Articles | Volume 16, issue 24
https://doi.org/10.5194/gmd-16-7461-2023
© Author(s) 2023. 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-16-7461-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| Highlight paper
| 
21 Dec 2023
Model description paper | Highlight paper |
| 21 Dec 2023
| 21 Dec 2023
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Department of Earth and Planetary Sciences, Rutgers University, Piscataway, NJ, USA
Rutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USA
Gregory G. Garner
Department of Earth and Planetary Sciences, Rutgers University, Piscataway, NJ, USA
Rutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USA
current address: Gro Intelligence, New York, NY, USA
Tim H. J. Hermans
Department of Estuarine & Delta Systems, NIOZ Royal Netherlands Institute for Sea Research, Yerseke, the Netherlands
Institute for Marine and Atmospheric research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands
Shantenu Jha
Rutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USA
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA
Praveen Kumar
Department of Earth and Planetary Sciences, Rutgers University, Piscataway, NJ, USA
Rutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USA
Alexander Reedy
Department of Earth and Planetary Sciences, Rutgers University, Piscataway, NJ, USA
Rutgers Climate and Energy Institute, Rutgers University, New Brunswick, NJ, USA
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
Aimée B. A. Slangen
Department of Estuarine & Delta Systems, NIOZ Royal Netherlands Institute for Sea Research, Yerseke, the Netherlands
Matteo Turilli
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA
Tamsin L. Edwards
Department of Geography, King's College London, London, UK
Jonathan M. Gregory
Met Office Hadley Centre, Exeter, UK
National Centre for Atmospheric Science, University of Reading, Reading, UK
George Koubbe
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
Anders Levermann
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Physics Institute, Potsdam University, Potsdam, Germany
Andre Merzky
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
Sophie Nowicki
Department of Geology, University at Buffalo, Buffalo, NY, USA
Matthew D. Palmer
Met Office Hadley Centre, Exeter, UK
School of Earth Sciences, University of Bristol, Bristol, UK
Chris Smith
Priestley International Centre for Climate, University of Leeds, UK
Energy, Climate and Environment Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
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Denis Felikson, Sophie Nowicki, Isabel Nias, Beata Csatho, Anton Schenk, Michael J. Croteau, and Bryant Loomis
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Anja Katzenberger and Anders Levermann
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2023-19, https://doi.org/10.5194/esd-2023-19, 2023
Revised manuscript accepted for ESD
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Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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Víctor Malagón-Santos, Aimée B. A. Slangen, Tim H. J. Hermans, Sönke Dangendorf, Marta Marcos, and Nicola Maher
Ocean Sci., 19, 499–515, https://doi.org/10.5194/os-19-499-2023, https://doi.org/10.5194/os-19-499-2023, 2023
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Climate change will alter heat and freshwater fluxes as well as ocean circulation, driving local changes in sea level. This sea-level change component is known as ocean dynamic sea level (DSL), and it is usually projected using computationally expensive global climate models. Statistical models are a cheaper alternative for projecting DSL but may contain significant errors. Here, we partly remove those errors (driven by internal climate variability) by using pattern recognition techniques.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Johannes Feldmann and Anders Levermann
The Cryosphere, 17, 327–348, https://doi.org/10.5194/tc-17-327-2023, https://doi.org/10.5194/tc-17-327-2023, 2023
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Here we present a scaling relation that allows the comparison of the timescales of glaciers with geometric similarity. According to the relation, thicker and wider glaciers on a steeper bed slope have a much faster timescale than shallower, narrower glaciers on a flatter bed slope. The relation is supported by observations and simplified numerical simulations. We combine the scaling relation with a statistical analysis of the topography of 13 instability-prone Antarctic outlet glaciers.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, Eike M. Schütt, Marta Marcos, Ismael Hernandez-Carrasco, and Aimée B. A. Slangen
Ocean Sci., 19, 17–41, https://doi.org/10.5194/os-19-17-2023, https://doi.org/10.5194/os-19-17-2023, 2023
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Sea-level change is mainly caused by variations in the ocean’s temperature and salinity and land ice melting. Here, we quantify the contribution of the different drivers to the regional sea-level change. We apply machine learning techniques to identify regions that have similar sea-level variability. These regions reduce the observational uncertainty that has limited the regional sea-level budget so far and highlight how large-scale ocean circulation controls regional sea-level change.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Antony Siahaan, Robin S. Smith, Paul R. Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Antony J. Payne, Jeff K. Ridley, and Colin G. Jones
The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, https://doi.org/10.5194/tc-16-4053-2022, 2022
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The UK Earth System Model is the first to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under the low-greenhouse-gas SSP1–1.9 (Shared Socioeconomic Pathway) scenario, the ice sheet remains stable over the 21st century. Under the strong-greenhouse-gas SSP5–8.5 scenario, the model predicts strong increases in melting of large ice shelves and snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, and Aimée B. A. Slangen
Earth Syst. Dynam., 13, 1351–1375, https://doi.org/10.5194/esd-13-1351-2022, https://doi.org/10.5194/esd-13-1351-2022, 2022
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The mass loss from Antarctica, Greenland and glaciers and variations in land water storage cause sea-level changes. Here, we characterize the regional trends within these sea-level contributions, taking into account mass variations since 1993. We take a comprehensive approach to determining the uncertainties of these sea-level changes, considering different types of errors. Our study reveals the importance of clearly quantifying the uncertainties of sea-level change trends.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
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Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Joseph A. MacGregor, Winnie Chu, William T. Colgan, Mark A. Fahnestock, Denis Felikson, Nanna B. Karlsson, Sophie M. J. Nowicki, and Michael Studinger
The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, https://doi.org/10.5194/tc-16-3033-2022, 2022
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Where the bottom of the Greenland Ice Sheet is frozen and where it is thawed is not well known, yet knowing this state is increasingly important to interpret modern changes in ice flow there. We produced a second synthesis of knowledge of the basal thermal state of the ice sheet using airborne and satellite observations and numerical models. About one-third of the ice sheet’s bed is likely thawed; two-fifths is likely frozen; and the remainder is too uncertain to specify.
Tanja Schlemm, Johannes Feldmann, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 16, 1979–1996, https://doi.org/10.5194/tc-16-1979-2022, https://doi.org/10.5194/tc-16-1979-2022, 2022
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Marine cliff instability, if it exists, could dominate Antarctica's contribution to future sea-level rise. It is likely to speed up with ice thickness and thus would accelerate in most parts of Antarctica. Here, we investigate a possible mechanism that might stop cliff instability through cloaking by ice mélange. It is only a first step, but it shows that embayment geometry is, in principle, able to stop marine cliff instability in most parts of West Antarctica.
Johannes Feldmann, Ronja Reese, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 16, 1927–1940, https://doi.org/10.5194/tc-16-1927-2022, https://doi.org/10.5194/tc-16-1927-2022, 2022
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We use a numerical model to simulate the flow of a simplified, buttressed Antarctic-type outlet glacier with an attached ice shelf. We find that after a few years of perturbation such a glacier responds much stronger to melting under the ice-shelf shear margins than to melting in the central fast streaming part of the ice shelf. This study explains the underlying physical mechanism which might gain importance in the future if melt rates under the Antarctic ice shelves continue to increase.
Erica L. Ashe, Nicole S. Khan, Lauren T. Toth, Andrea Dutton, and Robert E. Kopp
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 1–29, https://doi.org/10.5194/ascmo-8-1-2022, https://doi.org/10.5194/ascmo-8-1-2022, 2022
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We develop a new technique to integrate realistic uncertainties in probabilistic models of past sea-level change. The new framework performs better than past methods (in precision, accuracy, bias, and model fit) because it enables the incorporation of previously unused data and exploits correlations in the data. This method has the potential to assess the validity of past estimates of extreme sea-level rise and highstands providing better context in which to place current sea-level change.
Robin S. Smith, Steve George, and Jonathan M. Gregory
Geosci. Model Dev., 14, 5769–5787, https://doi.org/10.5194/gmd-14-5769-2021, https://doi.org/10.5194/gmd-14-5769-2021, 2021
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Many of the complex computer models used to study the physics of the natural world treat ice sheets as fixed and unchanging, capable of only simple interactions with the rest of the climate. This is partly because it is technically very difficult to usefully do anything more realistic. We have adapted a climate model so it can be joined together with a dynamical model of the Greenland ice sheet. This gives us a powerful tool to help us better understand how ice sheets and the climate interact.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036, https://doi.org/10.5194/gmd-14-3007-2021, https://doi.org/10.5194/gmd-14-3007-2021, 2021
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This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Anja Katzenberger, Jacob Schewe, Julia Pongratz, and Anders Levermann
Earth Syst. Dynam., 12, 367–386, https://doi.org/10.5194/esd-12-367-2021, https://doi.org/10.5194/esd-12-367-2021, 2021
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All state-of-the-art global climate models that contributed to the latest Coupled Model Intercomparison Project (CMIP6) show a robust increase in Indian summer monsoon rainfall that is even stronger than in the previous intercomparison (CMIP5). Furthermore, they show an increase in the year-to-year variability of this seasonal rainfall that crucially influences the livelihood of more than 1 billion people in India.
William H. Lipscomb, Gunter R. Leguy, Nicolas C. Jourdain, Xylar Asay-Davis, Hélène Seroussi, and Sophie Nowicki
The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, https://doi.org/10.5194/tc-15-633-2021, 2021
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This paper describes Antarctic climate change experiments in which the Community Ice Sheet Model is forced with ocean warming predicted by global climate models. Generally, ice loss begins slowly, accelerates by 2100, and then continues unabated, with widespread retreat of the West Antarctic Ice Sheet. The mass loss by 2500 varies from about 150 to 1300 mm of equivalent sea level rise, based on the predicted ocean warming and assumptions about how this warming drives melting beneath ice shelves.
Tanja Schlemm and Anders Levermann
The Cryosphere, 15, 531–545, https://doi.org/10.5194/tc-15-531-2021, https://doi.org/10.5194/tc-15-531-2021, 2021
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Ice loss from Greenland and Antarctica is often cloaked by a mélange of icebergs and sea ice. Here we provide a simple method to parametrize the resulting back stress on the ice flow for large-scale projection models.
Gillian Thornhill, William Collins, Dirk Olivié, Ragnhild B. Skeie, Alex Archibald, Susanne Bauer, Ramiro Checa-Garcia, Stephanie Fiedler, Gerd Folberth, Ada Gjermundsen, Larry Horowitz, Jean-Francois Lamarque, Martine Michou, Jane Mulcahy, Pierre Nabat, Vaishali Naik, Fiona M. O'Connor, Fabien Paulot, Michael Schulz, Catherine E. Scott, Roland Séférian, Chris Smith, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, and James Weber
Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, https://doi.org/10.5194/acp-21-1105-2021, 2021
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We find that increased temperatures affect aerosols and reactive gases by changing natural emissions and their rates of removal from the atmosphere. Changing the composition of these species in the atmosphere affects the radiative budget of the climate system and therefore amplifies or dampens the climate response of climate models of the Earth system. This study found that the largest effect is a dampening of climate change as warmer temperatures increase the emissions of cooling aerosols.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Jonathan M. Gregory, Steven E. George, and Robin S. Smith
The Cryosphere, 14, 4299–4322, https://doi.org/10.5194/tc-14-4299-2020, https://doi.org/10.5194/tc-14-4299-2020, 2020
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Melting of the Greenland ice sheet as a consequence of global warming could raise global-mean sea level by up to 7 m. We have studied this using a newly developed computer model. With recent climate maintained, sea level would rise by 0.5–2.5 m over many millennia due to Greenland ice loss: the warmer the climate, the greater the sea level rise. Beyond about 3.5 m it would become partially irreversible. In order to avoid this outcome, anthropogenic climate change must be reversed soon enough.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Maria Zeitz, Anders Levermann, and Ricarda Winkelmann
The Cryosphere, 14, 3537–3550, https://doi.org/10.5194/tc-14-3537-2020, https://doi.org/10.5194/tc-14-3537-2020, 2020
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The flow of ice drives mass losses in the large ice sheets. Sea-level rise projections rely on ice-sheet models, solving the physics of ice flow and melt. Unfortunately the parameters in the physics of flow are uncertain. Here we show, in an idealized setup, that these uncertainties can double flow-driven mass losses within the possible range of parameters. It is possible that this uncertainty carries over to realistic sea-level rise projections.
Eric Larour, Lambert Caron, Mathieu Morlighem, Surendra Adhikari, Thomas Frederikse, Nicole-Jeanne Schlegel, Erik Ivins, Benjamin Hamlington, Robert Kopp, and Sophie Nowicki
Geosci. Model Dev., 13, 4925–4941, https://doi.org/10.5194/gmd-13-4925-2020, https://doi.org/10.5194/gmd-13-4925-2020, 2020
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ISSM-SLPS is a new projection system for future sea level that increases the resolution and accuracy of current projection systems and improves the way uncertainty is treated in such projections. This will pave the way for better inclusion of state-of-the-art results from existing intercomparison efforts carried out by the scientific community, such as GlacierMIP2 or ISMIP6, into sea-level projections.
Nicolas C. Jourdain, Xylar Asay-Davis, Tore Hattermann, Fiammetta Straneo, Hélène Seroussi, Christopher M. Little, and Sophie Nowicki
The Cryosphere, 14, 3111–3134, https://doi.org/10.5194/tc-14-3111-2020, https://doi.org/10.5194/tc-14-3111-2020, 2020
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To predict the future Antarctic contribution to sea level rise, we need to use ice sheet models. The Ice Sheet Model Intercomparison Project for AR6 (ISMIP6) builds an ensemble of ice sheet projections constrained by atmosphere and ocean projections from the 6th Coupled Model Intercomparison Project (CMIP6). In this work, we present and assess a method to derive ice shelf basal melting in ISMIP6 from the CMIP6 ocean outputs, and we give examples of projected melt rates.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
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In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Hélène Seroussi, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
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The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
Ronja Reese, Anders Levermann, Torsten Albrecht, Hélène Seroussi, and Ricarda Winkelmann
The Cryosphere, 14, 3097–3110, https://doi.org/10.5194/tc-14-3097-2020, https://doi.org/10.5194/tc-14-3097-2020, 2020
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We compare 21st century projections of Antarctica's future sea-level contribution simulated with the Parallel Ice Sheet Model submitted to ISMIP6 with projections following the LARMIP-2 protocol based on the same model configuration. We find that (1) a preceding historic simulation increases mass loss by 5–50 % and that (2) the order of magnitude difference in the ice loss in our experiments following the two protocols can be explained by the translation of ocean forcing to sub-shelf melting.
Christopher J. Smith, Ryan J. Kramer, and Adriana Sima
Earth Syst. Sci. Data, 12, 2157–2168, https://doi.org/10.5194/essd-12-2157-2020, https://doi.org/10.5194/essd-12-2157-2020, 2020
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Radiative kernels allow efficient diagnosis of climate feedbacks and radiative adjustments to an external forcing using standard climate model output. We present a radiative kernel derived from the UK Met Office's HadGEM3-GA7.1 climate model. We show that a highly resolved stratosphere is important for correctly diagnosing the stratospheric temperature adjustment to greenhouse gas forcings and, by extension, the instantaneous radiative forcing.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
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The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Sophie Nowicki, Heiko Goelzer, Hélène Seroussi, Anthony J. Payne, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Patrick Alexander, Xylar S. Asay-Davis, Alice Barthel, Thomas J. Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan M. Gregory, Tore Hattermann, Nicolas C. Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher M. Little, Mathieu Morlighem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin S. Smith, Fiammetta Straneo, Luke D. Trusel, Michiel R. van den Broeke, and Roderik van de Wal
The Cryosphere, 14, 2331–2368, https://doi.org/10.5194/tc-14-2331-2020, https://doi.org/10.5194/tc-14-2331-2020, 2020
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This paper describes the experimental protocol for ice sheet models taking part in the Ice Sheet Model Intercomparion Project for CMIP6 (ISMIP6) and presents an overview of the atmospheric and oceanic datasets to be used for the simulations. The ISMIP6 framework allows for exploring the uncertainty in 21st century sea level change from the Greenland and Antarctic ice sheets.
Nicolas Bellouin, Will Davies, Keith P. Shine, Johannes Quaas, Johannes Mülmenstädt, Piers M. Forster, Chris Smith, Lindsay Lee, Leighton Regayre, Guy Brasseur, Natalia Sudarchikova, Idir Bouarar, Olivier Boucher, and Gunnar Myhre
Earth Syst. Sci. Data, 12, 1649–1677, https://doi.org/10.5194/essd-12-1649-2020, https://doi.org/10.5194/essd-12-1649-2020, 2020
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Quantifying the imbalance in the Earth's energy budget caused by human activities is important to understand and predict climate changes. This study presents new estimates of the imbalance caused by changes in atmospheric concentrations of carbon dioxide, methane, ozone, and particles of pollution. Over the period 2003–2017, the overall imbalance has been positive, indicating that the climate system has gained energy and will warm further.
Heiko Goelzer, Brice P. Y. Noël, Tamsin L. Edwards, Xavier Fettweis, Jonathan M. Gregory, William H. Lipscomb, Roderik S. W. van de Wal, and Michiel R. van den Broeke
The Cryosphere, 14, 1747–1762, https://doi.org/10.5194/tc-14-1747-2020, https://doi.org/10.5194/tc-14-1747-2020, 2020
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Future sea-level change projections with process-based ice sheet models are typically driven with surface mass balance forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the one used by the climate model. The proposed remapping method reproduces the original forcing data closely when applied to the original geometry and produces a physically meaningful forcing when applied to different modelled geometries.
Andreas Wernecke, Tamsin L. Edwards, Isabel J. Nias, Philip B. Holden, and Neil R. Edwards
The Cryosphere, 14, 1459–1474, https://doi.org/10.5194/tc-14-1459-2020, https://doi.org/10.5194/tc-14-1459-2020, 2020
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We investigate how the two-dimensional characteristics of ice thickness change from satellite measurements can be used to judge and refine a high-resolution ice sheet model of Antarctica. The uncertainty in 50-year model simulations for the currently most drastically changing part of Antarctica can be reduced by nearly 40 % compared to a simpler, non-spatial approach and nearly 90 % compared to the original spread in simulations.
Donald A. Slater, Denis Felikson, Fiamma Straneo, Heiko Goelzer, Christopher M. Little, Mathieu Morlighem, Xavier Fettweis, and Sophie Nowicki
The Cryosphere, 14, 985–1008, https://doi.org/10.5194/tc-14-985-2020, https://doi.org/10.5194/tc-14-985-2020, 2020
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Changes in the ocean around Greenland play an important role in determining how much the ice sheet will contribute to global sea level over the coming century. However, capturing these links in models is very challenging. This paper presents a strategy enabling an ensemble of ice sheet models to feel the effect of the ocean for the first time and should therefore result in a significant improvement in projections of the Greenland ice sheet's contribution to future sea level change.
Long Jiang, Theo Gerkema, Déborah Idier, Aimée B. A. Slangen, and Karline Soetaert
Ocean Sci., 16, 307–321, https://doi.org/10.5194/os-16-307-2020, https://doi.org/10.5194/os-16-307-2020, 2020
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A model downscaling approach is used to investigate the effects of sea-level rise (SLR) on local tides. Results indicate that SLR induces larger increases in tidal amplitude and stronger nonlinear tidal distortion in the bay compared to the adjacent shelf sea. SLR can also change shallow-water tidal asymmetry and influence the direction and magnitude of bed-load sediment transport. The model downscaling approach is widely applicable for local SLR projections in estuaries and coastal bays.
Alice Barthel, Cécile Agosta, Christopher M. Little, Tore Hattermann, Nicolas C. Jourdain, Heiko Goelzer, Sophie Nowicki, Helene Seroussi, Fiammetta Straneo, and Thomas J. Bracegirdle
The Cryosphere, 14, 855–879, https://doi.org/10.5194/tc-14-855-2020, https://doi.org/10.5194/tc-14-855-2020, 2020
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We compare existing coupled climate models to select a total of six models to provide forcing to the Greenland and Antarctic ice sheet simulations of the Ice Sheet Model Intercomparison Project (ISMIP6). We select models based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century.
Torsten Albrecht, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 14, 633–656, https://doi.org/10.5194/tc-14-633-2020, https://doi.org/10.5194/tc-14-633-2020, 2020
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A large ensemble of glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) was analyzed in which four relevant model parameters were systematically varied. These parameters were selected in a companion study and are associated with uncertainties in ice dynamics, climatic forcing, basal sliding and solid Earth deformation. For each ensemble member a statistical score is computed, which enables calibrating the model against both modern and geologic data.
Torsten Albrecht, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 14, 599–632, https://doi.org/10.5194/tc-14-599-2020, https://doi.org/10.5194/tc-14-599-2020, 2020
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During the last glacial cycles the Antarctic Ice Sheet experienced alternating climatic conditions and varying sea-level history. In response, changes in ice sheet volume and ice-covered area occurred, implying feedbacks on the global sea level. We ran model simulations of the ice sheet with the Parallel Ice Sheet Model (PISM) over the last two glacial cycles to evaluate the model's sensitivity to different choices of boundary conditions and parameters to gain confidence for future projections.
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
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We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Nicholas James Leach, Zebedee Nicholls, Stuart Jenkins, Christopher J. Smith, John Lynch, Michelle Cain, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-379, https://doi.org/10.5194/gmd-2019-379, 2020
Revised manuscript not accepted
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GIR is a simple climate model designed to make exploration of the impact of greenhouse gas and aerosol emissions on the climate easy and understandable for its users. It uses an intuitive input and output structure, and the model is itself a set of only six equations. This lends the model to applications such as teaching, or as a lowest common denominator model between groups in large-scale climate assessments. It could also be used to investigate more complex models through emulation.
Falko Ueckerdt, Katja Frieler, Stefan Lange, Leonie Wenz, Gunnar Luderer, and Anders Levermann
Earth Syst. Dynam., 10, 741–763, https://doi.org/10.5194/esd-10-741-2019, https://doi.org/10.5194/esd-10-741-2019, 2019
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We compute the global mean temperature increase at which the costs from climate-change damages and climate-change mitigation are minimal. This temperature is computed robustly around 2 degrees of global warming across a wide range of normative assumptions on the valuation of future welfare and inequality aversion.
Tanja Schlemm and Anders Levermann
The Cryosphere, 13, 2475–2488, https://doi.org/10.5194/tc-13-2475-2019, https://doi.org/10.5194/tc-13-2475-2019, 2019
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We provide a simple stress-based parameterization for cliff calving of ice sheets. According to the resulting increasing dependence of the calving rate on ice thickness, the parameterization might lead to a runaway ice loss in large parts of Greenland and Antarctica.
Anders Levermann and Johannes Feldmann
The Cryosphere, 13, 1621–1633, https://doi.org/10.5194/tc-13-1621-2019, https://doi.org/10.5194/tc-13-1621-2019, 2019
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Using scaling analysis we propose that the currently observed marine ice-sheet instability in the Amundsen Sea sector might be faster than all other potential instabilities in Antarctica.
Hélène Seroussi, Sophie Nowicki, Erika Simon, Ayako Abe-Ouchi, Torsten Albrecht, Julien Brondex, Stephen Cornford, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Thomas Kleiner, Eric Larour, Gunter Leguy, William H. Lipscomb, Daniel Lowry, Matthias Mengel, Mathieu Morlighem, Frank Pattyn, Anthony J. Payne, David Pollard, Stephen F. Price, Aurélien Quiquet, Thomas J. Reerink, Ronja Reese, Christian B. Rodehacke, Nicole-Jeanne Schlegel, Andrew Shepherd, Sainan Sun, Johannes Sutter, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, and Tong Zhang
The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, https://doi.org/10.5194/tc-13-1441-2019, 2019
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We compare a wide range of Antarctic ice sheet simulations with varying initialization techniques and model parameters to understand the role they play on the projected evolution of this ice sheet under simple scenarios. Results are improved compared to previous assessments and show that continued improvements in the representation of the floating ice around Antarctica are critical to reduce the uncertainty in the future ice sheet contribution to sea level rise.
Johannes Feldmann, Ronja Reese, Ricarda Winkelmann, and Anders Levermann
The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-109, https://doi.org/10.5194/tc-2018-109, 2018
Revised manuscript not accepted
Christopher J. Smith, Piers M. Forster, Myles Allen, Nicholas Leach, Richard J. Millar, Giovanni A. Passerello, and Leighton A. Regayre
Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, https://doi.org/10.5194/gmd-11-2273-2018, 2018
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FAIR v1.3 is a simple Python-based climate model emulator. It takes emissions of greenhouse gases and aerosol and ozone precursors to calculate radiative forcing and temperature change. It includes a simple representation of carbon cycle feedbacks due to temperature and accumulated carbon uptake. Large ensembles can be run with minimal computational expense for any user-specified emissions pathway. We produce such an ensemble using the RCP emissions datasets.
Heiko Goelzer, Sophie Nowicki, Tamsin Edwards, Matthew Beckley, Ayako Abe-Ouchi, Andy Aschwanden, Reinhard Calov, Olivier Gagliardini, Fabien Gillet-Chaulet, Nicholas R. Golledge, Jonathan Gregory, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Joseph H. Kennedy, Eric Larour, William H. Lipscomb, Sébastien Le clec'h, Victoria Lee, Mathieu Morlighem, Frank Pattyn, Antony J. Payne, Christian Rodehacke, Martin Rückamp, Fuyuki Saito, Nicole Schlegel, Helene Seroussi, Andrew Shepherd, Sainan Sun, Roderik van de Wal, and Florian A. Ziemen
The Cryosphere, 12, 1433–1460, https://doi.org/10.5194/tc-12-1433-2018, https://doi.org/10.5194/tc-12-1433-2018, 2018
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We have compared a wide spectrum of different initialisation techniques used in the ice sheet modelling community to define the modelled present-day Greenland ice sheet state as a starting point for physically based future-sea-level-change projections. Compared to earlier community-wide comparisons, we find better agreement across different models, which implies overall improvement of our understanding of what is needed to produce such initial states.
David Hassell, Jonathan Gregory, Jon Blower, Bryan N. Lawrence, and Karl E. Taylor
Geosci. Model Dev., 10, 4619–4646, https://doi.org/10.5194/gmd-10-4619-2017, https://doi.org/10.5194/gmd-10-4619-2017, 2017
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We present a formal data model for version 1.6 of the CF (Climate and Forecast) metadata conventions that provide a description of the physical meaning of geoscientific data and their spatial and temporal properties. We describe the CF conventions and how they lead to our CF data model, and compare it other data models for storing data and metadata. We present cf-python version 2.1: a software implementation of the CF data model capable of manipulating any CF-compliant dataset.
Renske C. de Winter, Thomas J. Reerink, Aimée B. A. Slangen, Hylke de Vries, Tamsin Edwards, and Roderik S. W. van de Wal
Nat. Hazards Earth Syst. Sci., 17, 2125–2141, https://doi.org/10.5194/nhess-17-2125-2017, https://doi.org/10.5194/nhess-17-2125-2017, 2017
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This paper provides a full range of possible future sea levels on a regional scale, since it includes extreme, but possible, contributions to sea level change from dynamical mass loss from the Greenland and Antarctica ice sheets. In contrast to the symmetric distribution used in the IPCC report, it is found that an asymmetric distribution toward high sea level change values locally can increase the mean sea level by 1.8 m this century.
Johannes Feldmann and Anders Levermann
The Cryosphere, 11, 1913–1932, https://doi.org/10.5194/tc-11-1913-2017, https://doi.org/10.5194/tc-11-1913-2017, 2017
Tony E. Wong, Alexander M. R. Bakker, Kelsey Ruckert, Patrick Applegate, Aimée B. A. Slangen, and Klaus Keller
Geosci. Model Dev., 10, 2741–2760, https://doi.org/10.5194/gmd-10-2741-2017, https://doi.org/10.5194/gmd-10-2741-2017, 2017
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We present the Building blocks for Relevant Ice and Climate Knowledge (BRICK) model v0.2. BRICK is a model for hindcasting past and projecting future surface temperature and sea-level rise, resolving the sea-level contributions from glaciers and ice caps, the Greenland and Antarctic ice sheets, and thermal expansion. BRICK is specifically designed to support decision analyses through its transparency, and includes functionality to scale global sea-level estimates to regional projections.
Jacob Schewe and Anders Levermann
Earth Syst. Dynam., 8, 495–505, https://doi.org/10.5194/esd-8-495-2017, https://doi.org/10.5194/esd-8-495-2017, 2017
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Monsoon systems have undergone abrupt changes in past climates, and theoretical considerations show that threshold behavior can follow from the internal dynamics of monsoons. So far, however, the possibility of abrupt changes has not been explored for modern monsoon systems. We analyze state-of-the-art climate model simulations and show that some models project abrupt changes in Sahel rainfall in response to a dynamic shift in the West African monsoon under 21st century climate change.
Tamás Kovács, Wuhu Feng, Anna Totterdill, John M. C. Plane, Sandip Dhomse, Juan Carlos Gómez-Martín, Gabriele P. Stiller, Florian J. Haenel, Christopher Smith, Piers M. Forster, Rolando R. García, Daniel R. Marsh, and Martyn P. Chipperfield
Atmos. Chem. Phys., 17, 883–898, https://doi.org/10.5194/acp-17-883-2017, https://doi.org/10.5194/acp-17-883-2017, 2017
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Sulfur hexafluoride (SF6) is a very potent greenhouse gas, which is present in the atmosphere only through its industrial use, for example as an electrical insulator. To estimate accurately the impact of SF6 emissions on climate we need to know how long it persists in the atmosphere before being removed. Previous estimates of the SF6 lifetime indicate a large degree of uncertainty. Here we use a detailed atmospheric model to calculate a current best estimate of the SF6 lifetime.
Stephen F. Price, Matthew J. Hoffman, Jennifer A. Bonin, Ian M. Howat, Thomas Neumann, Jack Saba, Irina Tezaur, Jeffrey Guerber, Don P. Chambers, Katherine J. Evans, Joseph H. Kennedy, Jan Lenaerts, William H. Lipscomb, Mauro Perego, Andrew G. Salinger, Raymond S. Tuminaro, Michiel R. van den Broeke, and Sophie M. J. Nowicki
Geosci. Model Dev., 10, 255–270, https://doi.org/10.5194/gmd-10-255-2017, https://doi.org/10.5194/gmd-10-255-2017, 2017
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We introduce the Cryospheric Model Comparison Tool (CmCt) and propose qualitative and quantitative metrics for evaluating ice sheet model simulations against observations. Greenland simulations using the Community Ice Sheet Model are compared to gravimetry and altimetry observations from 2003 to 2013. We show that the CmCt can be used to score simulations of increasing complexity relative to observations of dynamic change in Greenland over the past decade.
Sophie M. J. Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, Heiko Goelzer, William Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, and Andrew Shepherd
Geosci. Model Dev., 9, 4521–4545, https://doi.org/10.5194/gmd-9-4521-2016, https://doi.org/10.5194/gmd-9-4521-2016, 2016
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This paper describes an experimental protocol designed to quantify and understand the global sea level that arises due to past, present, and future changes in the Greenland and Antarctic ice sheets, along with investigating ice sheet–climate feedbacks. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) protocol includes targeted experiments, and a set of output diagnostic related to ice sheets, that are part of the 6th phase of the Coupled Model Intercomparison Project (CMIP6).
Peter Good, Timothy Andrews, Robin Chadwick, Jean-Louis Dufresne, Jonathan M. Gregory, Jason A. Lowe, Nathalie Schaller, and Hideo Shiogama
Geosci. Model Dev., 9, 4019–4028, https://doi.org/10.5194/gmd-9-4019-2016, https://doi.org/10.5194/gmd-9-4019-2016, 2016
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The nonlinMIP model intercomparison project is described. nonlinMIP provides experiments that account for state-dependent regional and global climate responses. The experiments have two main applications: 1) to focus understanding of responses to CO2 forcing on states relevant to specific policy or scientific questions (e.g.
change under low-forcing scenarios, the benefits of mitigation, or from past cold climates to
the present day), or 2) to understand state dependence of climate responses.
Jonathan M. Gregory, Nathaelle Bouttes, Stephen M. Griffies, Helmuth Haak, William J. Hurlin, Johann Jungclaus, Maxwell Kelley, Warren G. Lee, John Marshall, Anastasia Romanou, Oleg A. Saenko, Detlef Stammer, and Michael Winton
Geosci. Model Dev., 9, 3993–4017, https://doi.org/10.5194/gmd-9-3993-2016, https://doi.org/10.5194/gmd-9-3993-2016, 2016
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As a consequence of greenhouse gas emissions, changes in ocean temperature, salinity, circulation and sea level are expected in coming decades. Among the models used for climate projections for the 21st century, there is a large spread in projections of these effects. The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate and explain this spread by prescribing a common set of changes in the input of heat, water and wind stress to the ocean in the participating models.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Jan Wohland, Torsten Albrecht, and Anders Levermann
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-191, https://doi.org/10.5194/tc-2016-191, 2016
Preprint withdrawn
Anders Levermann and Ricarda Winkelmann
The Cryosphere, 10, 1799–1807, https://doi.org/10.5194/tc-10-1799-2016, https://doi.org/10.5194/tc-10-1799-2016, 2016
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In recent decades, the Greenland Ice Sheet has been losing mass and has thereby contributed to global sea-level rise. Here we derive the basic equations for the melt elevation feedback that can lead to self-amplifying melt of the Greenland Ice Sheet and ice sheets in general. The theory unifies the results of complex models when the feedback dominates the dynamics and it allows us to estimate the melt time of ice sheets from data in cases where ice dynamic loss can be neglected.
Johannes Feldmann and Anders Levermann
The Cryosphere, 10, 1753–1769, https://doi.org/10.5194/tc-10-1753-2016, https://doi.org/10.5194/tc-10-1753-2016, 2016
Lijing Cheng, Kevin E. Trenberth, Matthew D. Palmer, Jiang Zhu, and John P. Abraham
Ocean Sci., 12, 925–935, https://doi.org/10.5194/os-12-925-2016, https://doi.org/10.5194/os-12-925-2016, 2016
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A new method of observing ocean heat content throughout the entire ocean depth is provided. The new method is compared with simulated ocean heat content changes from climate models. The comparisons are carried out in various depth layers of the ocean waters. It is found that there is excellent agreement between the models and the observations. Furthermore, we propose that changes to ocean heat content be used as a fundamental metric to evaluate climate models.
Christine F. Dow, Mauro A. Werder, Sophie Nowicki, and Ryan T. Walker
The Cryosphere, 10, 1381–1393, https://doi.org/10.5194/tc-10-1381-2016, https://doi.org/10.5194/tc-10-1381-2016, 2016
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We examine the development and drainage of subglacial lakes in the Antarctic using a finite element hydrology model. Model outputs show development of slow-moving pressure waves initiated from water funneled from a large catchment into the ice stream. Lake drainage occurs due to downstream channel formation and changing system hydraulic gradients. These model outputs have implications for understanding controls on ice stream dynamics.
Heather Cannaby, Matthew D. Palmer, Tom Howard, Lucy Bricheno, Daley Calvert, Justin Krijnen, Richard Wood, Jonathan Tinker, Chris Bunney, James Harle, Andrew Saulter, Clare O'Neill, Clare Bellingham, and Jason Lowe
Ocean Sci., 12, 613–632, https://doi.org/10.5194/os-12-613-2016, https://doi.org/10.5194/os-12-613-2016, 2016
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The Singapore government commissioned a modelling study of regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events. We find that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century, these being 0.52 m(0.74 m) under the RCP 4.5(8.5) scenario.
André Düsterhus, Alessio Rovere, Anders E. Carlson, Benjamin P. Horton, Volker Klemann, Lev Tarasov, Natasha L. M. Barlow, Tom Bradwell, Jorie Clark, Andrea Dutton, W. Roland Gehrels, Fiona D. Hibbert, Marc P. Hijma, Nicole Khan, Robert E. Kopp, Dorit Sivan, and Torbjörn E. Törnqvist
Clim. Past, 12, 911–921, https://doi.org/10.5194/cp-12-911-2016, https://doi.org/10.5194/cp-12-911-2016, 2016
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This review/position paper addresses problems in creating new interdisciplinary databases for palaeo-climatological sea-level and ice-sheet data and gives an overview on new advances to tackle them. The focus therein is to define and explain strategies and highlight their importance to allow further progress in these fields. It also offers important insights into the general problem of designing competitive databases which are also applicable to other communities within the palaeo-environment.
K. Frieler, M. Mengel, and A. Levermann
Earth Syst. Dynam., 7, 203–210, https://doi.org/10.5194/esd-7-203-2016, https://doi.org/10.5194/esd-7-203-2016, 2016
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Sea level will continue to rise for centuries. We investigate the option of delaying sea-level rise by pumping ocean water onto Antarctica. Due to wave propagation ice is discharged much faster back into the ocean than expected from pure advection. A millennium-scale storage of > 80 % of the additional ice requires a distance of > 700 km from the coastline. The pumping energy required to elevate ocean water to mitigate a sea-level rise of 3 mm yr−1 exceeds 7 % of current global primary energy supply.
S. L. Cornford, D. F. Martin, A. J. Payne, E. G. Ng, A. M. Le Brocq, R. M. Gladstone, T. L. Edwards, S. R. Shannon, C. Agosta, M. R. van den Broeke, H. H. Hellmer, G. Krinner, S. R. M. Ligtenberg, R. Timmermann, and D. G. Vaughan
The Cryosphere, 9, 1579–1600, https://doi.org/10.5194/tc-9-1579-2015, https://doi.org/10.5194/tc-9-1579-2015, 2015
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We used a high-resolution ice sheet model capable of resolving grounding line dynamics (BISICLES) to compute responses of the major West Antarctic ice streams to projections of ocean and atmospheric warming. This is computationally demanding, and although other groups have considered parts of West Antarctica, we think this is the first calculation for the whole region at the sub-kilometer resolution that we show is required.
K. Frieler, A. Levermann, J. Elliott, J. Heinke, A. Arneth, M. F. P. Bierkens, P. Ciais, D. B. Clark, D. Deryng, P. Döll, P. Falloon, B. Fekete, C. Folberth, A. D. Friend, C. Gellhorn, S. N. Gosling, I. Haddeland, N. Khabarov, M. Lomas, Y. Masaki, K. Nishina, K. Neumann, T. Oki, R. Pavlick, A. C. Ruane, E. Schmid, C. Schmitz, T. Stacke, E. Stehfest, Q. Tang, D. Wisser, V. Huber, F. Piontek, L. Warszawski, J. Schewe, H. Lotze-Campen, and H. J. Schellnhuber
Earth Syst. Dynam., 6, 447–460, https://doi.org/10.5194/esd-6-447-2015, https://doi.org/10.5194/esd-6-447-2015, 2015
J. Feldmann and A. Levermann
The Cryosphere, 9, 631–645, https://doi.org/10.5194/tc-9-631-2015, https://doi.org/10.5194/tc-9-631-2015, 2015
M. A. Martin, A. Levermann, and R. Winkelmann
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-1705-2015, https://doi.org/10.5194/tcd-9-1705-2015, 2015
Preprint withdrawn
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Numerical ice sheet modelling shows that idealized, step-function type ocean warming in the Weddell Sea, where the ice sheet is close to floatation, leads to more immediate ice discharge with a higher sensitivity to small warming levels than the same warming in the Amundsen Sea. While the cumulative ice loss in the Amundsen Sea Sector is of similar magnitude after five centuries of continued warming, ice loss increases at a slower pace and only for significantly higher warming levels.
D. Ehlert and A. Levermann
Earth Syst. Dynam., 5, 383–397, https://doi.org/10.5194/esd-5-383-2014, https://doi.org/10.5194/esd-5-383-2014, 2014
A. Levermann, R. Winkelmann, S. Nowicki, J. L. Fastook, K. Frieler, R. Greve, H. H. Hellmer, M. A. Martin, M. Meinshausen, M. Mengel, A. J. Payne, D. Pollard, T. Sato, R. Timmermann, W. L. Wang, and R. A. Bindschadler
Earth Syst. Dynam., 5, 271–293, https://doi.org/10.5194/esd-5-271-2014, https://doi.org/10.5194/esd-5-271-2014, 2014
A. B. A. Slangen, R. S. W. van de Wal, Y. Wada, and L. L. A. Vermeersen
Earth Syst. Dynam., 5, 243–255, https://doi.org/10.5194/esd-5-243-2014, https://doi.org/10.5194/esd-5-243-2014, 2014
T. Howard, J. Ridley, A. K. Pardaens, R. T. W. L. Hurkmans, A. J. Payne, R. H. Giesen, J. A. Lowe, J. L. Bamber, T. L. Edwards, and J. Oerlemans
Ocean Sci., 10, 485–500, https://doi.org/10.5194/os-10-485-2014, https://doi.org/10.5194/os-10-485-2014, 2014
E. Fischer, S. Nowicki, M. Kelley, and G. A. Schmidt
Geosci. Model Dev., 7, 883–907, https://doi.org/10.5194/gmd-7-883-2014, https://doi.org/10.5194/gmd-7-883-2014, 2014
T. Albrecht and A. Levermann
The Cryosphere, 8, 587–605, https://doi.org/10.5194/tc-8-587-2014, https://doi.org/10.5194/tc-8-587-2014, 2014
C. F. Schleussner, J. Runge, J. Lehmann, and A. Levermann
Earth Syst. Dynam., 5, 103–115, https://doi.org/10.5194/esd-5-103-2014, https://doi.org/10.5194/esd-5-103-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 181–194, https://doi.org/10.5194/tc-8-181-2014, https://doi.org/10.5194/tc-8-181-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 195–208, https://doi.org/10.5194/tc-8-195-2014, https://doi.org/10.5194/tc-8-195-2014, 2014
B. Marzeion, A. H. Jarosch, and J. M. Gregory
The Cryosphere, 8, 59–71, https://doi.org/10.5194/tc-8-59-2014, https://doi.org/10.5194/tc-8-59-2014, 2014
A. Menon, A. Levermann, J. Schewe, J. Lehmann, and K. Frieler
Earth Syst. Dynam., 4, 287–300, https://doi.org/10.5194/esd-4-287-2013, https://doi.org/10.5194/esd-4-287-2013, 2013
A. B. A. Slangen and R. S. W. van de Wal
The Cryosphere, 5, 673–686, https://doi.org/10.5194/tc-5-673-2011, https://doi.org/10.5194/tc-5-673-2011, 2011
Related subject area
Climate and Earth system modeling
TorchClim v1.0: a deep-learning plugin for climate model physics
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
Applying double-cropping and interactive irrigation in the North China Plain using WRF4.5
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-38, https://doi.org/10.5194/gmd-2024-38, 2024
Revised manuscript accepted for GMD
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Peters, Bjørn Hallvard Samset, Benjamin M. Sanderson, and Ragnhild Bieltvedt Skeie
EGUsphere, https://doi.org/10.5194/egusphere-2024-196, https://doi.org/10.5194/egusphere-2024-196, 2024
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The CICERO-SCM has existed as a FORTRAN model since 1999 and consists of a part that calculates radiative forcing and concentrations from emissions, and an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper we describe an updated version ported to python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Cited articles
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Balasubramanian, V., Turilli, M., Hu, W., Lefebvre, M., Lei, W., Modrak, R. T., Cervone, G., Tromp, J., and Jha, S.: Harnessing the Power of Many: Extensible Toolkit for Scalable Ensemble Applications, in: 2018 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018, Vancouver, BC, Canada, 21–25 May 2018, 536–545, https://doi.org/10.1109/IPDPS.2018.00063, 2018. a
Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W., and Cooke, R. M.: Ice sheet contributions to future sea level rise from structured expert judgement, P. Natl. Acad. Sci. USA, 116, 11195–11200, https://doi.org/10.1073/pnas.1817205116, 2019. a, b, c, d
Buchanan, M. K., Kopp, R. E., Oppenheimer, M., and Tebaldi, C.: Allowances for evolving coastal flood risk under uncertain local sea-level rise, Clim. Change, 137, 347–362, https://doi.org/10.1007/s10584-016-1664-7, 2016. a
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DeConto, R. M., Pollard, D., Alley, R. B., Vellicogna, I., Gassons, E., Gomez, N., Rogstad, S., Gilford, D. M., Ashe, E. L., Kopp, R. E., Li, D., and Dutton, A. L.: The Paris Climate Agreement and future sea-level rise from Antarctica, Nature, 593, 83–88, https://doi.org/10.1038/s41586-021-03427-0, 2021. a, b, c, d
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Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, Y.: Ocean, Cryosphere, and Sea Level Change, in: Climate Change 2021: The Physical Science Basis, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., 1211–1362, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157896.011, 2021a. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, Y.: Ocean, Cryosphere, and Sea Level Change Supplementary Material, in: Climate Change 2021: The Physical Science Basis, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157896.011, 2021b. a, b, c
Frederikse, T., Buchanan, M. K., Lambert, E., Kopp, R. E., Oppenheimer, M., Rasmussen, D., and van de Wal, R. S.: Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes, Nat. Commun., 11, 1–11, https://doi.org/10.1038/s41467-019-14049-6, 2020. a, b
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Executive editor
This manuscript provides a novel and comprehensive assessment of uncertainty associated with sea level rise. The model description is thorough and it is applied to a number of possible scenarios. The conclusions are important for framing future discussions on sea level rise.
This manuscript provides a novel and comprehensive assessment of uncertainty associated with sea...
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be...
