Articles | Volume 14, issue 9
Geosci. Model Dev., 14, 5769–5787, 2021
https://doi.org/10.5194/gmd-14-5769-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: The FAMOUS climate model
Development and technical paper
17 Sep 2021
Development and technical paper
| 17 Sep 2021
FAMOUS version xotzt (FAMOUS-ice): a general circulation model (GCM) capable of energy- and water-conserving coupling to an ice sheet model
Robin S. Smith et al.
Related authors
Antony Siahaan, Robin Smith, Paul Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Tony Payne, Jeff Ridley, and Colin Jones
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-371, https://doi.org/10.5194/tc-2021-371, 2021
Preprint under review for TC
Short summary
Short summary
UKESM is the first Earth system model to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under low greenhouse-gas scenario, the ice sheet remains stable over the 21st century. Under strong greenhouse-gas scenario, the model predicts strong increases in melting of large ice shelves and strong snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Charles J. R. Williams, Alistair A. Sellar, Xin Ren, Alan M. Haywood, Peter Hopcroft, Stephen J. Hunter, William H. G. Roberts, Robin S. Smith, Emma J. Stone, Julia C. Tindall, and Daniel J. Lunt
Clim. Past, 17, 2139–2163, https://doi.org/10.5194/cp-17-2139-2021, https://doi.org/10.5194/cp-17-2139-2021, 2021
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Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from a simulation of the mid-Pliocene (approximately 3 million years ago) using the latest version of the UK’s climate model. The simulation reproduces temperatures as expected and shows some improvement relative to previous versions of the same model. The simulation is, however, arguably too warm when compared to other models and available observations.
Adam T. Blaker, Manoj Joshi, Bablu Sinha, David P. Stevens, Robin S. Smith, and Joël J.-M. Hirschi
Geosci. Model Dev., 14, 275–293, https://doi.org/10.5194/gmd-14-275-2021, https://doi.org/10.5194/gmd-14-275-2021, 2021
Short summary
Short summary
FORTE 2.0 is a flexible coupled atmosphere–ocean general circulation model that can be run on modest hardware. We present two 2000-year simulations which show that FORTE 2.0 is capable of producing a stable climate. Earlier versions of FORTE were used for a wide range of studies, ranging from aquaplanet configurations to investigating the cold European winters of 2009–2010. This paper introduces the updated model for which the code and configuration are now publicly available.
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
Short summary
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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.
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
Short summary
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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.
Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
Geosci. Commun., 3, 263–278, https://doi.org/10.5194/gc-3-263-2020, https://doi.org/10.5194/gc-3-263-2020, 2020
Short summary
Short summary
We use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces for piano. Each of the six pieces help to explain either a scientific principle or a practical aspect of Earth system modelling. We describe the methods that were used to create these pieces, discuss the limitations of this pilot study and list several approaches to extend and expand upon this work.
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
Short summary
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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.
Sarah Shannon, Robin Smith, Andy Wiltshire, Tony Payne, Matthias Huss, Richard Betts, John Caesar, Aris Koutroulis, Darren Jones, and Stephan Harrison
The Cryosphere, 13, 325–350, https://doi.org/10.5194/tc-13-325-2019, https://doi.org/10.5194/tc-13-325-2019, 2019
Short summary
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We present global glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding 2 °C global average warming. The ice loss contribution to sea level rise for all glaciers excluding those on the peripheral of the Antarctic ice sheet is 215.2 ± 21.3 mm. Such large ice losses will have consequences for sea level rise and for water supply in glacier-fed river systems.
B. A. A. Hoogakker, R. S. Smith, J. S. Singarayer, R. Marchant, I. C. Prentice, J. R. M. Allen, R. S. Anderson, S. A. Bhagwat, H. Behling, O. Borisova, M. Bush, A. Correa-Metrio, A. de Vernal, J. M. Finch, B. Fréchette, S. Lozano-Garcia, W. D. Gosling, W. Granoszewski, E. C. Grimm, E. Grüger, J. Hanselman, S. P. Harrison, T. R. Hill, B. Huntley, G. Jiménez-Moreno, P. Kershaw, M.-P. Ledru, D. Magri, M. McKenzie, U. Müller, T. Nakagawa, E. Novenko, D. Penny, L. Sadori, L. Scott, J. Stevenson, P. J. Valdes, M. Vandergoes, A. Velichko, C. Whitlock, and C. Tzedakis
Clim. Past, 12, 51–73, https://doi.org/10.5194/cp-12-51-2016, https://doi.org/10.5194/cp-12-51-2016, 2016
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In this paper we use two climate models to test how Earth’s vegetation responded to changes in climate over the last 120 000 years, looking at warm interglacial climates like today, cold ice-age glacial climates, and intermediate climates. The models agree well with observations from pollen, showing smaller forested areas and larger desert areas during cold periods. Forests store most terrestrial carbon; the terrestrial carbon lost during cold climates was most likely relocated to the oceans.
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
J. H. T. Williams, R. S. Smith, P. J. Valdes, B. B. B. Booth, and A. Osprey
Geosci. Model Dev., 6, 141–160, https://doi.org/10.5194/gmd-6-141-2013, https://doi.org/10.5194/gmd-6-141-2013, 2013
Antony Siahaan, Robin Smith, Paul Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Tony Payne, Jeff Ridley, and Colin Jones
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-371, https://doi.org/10.5194/tc-2021-371, 2021
Preprint under review for TC
Short summary
Short summary
UKESM is the first Earth system model to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under low greenhouse-gas scenario, the ice sheet remains stable over the 21st century. Under strong greenhouse-gas scenario, the model predicts strong increases in melting of large ice shelves and strong snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Charles J. R. Williams, Alistair A. Sellar, Xin Ren, Alan M. Haywood, Peter Hopcroft, Stephen J. Hunter, William H. G. Roberts, Robin S. Smith, Emma J. Stone, Julia C. Tindall, and Daniel J. Lunt
Clim. Past, 17, 2139–2163, https://doi.org/10.5194/cp-17-2139-2021, https://doi.org/10.5194/cp-17-2139-2021, 2021
Short summary
Short summary
Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from a simulation of the mid-Pliocene (approximately 3 million years ago) using the latest version of the UK’s climate model. The simulation reproduces temperatures as expected and shows some improvement relative to previous versions of the same model. The simulation is, however, arguably too warm when compared to other models and available observations.
Adam T. Blaker, Manoj Joshi, Bablu Sinha, David P. Stevens, Robin S. Smith, and Joël J.-M. Hirschi
Geosci. Model Dev., 14, 275–293, https://doi.org/10.5194/gmd-14-275-2021, https://doi.org/10.5194/gmd-14-275-2021, 2021
Short summary
Short summary
FORTE 2.0 is a flexible coupled atmosphere–ocean general circulation model that can be run on modest hardware. We present two 2000-year simulations which show that FORTE 2.0 is capable of producing a stable climate. Earlier versions of FORTE were used for a wide range of studies, ranging from aquaplanet configurations to investigating the cold European winters of 2009–2010. This paper introduces the updated model for which the code and configuration are now publicly available.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
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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.
Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
Geosci. Commun., 3, 263–278, https://doi.org/10.5194/gc-3-263-2020, https://doi.org/10.5194/gc-3-263-2020, 2020
Short summary
Short summary
We use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces for piano. Each of the six pieces help to explain either a scientific principle or a practical aspect of Earth system modelling. We describe the methods that were used to create these pieces, discuss the limitations of this pilot study and list several approaches to extend and expand upon this work.
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
Short summary
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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.
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.
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.
Sarah Shannon, Robin Smith, Andy Wiltshire, Tony Payne, Matthias Huss, Richard Betts, John Caesar, Aris Koutroulis, Darren Jones, and Stephan Harrison
The Cryosphere, 13, 325–350, https://doi.org/10.5194/tc-13-325-2019, https://doi.org/10.5194/tc-13-325-2019, 2019
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We present global glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding 2 °C global average warming. The ice loss contribution to sea level rise for all glaciers excluding those on the peripheral of the Antarctic ice sheet is 215.2 ± 21.3 mm. Such large ice losses will have consequences for sea level rise and for water supply in glacier-fed river systems.
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.
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.
B. A. A. Hoogakker, R. S. Smith, J. S. Singarayer, R. Marchant, I. C. Prentice, J. R. M. Allen, R. S. Anderson, S. A. Bhagwat, H. Behling, O. Borisova, M. Bush, A. Correa-Metrio, A. de Vernal, J. M. Finch, B. Fréchette, S. Lozano-Garcia, W. D. Gosling, W. Granoszewski, E. C. Grimm, E. Grüger, J. Hanselman, S. P. Harrison, T. R. Hill, B. Huntley, G. Jiménez-Moreno, P. Kershaw, M.-P. Ledru, D. Magri, M. McKenzie, U. Müller, T. Nakagawa, E. Novenko, D. Penny, L. Sadori, L. Scott, J. Stevenson, P. J. Valdes, M. Vandergoes, A. Velichko, C. Whitlock, and C. Tzedakis
Clim. Past, 12, 51–73, https://doi.org/10.5194/cp-12-51-2016, https://doi.org/10.5194/cp-12-51-2016, 2016
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In this paper we use two climate models to test how Earth’s vegetation responded to changes in climate over the last 120 000 years, looking at warm interglacial climates like today, cold ice-age glacial climates, and intermediate climates. The models agree well with observations from pollen, showing smaller forested areas and larger desert areas during cold periods. Forests store most terrestrial carbon; the terrestrial carbon lost during cold climates was most likely relocated to the oceans.
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
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
J. H. T. Williams, R. S. Smith, P. J. Valdes, B. B. B. Booth, and A. Osprey
Geosci. Model Dev., 6, 141–160, https://doi.org/10.5194/gmd-6-141-2013, https://doi.org/10.5194/gmd-6-141-2013, 2013
Related subject area
Climate and Earth system modeling
Precipitation over southern Africa: is there consensus among global climate models (GCMs), regional climate models (RCMs) and observational data?
On the impact of dropsondes on the ECMWF Integrated Forecasting System model (CY47R1) analysis of convection during the OTREC (Organization of Tropical East Pacific Convection) field campaign
Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration
CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)
An evaluation of the E3SMv1 Arctic ocean and sea-ice regionally refined model
Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset
The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments
Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1
Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: a new modular toolkit for landslide susceptibility assessment
Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 1: Precipitation
Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 2: Max and min temperature
Constraining a land cover map with satellite-based aboveground biomass estimates over Africa
Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)
Impacts of a revised surface roughness parameterization in the Community Land Model 5.1
Novel coupled permafrost–forest model (LAVESI–CryoGrid v1.0) revealing the interplay between permafrost, vegetation, and climate across eastern Siberia
The effects of ocean surface waves on global intraseasonal prediction: case studies with a coupled CFSv2.0–WW3 system
Earth system model parameter adjustment using a Green's functions approach
Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment
From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3)
Global simulation of dissolved 231Pa and 230Th in the ocean and the sedimentary 231Pa∕230Th ratios with the ocean general circulation model COCO ver4.0
The linear feedback precipitation model (LFPM 1.0) – a simple and efficient model for orographic precipitation in the context of landform evolution modeling
Building a machine learning surrogate model for wildfire activities within a global Earth system model
Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)
Extreme events representation in CMCC-CM2 standard and high-resolution general circulation models
TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1
CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates
Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)
Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models
GAN–argcPredNet v1.0: a generative adversarial model for radar echo extrapolation based on convolutional recurrent units
A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes
An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie
ShellChron 0.4.0: a new tool for constructing chronologies in accretionary carbonate archives from stable oxygen isotope profiles
Comparison of ocean heat content estimated using two eddy-resolving hindcast simulations based on OFES1 and OFES2
Enhancing the accessibility of unified modeling systems: GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD) v2021b in a container
Minimal CMIP Emulator (MCE v1.2): a new simplified method for probabilistic climate projections
Influence of modifications (from AoB2015 to v0.5) in the Vegetation Optimality Model
C-LLAMA 1.0: a traceable model for food, agriculture, and land use
The Earth Model Column Collaboratory (EMC2) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models
MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models
Description and evaluation of a secondary organic aerosol and new particle formation scheme within TM5-MP v1.2
PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5
Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0
Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix
Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study
Coupling the Community Land Model version 5.0 to the parallel data assimilation framework PDAF: description and applications
Convolutional conditional neural processes for local climate downscaling
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
Modeling reservoir surface temperatures for regional and global climate models: a multi-model study on the inflow and level variation effects
Importance of radiative transfer processes in urban climate models: a study based on the PALM 6.0 model system
Maria Chara Karypidou, Eleni Katragkou, and Stefan Pieter Sobolowski
Geosci. Model Dev., 15, 3387–3404, https://doi.org/10.5194/gmd-15-3387-2022, https://doi.org/10.5194/gmd-15-3387-2022, 2022
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The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Reliable climatic information is therefore necessary for the optimal adaptation of local communities. In this work we show that regional climate models are reliable tools for the simulation of precipitation over southern Africa. However, there is still a great need for the expansion and maintenance of observational data.
Stipo Sentić, Peter Bechtold, Željka Fuchs-Stone, Mark Rodwell, and David J. Raymond
Geosci. Model Dev., 15, 3371–3385, https://doi.org/10.5194/gmd-15-3371-2022, https://doi.org/10.5194/gmd-15-3371-2022, 2022
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The Organization of Tropical East Pacific Convection (OTREC) field campaign focuses on studying convection in the eastern Pacific and Caribbean. Observations obtained from dropsondes have been assimilated into the ECMWF model and compared to a model run in which sondes have not been assimilated. The model performs well in both simulations, but the assimilation of sondes helps to reduce the departure for pre-tropical-storm conditions. Variables important to studying convection are also studied.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon
Geosci. Model Dev., 15, 3205–3231, https://doi.org/10.5194/gmd-15-3205-2022, https://doi.org/10.5194/gmd-15-3205-2022, 2022
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This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.
Milena Veneziani, Wieslaw Maslowski, Younjoo J. Lee, Gennaro D'Angelo, Robert Osinski, Mark R. Petersen, Wilbert Weijer, Anthony P. Craig, John D. Wolfe, Darin Comeau, and Adrian K. Turner
Geosci. Model Dev., 15, 3133–3160, https://doi.org/10.5194/gmd-15-3133-2022, https://doi.org/10.5194/gmd-15-3133-2022, 2022
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We present an Earth system model (ESM) simulation, E3SM-Arctic-OSI, with a refined grid to better resolve the Arctic ocean and sea-ice system and low spatial resolution elsewhere. The configuration satisfactorily represents many aspects of the Arctic system and its interactions with the sub-Arctic, while keeping computational costs at a fraction of those necessary for global high-resolution ESMs. E3SM-Arctic can thus be an efficient tool to study Arctic processes on climate-relevant timescales.
Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, https://doi.org/10.5194/gmd-15-3041-2022, 2022
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This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Hengqi Wang, Yiran Peng, Knut von Salzen, Yan Yang, Wei Zhou, and Delong Zhao
Geosci. Model Dev., 15, 2949–2971, https://doi.org/10.5194/gmd-15-2949-2022, https://doi.org/10.5194/gmd-15-2949-2022, 2022
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The aerosol activation scheme is an important part of the general circulation model, but evaluations using observed data are mostly regional. This research introduced a numerically efficient aerosol activation scheme and evaluated it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The decent performance indicates that the scheme is suitable for simulations of cloud droplet number concentrations over wide conditions.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Jewgenij Torizin, Nick Schüßler, and Michael Fuchs
Geosci. Model Dev., 15, 2791–2812, https://doi.org/10.5194/gmd-15-2791-2022, https://doi.org/10.5194/gmd-15-2791-2022, 2022
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With LSAT PM we introduce an open-source, stand-alone, easy-to-use application that supports scientific principles of openness, knowledge integrity, and replicability. Doing so, we want to share our experience in the implementation of heuristic and data-driven landslide susceptibility assessment methods such as analytic hierarchy process, weights of evidence, logistic regression, and artificial neural networks. A test dataset is available.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, https://doi.org/10.5194/gmd-15-2635-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with a recent observational gridded dataset as a reference, covering the entire Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional climate models encouraged this study. For precipitation, most models reveal added value. The gains are even more evident for precipitation extremes, particularly at a more local scale.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2653–2671, https://doi.org/10.5194/gmd-15-2653-2022, https://doi.org/10.5194/gmd-15-2653-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with an observational gridded dataset as a reference covering the Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional models encouraged this study. For the max and min temperature, although most models reveal added value, some display losses. At more local scales, coastal sites display important gains, contrasting with the interior.
Guillaume Marie, B. Sebastiaan Luyssaert, Cecile Dardel, Thuy Le Toan, Alexandre Bouvet, Stéphane Mermoz, Ludovic Villard, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 15, 2599–2617, https://doi.org/10.5194/gmd-15-2599-2022, https://doi.org/10.5194/gmd-15-2599-2022, 2022
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Most Earth system models make use of vegetation maps to initialize a simulation at global scale. Satellite-based biomass map estimates for Africa were used to estimate cover fractions for the 15 land cover classes. This study successfully demonstrates that satellite-based biomass maps can be used to better constrain vegetation maps. Applying this approach at the global scale would increase confidence in assessments of present-day biomass stocks.
Anni Zhao, Chris M. Brierley, Zhiyi Jiang, Rachel Eyles, Damián Oyarzún, and Jose Gomez-Dans
Geosci. Model Dev., 15, 2475–2488, https://doi.org/10.5194/gmd-15-2475-2022, https://doi.org/10.5194/gmd-15-2475-2022, 2022
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We describe the way that our group have chosen to perform our recent analyses of the Palaeoclimate Modelling Intercomparison Project ensemble simulations. We document the approach used to obtain and curate the simulations, process those outputs via the Climate Variability Diagnostics Package, and then continue through to compute ensemble-wide statistics and create figures. We also provide interim data from all steps, the codes used and the ability for users to perform their own analyses.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Stefan Kruse, Simone M. Stuenzi, Julia Boike, Moritz Langer, Josias Gloy, and Ulrike Herzschuh
Geosci. Model Dev., 15, 2395–2422, https://doi.org/10.5194/gmd-15-2395-2022, https://doi.org/10.5194/gmd-15-2395-2022, 2022
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We coupled established models for boreal forest (LAVESI) and permafrost dynamics (CryoGrid) in Siberia to investigate interactions of the diverse vegetation layer with permafrost soils. Our tests showed improved active layer depth estimations and newly included species growth according to their species-specific limits. We conclude that the new model system can be applied to simulate boreal forest dynamics and transitions under global warming and disturbances, expanding our knowledge.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Hong Li, Xiang Li, and Yunfei Zhang
Geosci. Model Dev., 15, 2345–2363, https://doi.org/10.5194/gmd-15-2345-2022, https://doi.org/10.5194/gmd-15-2345-2022, 2022
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To better understand the effects of surface waves on global intraseasonal prediction, we incorporated the WW3 model into CFSv2.0. Processes of Langmuir mixing, Stokes–Coriolis force with entrainment, air–sea fluxes modified by Stokes drift, and momentum roughness length were considered. Results from two groups of 56 d experiments show that overestimated sea surface temperature, 2 m air temperature, 10 m wind, wave height, and underestimated mixed layer from the original CFSv2.0 are improved.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
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We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Yusuke Sasaki, Hidetaka Kobayashi, and Akira Oka
Geosci. Model Dev., 15, 2013–2033, https://doi.org/10.5194/gmd-15-2013-2022, https://doi.org/10.5194/gmd-15-2013-2022, 2022
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For realistically simulating the recently observed distributions of dissolved 230Th and 231Pa in the ocean, we highlight the importance of the removal process of 231Pa and 230Th at the seafloor (bottom scavenging) and the dependence of scavenging efficiency on particle concentration. We show that consideration of these two processes can well reproduce not only the oceanic distribution of 231Pa and 230Th but also the sedimentary 231Pa/230Th ratios.
Stefan Hergarten and Jörg Robl
Geosci. Model Dev., 15, 2063–2084, https://doi.org/10.5194/gmd-15-2063-2022, https://doi.org/10.5194/gmd-15-2063-2022, 2022
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The influence of climate on landform evolution has attracted great interest over the past decades. This paper presents a simple model for simulating the influence of topography on precipitation and the decrease in precipitation over large continental areas. The approach can be included in numerical models of large-scale landform evolution and causes only a moderate increase in the numerical complexity. It opens a door to investigating feedbacks between climate and landform evolution.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Justus Contzen, Thorsten Dickhaus, and Gerrit Lohmann
Geosci. Model Dev., 15, 1803–1820, https://doi.org/10.5194/gmd-15-1803-2022, https://doi.org/10.5194/gmd-15-1803-2022, 2022
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Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Enrico Scoccimarro, Daniele Peano, Silvio Gualdi, Alessio Bellucci, Tomas Lovato, Pier Giuseppe Fogli, and Antonio Navarra
Geosci. Model Dev., 15, 1841–1854, https://doi.org/10.5194/gmd-15-1841-2022, https://doi.org/10.5194/gmd-15-1841-2022, 2022
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This study evaluated the ability of the CMCC-CM2 climate model participating to the last CMIP6 effort, in representing extreme events of precipitation and temperature at the daily and 6-hourly frequencies. The 1/4° resolution version of the atmospheric model provides better results than the version at 1° resolution for temperature extremes, at both time frequencies. For precipitation extremes, especially at the daily time frequency, the higher resolution does not improve model results.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
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This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
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Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Christopher Holder, Anand Gnanadesikan, and Marie Aude-Pradal
Geosci. Model Dev., 15, 1595–1617, https://doi.org/10.5194/gmd-15-1595-2022, https://doi.org/10.5194/gmd-15-1595-2022, 2022
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It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.
Kun Zheng, Yan Liu, Jinbiao Zhang, Cong Luo, Siyu Tang, Huihua Ruan, Qiya Tan, Yunlei Yi, and Xiutao Ran
Geosci. Model Dev., 15, 1467–1475, https://doi.org/10.5194/gmd-15-1467-2022, https://doi.org/10.5194/gmd-15-1467-2022, 2022
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In extrapolation methods, there is a phenomenon that causes the extrapolated image to be blurred and unrealistic. The paper proposes the GAN–argcPredNet v1.0 network model, which aims to solve this problem through GAN's ability to strengthen the characteristics of multi-modal data modeling. GAN–argcPredNet v1.0 has achieved excellent results. Our model can reduce the prediction loss in a small-scale space so that the prediction results have more detailed features.
Swen Brands
Geosci. Model Dev., 15, 1375–1411, https://doi.org/10.5194/gmd-15-1375-2022, https://doi.org/10.5194/gmd-15-1375-2022, 2022
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The present study evaluates the last two global climate model generations in terms of their capability to reproduce recurrent regional atmospheric circulation patterns in the Northern Hemisphere mid-to-high latitudes under present climate conditions. These patterns are linked with many environmental variables on the local scale and thus provide an overarching concept for model verification. The results are expected to be of interest for model developers and regional climate scientists.
Shuqi Lin, Leon Boegman, Shiliang Shan, and Ryan Mulligan
Geosci. Model Dev., 15, 1331–1353, https://doi.org/10.5194/gmd-15-1331-2022, https://doi.org/10.5194/gmd-15-1331-2022, 2022
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An operational hydrodynamics forecast system, COASTLINES, using the Windows Task Scheduler, Python, and MATLAB scripts, to automate application of a 3-D model (AEM3D) in Lake Erie was developed. The system predicted storm-surge and up-/downwelling events that are important for flood water and drinking water/fishery management. This example of the successful development of an operational forecast system can be adapted to simulate aquatic systems as required for management and public safety.
Niels J. de Winter
Geosci. Model Dev., 15, 1247–1267, https://doi.org/10.5194/gmd-15-1247-2022, https://doi.org/10.5194/gmd-15-1247-2022, 2022
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ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives based on the seasonal variability in temperature and salinity or precipitation recorded in stable oxygen isotope measurements. The model allows dating of fossil archives within a year, which is important for climate reconstructions on the sub-seasonal to decadal scale. In this paper, I introduce ShellChron and test it on a range of real and virtual datasets to demonstrate its use.
Fanglou Liao, Xiao Hua Wang, and Zhiqiang Liu
Geosci. Model Dev., 15, 1129–1153, https://doi.org/10.5194/gmd-15-1129-2022, https://doi.org/10.5194/gmd-15-1129-2022, 2022
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The ocean heat content (OHC) estimated using two eddying hindcast simulations, OFES1 and OFES2, was compared from 1960 to 2016, with observation-based results as a reference. Marked differences were found, especially in the Atlantic Ocean. These were related to the differences in the net surface heating, heat advection, and vertical heat diffusion. These documented differences may help the community better understand and use these quasi-global high-resolution datasets for their own purposes.
Kai-Yuan Cheng, Lucas M. Harris, and Yong Qiang Sun
Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, https://doi.org/10.5194/gmd-15-1097-2022, 2022
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This paper presents the implementation of container technology for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model that can be used as a global, a global–nest, and a regional model for weather-to-seasonal prediction. Container technology makes SHiELD cross-platform and easy to use, which opens opportunities for collaborative research and development. The performance and scalability of the containerized SHiELD are evaluated and discussed.
Junichi Tsutsui
Geosci. Model Dev., 15, 951–970, https://doi.org/10.5194/gmd-15-951-2022, https://doi.org/10.5194/gmd-15-951-2022, 2022
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A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
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The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
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C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
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The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
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The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev., 15, 683–713, https://doi.org/10.5194/gmd-15-683-2022, https://doi.org/10.5194/gmd-15-683-2022, 2022
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We describe in this paper the implementation of a process-based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.2. The performance of the model simulations for the year 2010 is evaluated against in situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved, although in some areas the model shows a decline in performance.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise
Geosci. Model Dev., 15, 429–447, https://doi.org/10.5194/gmd-15-429-2022, https://doi.org/10.5194/gmd-15-429-2022, 2022
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Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
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Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Xavier Yepes-Arbós, Gijs van den Oord, Mario C. Acosta, and Glenn D. Carver
Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, https://doi.org/10.5194/gmd-15-379-2022, 2022
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Climate prediction models produce a large volume of simulated data that sometimes might not be efficiently managed. In this paper we present an approach to address this issue by reducing the computing time and storage space. As a case study, we analyse the output writing process of the ECMWF atmospheric model called IFS, and we integrate into it a data writing tool called XIOS. The results suggest that the integration between the two components achieves an adequate computational performance.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
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We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Anna Vaughan, Will Tebbutt, J. Scott Hosking, and Richard E. Turner
Geosci. Model Dev., 15, 251–268, https://doi.org/10.5194/gmd-15-251-2022, https://doi.org/10.5194/gmd-15-251-2022, 2022
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We develop a new method for climate downscaling, i.e. transforming low-resolution climate model output to high-resolution projections, using a deep-learning model known as a convolutional conditional neural process. This model is shown to outperform an ensemble of baseline methods for downscaling daily maximum temperature and precipitation and provides a powerful new downscaling framework for climate impact studies.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
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Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Manuel C. Almeida, Yurii Shevchuk, Georgiy Kirillin, Pedro M. M. Soares, Rita M. Cardoso, José P. Matos, Ricardo M. Rebelo, António C. Rodrigues, and Pedro S. Coelho
Geosci. Model Dev., 15, 173–197, https://doi.org/10.5194/gmd-15-173-2022, https://doi.org/10.5194/gmd-15-173-2022, 2022
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In this study, we have evaluated the importance of the input of energy conveyed by river inflows into lakes and reservoirs when modeling surface water energy fluxes. Our results suggest that there is a strong correlation between water residence time and the surface water temperature prediction error and that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air–lake heat and moisture fluxes.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
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Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
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Short summary
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.
Many of the complex computer models used to study the physics of the natural world treat ice...
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