crystal size distribution shape parameter (μi). After that, how the μi impacts cloud microphysical processes and then climate simulations is clearly illustrated by offline tests and CAM6 model experiments. Our results and findings are useful for the further development of μi-related parameterizations.
Yona Silvy, Clément Rousset, Eric Guilyardi, Jean-Baptiste Sallée, Juliette Mignot, Christian Ethé, and Gurvan Madec
Geosci. Model Dev., 15, 7683–7713, https://doi.org/10.5194/gmd-15-7683-2022, https://doi.org/10.5194/gmd-15-7683-2022, 2022
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A modeling framework is introduced to understand and decompose the mechanisms causing the ocean temperature, salinity and circulation to change since the pre-industrial period and into 21st century scenarios of global warming. This framework aims to look at the response to changes in the winds and in heat and freshwater exchanges at the ocean interface in global climate models, throughout the 1850–2100 period, to unravel their individual effects on the changing physical structure of the ocean.
Aiko Voigt, Petra Schwer, Noam von Rotberg, and Nicole Knopf
Geosci. Model Dev., 15, 7489–7504, https://doi.org/10.5194/gmd-15-7489-2022, https://doi.org/10.5194/gmd-15-7489-2022, 2022
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
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OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Sergey Kravtsov, Ilijana Mastilovic, Andrew McC. Hogg, William K. Dewar, and Jeffrey R. Blundell
Geosci. Model Dev., 15, 7449–7469, https://doi.org/10.5194/gmd-15-7449-2022, https://doi.org/10.5194/gmd-15-7449-2022, 2022
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Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial scales and timescales. In hierarchical modeling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.
Feijia Yin, Volker Grewe, Federica Castino, Pratik Rao, Sigrun Matthes, Katrin Dahlmann, Simone Dietmüller, Christine Frömming, Hiroshi Yamashita, Patrick Peter, Emma Klingaman, Keith Shine, Benjamin Lührs, and Florian Linke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-220, https://doi.org/10.5194/gmd-2022-220, 2022
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This paper describes a newly developed submodel ACCF V1.0 based on the MESSy 2.53.0 infrastructure. The ACCF V1.0 is based on the prototype algorithmic climate change functions (aCCFs) v1.0 to enable climate-optimized flight trajectories. One highlight of this paper is that we, for the first time, describe a consistent set of aCCFs formulas w.r.t. fuel scenario and metrics. We demonstrate the usage of ACCF submodel using AirTraf V2.0 to optimize trajectories for cost and climate impact.
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
EGUsphere, https://doi.org/10.5194/egusphere-2022-943, https://doi.org/10.5194/egusphere-2022-943, 2022
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It is hard for scientists to write efficient code which runs fast on all kinds of supercomputers. They like writing Python because it is easier to read and use. We re-wrote a Fortran code that simulates weather and climate into Python. The Python code re-writes itself to a much faster language to run on either normal processors or graphics cards. On one big computer system, our code is 3.5–4x faster on its graphics cards than the original code is on its processors.
Ingo Wohltmann, Daniel Kreyling, and Ralph Lehmann
Geosci. Model Dev., 15, 7243–7255, https://doi.org/10.5194/gmd-15-7243-2022, https://doi.org/10.5194/gmd-15-7243-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Enrico Zorzetto, Sergey Malyshev, Nathaniel Chaney, David Paynter, Raymond Menzel, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2022-770, https://doi.org/10.5194/egusphere-2022-770, 2022
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In this paper we develop a methodology to model the spatial distribution of solar radiation received by land over mountainous terrain. The approach is designed to be used in Earth System Models, where coarse grid cells hinder the description of fine scale land-atmosphere interactions. We adopt a clustering algorithm to partiton land domain in a set of homogeneous sub-grid “tiles”, and for each evaluate solar radiation receive by land based on terrain properties.
Cited articles
Adam, O., Schneider, T., Brient, F., and Bischoff, T.: Relation of the double-ITCZ bias to the atmospheric energy budget in climate models, Geophys. Res. Lett., 43, 7670–7677, https://doi.org/10.1002/2016GL069465, 2016.
Adam, O., Schneider, T., and Brient, F.: Regional and seasonal variations of the double-ITCZ bias in CMIP5 models, Clim. Dynam., 51, 101–117, https://doi.org/10.1007/s00382-017-3909-1, 2018.
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., and Gruber, A.: The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003 (data available at: https://psl.noaa.gov/data/gridded/data.gpcp.html, last access: 1 August 2020).
Andrews, T., Andrews, M. B., Bodas-Salcedo, A., Jones, G. S., Kuhlbrodt, T., Manners, J., Menary, M. B., Ridley, J., Ringer, M. A., Sellar, A. A., and Senior, C. A.: Forcings, feedbacks, and climate sensitivity in HadGEM3-GC3. 1 and UKESM1, J. Adv. Model. Earth Sy., 11, 4377–4394, https://doi.org/10.1029/2019MS001866, 2019.
Bador, M., Boé, J., Terray, L., Alexander, L. V., Baker, A., Bellucci, A., Haarsma, R., Koenigk, T., Moine, M. P., Lohmann, K., and Putrasahan, D. A.: Impact of higher spatial atmospheric resolution on precipitation extremes over land in global climate models, J. Geophys. Res.-Atmos., 125, e2019JD032184, https://doi.org/10.1029/2019JD032184, 2020.
Beadling, R. L., Russell, J. L., Stouffer, R. J., Mazloff, M., Talley, L. D., Goodman, P. J., Sallée, J. B., Hewitt, H. T., Hyder, P., and Pandde, A.: Representation of Southern Ocean properties across coupled model intercomparison project generations: CMIP3 to CMIP6, J. Climate, 33, 6555–6581, https://doi.org/10.1175/JCLI-D-19-0970.1, 2020.
Bellucci, A., Athanasiadis, P. J., Scoccimarro, E., Ruggieri, P., Gualdi, S., Fedele, G., Haarsma, R. J., Garcia-Serrano, J., Castrillo, M., Putrahasan, D., and Sanchez-Gomez, E.: Air-Sea interaction over the Gulf Stream in an ensemble of HighResMIP present climate simulations, Clim. Dynam., 56, 2093–2111, https://doi.org/10.1007/s00382-020-05573-z, 2021.
Bischoff, T. and Schneider, T.: The equatorial energy balance, ITCZ position, and double-ITCZ bifurcations, J. Climate, 29, 2997–3013, https://doi.org/10.1175/JCLI-D-15-0328.1, 2016.
Boberg, F. and Christensen, J. H.: Overestimation of Mediterranean summer temperature projections due to model deficiencies, Nat. Clim. Change, 2, 433–436, https://doi.org/10.1038/nclimate1454, 2012.
Bodas-Salcedo, A., Williams, K. D., Field, P. R., and Lock, A. P.: The surface downwelling solar radiation surplus over the Southern Ocean in the Met Office model: The role of midlatitude cyclone clouds, J. Climate, 25, 7467–7486, https://doi.org/10.1175/JCLI-D-11-00702.1, 2012.
Bodas-Salcedo, A., Williams, K. D., Ringer, M. A., Beau, I., Cole, J. N., Dufresne, J. L., Koshiro, T., Stevens, B., Wang, Z., and Yokohata, T.: Origins of the solar radiation biases over the Southern Ocean in CFMIP2 models, J. Climate, 27, 41–56, https://doi.org/10.1175/JCLI-D-13-00169.1, 2014.
Bodas-Salcedo, A., Mulcahy, J. P., Andrews, T., Williams, K. D., Ringer, M. A., Field, P. R., and Elsaesser, G. S.: Strong dependence of atmospheric feedbacks on mixed-phase microphysics and aerosol-cloud interactions in HadGEM3, J. Adv. Model. Earth Sy., 11, 1735–1758, https://doi.org/10.1029/2019MS001688, 2019.
Bryan, F. O., Hecht, M. W., and Smith, R. D.: Resolution convergence and sensitivity studies with North Atlantic circulation models. Part I: The western boundary current system, Ocean Model., 16, 141–159, https://doi.org/10.1016/j.ocemod.2006.08.005, 2007.
Calisto, M., Folini, D., Wild, M., and Bengtsson, L.: Cloud radiative forcing intercomparison between fully coupled CMIP5 models and CERES satellite data, Ann. Geophys., 32, 793–807, https://doi.org/10.5194/angeo-32-793-2014, 2014.
Ceppi, P., Hwang, Y. T., Frierson, D. M., and Hartmann, D. L.: Southern Hemisphere jet latitude biases in CMIP5 models linked to shortwave cloud forcing, Geophys. Res. Lett., 39, L19708, https://doi.org/10.1029/2012GL053115, 2012.
Coward, A. and Roberts, M.: NERC HadGEM3-GC31-HH model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6039, 2018.
de Souza Custodio, M., Da Rocha, R. P., Ambrizzi, T., Vidale, P. L., and Demory, M. E.: Impact of increased horizontal resolution in coupled and atmosphere-only models of the HadGEM1 family upon the climate patterns of South America, Clim. Dynam., 48, 3341–3364, https://doi.org/10.1007/s00382-016-3271-8, 2017.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, D. P., and Bechtold, P.: 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.
Delworth, T. L., Rosati, A., Anderson, W., Adcroft, A. J., Balaji, V., Benson, R., Dixon, K., Griffies, S. M., Lee, H. C., Pacanowski, R. C., and Vecchi, G. A.: Simulated climate and climate change in the GFDL CM2.5 high-resolution coupled climate model, J. Climate, 25, 2755–2781, https://doi.org/10.1175/JCLI-D-11-00316.1, 2012.
Demory, M.-E., Berthou, S., Fernández, J., Sørland, S. L., Brogli, R., Roberts, M. J., Beyerle, U., Seddon, J., Haarsma, R., Schär, C., Buonomo, E., Christensen, O. B., Ciarlo`, J. M., Fealy, R., Nikulin, G., Peano, D., Putrasahan, D., Roberts, C. D., Senan, R., Steger, C., Teichmann, C., and Vautard, R.: European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, 2020.
Deppenmeier, A. L., Haarsma, R. J., van Heerwaarden, C., and Hazeleger, W.: The Southeastern Tropical Atlantic SST Bias Investigated with a Coupled Atmosphere–Ocean Single-Column Model at a PIRATA Mooring Site, J. Climate, 33, 6255–6271, https://doi.org/10.1175/JCLI-D-19-0608.1, 2020.
Doi, T., Vecchi, G. A., Rosati, A. J., and Delworth, T. L.: Biases in the Atlantic ITCZ in seasonal–interannual variations for a coarse-and a high-resolution coupled climate model, J. Climate, 25, 5494–5511, https://doi.org/10.1175/JCLI-D-11-00360.1, 2012.
Drews, A., Greatbatch, R. J., Ding, H., Latif, M., and Park, W.: The use of a flow field correction technique for alleviating the North Atlantic cold bias with application to the Kiel Climate Model, Ocean Dynam., 65, 1079–1093, https://doi.org/10.1007/s10236-015-0853-7, 2015.
EC-Earth Consortium (EC-Earth): EC-Earth-Consortium
EC-Earth3P-HR model output prepared for CMIP6 HighResMIP hist-1950,
Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4683, 2018.
EC-Earth Consortium (EC-Earth): EC-Earth-Consortium
EC-Earth3P model output prepared for CMIP6 HighResMIP hist-1950,
Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4682, 2019.
Exarchou, E., Prodhomme, C., Brodeau, L., Guemas, V., and Doblas-Reyes, F.: Origin of the warm eastern tropical Atlantic SST bias in a climate model, Clim. Dynam., 51, 1819–1840, https://doi.org/10.1007/s00382-017-3984-3, 2018.
Exarchou, E., Ortega, P., Rodríguez-Fonseca, B., Losada, T., Polo, I., and Prodhomme, C.: Impact of equatorial Atlantic variability on ENSO predictive skill, Nat. Commun., 12, 1–8, https://doi.org/10.1038/s41467-021-21857-2, 2021.
Eyring, V., Bock, L., Lauer, A., Righi, M., Schlund, M., Andela, B., Arnone, E., Bellprat, O., Brötz, B., Caron, L.-P., Carvalhais, N., Cionni, I., Cortesi, N., Crezee, B., Davin, E. L., Davini, P., Debeire, K., de Mora, L., Deser, C., Docquier, D., Earnshaw, P., Ehbrecht, C., Gier, B. K., Gonzalez-Reviriego, N., Goodman, P., Hagemann, S., Hardiman, S., Hassler, B., Hunter, A., Kadow, C., Kindermann, S., Koirala, S., Koldunov, N., Lejeune, Q., Lembo, V., Lovato, T., Lucarini, V., Massonnet, F., Müller, B., Pandde, A., Pérez-Zanón, N., Phillips, A., Predoi, V., Russell, J., Sellar, A., Serva, F., Stacke, T., Swaminathan, R., Torralba, V., Vegas-Regidor, J., von Hardenberg, J., Weigel, K., and Zimmermann, K.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP, Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, 2020.
Furtado, K. and Field, P.: The role of ice microphysics parametrizations in determining the prevalence of supercooled liquid water in high-resolution simulations of a Southern Ocean midlatitude cyclone, J. Atmos. Sci., 74, 2001–2021, https://doi.org/10.1175/JAS-D-16-0165.1, 2017.
Gent, P. R. and McWilliams, J. C.: Isopycnal mixing in ocean circulation models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990.
Gent, P. R., Yeager, S. G., Neale, R. B., Levis, S., and Bailey, D. A.: Improvements in a half degree atmosphere/land version of the CCSM, Clim. Dynam., 34, 819–833, https://doi.org/10.1007/s00382-009-0614-8, 2010.
Gleckler, P. J., Taylor, K. E., and Doutriaux, C.: Performance metrics for climate models, J. Geophys. Res.-Atmos., 113, D06104, https://doi.org/10.1029/2007JD008972, 2008.
Goubanova, K., Sanchez-Gomez, E., Frauen, C., and Voldoire, A.: Respective roles of remote and local wind stress forcings in the development of warm SST errors in the South-Eastern Tropical Atlantic in a coupled high-resolution model, Clim. Dynam., 52, 1359–1382, https://doi.org/10.1007/s00382-018-4197-0, 2019.
Grist, J. P., Josey, S. A., Sinha, B., Catto, J. L., Roberts, M. J., and Coward, A. C.: Future evolution of an eddy rich ocean associated with enhanced east Atlantic storminess in a coupled model projection, Geophys. Res. Lett., 48, p.e2021GL092719, https://doi.org/10.1029/2021GL092719, 2021.
Gutjahr, O., Putrasahan, D., Lohmann, K., Jungclaus, J. H., von Storch, J.-S., Brüggemann, N., Haak, H., and Stössel, A.: Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP), Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, 2019.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Haarsma, R., Acosta, M., Bakhshi, R., Bretonnière, P.-A., Caron, L.-P., Castrillo, M., Corti, S., Davini, P., Exarchou, E., Fabiano, F., Fladrich, U., Fuentes Franco, R., García-Serrano, J., von Hardenberg, J., Koenigk, T., Levine, X., Meccia, V. L., van Noije, T., van den Oord, G., Palmeiro, F. M., Rodrigo, M., Ruprich-Robert, Y., Le Sager, P., Tourigny, E., Wang, S., van Weele, M., and Wyser, K.: HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR – description, model computational performance and basic validation, Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, 2020.
Harlaß, J., Latif, M., and Park, W.: Alleviating tropical Atlantic sector biases in the Kiel climate model by enhancing horizontal and vertical atmosphere model resolution: climatology and interannual variability, Clim. Dynam., 50, 2605–2635, https://doi.org/10.1007/s00382-017-3760-4, 2018.
Hawcroft, M., Haywood, J. M., Collins, M., Jones, A., Jones, A. C., and Stephens, G.: Southern Ocean albedo, inter-hemispheric energy transports and the double ITCZ: Global impacts of biases in a coupled model, Clim. Dynam., 48, 2279–2295, https://doi.org/10.1007/s00382-016-3205-5, 2017.
Hazeleger, W. and Haarsma, R. J.: Sensitivity of tropical Atlantic climate to mixing in a coupled ocean–atmosphere model, Clim. Dynam., 25, 387–399, https://doi.org/10.1007/s00382-005-0047-y, 2005.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on pressure levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.6860a573, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020 (data available at: https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5, last access: 20 October 2021).
Hewitt, H. T., Bell, M. J., Chassignet, E. P., Czaja, A., Ferreira, D., Griffies, S. M., Hyder, P., McClean, J. L., New, A. L., and Roberts, M. J.: Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?, Ocean Model., 120, 120–136, https://doi.org/10.1016/j.ocemod.2017.11.002, 2017.
Hodges, K. I., Lee, R. W., and Bengtsson, L.: A comparison of extratropical cyclones in recent reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25, J. Climate, 24, 4888–4906, https://doi.org/10.1175/2011JCLI4097.1, 2011.
Hourdin, F., Găinusă-Bogdan, A., Braconnot, P., Dufresne, J. L., Traore, A. K., and Rio, C.: Air moisture control on ocean surface temperature, hidden key to the warm bias enigma, Geophys. Res. Lett., 42, 10–885, https://doi.org/10.1002/2015GL066764, 2015.
Hu, Z. Z., Huang, B., and Pegion, K.: Low cloud errors over the southeastern Atlantic in the NCEP CFS and their association with lower-tropospheric stability and air-sea interaction, J. Geophys. Res., 113, D12114, https://doi.org/10.1029/2007JD009514, 2008.
Huang, B., Hu, Z. Z., and Jha, B.: Evolution of model systematic errors in the tropical Atlantic basin from coupled climate hindcasts, Clim. Dynam., 28, 661–682, https://doi.org/10.1007/s00382-006-0223-8, 2007.
Hwang, Y. T. and Frierson, D. M.: Link between the double-Intertropical Convergence Zone problem and cloud biases over the Southern Ocean, P. Natl. Acad. Sci. USA, 110, 4935–4940, https://doi.org/10.1073/pnas.1213302110, 2013.
Hyder, P., Edwards, J. M., Allan, R. P., Hewitt, H. T., Bracegirdle, T. J., Gregory, J. M., Wood, R. A., Meijers, A. J., Mulcahy, J., Field, P., and Furtado, K.: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors, Nat. Commun., 9, 1–17, https://doi.org/10.1038/s41467-018-05634-2, 2018.
IPCC: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change, edited by:
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen,
S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK, New York, NY, USA, 1535 pp., 2013.
Jochum, M., Murtugudde, R., Ferrari, R., and Malanotte-Rizzoli, P.: The impact of horizontal resolution on the tropical heat budget in an Atlantic Ocean model, J. Climate, 18, 841–851, https://doi.org/10.1175/JCLI-3288.1, 2005.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling, D. R., Huang, X., Smith, W. L., Su, W., and Ham, S. H.: Surface irradiances of edition 4.0 clouds and the earth's radiant energy system (CERES) energy balanced and filled (EBAF) data product, J. Climate, 31, 4501–4527, https://doi.org/10.1175/JCLI-D-17-0523.1, 2018 (data available at: https://ceres.larc.nasa.gov/data/, last access: 20 October 2020).
Kay, J. E., Wall, C., Yettella, V., Medeiros, B., Hannay, C., Caldwell, P., and Bitz, C.: Global climate impacts of fixing the Southern Ocean shortwave radiation bias in the Community Earth System Model (CESM), J. Climate, 29, 4617–4636, https://doi.org/10.1175/JCLI-D-15-0358.1, 2016.
Keeley, S. P. E., Sutton, R. T., and Shaffrey, L. C.: The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate, Q. J. Roy. Meteor. Soc., 138, 1774–1783, https://doi.org/10.1002/qj.1912, 2012.
Kennedy, J., Titchner, H., Rayner, N., and Roberts, M. : input4MIPs.MOHC.SSTsAndSeaIce.HighResMIP.MOHC-HadISST-2-2-0-0-0, version 20170505, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/input4MIPs.1221, 2017.
Kirtman, B. P., Bitz, C., Bryan, F., Collins, W., Dennis, J., Hearn, N., Kinter, J. L., Loft, R., Rousset, C., Siqueira, L., and Stan, C.: Impact of ocean model resolution on CCSM climate simulations, Clim. Dynam., 39, 1303–1328, https://doi.org/10.1007/s00382-012-1500-3, 2012.
Klaver, R., Haarsma, R., Vidale, P. L., and Hazeleger, W.: Effective resolution in high resolution global atmospheric models for climate studies, Atmos. Sci. Lett., 21, e952, https://doi.org/10.1002/asl.952, 2020.
Klocke, D., Brueck, M., Hohenegger, C., and Stevens, B.: Rediscovery of the doldrums in storm-resolving simulations over the tropical Atlantic, Nat. Geosci., 10, 891–896, https://doi.org/10.1038/s41561-017-0005-4, 2017.
Koenigk, T., Fuentes-Franco, R., Meccia, V. L., Gutjahr, O., Jackson, L. C., New, A. L., Ortega, P., Roberts, C. D., Roberts, M. J., Arsouze, T., and Iovino, D.: Deep mixed ocean volume in the Labrador Sea in HighResMIP models, Clim. Dynam., 57, 1895–1918, https://doi.org/10.1007/s00382-021-05785-x, 2021.
Koseki, S., Keenlyside, N., Demissie, T., Toniazzo, T., Counillon, F., Bethke, I., Ilicak, M., and Shen, M. L.: Causes of the large warm bias in the Angola–Benguela Frontal Zone in the Norwegian Earth System Model, Clim. Dynam., 50, 4651–4670, https://doi.org/10.1007/s00382-017-3896-2, 2018.
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.
Lee, R. W., Woollings, T. J., Hoskins, B. J., Williams, K. D., O'Reilly, C. H., and Masato, G.: Impact of Gulf Stream SST biases on the global atmospheric circulation, Clim. Dynam., 51, 3369–3387, https://doi.org/10.1007/s00382-018-4083-9, 2018.
Li, G. and Xie, S. P.: Origins of tropical-wide SST biases in CMIP multi-model ensembles, Geophys. Res. Lett., 39, L22703, https://doi.org/10.1029/2012GL053777, 2012.
Li, G. and Xie, S. P.: Tropical biases in CMIP5 multimodel ensemble: The excessive equatorial Pacific cold tongue and double ITCZ problems, J. Climate, 27, 1765–1780, https://doi.org/10.1175/JCLI-D-13-00337.1, 2014.
Lin, J. L.: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean–atmosphere feedback analysis, J. Climate, 20, 4497–4525, https://doi.org/10.1175/JCLI4272.1, 2007.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the earth's radiant energy system (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) Edition-4.0 data product, J. Climate, 31, 895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Madec, G., Bourdallé-Badie, R., Bouttier, P.-A., Bricaud, C., Bruciaferri, D., Calvert, D., Jérôme Chanut, J., Clementi, E., Coward, A., Delrosso, D., Ethé, C., Flavoni, S., Graham, T., Harle, J., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S., Paul, J., Rousset, C., Storkey, D., Storto, A., and Vancoppenolle, M.: NEMO ocean engine (Version v3.6), Notes Du Pôle De Modélisation De L'institut Pierre-simon Laplace (IPSL), Zenodo, https://doi.org/10.5281/zenodo.1472492, 2017.
Maraun, D.: Bias correcting climate change simulations-a critical review, Current Climate Change Reports, 2, 211–220, https://doi.org/10.1007/s40641-016-0050-x, 2016.
Marzocchi, A., Hirschi, J. J. M., Holliday, N. P., Cunningham, S. A., Blaker, A. T., and Coward, A. C.: The North Atlantic subpolar circulation in an eddy-resolving global ocean model, J. Marine Syst., 142, 126–143, https://doi.org/10.1016/j.jmarsys.2014.10.007, 2015.
McClean, J. L., Bader, D. C., Bryan, F. O., Maltrud, M. E., Dennis, J. M., Mirin, A. A., Jones, P. W., Kim, Y. Y., Ivanova, D. P., Vertenstein, M., and Boyle, J. S.: A prototype two-decade fully-coupled fine-resolution CCSM simulation, Ocean Model., 39, 10–30, https://doi.org/10.1016/j.ocemod.2011.02.011, 2011.
McCoy, D. T., Hartmann, D. L., Zelinka, M. D., Ceppi, P., and Grosvenor, D. P.: Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models, J. Geophys. Res.-Atmos., 120, 9539–9554, https://doi.org/10.1002/2015JD023603, 2015.
Menary, M. B., Hodson, D. L., Robson, J. I., Sutton, R. T., Wood, R. A., and Hunt, J. A.: Exploring the impact of CMIP5 model biases on the simulation of North Atlantic decadal variability, Geophys. Res. Lett., 42, 5926–5934, https://doi.org/10.1002/2015GL064360, 2015.
Meehl, G. A., Goddard, L., Boer, G., Burgman, R., Branstator, G., Cassou, C., Corti, S., Danabasoglu, G., Doblas-Reyes, F., Hawkins, E., and Karspeck, A.: Decadal climate prediction: an update from the trenches, B. Am. Meteorol. Soc., 95, 243–267, https://doi.org/10.1175/BAMS-D-12-00241.1, 2014.
Mertens, C., Rhein, M., Walter, M., Böning, C. W., Behrens, E., Kieke, D., Steinfeldt, R., and Stöber, U.: Circulation and transports in the Newfoundland Basin, western subpolar North Atlantic, J. Geophys. Res.-Oceans, 119, 7772–7793, https://doi.org/10.1002/2014JC010019, 2014.
Milinski, S., Bader, J., Haak, H., Siongco, A. C., and Jungclaus, J. H.: High atmospheric horizontal resolution eliminates the wind-driven coastal warm bias in the southeastern tropical Atlantic, Geophys. Res. Lett., 43, 10455–10462, https://doi.org/10.1002/2016GL070530, 2016.
Monerie, P.-A., Chevuturi, A., Cook, P., Klingaman, N. P., and Holloway, C. E.: Role of atmospheric horizontal resolution in simulating tropical and subtropical South American precipitation in HadGEM3-GC31, Geosci. Model Dev., 13, 4749–4771, https://doi.org/10.5194/gmd-13-4749-2020, 2020.
Moreno-Chamarro, E.: Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models, Zenodo [data set], https://doi.org/10.5281/zenodo.5006136, 2021.
Moreno-Chamarro, E., Caron, L. P., Ortega, P., Tomas, S. L., and Roberts, M. J.: Can we trust CMIP5/6 future projections of European winter precipitation?, Environ. Res. Lett., 16, 054063, https://doi.org/10.1088/1748-9326/abf28a, 2021.
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M., Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H. Ilyina, T., Kleine, T., Kornblueh, L., Li, H., Modali, K., Notz, D., Pohlmann, H., Roeckner, E., Stemmler, I., Tian, F., and Marotzke, J.: A Higher-resolution Version of the Max Planck Institute Earth System Model (MPI-ESM1. 2-HR), J. Adv. Model. Earth Sy., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018.
Oueslati, B. and Bellon, G.: The double ITCZ bias in CMIP5 models: Interaction between SST, large-scale circulation and precipitation, Clim. Dynam., 44, 585–607, https://doi.org/10.1007/s00382-015-2468-6, 2015.
Patricola, C. M., Li, M., Xu, Z., Chang, P., Saravanan, R., and Hsieh, J. S.: An investigation of tropical Atlantic bias in a high-resolution coupled regional climate model, Clim. Dynam., 39, 2443–2463, https://doi.org/10.1007/s00382-012-1320-5, 2012.
Qin, Y. and Lin, Y.: Alleviated double ITCZ problem in the NCAR CESM1: A new cloud scheme and the working mechanisms, J. Adv. Model. Earth Sy., 10, 2318–2332, https://doi.org/10.1029/2018MS001343, 2018.
Raj, J., Bangalath, H. K., and Stenchikov, G.: West African Monsoon: current state and future projections in a high-resolution AGCM, Clim. Dynam., 52, 6441–6461, https://doi.org/10.1007/s00382-018-4522-7, 2019.
Richter, I.: Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward, Wires Clim. Change, 6, 345–358, https://doi.org/10.1002/wcc.338, 2015.
Richter, I. and Tokinaga, H.: An overview of the performance of CMIP6 models in the tropical Atlantic: mean state, variability, and remote impacts, Clim. Dynam., 55, 2579–2601, https://doi.org/10.1007/s00382-020-05409-w, 2020.
Richter, I., Xie, S. P., Wittenberg, A. T., and Masumoto, Y.: Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation, Clim. Dynam., 38, 985–1001, https://doi.org/10.1007/s00382-011-1038-9, 2012.
Roberts, C. D., Senan, R., Molteni, F., Boussetta, S.,
and Keeley, S.: ECMWF ECMWF-IFS-HR model output prepared for CMIP6
HighResMIP hist-1950, Earth System Grid Federation [data set],
https://doi.org/10.22033/ESGF/CMIP6.4981, 2017.
Roberts, C. D., Senan, R., Molteni, F., Boussetta, S., and Keeley, S.: ECMWF ECMWF-IFS-LR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4982, 2018a.
Roberts, C. D., Senan, R., Molteni, F., Boussetta, S., Mayer, M., and Keeley, S. P. E.: Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP, Geosci. Model Dev., 11, 3681–3712, https://doi.org/10.5194/gmd-11-3681-2018, 2018b.
Roberts, C. D., Vitart, F., Balmaseda, M. A., and Molteni, F.: The time-scale-dependent response of the wintertime North Atlantic to increased ocean model resolution in a coupled forecast model, J. Climate, 33, 3663–3689, https://doi.org/10.1175/JCLI-D-19-0235.1, 2020a.
Roberts, C. D., Weisheimer, A., Johnson, S., Stockdale,
T., Alonso-Balmaseda, M., Browne, P., Dawson, A., Leutbecher, M., and Vitart, F.: Reduced-resolution ocean configurations for efficient testing with the ECMWF coupled model, Technical memorandum, ECMWF Technical Memoranda, 858, https://doi.org/10.21957/6fz18mn9r, 2020b.
Roberts, M. J.: MOHC HadGEM3-GC31-LL model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6042, 2017.
Roberts, M. J., Vidale, P. L., Senior, C., Hewitt, H. T., Bates, C., Berthou, S., Chang, P., Christensen, H. M., Danilov, S., Demory, M. E., and Griffies, S. M.: The benefits of global high resolution for climate simulation: process understanding and the enabling of stakeholder decisions at the regional scale, B. Am. Meteorol. Soc., 99, 2341–2359, https://doi.org/10.1175/BAMS-D-15-00320.1, 2018.
Roberts, M. J., Baker, A., Blockley, E. W., Calvert, D., Coward, A., Hewitt, H. T., Jackson, L. C., Kuhlbrodt, T., Mathiot, P., Roberts, C. D., Schiemann, R., Seddon, J., Vannière, B., and Vidale, P. L.: Description of the resolution hierarchy of the global coupled HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments, Geosci. Model Dev., 12, 4999–5028, https://doi.org/10.5194/gmd-12-4999-2019, 2019.
Roberts, M. J., Camp, J., Seddon, J., Vidale, P. L., Hodges, K., Vanniere, B., Mecking, J., Haarsma, R., Bellucci, A., Scoccimarro, E., and Caron, L. P.: Impact of model resolution on tropical cyclone simulation using the HighResMIP–PRIMAVERA multimodel ensemble, J. Climate, 33, 2557–2583, https://doi.org/10.1175/JCLI-D-19-0639.1, 2020a.
Roberts, M. J., Jackson, L. C., Roberts, C. D., Meccia, V., Docquier, D., Koenigk, T., Ortega, P., Moreno-Chamarro, E., Bellucci, A., Coward, A., and Drijfhout, S.: Sensitivity of the Atlantic meridional overturning circulation to model resolution in CMIP6 HighResMIP simulations and implications for future changes, J. Adv. Model. Earth Sy., 12, e2019MS002014, https://doi.org/10.1029/2019MS002014, 2020b.
Samanta, D., Karnauskas, K. B., and Goodkin, N. F.: Tropical Pacific SST and ITCZ biases in climate models: Double trouble for future rainfall projections?, Geophys. Res. Lett., 46, 2242–2252, https://doi.org/10.1029/2018GL081363, 2019.
Scaife, A. A., Copsey, D., Gordon, C., Harris, C., Hinton, T., Keeley, S., O'Neill, A., Roberts, M., and Williams, K.: Improved Atlantic winter blocking in a climate model, Geophys. Res. Lett., 38, L23703, https://doi.org/10.1029/2011GL049573, 2011.
Schiemann, R., Vidale, P. L., Hatcher, R., and Roberts, M.: NERC HadGEM3-GC31-HM model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.446, 2019.
Schiemann, R., Athanasiadis, P., Barriopedro, D., Doblas-Reyes, F., Lohmann, K., Roberts, M. J., Sein, D. V., Roberts, C. D., Terray, L., and Vidale, P. L.: Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution, Weather Clim. Dynam., 1, 277–292, https://doi.org/10.5194/wcd-1-277-2020, 2020.
Schneider, D. P. and Reusch, D. B.: Antarctic and Southern Ocean surface temperatures in CMIP5 models in the context of the surface energy budget, J. Climate, 29, 1689–1716, https://doi.org/10.1175/JCLI-D-15-0429.1, 2016.
Schneider, T., Bischoff, T., and Haug, G. H.: Migrations and dynamics of the intertropical convergence zone, Nature, 513, 45–53, https://doi.org/10.1038/nature13636, 2014.
Seiki, T. and Roh, W.: Improvements in Supercooled Liquid Water Simulations of Low-Level Mixed-Phase Clouds over the Southern Ocean Using a Single-Column Model, J. Atmos. Sci., 77, 3803–3819, https://doi.org/10.1175/JAS-D-19-0266.1, 2020.
Seo, H., Jochum, M., Murtugudde, R., and Miller, A. J.: Effect of ocean mesoscale variability on the mean state of tropical Atlantic climate, Geophys. Res. Lett., 33, L09606, https://doi.org/10.1029/2005GL025651, 2006.
Siongco, A. C., Hohenegger, C., and Stevens, B.: The Atlantic ITCZ bias in CMIP5 models, Clim. Dynam., 45, 1169–1180, https://doi.org/10.1007/s00382-014-2366-3, 2016.
Small, R. J., Curchitser, E., Hedstrom, K., Kauffman, B., and Large, W. G.: The Benguela upwelling system: Quantifying the sensitivity to resolution and coastal wind representation in a global climate model, J. Climate, 28, 9409–9432, https://doi.org/10.1175/JCLI-D-15-0192.1, 2015.
Smith, R. D., Maltrud, M. E., Bryan, F. O., and Hecht, M. W.: Numerical simulation of the North Atlantic Ocean at 1
Song, F. and Zhang, G. J.: The Impacts of Horizontal Resolution on the Seasonally Dependent Biases of the Northeastern Pacific ITCZ in Coupled Climate Models, J. Climate, 33, 941–957, https://doi.org/10.1175/JCLI-D-19-0399.1, 2020.
Song, X. and Zhang, G. J.: Culprit of the eastern Pacific double-ITCZ bias in the NCAR CESM1.2, J. Climate, 32, 6349–6364, https://doi.org/10.1175/JCLI-D-18-0580.1, 2019.
Stengel, M., Stapelberg, S., Sus, O., Finkensieper, S., Würzler, B., Philipp, D., Hollmann, R., Poulsen, C., Christensen, M., and McGarragh, G.: Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset version 3: 35 year climatology of global cloud and radiation properties, Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, 2020 (data available at: https://climate.esa.int/en/projects/cloud/data/, last access: 20 October 2020).
Tan, I., Storelvmo, T., and Zelinka, M. D.: Observational constraints on mixed-phase clouds imply higher climate sensitivity, Science, 352, 224–227, https://doi.org/10.1126/science.aad5300, 2016.
Tian, B. and Dong, X.: The double-ITCZ bias in CMIP3, CMIP5, and CMIP6 models based on annual mean precipitation, Geophys. Res. Lett., 47, e2020GL087232, https://doi.org/10.1029/2020GL087232, 2020.
Vannière, B., Demory, M. E., Vidale, P. L., Schiemann, R., Roberts, M. J., Roberts, C. D., Matsueda, M., Terray, L., Koenigk, T., and Senan, R.: Multi-model evaluation of the sensitivity of the global energy budget and hydrological cycle to resolution, Clim. Dynam., 52, 6817–6846, https://doi.org/10.1007/s00382-018-4547-y, 2019.
Vannière, B., Roberts, M., Vidale, P. L., Hodges, K., Demory, M. E., Caron, L. P., Scoccimarro, E., Terray, L., and Senan, R.: The moisture budget of tropical cyclones in HighResMIP models: large-scale environmental balance and sensitivity to horizontal resolution, J. Climate, 33, 8457–8474, https://doi.org/10.1175/JCLI-D-19-0999.1, 2020.
Varma, V., Morgenstern, O., Field, P., Furtado, K., Williams, J., and Hyder, P.: Improving the Southern Ocean cloud albedo biases in a general circulation model, Atmos. Chem. Phys., 20, 7741–7751, https://doi.org/10.5194/acp-20-7741-2020, 2020.
Vidale, P. L., Hodges, K., Vannière, B., Davini, P., Roberts, M. J., Strommen, K., Weisheimer, A., Plesca, E., and Corti, S.: Impact of stochastic physics and model resolution on the simulation of Tropical Cyclones in climate GCMs, J. Climate, 34, 4315–4341, https://doi.org/10.1175/JCLI-D-20-0507.1, 2021.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1 model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4039, 2019a.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4040, 2019b.
Voldoire, A., Exarchou, E., Sanchez-Gomez, E., Demissie, T., Deppenmeier, A. L., Frauen, C., Goubanova, K., Hazeleger, W., Keenlyside, N., Koseki, S., and Prodhomme, C.: Role of wind stress in driving SST biases in the Tropical Atlantic, Clim. Dynam., 53, 3481–3504, https://doi.org/10.1007/s00382-019-04717-0, 2019a.
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J. F., Michou, M., Moine, M. P., and Nabat, P.: Evaluation of CMIP6 deck experiments with CNRM-CM6-1, J. Adv. Model. Earth Sy., 11, 2177–2213, https://doi.org/10.1029/2019MS001683, 2019b.
von Storch, H. and Zwiers, F. W.: Statistical analysis in climate research, Cambridge Univ. Press, New York, 484 pp., 1999.
von Storch, J.-S., Putrasahan, D., Lohmann, K., Gutjahr, O., Jungclaus, J., Bittner, M., Haak, H., Wieners, K.-H., Giorgetta, M., Reick, C., Esch, M., Gayler, V., de Vrese, P., Raddatz, T., Mauritsen, T., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Mülller, W., Nabel, J., Notz, D., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6586, 2018a.
von Storch, J.-S., Putrasahan, D., Lohmann, K., Gutjahr, O., Jungclaus, J., Bittner, M., Haak, H., Wieners, K.-H., Giorgetta, M., Reick, C., Esch, M., Gayler, V., de Vrese, P., Raddatz, T., Mauritsen, T., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-XR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.10307, 2018b.
Wang, C., Zhang, L., Lee, S. K., Wu, L., and Mechoso, C. R.: A global perspective on CMIP5 climate model biases, Nat. Clim. Change, 4, 201–205, https://doi.org/10.1038/nclimate2118, 2014.
Wengel, C., Lee, S. S., Stuecker, M. F., Timmermann, A., Chu, J. E., and Schloesser, F.: Future high-resolution El Niño/Southern Oscillation dynamics, Nat. Clim. Change, 1–8, https://doi.org/10.1038/s41558-021-01132-4, 2021.
Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., and Hyder, P.: The Met Office global coupled model 3.0 and 3.1 (GC3.0 and GC3.1) configurations, J. Adv. Model. Earth Sy., 10, 357–380, https://doi.org/10.1002/2017MS001115, 2017.
Willison, J., Robinson, W. A., and Lackmann, G. M.: The importance of resolving mesoscale latent heating in the North Atlantic storm track, J. Atmos. Sci., 70, 2234–2250, https://doi.org/10.1175/JAS-D-12-0226.1, 2013.
Xu, Z., Chang, P., Richter, I., and Tang, G.: Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble, Clim. Dynam., 43, 3123–3145, https://doi.org/10.1007/s00382-014-2247-9, 2014a.
Xu, Z., Li, M., Patricola, C. M., and Chang, P.: Oceanic origin of southeast tropical Atlantic biases, Clim. Dynam., 43, 2915–2930, https://doi.org/10.1007/s00382-013-1901-y, 2014b.
Zhang, G. J. and Wang, H.: Toward mitigating the double ITCZ problem in NCAR CCSM3, Geophys. Res. Lett., 33, L06709, https://doi.org/10.1029/2005GL025229, 2006.
Zhang, G. J., Song, X., and Wang, Y: The double ITCZ syndrome in GCMs: A coupled feedback problem among convection, clouds, atmospheric and ocean circulations, Atmos. Res., 229, 255–268, https://doi.org/10.1016/j.atmosres.2019.06.023, 2019.
Zhang, W., Villarini, G., Scoccimarro, E., Roberts, M., Vidale, P. L., Vanniere, B., Caron, L. P., Putrasahan, D., Roberts, C., Senan, R., and Moine, M. P.: Tropical cyclone precipitation in the HighResMIP atmosphere-only experiments of the PRIMAVERA Project, Clim. Dynam., 57, 253–273, https://doi.org/10.1007/s00382-021-05707-x, 2021.
Zhang, X., Liu, H., and Zhang, M.: Double ITCZ in coupled ocean-atmosphere models: From CMIP3 to CMIP5, Geophys. Res. Lett., 42, 8651–8659, https://doi.org/10.1002/2015GL065973, 2015.
Zhou, W. and Xie, S. P.: Intermodel spread of the double-ITCZ bias in coupled GCMs tied to land surface temperature in AMIP GCMs, Geophys. Res. Lett., 44, 7975–7984, https://doi.org/10.1002/2017GL074377, 2017.
Short summary
Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Climate models do not fully reproduce observations: they show differences (biases) in regional...
