Articles | Volume 12, issue 9
https://doi.org/10.5194/gmd-12-4165-2019
© Author(s) 2019. 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-12-4165-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Sep 2019
Model description paper |
| 25 Sep 2019
| 25 Sep 2019
eSCAPE: Regional to Global Scale Landscape Evolution Model v2.0
Tristan Salles
CORRESPONDING AUTHOR
School of Geosciences, University of Sydney, Sydney, NSW, 2006, Australia
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Yinbing Zhu, Patrice Rey, and Tristan Salles
EGUsphere, https://doi.org/10.5194/egusphere-2025-1585, https://doi.org/10.5194/egusphere-2025-1585, 2025
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
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We use computer models to study how landscapes respond to changes in rainfall and tectonic uplift. We find that rainfall rate changes produce unique slope change reversals near the headwaters, which differ from the simpler responses caused by uplift rate changes. These reversals are more pronounced when hillslope diffusion is dominant. These findings help us understand how climate and tectonic forcing shape the landscape differently and may allow scientists to tell their effects apart in nature.
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We studied how erosion and tectonic forces can affect the exposure and preservation of copper deposits formed in subduction zones in the past 65 million years. We used a global model that simulates landscape changes over time based on climate and elevation changes. Our findings show that climate is more important in preserving or exposing copper deposits than previously described. We help improve methods for locating copper deposits offering new insights for mineral exploration.
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Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport, and sea level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
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We present new tools in the landscape evolution model Badlands to simulate 10Be production, erosion and transport. These tools are applied to a source-to-sink system in the SW French Alps, where the model is calibrated. We propose a model that fits river incision rates and 10Be concentrations in sediments, and we show that 10Be in deep marine sediments is a signal with multiple contributions that cannot be easily interpreted in terms of climate forcing.
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Preprint withdrawn
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Using landscape evolution models integrating mantle dynamics, climate, eustatism and surface processes, we break down a previous idea that considers mantle flow as the main driver of the pulse of sedimentation in the Orange Basin, SA, over the last 30 Ma. Instead, climate impact seems to be a predominant mechanism. We also show that sediment flux and landscape evolution in the region is the product of interlinked processes accounting for both lithology variations, mantle dynamics and climate.
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The rise of a mountain affects the circulation of water, both in the atmosphere and over the land surface, thereby affecting the erosion of the land surface. We document how the rise of a mountain in central Guatemala has affected the erosion of an older range nearby. The new range intercepts precipitation formerly delivered to the older range. River response to the uplift of the new range has decreased incision across the older one. Both have reduced hillslope erosion over the old range.
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Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Xuesong Ding, Tristan Salles, Nicolas Flament, and Patrice Rey
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This work introduced a quantitative stratigraphic framework within a source-to-sink numerical code, pyBadlands, and evaluated two stratigraphic interpretation techniques. This quantitative framework allowed us to quickly construct the strata formations and automatically produce strata interpretations. We further showed that the accommodation succession method, compared with the trajectory analysis method, provided more reliable interpretations as it is independent of time-dependent processes.
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Geosci. Model Dev., 11, 2093–2110, https://doi.org/10.5194/gmd-11-2093-2018, https://doi.org/10.5194/gmd-11-2093-2018, 2018
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We present a 1-D model of coral reefs' evolution over centennial to millennial timescales. The model enables us to estimate the effects of environmental conditions (such as oceanic variability, sedimentation rate, sea-level fluctuations or tectonics) and ecological coral competition on reef vertical accretion and stratigraphic succession. The tool can quantitatively test carbonate platform development and efficiently interpret vertical growth under various forcing scenarios.
Yinbing Zhu, Patrice Rey, and Tristan Salles
EGUsphere, https://doi.org/10.5194/egusphere-2025-1585, https://doi.org/10.5194/egusphere-2025-1585, 2025
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
Short summary
Short summary
We use computer models to study how landscapes respond to changes in rainfall and tectonic uplift. We find that rainfall rate changes produce unique slope change reversals near the headwaters, which differ from the simpler responses caused by uplift rate changes. These reversals are more pronounced when hillslope diffusion is dominant. These findings help us understand how climate and tectonic forcing shape the landscape differently and may allow scientists to tell their effects apart in nature.
Beatriz Hadler Boggiani, Tristan Salles, Claire Mallard, and Nicholas Atwood
EGUsphere, https://doi.org/10.5194/egusphere-2024-1868, https://doi.org/10.5194/egusphere-2024-1868, 2024
Short summary
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We studied how erosion and tectonic forces can affect the exposure and preservation of copper deposits formed in subduction zones in the past 65 million years. We used a global model that simulates landscape changes over time based on climate and elevation changes. Our findings show that climate is more important in preserving or exposing copper deposits than previously described. We help improve methods for locating copper deposits offering new insights for mineral exploration.
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
Earth Surf. Dynam., 12, 301–320, https://doi.org/10.5194/esurf-12-301-2024, https://doi.org/10.5194/esurf-12-301-2024, 2024
Short summary
Short summary
Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport, and sea level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
Carole Petit, Tristan Salles, Vincent Godard, Yann Rolland, and Laurence Audin
Earth Surf. Dynam., 11, 183–201, https://doi.org/10.5194/esurf-11-183-2023, https://doi.org/10.5194/esurf-11-183-2023, 2023
Short summary
Short summary
We present new tools in the landscape evolution model Badlands to simulate 10Be production, erosion and transport. These tools are applied to a source-to-sink system in the SW French Alps, where the model is calibrated. We propose a model that fits river incision rates and 10Be concentrations in sediments, and we show that 10Be in deep marine sediments is a signal with multiple contributions that cannot be easily interpreted in terms of climate forcing.
Claire A. Mallard and Tristan Salles
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-89, https://doi.org/10.5194/esurf-2021-89, 2021
Preprint withdrawn
Short summary
Short summary
Using landscape evolution models integrating mantle dynamics, climate, eustatism and surface processes, we break down a previous idea that considers mantle flow as the main driver of the pulse of sedimentation in the Orange Basin, SA, over the last 30 Ma. Instead, climate impact seems to be a predominant mechanism. We also show that sediment flux and landscape evolution in the region is the product of interlinked processes accounting for both lithology variations, mantle dynamics and climate.
Gilles Brocard, Jane Kathrin Willenbring, Tristan Salles, Michael Cosca, Axel Guttiérez-Orrego, Noé Cacao Chiquín, Sergio Morán-Ical, and Christian Teyssier
Earth Surf. Dynam., 9, 795–822, https://doi.org/10.5194/esurf-9-795-2021, https://doi.org/10.5194/esurf-9-795-2021, 2021
Short summary
Short summary
The rise of a mountain affects the circulation of water, both in the atmosphere and over the land surface, thereby affecting the erosion of the land surface. We document how the rise of a mountain in central Guatemala has affected the erosion of an older range nearby. The new range intercepts precipitation formerly delivered to the older range. River response to the uplift of the new range has decreased incision across the older one. Both have reduced hillslope erosion over the old range.
Tristan Salles, Patrice Rey, and Enrico Bertuzzo
Earth Surf. Dynam., 7, 895–910, https://doi.org/10.5194/esurf-7-895-2019, https://doi.org/10.5194/esurf-7-895-2019, 2019
Short summary
Short summary
Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Xuesong Ding, Tristan Salles, Nicolas Flament, and Patrice Rey
Geosci. Model Dev., 12, 2571–2585, https://doi.org/10.5194/gmd-12-2571-2019, https://doi.org/10.5194/gmd-12-2571-2019, 2019
Short summary
Short summary
This work introduced a quantitative stratigraphic framework within a source-to-sink numerical code, pyBadlands, and evaluated two stratigraphic interpretation techniques. This quantitative framework allowed us to quickly construct the strata formations and automatically produce strata interpretations. We further showed that the accommodation succession method, compared with the trajectory analysis method, provided more reliable interpretations as it is independent of time-dependent processes.
Tristan Salles, Jodie Pall, Jody M. Webster, and Belinda Dechnik
Geosci. Model Dev., 11, 2093–2110, https://doi.org/10.5194/gmd-11-2093-2018, https://doi.org/10.5194/gmd-11-2093-2018, 2018
Short summary
Short summary
We present a 1-D model of coral reefs' evolution over centennial to millennial timescales. The model enables us to estimate the effects of environmental conditions (such as oceanic variability, sedimentation rate, sea-level fluctuations or tectonics) and ecological coral competition on reef vertical accretion and stratigraphic succession. The tool can quantitatively test carbonate platform development and efficiently interpret vertical growth under various forcing scenarios.
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Cited articles
Ahrens, J., Jourdain, S., O'Leary, P., Patchett, J., Rogers, D. H., and
Petersen, M.: An image-based approach to extreme scale in situ visualization
and analysis, Proceedings of the International Conference for High
Performance Computing, https://doi.org/10.1109/SC.2014.40, 2014. a
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis., NOAA Technical Memorandum NESDIS
NGDC-24, 19 pp., available at: http://www.ngdc.noaa.gov/mgg/global/global.html (last access: 23 September 2019), 2009. a
Armitage, J. J.: Short communication: flow as distributed lines within the landscape, Earth Surf. Dynam., 7, 67–75, https://doi.org/10.5194/esurf-7-67-2019, 2019. a, b, c, d
Barnes, R.: Parallel non-divergent flow accumulation for trillion cell
digital elevation models on desktops or clusters, Environ. Model.
Softw., 92, 202–212, https://doi.org/10.1016/j.envsoft.2017.02.022, 2017. a, b
Barnes, R.: Accelerating a fluvial incision and landscape evolution model
with parallelism, Geomorphology, 330, 28–39,
https://doi.org/10.1016/j.geomorph.2019.01.002, 2019. a, b, c
Beaumont, C., Fullsack, P., and Hamilton, J.: Erosional control of active
compressional orogens, in: Thrust Tectonics, edited by: McClay, K. R.,
Chapman Hall, New York, 1–18, https://doi.org/10.1007/978-94-011-3066-0_1, 1992. a, b
Bellugi, D., Dietrich, W. E., Stock, J., McKean, J., Kazian, B., and Hargrove,
P.: Spatially explicit shallow landslide susceptibility mapping over large
areas, in: Fifth International Conference on Debris-flow Hazards Mitigation,
Mechanics, Prediction and Assessment, edited by: Genevois, R., Hamilton, D. L., and Prestininzi, A., Casa Editrice Universita La Sapienza, Rome, pp. 309–407, https://doi.org/10.4408/IJEGE.2011-03.B-045, 2011. a
Beucher, R., Moresi, L., Giordani, J., Mansour, J., Sandiford, D., Farrington,
R., Mondy, L., Mallard, C., Rey, P., Duclaux, G., Kaluza, O., Laik, A., and
Moroon, S.: UWGeodynamics: A teaching and research tool for numerical
geodynamic modelling, J. Open Source Softw., 4, 1136,
https://doi.org/10.21105/joss.01136, 2019. a
Bianchi, V., Salles, T., Ghinassi, M., Billi, P., Dallanave, E., and Duclaux,
G.: Numerical modeling of tectonically driven river dynamics and deposition
in an upland incised valley, Geomorphology, 241, 353–370,
https://doi.org/10.1016/j.geomorph.2015.04.007, 2015. a
Bovy, B., Braun, J., and Demoulin, A.: Soil production and hillslope transport
in mid-latitudes during the last glacial-interglacial cycle: a combined data
and modelling approach in northern Ardennes, Earth Surf. Proc. Land., 41, 1758–1775, https://doi.org/10.1002/esp.3993, 2016. a, b
Carretier, S., Martinod, P., Reich, M., and Godderis, Y.: Modelling sediment clasts transport during landscape evolution, Earth Surf. Dynam., 4, 237–251, https://doi.org/10.5194/esurf-4-237-2016, 2016. a
Chen, A., Darbon, J., and Morel, J.-M.: Landscape evolution models: a review
of their fundamental equations, Geomorphology, 219, 68–86, 2014. a
Cordonnier, G., Bovy, B., and Braun, J.: A versatile, linear complexity algorithm for flow routing in topographies with depressions, Earth Surf. Dynam., 7, 549–562, https://doi.org/10.5194/esurf-7-549-2019, 2019. a, b
Coulthard, T. J., Macklin, M. G., and Kirkby, M. J.: A cellular model of
Holocene upland river basin and alluvial fan evolution, Earth Surf. Proc.
Land., 27, 269–288, https://doi.org/10.1002/esp.318, 2002. a, b
Davy, P. and Lague, D.: Fluvial erosion/transport equation of landscape
evolution models revisited., J. Geophys. Res.-Earth, 114, F03007,
https://doi.org/10.1029/2008JF001146, 2009. a, b
DiBiase, R. A., Whipple, K. X., Heimsath, A. M., and Ouimet, W. B.: Landscape
form and millennial erosion rates in the San Gabriel Mountains, CA,
Earth Planet. Sc. Lett., 289, 134–144, 2010. a
Dietrich, W. E., Bellugi, D., Sklar, L. S., Stock, J., Heimsath, A. M., and
Roering, J. J.: Geomorphic transport laws for predicting landscape form and
dynamics, in: Prediction in
Geomorphology, edited by: Wilcock, P. R. and Iverson, R. M., 135, 103–132, Blackwell Publishing Ltd, 2003. a
Eddins, S.: Upslope area – Forming and solving the flow matrix, MathWorks, available at:
http://blogs.mathworks.com/steve/2007/08/07/upslope-area-flow-matrix (last access: 23 September 2019), 2007. a
Falgout, R., Kolev, T., Schroder, J., Vassilevski, P., and Yang, U. M.:
Lawrence Livermore National Laboratory, HYPRE Package, available at:
https://computation.llnl.gov/casc/hypre/software.html (last access: 23 September 2019), 2012. a
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1-km spatial resolution
climate surfaces for global land areas, Int. J. Climatol.,
37, 4302–4315, https://doi.org/10.1002/joc.5086, 2017. a
Foufoula-Georgiou, E., Ganti, V., and Dietrich, W. E.: A nonlocal theory of
sediment transport on hillslopes, J. Geophys. Res.-Earth, 115, F00A16, https://doi.org/10.1029/2009JF001280, 2010. a
Grieve, S., Mudd, S., and Hurst, M.: How long is a hillslope?, Earth Surf.
Process. Landforms, 41, 1039–1054, https://doi.org/10.1002/esp.3884,
2016a. a
Grieve, S. W. D., Mudd, S. M., Hurst, M. D., and Milodowski, D. T.: A nondimensional framework for exploring the relief structure of landscapes, Earth Surf. Dynam., 4, 309–325, https://doi.org/10.5194/esurf-4-309-2016, 2016b. a
Hobley, D. E. J., Sinclar, H. D., Mudd, S. M., and Cowie, P. A.: Field
calibration of sediment flux dependent river incision, J. Geophys. Res.-Earth, 116, F04017, https://doi.org/10.1029/2010JF001935, 2011. a
Hobley, D. E. J., Adams, J. M., Nudurupati, S. S., Hutton, E. W. H., Gasparini, N. M., Istanbulluoglu, E., and Tucker, G. E.: Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics, Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, 2017. a, b, c
Hodge, R. A. and Hoey, T. B.: Upscaling from grain-scale processes to
alluviation in bedrock channels using a cellular automaton model, J. Geophys.
Res., 117, F01017, https://doi.org/10.1029/2011JF002145, 2012. a
Jenson, S. and Domingue, J.: Extracting topographic structure from digital
elevation data for geographic information system analysis, Photogramm. Eng.
Remote Sens., 54, 1593–1600, 1988. a
Lague, D.: Reduction of long-term bedrock incision efficiency by short-term
alluvial cover intermittency, J. Geophys. Res., 115, F02011,
https://doi.org/10.1029/2008JF001210, 2010. a
Larsen, I. J. and Montgomery, D. R.: Landslide erosion coupled to tectonics and river incision, Nat. Geosci., 5, 468–473, 2012. a
Li, F., Griffiths, C. M., Dyt, C. P., Weill, P., Feng, M., Salles, T., and
Jenkins, C.: Multigrain seabed sediment transport modelling for the
south-west Australian Shelf, Mar. Freshwater Res. 60, 774–785,
https://doi.org/10.1071/MF08049, 2009. a
Mark, D. M.: Network models in geomorphology, Modelling Geomorphological
Systems, edited by: Anderson, M. G., Wiley, NY, 73–97, 1988. a
Milliman, J. and Syvitski, J.: Geomorphic/tectonic control of sediment
discharge to the ocean: the importance of small mountainous rivers,
J. Geol., 100, 525–544, 1992. a
Murphy, B. P., Johnson, J. P. L., Gasparini, N. M., and Sklar, L. S.: Chemical weathering as a mechanism for the climatic control of bedrock river incision, Nature, 532, 223–227, 2016. a
O'Callaghan, J. F. and Mark, D. M.: The extraction of drainage networks from
digital elevation data, Comput. Vision Graph., 28,
323–344, 1984. a
Pelletier, J. D.: Persistent drainage migration in a numerical landscape
evolution model, Geophys. Res. Lett., 31, L20501, https://doi.org/10.1029/2004GL020802, 2004. a
Perron, J. T. and Hamon, J. L.: Equilibrium form of horizontally retreating,
soil-mantled hillslopes: Model development and application to a groundwater
sapping landscape, J. Geophys. Res., 117, F01027, https://doi.org/10.1029/2011JF002139, 2012. a, b
Planchon, O. and Darboux, F.: A fast, simple and versatile algorithm to fill
the depressions of digital elevation models, Catena, 46, 159–176,
https://doi.org/10.1016/S0341-8162(01)00164-3, 2002. a
Quinn, P., Beven, K., Chevallier, P., and Planchon, O.: The prediction of
hillslope flow paths for distributed hydrological modelling using digital
terrain models, Hydrol. Process., 5, 59–79, https://doi.org/10.1002/hyp.3360050106,
1991. a
Saad, Y.: Iterative Methods for Sparse Linear Systems, Society for Industrial and Applied Mathematics, Philadelphia, PA, 2003. a
Salles, T.: Badlands: A parallel basin and landscape dynamics model, SoftwareX, 5, 195–202, 2016. a
Salles, T.: eSCAPE: parallel global-scale landscape evolution model, J. Open Source Softw., 3, 964, https://doi.org/10.21105/joss.00964, 2018. a, b
Salles, T.: Geodels/eSCAPE: eSCAPE: Regional to Global Scale Landscape
Evolution Model v2.0 (Version v2.0), Zenodo, https://doi.org/10.5281/zenodo.3239569 , 2019. a
Salles, T. and Duclaux, G.: Combined hillslope diffusion and sediment
transport simulation applied to landscape dynamics modelling., Earth Surf.
Process Landf., 40, 823–839, 2015. a
Salles, T., Griffiths, C., Dyt, C., and Li, F.: Australian shelf sediment
transport responses to climate change-driven ocean perturbations, Mar.
Geol., 282, 268–274, 2011. a
Salles, T., Ding, X., and Brocard, G.: pyBadlands: A framework to simulate
sediment transport, landscape dynamics and basin stratigraphic evolution
through space and time, PLOS ONE, 13, 1–24,
https://doi.org/10.1371/journal.pone.0195557, 2018. a, b
Schoorl, J. M., Sonneveld, M. P. W., and Veldkamp, A.: Three-dimensional
landscape process modelling: the effect of DEM resolution, Earth Surf. Proc.
Land., 25, 1025–1034, 2000. a
Schwanghart, W. and Kuhn, N. J.: Topotoolbox: A set of Matlab functions for
topographic analysis, Environ. Modell. Softw., 25, 770–781,
https://doi.org/10.1016/j.envsoft.2009.12.002, 2010. a
Shobe, C. M., Tucker, G. E., and Barnhart, K. R.: The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution, Geosci. Model Dev., 10, 4577–4604, https://doi.org/10.5194/gmd-10-4577-2017, 2017. a, b, c
Simoes, M., Braun, J., and Bonnet, S.: Continental-scale erosion and transport laws: A new approach to quantitatively investigate macroscale landscapes and associated sediment fluxes over the geological past, Geochem. Geophy. Geosy., 11, Q09001, https://doi.org/10.1029/2010GC003121, 2010. a
Simpson, G. and Schlunegger, F.: Topographic evolution and morphology of
surfaces evolving in response to coupled fluvial and hillslope sediment
transport, J. Geophys. Res., 108, 2300, https://doi.org/10.1029/2002JB002162, 2003. a
Snyder, N. P., Whipple, K. X., Tucker, G. E., and Merritts, D. J.: Importance
of a stochastic distribution of floods and erosion thresholds in the bedrock
river incision problem, Water Resour. Res., 108, 2117,
https://doi.org/10.1029/2001JB001655, 2003. a
Syvitski, J., Peckham, S., Hilberman, R., and T., M.: Predicting the
terrestrial flux of sediment to the global ocean: a planetary perspective,
Sediment. Geol., 162, 5–24, https://doi.org/10.1016/S0037-0738(03)00232-X, 2003. a
Tarboton, D. G.: A new method for the determination of flow directions and
upslope areas in grid digital elevation models, Water Resour. Res., 33,
309–319, https://doi.org/10.1029/96WR03137, 1997. a
Tarboton, D. G.: Utah State University, TauDEM Web page, available at:
http://hydrology.usu.edu/taudem/taudem5 (last access: 23 September 2019), 2013. a
Tesfa, T., Tarboton, D., Watson, D., Schreuders, K., Baker, M., and Wallace,
R.: Extraction of hydrological proximity measures from DEMs using parallel
processing, Environ. Model. Softw., 26, 1696–1709, 2011. a
Thieulot, C., Steer, P., and Huismans, R. S.: Three-dimensional numerical
simulations of crustal systems undergoing orogeny and subjected to surface
processes, Geochem. Geophy. Geosy., 15, 4936–4957, 2014. a
Tomkin, J. H., Brandon, M. T., Pazzaglia, F. J., Barbour, J. R., and Willett,
S. D.: Quantitative testing of bedrock incision models for the Clearwater
River, NW Washington State, J. Geophys. Res., 108, 2308,
https://doi.org/10.1029/2001JB000862, 2003. a
Tucker, G. E. and Bradley, D. N.: Trouble with diffusion: Reassessing hillslope erosion laws with a particle-based model, J. Geophys. Res.-Earth, 115, F00A10, https://doi.org/10.1029/2009JF001264, 2010. a
Tucker, G. E. and Bras, R. L.: Hillslope processes, drainage density, and
landscape morphology, Water Resour. Res., 34, 2751–2764, 1998. a
Tucker, G. E. and Slingerland, R. L.: Erosional dynamics, flexural isostasy,
and long-lived escarpments: A numerical modeling study, J. Geophys. Res., 99,
12229–12243, https://doi.org/10.1029/94JB00320, 2017. a
Tucker, G. E., Lancaster, S. T., Gasparini, N. M., Bras, R. L., and Rybarczyk, S. M.: An object-oriented framework for distributed hydrologic and geomorphic
modeling using triangulated irregular networks, Comput. Geosci., 27,
959–973, 2001. a
Turowski, J. M. and Hodge, R.: A probabilistic framework for the cover effect in bedrock erosion, Earth Surf. Dynam., 5, 311–330, https://doi.org/10.5194/esurf-5-311-2017, 2017. a
Valla, P. G., van der Beek, P. A., and Lague, D.: Fluvial incision into
bedrock: insights from morphometric analysis and numerical modeling of gorges
incising glacial hanging valleys (Western Alps, France), J. Geophys. Res.-Earth, 115, F02010, https://doi.org/10.1029/2008JF001079, 2010. a
van der Beek, P. and Bishop, P.: Cenozoic river profile development in the
Upper Lachlan catchment (SE Australia) as a test of quantitative fluvial
incision models, J. Geophys. Res., 108, 2309, https://doi.org/10.1029/2002JB002125, 2003. a
Wallace, R. M., Tarboton, D. G., Watson, D. W., Schreuders, K. A. T., and
Tesfa, T. K.: Parallel algorithms for processing hydrologic properties from
digital terrain, in: Sixth International Conference on Geographic
Information Science, edited by: Purves, R. and Weibel, R., Zurich,
Switzerland, 2010. a
Wallis, C., Wallace, R. M., Tarboton, D. G., Watson, D. W., Schreuders, K.
A. T., and Tesfa, T. K.: Hydrologic terrain processing using parallel
computing, in: 18th World IMACS Congress and MODSIM09 International Congress
on Modelling and Simulation, edited by: Anderssen, R. S., Braddock, R. D., and Newham, L. T. H., 2540–2545, 2009. a, b
Wang, L. and Liu, H.: An efficient method for identifying and filling surface
depressions in digital elevation models for hydrologic analysis and
modelling, Int. J. Geogr. Inf. Sci., 20,
193–213, https://doi.org/10.1080/13658810500433453, 2006. a
Wei, H., Zhou, G., and Fu, S.: Efficient Priority-Flood depression filling in
raster digital elevation models, Int. J. Digit Earth, 12, 415–427, https://doi.org/10.1080/17538947.2018.1429503, 2018. a
Willgoose, G. R., Bras, R. L., and Rodriguez-Iturbe, I.: A physically based
coupled network growth and hillslope evolution model: 1 – Theory, Water
Resour. Res., 27, 1671–1684, https://doi.org/10.1029/91WR00935, 1991.
a, b
Yang, R., Willett, S. D., and Goren, L.: In situ low-relief landscape formation
as a result of river network disruption, Nature, 526–529,
https://doi.org/10.1038/nature14354, 2015. a
Yıldırım, A., Watson, D., Tarboton, D., and Wallace, R.: A virtual tile
approach to raster-based calculations of large digital elevation models in a
shared-memory system, Comput. Geosci., 82, 78–88, 2015. a
Zhou, G., Sun, Z., and Fu, S.: An efficient variant of the priority-flood
algorithm for filling depressions in raster digital elevation models,
Comput. Geosci., 90, 87–96, https://doi.org/10.1016/j.cageo.2016.02.021, 2016. a
Zhou, G., Liu, X., Fu, S., and Sun, Z.: Parallel Identification and Filling of
Depressions in Raster Digital Elevation Models, Int. J. Geogr. Inf. Sci., 31, 1061–1078, https://doi.org/10.1080/13658816.2016.1262954, 2017. a, b
Short summary
This paper presents a new numerical model able to simulate for the first time the evolution of Earth's surface at a global scale under different precipitation, sea level, and tectonic conditions. This is significant as it can help to bridge the gap between local- and global-scale predictions of Earth's past and future variations.
This paper presents a new numerical model able to simulate for the first time the evolution of...
