Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-929-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-929-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
01 Feb 2022
Model description paper |
| 01 Feb 2022
| 01 Feb 2022
C-LLAMA 1.0: a traceable model for food, agriculture, and land use
School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Naomi E. Vaughan
School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Tyndall Centre for Climate Change Research, University of East Anglia, Norwich, NR4 7TJ, UK
Thomas W. Powell
Global Systems Institute, University of Exeter, Exeter, EX4 4PY, UK
Andrew Lovett
School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Timothy M. Lenton
Global Systems Institute, University of Exeter, Exeter, EX4 4PY, UK
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Mark S. Williamson and Timothy M. Lenton
Earth Syst. Dynam., 15, 1483–1508, https://doi.org/10.5194/esd-15-1483-2024, https://doi.org/10.5194/esd-15-1483-2024, 2024
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Climate models have transitioned to a superrotating atmospheric state under a broad range of warm climates. Such a transition would change global weather patterns should it occur. Here we simulate this transition using an idealized climate model and look for any early warnings of the superrotating state before it happens. We find several early warning indicators that we attribute to an oscillating pattern in the windfield fluctuations.
Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm
Earth Syst. Dynam., 15, 789–800, https://doi.org/10.5194/esd-15-789-2024, https://doi.org/10.5194/esd-15-789-2024, 2024
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Cascading effects through cross-system interactions are one of the biggest promises of positive tipping points to create rapid climate and sustainability action. Here, we review these in terms of their interactions with sociotechnical systems such as energy, transport, agriculture, society, and policy.
Antony Philip Emenyu, Thomas Pienkowski, Andrew M. Cunliffe, Timothy M. Lenton, and Tom Powell
EGUsphere, https://doi.org/10.5194/egusphere-2023-2531, https://doi.org/10.5194/egusphere-2023-2531, 2023
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This paper explores what processes could boost adoption rates for regenerative agriculture programs in Africa and draws on insights from successful rapid scaling of TIST in east Africa. Found that the cultivation of reinforcing feedback processes that strengthened the social capital around adoption and elimination of barriers to carbon accreditation for RA projects to be key success factors and possible opportunities new and ongoing RA programs to boost their adoption rates.
Stephen P. Hesselbo, Aisha Al-Suwaidi, Sarah J. Baker, Giorgia Ballabio, Claire M. Belcher, Andrew Bond, Ian Boomer, Remco Bos, Christian J. Bjerrum, Kara Bogus, Richard Boyle, James V. Browning, Alan R. Butcher, Daniel J. Condon, Philip Copestake, Stuart Daines, Christopher Dalby, Magret Damaschke, Susana E. Damborenea, Jean-Francois Deconinck, Alexander J. Dickson, Isabel M. Fendley, Calum P. Fox, Angela Fraguas, Joost Frieling, Thomas A. Gibson, Tianchen He, Kat Hickey, Linda A. Hinnov, Teuntje P. Hollaar, Chunju Huang, Alexander J. L. Hudson, Hugh C. Jenkyns, Erdem Idiz, Mengjie Jiang, Wout Krijgsman, Christoph Korte, Melanie J. Leng, Timothy M. Lenton, Katharina Leu, Crispin T. S. Little, Conall MacNiocaill, Miguel O. Manceñido, Tamsin A. Mather, Emanuela Mattioli, Kenneth G. Miller, Robert J. Newton, Kevin N. Page, József Pálfy, Gregory Pieńkowski, Richard J. Porter, Simon W. Poulton, Alberto C. Riccardi, James B. Riding, Ailsa Roper, Micha Ruhl, Ricardo L. Silva, Marisa S. Storm, Guillaume Suan, Dominika Szűcs, Nicolas Thibault, Alfred Uchman, James N. Stanley, Clemens V. Ullmann, Bas van de Schootbrugge, Madeleine L. Vickers, Sonja Wadas, Jessica H. Whiteside, Paul B. Wignall, Thomas Wonik, Weimu Xu, Christian Zeeden, and Ke Zhao
Sci. Dril., 32, 1–25, https://doi.org/10.5194/sd-32-1-2023, https://doi.org/10.5194/sd-32-1-2023, 2023
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We present initial results from a 650 m long core of Late Triasssic to Early Jurassic (190–202 Myr) sedimentary strata from the Cheshire Basin, UK, which is shown to be an exceptional record of Earth evolution for the time of break-up of the supercontinent Pangaea. Further work will determine periodic changes in depositional environments caused by solar system dynamics and used to reconstruct orbital history.
Mila Kim-Chau Fiona Ong, Fenna Blomsma, and Timothy Michael Lenton
EGUsphere, https://doi.org/10.5194/egusphere-2023-2361, https://doi.org/10.5194/egusphere-2023-2361, 2023
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We investigate the initially successful transition from regional bottle reuse for mineral water to a widespread bottle reuse system in Germany, its subsequent destabilisation, and what this teaches us about tipping dynamics in packaging systems. Our findings demonstrate opportunities to create an enabling environment for change, and the role of specific reinforcing feedback loops and interventions in accelerating or impeding sustainable transitions.
Chris A. Boulton, Joshua E. Buxton, and Timothy M. Lenton
EGUsphere, https://doi.org/10.5194/egusphere-2023-2234, https://doi.org/10.5194/egusphere-2023-2234, 2023
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Early warning signals (EWS) of tipping points (TP), are used to detect resilience loss in the incumbent regime of ICEVs, towards an electric vehicle (EV) dominated state. View share of EV ads on a UK car selling platform shows evidence of approaching a TP, with results suggesting low-mid price ranges may have passed it, likely due to achieved price parity between EVs and non-EVs in sectors of the second-hand market, showing that EWS of positive TPs are possible in social-technological systems.
Jakob Emanuel Deutloff, Hermann Held, and Timothy Michael Lenton
EGUsphere, https://doi.org/10.5194/egusphere-2023-1469, https://doi.org/10.5194/egusphere-2023-1469, 2023
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We investigate the probabilities of triggering climate tipping points under various emission scenarios and how they are altered by additional carbon emissions from tipping points within the Earth's carbon cycle. We find that even “middle of the road” emission scenarios are highly unsafe with regard to triggering climate tipping points. Under such scenarios, probabilities of triggering are increased substantially by carbon emissions from tipping points within the Earth's carbon cycle.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
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Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Elisa Lovecchio and Timothy M. Lenton
Geosci. Model Dev., 13, 1865–1883, https://doi.org/10.5194/gmd-13-1865-2020, https://doi.org/10.5194/gmd-13-1865-2020, 2020
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We present here the newly developed BPOP box model. BPOP is aimed at studying the impact of large-scale changes in the biological pump, i.e. the cycle of production, export and remineralization of the marine organic matter, on the nutrient and oxygen concentrations in the shelf and open ocean. This model has been developed to investigate the global consequences of the evolution of larger and heavier phytoplankton cells but can be applied to a variety of past and future case studies.
Emma W. Littleton, Anna B. Harper, Naomi E. Vaughan, Rebecca J. Oliver, Maria Carolina Duran-Rojas, and Timothy M. Lenton
Geosci. Model Dev., 13, 1123–1136, https://doi.org/10.5194/gmd-13-1123-2020, https://doi.org/10.5194/gmd-13-1123-2020, 2020
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This study presents new functionality to represent bioenergy crops and harvests in JULES, a land surface model. Such processes must be explicitly represented before the environmental effects of large-scale bioenergy production can be fully evaluated, using Earth system modelling. This new functionality allows for many types of bioenergy plants and harvesting regimes to be simulated, such as perennial grasses, short rotation coppicing, and forestry rotations.
David I. Armstrong McKay and Timothy M. Lenton
Clim. Past, 14, 1515–1527, https://doi.org/10.5194/cp-14-1515-2018, https://doi.org/10.5194/cp-14-1515-2018, 2018
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This study uses statistical analyses to look for signs of declining resilience (i.e. greater sensitivity to small shocks) in the global carbon cycle and climate system across the Palaeocene–Eocene Thermal Maximum (PETM), a global warming event 56 Myr ago driven by rapid carbon release. Our main finding is that carbon cycle resilience declined in the 1.5 Myr beforehand (a time of significant volcanic emissions), which is consistent with but not proof of a carbon release tipping point at the PETM.
Sebastian Bathiany, Bregje van der Bolt, Mark S. Williamson, Timothy M. Lenton, Marten Scheffer, Egbert H. van Nes, and Dirk Notz
The Cryosphere, 10, 1631–1645, https://doi.org/10.5194/tc-10-1631-2016, https://doi.org/10.5194/tc-10-1631-2016, 2016
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We examine if a potential "tipping point" in Arctic sea ice, causing abrupt and irreversible sea-ice loss, could be foreseen with statistical early warning signals. We assess this idea by using several models of different complexity. We find robust and consistent trends in variability that are not specific to the existence of a tipping point. While this makes an early warning impossible, it allows to estimate sea-ice variability from only short observational records or reconstructions.
Timothy M. Lenton, Peter-Paul Pichler, and Helga Weisz
Earth Syst. Dynam., 7, 353–370, https://doi.org/10.5194/esd-7-353-2016, https://doi.org/10.5194/esd-7-353-2016, 2016
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We identify six past revolutions in energy input and material cycling in Earth and human history. We find that human energy use has now reached a magnitude comparable to the biosphere, and conclude that a prospective sustainability revolution will require scaling up new solar energy technologies and the development of much more efficient material recycling systems. Our work was inspired by recognising the connections between Earth system science and industrial ecology at the "LOOPS" workshop.
Mark S. Williamson, Sebastian Bathiany, and Timothy M. Lenton
Earth Syst. Dynam., 7, 313–326, https://doi.org/10.5194/esd-7-313-2016, https://doi.org/10.5194/esd-7-313-2016, 2016
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We find early warnings of abrupt changes in complex dynamical systems such as the climate where the usual early warning indicators do not work. In particular, these are systems that are periodically forced, for example by the annual cycle of solar insolation. We show these indicators are good theoretically in a general setting then apply them to a specific system, that of the Arctic sea ice, which has been conjectured to be close to such a tipping point. We do not find evidence of it.
Z. A. Thomas, F. Kwasniok, C. A. Boulton, P. M. Cox, R. T. Jones, T. M. Lenton, and C. S. M. Turney
Clim. Past, 11, 1621–1633, https://doi.org/10.5194/cp-11-1621-2015, https://doi.org/10.5194/cp-11-1621-2015, 2015
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Using a combination of speleothem records and model simulations of the East Asian Monsoon over the penultimate glacial cycle, we search for early warning signals of past tipping points. We detect a characteristic slower response to perturbations prior to an abrupt monsoon shift at the glacial termination; however, we do not detect these signals in the preceding shifts. Our results have important implications for detecting tipping points in palaeoclimate records outside glacial terminations.
G. Colbourn, A. Ridgwell, and T. M. Lenton
Geosci. Model Dev., 6, 1543–1573, https://doi.org/10.5194/gmd-6-1543-2013, https://doi.org/10.5194/gmd-6-1543-2013, 2013
V. N. Livina and T. M. Lenton
The Cryosphere, 7, 275–286, https://doi.org/10.5194/tc-7-275-2013, https://doi.org/10.5194/tc-7-275-2013, 2013
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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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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
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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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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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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.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a sub-sea CO2 injection.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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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.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used 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. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model 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.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged 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.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
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We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Ulrich Georg Wortmann, Tina Tsan, Mahrukh Niazi, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
EGUsphere, https://doi.org/10.5194/egusphere-2024-1864, https://doi.org/10.5194/egusphere-2024-1864, 2024
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The Earth Science Box Modeling Toolkit (ESBMTK) is a Python library designed to separate model description from numerical implementation. This approach results in well-documented, easily readable, and maintainable model code, allowing students and researchers to concentrate on conceptual challenges rather than mathematical intricacies.
Malcolm John Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
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HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present day and future projections, and to build links with other communities to provide more robust climate information.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O’Rourke, and Beth Dingley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2363, https://doi.org/10.5194/egusphere-2024-2363, 2024
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most heavily used variables from Earth System Models, based on an assessment of data publication and download records from the largest archive of global climate projects.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-142, https://doi.org/10.5194/gmd-2024-142, 2024
Revised manuscript accepted for GMD
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1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. 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).
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Cited articles
Alexander, P., Brown, C., Arneth, A., Finnigan, J., and Rounsevell, M. D. A.: Human appropriation of land for food: The role of diet, Global Environ. Chang., 41, 88–98, https://doi.org/10.1016/j.gloenvcha.2016.09.005, 2016.
Alexander, P., Brown, C., Arneth, A., Finnigan, J., Moran, D., and Rounsevell, M. D. A.: Losses, inefficiencies and waste in the global food system, Agr. Syst., 153, 190–200, https://doi.org/10.1016/j.agsy.2017.01.014, 2017.
Allen, M. R., Dube, O. P., Solecki, W., Aragón-Durand, F., Cramer, W., Humphreys, S., Kainuma, M., Kala, J., Mahowald, N., Mulugetta, Y., Perez, R., Wairiu, M., and Zickfeld, K.: Framing and Context. Global Warming of 1.5 ∘C, in: IPCC Special Report on the impacts of global warming of 1.5 ∘C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty, IPCC, 2022.
Arneth, A., Denton, F., Agus, F., Elbehri, A., Erb, K., Osman Elasha, B., Rahimi, M., Rounsevell, M., Spence, M., and Valentini, R.: Framing and Context. Climate Change and Land, in: IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, IPCC, 2022.
Ball, T. S.: C-LLAMA v1.0: a traceable model for food, agriculture and land-use, Zenodo [code], https://doi.org/10.5281/zenodo.5083000, 2021.
Bijl, D. L., Bogaart, P. W., Dekker, S. C., Stehfest, E., de Vries, B. J. M., and van Vuuren, D. P.: A physically-based model of long-term food demand, Global Environ. Chang., 45, 47–62, https://doi.org/10.1016/j.gloenvcha.2017.04.003, 2017.
Bordonal, R. de O., Carvalho, J. L. N., Lal, R., de Figueiredo, E. B., de Oliveira, B. G., and La Scala, N.: Sustainability of sugarcane production in Brazil. A review, Agron. Sustain. Dev., 38, 13, https://doi.org/10.1007/s13593-018-0490-x, 2018.
Calvin, K., Wise, M., Clarke, L., Edmonds, J., Kyle, P., Luckow, P., and Thomson, A.: Implications of simultaneously mitigating and adapting to climate change: Initial experiments using GCAM, Climatic Change, 117, 545–560, https://doi.org/10.1007/s10584-012-0650-y, 2013.
Davis, K. F. and D'Odorico, P.: Livestock intensification and the influence of dietary change: A calorie-based assessment of competition for crop production, Sci. Total Environ., 538, 817–823, https://doi.org/10.1016/j.scitotenv.2015.08.126, 2015.
De Miranda, E. E. and Fonseca, M. F.: Chapter 4 – Sugarcane: Food production, energy, and environment, in: Sugarcane Biorefinery, Technology and Perspectives, Elsevier Inc., 67–88, ISBN: 978-0-12-814236-3, 2019.
Duro, J. A., Lauk, C., Kastner, T., Erb, K. H., and Haberl, H.: Global inequalities in food consumption, cropland demand and land-use efficiency: A decomposition analysis, Global Environ. Chang., 64, 102124, https://doi.org/10.1016/j.gloenvcha.2020.102124, 2020.
Eitelberg, D. A., van Vliet, J., and Verburg, P. H.: A review of global potentially available cropland estimates and their consequences for model-based assessments, Global Change Biol., 21, 1236–1248, https://doi.org/10.1111/gcb.12733, 2015.
Erb, K. H., Luyssaert, S., Meyfroidt, P., Pongratz, J., Don, A., Kloster, S., Kuemmerle, T., Fetzel, T., Fuchs, R., Herold, M., Haberl, H., Jones, C. D., Marín-Spiotta, E., McCallum, I., Robertson, E., Seufert, V., Fritz, S., Valade, A., Wiltshire, A., and Dolman, A. J.: Land management: data availability and process understanding for global change studies, Global Change Biol., 23, 512–533, https://doi.org/10.1111/gcb.13443, 2017.
FAOSTAT (Food and Agriculture Organization Corporate Statistical Database): https://doi.org/10.25504/FAIRsharing.z0rqUk, 2012.
FAOSTAT: Food and Agriculture Organization Corporate Statistical Database,
https://doi.org/10.25504/FAIRsharing.z0rqUk, 2012.
FAOSTAT: Crops and livestock products, FAOSTAT [data set], https://www.fao.org/faostat/en/#data/QCL (last access: 13 January 2022), 2021a.
FAOSTAT: Food Balances (-2013, old methodology and population), FAOSTAT [data set], available at: https://www.fao.org/faostat/en/#data/FBSH (last access: 13 January 2022), 2021b.
FAOSTAT: Inputs – Land Use, FAOSTAT [data set], available at: https://www.fao.org/faostat/en/#data/RL (last access: 13 January 2022), 2021c.
FAOSTAT: Agriculture – Total, FAOSTAT [data set], available at: https://www.fao.org/faostat/en/#data, last access: 13 January 2022.
Fricko, O., Havlik, P., Rogelj, J., Klimont, Z., Gusti, M., Johnson, N., Kolp, P., Strubegger, M., Valin, H., Amann, M., Ermolieva, T., Forsell, N., Herrero, M., Heyes, C., Kindermann, G., Krey, V., McCollum, D. L., Obersteiner, M., Pachauri, S., Rao, S., Schmid, E., Schoepp, W., and Riahi, K.: The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century, Global Environ. Chang., 42, 251–267, https://doi.org/10.1016/j.gloenvcha.2016.06.004, 2017.
Frieler, K., Schauberger, B., Arneth, A., Balkovič, J., Chryssanthacopoulos, J., Deryng, D., Elliott, J., Folberth, C., Khabarov, N., Müller, C., Olin, S., Pugh, T. A. M., Schaphoff, S., Schewe, J., Schmid, E., Warszawski, L., and Levermann, A.: Understanding the weather signal in national crop-yield variability, Earths Future, 5, 605–616, https://doi.org/10.1002/2016EF000525, 2017.
Fritz, S., See, L., Mccallum, I., You, L., Bun, A., Moltchanova, E., Duerauer, M., Albrecht, F., Schill, C., Perger, C., Havlik, P., Mosnier, A., Thornton, P., Wood-Sichra, U., Herrero, M., Becker-Reshef, I., Justice, C., Hansen, M., Gong, P., Abdel Aziz, S., Cipriani, A., Cumani, R., Cecchi, G., Conchedda, G., Ferreira, S., Gomez, A., Haffani, M., Kayitakire, F., Malanding, J., Mueller, R., Newby, T., Nonguierma, A., Olusegun, A., Ortner, S., Rajak, D. R., Rocha, J., Schepaschenko, D., Schepaschenko, M., Terekhov, A., Tiangwa, A., Vancutsem, C., Vintrou, E., Wenbin, W., van der Velde, M., Dunwoody, A., Kraxner, F., and Obersteiner, M.: Mapping global cropland and field size, Global Change Biol., 21, 1980–1992, https://doi.org/10.1111/gcb.12838, 2015.
Fujimori, S., Masui, T., and Matsuoka, Y.: AIM/CGE [basic] manual, Center for Social and Environmental Systems Research, NIES: Tsukuba, Japan, 2012.
Gough, C., Garcia-Freites, S., Jones, C., Mander, S., Moore, B., Pereira, C., Röder, M., Vaughan, N., and Welfle, A.: Challenges to the use of BECCS as a keystone technology in pursuit of 1.5 ∘C, Global Sustainability, 1, E5, https://doi.org/10.1017/sus.2018.3, 2018.
Gustavsson, J. and Cederberg, C.: Global Food losses and Food waste, in: Save Food Congress, Düsseldorf, Germany, 16 May 2011.
Haberl, H., Erb, K. H., Krausmann, F., Gaube, V., Bondeau, A., Plutzar, C., Gingrich, S., Lucht, W., and Fischer-Kowalski, M.: Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems, P. Natl. Acad. Sci. USA, 104, 12942–12947, https://doi.org/10.1073/pnas.0704243104, 2007.
Havlík, P., Valin, H., Herrero, M., Obersteiner, M., Schmid, E., Rufino, M. C., Mosnier, A., Thornton, P. K., Böttcher, H., Conant, R. T., Frank, S., Fritz, S., Fuss, S., Kraxner, F., and Notenbaert, A.: Climate change mitigation through livestock system transitions, P. Natl. Acad. Sci. USA, 111, 3709–3714, https://doi.org/10.1073/pnas.1308044111, 2014.
Herrero, M., Henderson, B., Havlík, P., Thornton, P. K., Conant, R. T., Smith, P., Wirsenius, S., Hristov, A. N., Gerber, P., Gill, M., Butterbach-Bahl, K., Valin, H., Garnett, T., and Stehfest, E.: Greenhouse gas mitigation potentials in the livestock sector, Nat. Clim. Chang., 6, 452–461, https://doi.org/10.1038/nclimate2925, 2016.
Holman, B. W. B. and Malau-Aduli, A. E. O.: Spirulina as a livestock supplement and animal feed, J. Anim. Physiol. An. N., 97, 615–623, https://doi.org/10.1111/j.1439-0396.2012.01328.x, 2013.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., and Fischer, G.: Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands, Climatic Change, 109, 117–161, https://doi.org/10.1007/s10584-011-0153-2, 2011.
Iizumi, T., Furuya, J., Shen, Z., Kim, W., Okada, M., Fujimori, S., Hasegawa, T., and Nishimori, M.: Responses of crop yield growth to global temperature and socioeconomic changes, Sci. Rep., 7, 1–10, https://doi.org/10.1038/s41598-017-08214-4, 2017.
KC, S. and Lutz, W.: The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100, Global Environ. Chang., 42, 181–192, https://doi.org/10.1016/j.gloenvcha.2014.06.004, 2017.
Kearney, J.: Food consumption trends and drivers, Philos. T. Roy. Soc. B, 365, 2793–2807, https://doi.org/10.1098/rstb.2010.0149, 2010.
Kitinoja, L.: Use of cold chains for reducing food losses in developing countries, PEF White Pap., 6, 1–16, 2013.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Krausmann, F., Erb, K. H., Gingrich, S., Lauk, C., and Haberl, H.: Global patterns of socioeconomic biomass flows in the year 2000: A comprehensive assessment of supply, consumption and constraints, Ecol. Econ., 65, 471–487, https://doi.org/10.1016/j.ecolecon.2007.07.012, 2008.
Lambin, E. F. and Meyfroidt, P.: Global land use change, economic globalization, and the looming land scarcity, P. Natl. Acad. Sci. USA, 108, 3465–3472, https://doi.org/10.1073/pnas.1100480108, 2011.
Lambin, E. F., Geist, H. J., and Lepers, E.: Dynamics of land-use and land-cover change in tropical regions, Annu. Rev. Env. Resour., 28, 205–241, https://doi.org/10.1146/annurev.energy.28.050302.105459, 2003.
Lipinski, B., Hanson, C., Lomax, J., Kitinoja, L., Waite, R., and Searchinger, T.: Reducing Food Loss and Waste, working paper, World Resources Institute, available at: https://www.wri.org/research/reducing-food-loss-and-waste (last access: 7 December 2021), 2013.
Liu, C., Hotta, Y., Santo, A., Hengesbaugh, M., Watabe, A., Totoki, Y., Allen, D., and Bengtsson, M.: Food waste in Japan: Trends, current practices and key challenges, J. Clean. Prod., 133, 557–564, https://doi.org/10.1016/j.jclepro.2016.06.026, 2016.
Mohanty, S. K. and Swain, M. R.: Chapter 3 – Bioethanol Production From Corn and Wheat: Food, Fuel, and Future, in: Bioethanol Production from Food Crops, Elsevier Inc., 45-59, ISBN: 978-0-12-813766-6, 2019.
Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., and Foley, J. A.: Closing yield gaps through nutrient and water management, Nature, 490, 254–257, https://doi.org/10.1038/nature11420, 2012.
Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J. S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A. P., Kriegler, E., Leach, N. J., Marchegiani, D., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A. N., Skeie, R. B., Smith, C. J., Smith, S., Tanaka, K., Tsutsui, J., and Xie, Z.: Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response, Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, 2020.
Oerke, E. C. and Dehne, H. W.: Safeguarding production – Losses in major crops and the role of crop protection, Crop Prot., 23, 275–285, https://doi.org/10.1016/j.cropro.2003.10.001, 2004.
Oliveira Vieira, E., Venturoso, O. J., Reinicke, F., Cézar, C., Silva, D., Oliveira Porto, M., Cavali, J., Vieira, N. T., and Ferreira, E.: Production, Conservation and Health Assessment of Acid Silage Vicera of Freshwater Fish as a Component of Animal Feed, International Journal of Agriculture and Forestry, 5, 177–181, https://doi.org/10.5923/j.ijaf.20150503.01, 2015.
Parfitt, J., Barthel, M., and MacNaughton, S.: Food waste within food supply chains: Quantification and potential for change to 2050, Philos. T. R. Soc. B, 365, 3065–3081, https://doi.org/10.1098/rstb.2010.0126, 2010.
Pikaar, I., Matassa, S., Bodirsky, B. L., Weindl, I., Der, F. H., Rabaey, K., Boon, N., Bruschi, M., Yuan, Z., Van Zanten, H., Herrero, M., Verstraete, W., and Popp, A.: Decoupling Livestock from Land Use through Industrial Feed Production Pathways, Environ. Sci. Technol., 52, 7351–7359, https://doi.org/10.1021/acs.est.8b00216, 2018.
Popp, A., Rose, S. K., Calvin, K., Van Vuuren, D. P., Dietrich, J. P., Wise, M., Stehfest, E., Humpenöder, F., Kyle, P., Van Vliet, J., Bauer, N., Lotze-Campen, H., Klein, D., and Kriegler, E.: Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options, Clim. Change, 123, 495–509, https://doi.org/10.1007/s10584-013-0926-x, 2014.
Popp, A., Calvin, K., Fujimori, S., Havlik, P.,
Humpenöder, F., Stehfest, E., Bodirsky, B. L., Dietrich, J. P.,
Doelmann, J. C., Gusti, M., Hasegawa, T., Kyle, P., Obersteiner, M.,
Tabeau, A., Takahashi, K., Valin, H., Waldhoff, S., Weindl, I.,
Wise, M., Kriegler, E., Lotze-Campen, H., Fricko, O., Riahi, K., and
Van Vuuren, D. P.: Land-use futures in the shared socio-economic pathways, Global Environ. Chang., 42, 331–345, https://doi.org/10.1016/j.gloenvcha.2016.10.002, 2017.
Powell, T.: Closing loops to rebalance the global carbon cycle: Biomass flows modelling of global agricultural carbon fluxes, PhD Thesis, Univ. Exet., 2015.
Powell, T. W. R. and Lenton, T. M.: Future carbon dioxide removal via biomass energy constrained by agricultural efficiency and dietary trends, Energy Environ. Sci., 5, 8116–8133, https://doi.org/10.1039/c2ee21592f, 2012.
Ray, D. K., Ramankutty, N., Mueller, N. D., West, P. C., and Foley, J. A.: Recent patterns of crop yield growth and stagnation, Nat. Commun., 3, 1293–1297, https://doi.org/10.1038/ncomms2296, 2012.
Ray, D. K., Gerber, J. S., Macdonald, G. K., and West, P. C.: Climate variation explains a third of global crop yield variability, Nat. Commun., 6, 1–9, https://doi.org/10.1038/ncomms6989, 2015.
Roe, S., Streck, C., Obersteiner, M., Frank, S., Griscom, B., Drouet, L., Fricko, O., Gusti, M., Harris, N., Hasegawa, T., Hausfather, Z., Havlík, P., House, J., Nabuurs, G., Popp, A., José, M., Sánchez, S., Sanderman, J., Smith, P., Stehfest, E., and Lawrence, D.: Contribution of the land sector to a 1.5 ∘C world, Nat. Clim. Chang., 9, 817–828, https://doi.org/10.1038/s41558-019-0591-9, 2019.
Rogelj, J., Shindell, D., Jiang, K., Fifita, S., Forster, P., Ginzburg, V., Handa, C., Kheshgi, H., Kobayashi, S., Kriegler, E., Mundaca, L., Séférian, R. and Vilariño, M. V.: Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development, in: Global Warming of 1.5 ∘C, in: IPCC Special Report on the impacts of global warming of 1.5 ∘C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty, IPCC, 2022.
Röös, E., Bajželj, B., Smith, P., Patel, M., Little, D., and Garnett, T.: Greedy or needy? Land use and climate impacts of food in 2050 under different livestock futures, Global Environ. Chang., 47, 1–12, https://doi.org/10.1016/j.gloenvcha.2017.09.001, 2017.
Sarofim, M. C., Smith, J. B., St. Juliana, A., and Hartin, C.: Improving reduced complexity model assessment and usability, Nat. Clim. Chang., 11, 9–11, https://doi.org/10.1038/s41558-020-00973-9, 2021.
Savary, S., Ficke, A., Aubertot, J. N., and Hollier, C.: Crop losses due to diseases and their implications for global food production losses and food security, Food Secur., 4, 519–537, https://doi.org/10.1007/s12571-012-0200-5, 2012.
Shepon, A., Eshel, G., Noor, E., and Milo, R.: Energy and protein feed-to-food conversion efficiencies in the US and potential food security gains from dietary changes, Environ. Res. Lett., 11, 105002, https://doi.org/10.1088/1748-9326/11/10/105002, 2016.
Singh, I. D. and Stoskopf, N. C.: Harvest Index in Cereals1, Agron. J., 63, 224–226, https://doi.org/10.2134/agronj1971.00021962006300020008x, 1971.
Stancu, V., Haugaard, P., and Lähteenmäki, L.: Determinants of consumer food waste behaviour: Two routes to food waste, Appetite, 96, 7–17, https://doi.org/10.1016/j.appet.2015.08.025, 2016.
Swain, M., Blomqvist, L., McNamara, J., and Ripple, W. J.: Reducing the environmental impact of global diets, Sci. Total Environ., 610–611, 1207–1209, https://doi.org/10.1016/j.scitotenv.2017.08.125, 2018.
Willett, W., Rockström, J., Loken, B., et al.: Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems, The Lancet, 393, 10170, 447–492, https://doi.org/10.1016/S0140-6736(18)31788-4, 2019.
Thornton, P. K.: Livestock production: Recent trends, future prospects, Philos. T. R. Soc. B, 365, 2853–2867, https://doi.org/10.1098/rstb.2010.0134, 2010.
Tilman, D. and Clark, M.: Global diets link environmental sustainability and human health, Nature, 515, 518–522, https://doi.org/10.1038/nature13959, 2014.
Tsugane, S. and Sawada, N.: The JPHC study: Design and some findings on the typical Japanese diet, Jpn. J. Clin. Oncol., 44, 777–782, https://doi.org/10.1093/jjco/hyu096, 2014.
Tufarelli, V., Ragni, M., and Laudadio, V.: Feeding forage in poultry: A promising alternative for the future of production systems, Agriculture, 8, 1–10, https://doi.org/10.3390/agriculture8060081, 2018.
UNFCCC: Conference of the Parties, Adoption of the Paris Agreement, U.N. Doc. FCCC/CP/2015/L.9/Rev/1, available at: https://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf (last access: 7 December 2021), 2015.
United Nations Environment Programme: Food Waste Index – Report 2021, Report, ISBN: 978-92-807-3851-3, 2021.
Van Dyk, J. S., Gama, R., Morrison, D., Swart, S., and Pletschke, B. I.: Food processing waste: Problems, current management and prospects for utilisation of the lignocellulose component through enzyme synergistic degradation, Renew. Sust. Energ. Rev., 26, 521–531, https://doi.org/10.1016/j.rser.2013.06.016, 2013.
Van Rossum, G. and Drake Jr., F. L.: Python reference manual, Centrum voor Wiskunde en Informatica, Amsterdam, 1995.
Van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Clim. Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Van Zanten, H. H. E., Herrero, M., Van Hal, O., Röös, E., Muller, A., Garnett, T., Gerber, P. J., Schader, C., and De Boer, I. J. M.: Defining a land boundary for sustainable livestock consumption, Global Change Biol., 24, 4185–4194, https://doi.org/10.1111/gcb.14321, 2018.
Vaughan, N. E., Gough, C., Mander, S., Littleton, E. W., Welfle, A., Gernaat, D. E. H. J., and Van Vuuren, D. P.: Evaluating the use of biomass energy with carbon capture and storage in low emission scenarios, Environ. Res. Lett., 13, 044014, https://doi.org/10.1088/1748-9326/aaaa02, 2018.
Weindl, I., Popp, A., Bodirsky, B. L., Rolinski, S., Lotze-Campen, H., Biewald, A., Humpenöder, F., Dietrich, J. P., and Stevanović, M.: Livestock and human use of land: Productivity trends and dietary choices as drivers of future land and carbon dynamics, Global Planet. Change, 159, 1–10, https://doi.org/10.1016/j.gloplacha.2017.10.002, 2017.
Winkler, K., Fuchs, R., Rounsevell, M., and Herold, M.: Global land use changes are four times greater than previously estimated, Nat. Commun., 12, 1–10, https://doi.org/10.1038/s41467-021-22702-2, 2021.
Wirsenius, S., Azar, C., and Berndes, G.: How much land is needed for global food production under scenarios of dietary changes and livestock productivity increases in 2030?, Agr. Syst., 103, 621–638, https://doi.org/10.1016/j.agsy.2010.07.005, 2010.
World Bank: Worldwide Governance IndicatorsWorldwide Governance Indicators, available at: https://databank.worldbank.org/source/worldwide-governance-indicators/ (last access: 13 January 2022), 2020.
Short summary
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.
C-LLAMA is a simple model of the global food system operating at a country level from 2013 to...
