- Articles & preprints
- Submission
- Policies
- Peer-review process
- Editorial board
- About
- EGU publications
- Manuscript tracking
Journal cover
Journal topic
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
Journal topic
- Articles & preprints
- Submission
- Policies
- Peer-review process
- Editorial board
- About
- EGU publications
- Manuscript tracking
Journal metrics
IF5.240
IF 5-year
5.768
5.768
CiteScore
8.9
8.9
SNIP1.713
IPP5.53
SJR3.18
Scimago H
index71
index71
h5-index51
Abstracted/indexed
Abstracted/indexed
GMD | Articles | Volume 12, issue 1
Geosci. Model Dev., 12, 179–193, 2019
https://doi.org/10.5194/gmd-12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue: Joint UK Land Environment Simulator (JULES) – configurations,...
Geosci. Model Dev., 12, 179–193, 2019
https://doi.org/10.5194/gmd-12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Development and technical paper 09 Jan 2019
Development and technical paper | 09 Jan 2019
Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)
Chantelle Burton et al.
Related authors
Douglas I. Kelley, Chantelle Burton, Chris Huntingford, Megan A. J. Brown, Rhys Whitley, and Ning Dong
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-123, https://doi.org/10.5194/bg-2020-123, 2020
Revised manuscript accepted for BG
Short summary
Short summary
Initial evidence suggests human ignitions or landscape changes caused most Amazon fires during August 2019. However, confirmation is needed that meteorological conditions did not also have a substantial role. Assessing the influence of historical weather on fire frequency, and in an uncertainty framework, we find that 2019 meteorological conditions alone would have meant fewer-than-usual fires. We conclude socio-economic factors likely had a strong role in the high recorded 2019 fire activity.
Gilvan Sampaio, Marília Shimizu, Carlos A. Guimarães-Júnior, Felipe Alexandre, Manoel Cardoso, Tomas F. Domingues, Anja Rammig, Celso von Randow, Luiz F. C. Rezende, and David M. Lapola
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-386, https://doi.org/10.5194/bg-2020-386, 2020
Preprint under review for BG
Short summary
Short summary
The impact of large-scale deforestation and the physiological effects of elevated atmospheric CO2 on Amazon rainfall are systematically compared in this study. Our results are remarkable in showing that the two disturbances cause equivalent rainfall decrease, though through different causal mechanisms. These results highlight the importance of not only curbing regional deforestation but also reducing global CO2 emissions to avoid climatic changes in the Amazon.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastien Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-286, https://doi.org/10.5194/essd-2020-286, 2020
Revised manuscript accepted for ESSD
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ärdo, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-273, https://doi.org/10.5194/gmd-2020-273, 2020
Preprint under review for GMD
Short summary
Short summary
Drought is predicted to increase in the future due to climate change. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid damage, and this response is important for the global carbon cycle and local/regional climate feedbacks. We evaluated ten representations of stress in the JULES land-surface model against site observations, and make recommendations for future use of the model.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
Short summary
Short summary
The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-319, https://doi.org/10.5194/bg-2020-319, 2020
Preprint under review for BG
Short summary
Short summary
Global climate modelsare the scientist's
toolsused in studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land and atmosphere, and climate. This work shows that discrepancies compared to observations remain demanding further polishing of these tools.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
Short summary
Short summary
Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
Short summary
Short summary
The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Thomas A. M. Pugh, Tim Rademacher, Sarah L. Shafer, Jörg Steinkamp, Jonathan Barichivich, Brian Beckage, Vanessa Haverd, Anna Harper, Jens Heinke, Kazuya Nishina, Anja Rammig, Hisashi Sato, Almut Arneth, Stijn Hantson, Thomas Hickler, Markus Kautz, Benjamin Quesada, Benjamin Smith, and Kirsten Thonicke
Biogeosciences, 17, 3961–3989, https://doi.org/10.5194/bg-17-3961-2020, https://doi.org/10.5194/bg-17-3961-2020, 2020
Short summary
Short summary
The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle. Estimates from six contemporary models found this time to range from 12.2 to 23.5 years for the global mean for 1985–2014. Future projections do not give consistent results, but 13 model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce large current uncertainty.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen A. Sitch, and Sonke Zaehle
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-205, https://doi.org/10.5194/gmd-2020-205, 2020
Preprint under review for GMD
Short summary
Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle which is included within the UK Earth System model to improve projections of cliamte change and impacts on ecosystems.
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
Short summary
Short summary
Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
Short summary
Short summary
Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
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. Discuss., https://doi.org/10.5194/esd-2020-24, https://doi.org/10.5194/esd-2020-24, 2020
Preprint under review for ESD
Short summary
Short summary
In the Paris Climate Agreement, countries agreed to keep global warming since pre-industrial times below 2 °C and ideally below 1.5 °C, requiring major reductions in greenhouse gas emissions. We investigate the regional effectiveness of lowering methane emissions from human activities, (re)afforestation, and growing bioenergy crops. Methane reduction always helps, especially for major methane-emitting regions. However, the preferred land-management strategy and its effectiveness is more variable.
Andrew H. MacDougall, Thomas L. Frölicher, Chris D. Jones, Joeri Rogelj, H. Damon Matthews, Kirsten Zickfeld, Vivek K. Arora, Noah J. Barrett, Victor Brovkin, Friedrich A. Burger, Micheal Eby, Alexey V. Eliseev, Tomohiro Hajima, Philip B. Holden, Aurich Jeltsch-Thömmes, Charles Koven, Nadine Mengis, Laurie Menviel, Martine Michou, Igor I. Mokhov, Akira Oka, Jörg Schwinger, Roland Séférian, Gary Shaffer, Andrei Sokolov, Kaoru Tachiiri, Jerry Tjiputra, Andrew Wiltshire, and Tilo Ziehn
Biogeosciences, 17, 2987–3016, https://doi.org/10.5194/bg-17-2987-2020, https://doi.org/10.5194/bg-17-2987-2020, 2020
Short summary
Short summary
The Zero Emissions Commitment (ZEC) is the change in global temperature expected to occur following the complete cessation of CO2 emissions. Here we use 18 climate models to assess the value of ZEC. For our experiment we find that ZEC 50 years after emissions cease is between −0.36 to +0.29 °C. The most likely value of ZEC is assessed to be close to zero. However, substantial continued warming for decades or centuries following cessation of CO2 emission cannot be ruled out.
Felix Leung, Karina Williams, Stephen Sitch, Amos P.K. Tai, Andy Wiltshire, Jemma Gornall, Elizabeth A. Ainsworth, Timiothy Arkebauer, and David Scoby
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-97, https://doi.org/10.5194/gmd-2020-97, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Ground-level ozone (O3) is detrimental to plant productivity and crop yield. Currently the Joint UK Land Environment Simulator (JULES) includes a representation of crops (JULES-crop). The parameters for O3 damage in soybean in JULES-crop were calibrated against photosynthesis measurements from the Soybean Free-Air-Concentration-Enrichment (SoyFACE). The result shows good performance for yield and it helps contribute to understanding of the impacts of climate and air pollution on food production.
Doug McNeall, Jonny Williams, Richard Betts, Ben Booth, Peter Challenor, Peter Good, and Andy Wiltshire
Geosci. Model Dev., 13, 2487–2509, https://doi.org/10.5194/gmd-13-2487-2020, https://doi.org/10.5194/gmd-13-2487-2020, 2020
Short summary
Short summary
In the climate model FAMOUS, matching the modelled Amazon rainforest to observations required different land surface parameter settings than for other forests. It was unclear if this discrepancy was due to a bias in the modelled climate or an error in the land surface component of the model. Correcting the climate of the model with a statistical model corrects the simulation of the Amazon forest, suggesting that the land surface component of the model is not the source of the discrepancy.
Douglas I. Kelley, Chantelle Burton, Chris Huntingford, Megan A. J. Brown, Rhys Whitley, and Ning Dong
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-123, https://doi.org/10.5194/bg-2020-123, 2020
Revised manuscript accepted for BG
Short summary
Short summary
Initial evidence suggests human ignitions or landscape changes caused most Amazon fires during August 2019. However, confirmation is needed that meteorological conditions did not also have a substantial role. Assessing the influence of historical weather on fire frequency, and in an uncertainty framework, we find that 2019 meteorological conditions alone would have meant fewer-than-usual fires. We conclude socio-economic factors likely had a strong role in the high recorded 2019 fire activity.
Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu
Earth Syst. Sci. Data, 12, 789–804, https://doi.org/10.5194/essd-12-789-2020, https://doi.org/10.5194/essd-12-789-2020, 2020
Short summary
Short summary
We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.
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
Short summary
Short summary
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.
Andrew J. Wiltshire, Maria Carolina Duran Rojas, John M. Edwards, Nicola Gedney, Anna B. Harper, Andrew J. Hartley, Margaret A. Hendry, Eddy Robertson, and Kerry Smout-Day
Geosci. Model Dev., 13, 483–505, https://doi.org/10.5194/gmd-13-483-2020, https://doi.org/10.5194/gmd-13-483-2020, 2020
Short summary
Short summary
We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator (JULES). JULES-GL7 can be used to simulate the exchange of heat, water and momentum over land and is therefore applicable for helping understand past and future changes, and forms the land component of the HadGEM3-GC3.1 climate model. The configuration is freely available subject to licence restrictions.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd Folberth, Paul Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark G. Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, Joao C. Teixeira, Steven Turnock, Jonny Williams, Andy Wiltshire, and Guang Zeng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1152, https://doi.org/10.5194/acp-2019-1152, 2020
Revised manuscript accepted for ACP
Short summary
Short summary
This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day, using a metric called effective radiative forcing. The impact of land use change has also been assessed. We find that individual contributions do not add linearly and different Earth System interactions can affect the magnitude of the calculated effective radiative forcing.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
Short summary
Short summary
The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
Short summary
Short summary
This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Brendan Byrne, Dylan B. A. Jones, Kimberly Strong, Saroja M. Polavarapu, Anna B. Harper, David F. Baker, and Shamil Maksyutov
Atmos. Chem. Phys., 19, 13017–13035, https://doi.org/10.5194/acp-19-13017-2019, https://doi.org/10.5194/acp-19-13017-2019, 2019
Short summary
Short summary
Interannual variations in net ecosystem exchange (NEE) estimated from the Greenhouse Gases Observing Satellite (GOSAT) XCO2 measurements are shown to be correlated (P < 0.05) with temperature and FLUXCOM NEE anomalies. Furthermore, the GOSAT-informed NEE anomalies are found to be better correlated with temperature and FLUXCOM anomalies than NEE estimates from most terrestrial biosphere models, suggesting that GOSAT CO2 measurements provide a useful constraint on NEE interannual variability.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, https://doi.org/10.5194/gmd-12-4375-2019, 2019
Short summary
Short summary
Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
Short summary
Short summary
Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Sihan Li, David E. Rupp, Linnia Hawkins, Philip W. Mote, Doug McNeall, Sarah N. Sparrow, David C. H. Wallom, Richard A. Betts, and Justin J. Wettstein
Geosci. Model Dev., 12, 3017–3043, https://doi.org/10.5194/gmd-12-3017-2019, https://doi.org/10.5194/gmd-12-3017-2019, 2019
Short summary
Short summary
Understanding the unfolding challenges of climate change relies on climate models, many of which have regional biases larger than the expected climate signal over the next half-century. This work shows the potential for improving climate model simulations through a multiphased parameter refinement approach. Regional warm biases are substantially reduced, suggesting this iterative approach is one path to improving climate models and simulations of present and future climate.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-85, https://doi.org/10.5194/gmd-2019-85, 2019
Revised manuscript under review for GMD
Short summary
Short summary
Tropical regions commonly plant different crops in the same field one after the other in rotation, this is sequential cropping (also known as multiple or double cropping). Land surface models (LSMs) typically simulate a single crop per year, but to understand demand for resources we need to simulate all of the crops grown within a year in a seamless way. We implement sequential cropping into JULES and demonstrate it works for a site in Avignon and 4 locations in India.
Sarah Shannon, Robin Smith, Andy Wiltshire, Tony Payne, Matthias Huss, Richard Betts, John Caesar, Aris Koutroulis, Darren Jones, and Stephan Harrison
The Cryosphere, 13, 325–350, https://doi.org/10.5194/tc-13-325-2019, https://doi.org/10.5194/tc-13-325-2019, 2019
Short summary
Short summary
We present global glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding 2 °C global average warming. The ice loss contribution to sea level rise for all glaciers excluding those on the peripheral of the Antarctic ice sheet is 215.2 ± 21.3 mm. Such large ice losses will have consequences for sea level rise and for water supply in glacier-fed river systems.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
Short summary
Short summary
Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
Short summary
Short summary
Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Gregory Duveiller, Giovanni Forzieri, Eddy Robertson, Wei Li, Goran Georgievski, Peter Lawrence, Andy Wiltshire, Philippe Ciais, Julia Pongratz, Stephen Sitch, Almut Arneth, and Alessandro Cescatti
Earth Syst. Sci. Data, 10, 1265–1279, https://doi.org/10.5194/essd-10-1265-2018, https://doi.org/10.5194/essd-10-1265-2018, 2018
Short summary
Short summary
Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate. While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
Short summary
Short summary
Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Stephan Harrison, Jeffrey S. Kargel, Christian Huggel, John Reynolds, Dan H. Shugar, Richard A. Betts, Adam Emmer, Neil Glasser, Umesh K. Haritashya, Jan Klimeš, Liam Reinhardt, Yvonne Schaub, Andy Wiltshire, Dhananjay Regmi, and Vít Vilímek
The Cryosphere, 12, 1195–1209, https://doi.org/10.5194/tc-12-1195-2018, https://doi.org/10.5194/tc-12-1195-2018, 2018
Short summary
Short summary
Most mountain glaciers have receded throughout the last century in response to global climate change. This recession produces a range of natural hazards including glacial lake outburst floods (GLOFs). We have produced the first global inventory of GLOFs associated with the failure of moraine dams and show, counterintuitively, that these have reduced in frequency over recent decades. In this paper we explore the reasons for this pattern.
David P. Keller, Andrew Lenton, Vivian Scott, Naomi E. Vaughan, Nico Bauer, Duoying Ji, Chris D. Jones, Ben Kravitz, Helene Muri, and Kirsten Zickfeld
Geosci. Model Dev., 11, 1133–1160, https://doi.org/10.5194/gmd-11-1133-2018, https://doi.org/10.5194/gmd-11-1133-2018, 2018
Short summary
Short summary
There is little consensus on the impacts and efficacy of proposed carbon dioxide removal (CDR) methods as a potential means of mitigating climate change. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDR-MIP) has been initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDR-MIP experiments.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
Short summary
Short summary
In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
Short summary
Short summary
This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
Short summary
Short summary
We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
Short summary
Short summary
Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
Short summary
Short summary
Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Karina Williams, Jemma Gornall, Anna Harper, Andy Wiltshire, Debbie Hemming, Tristan Quaife, Tim Arkebauer, and David Scoby
Geosci. Model Dev., 10, 1291–1320, https://doi.org/10.5194/gmd-10-1291-2017, https://doi.org/10.5194/gmd-10-1291-2017, 2017
Short summary
Short summary
This study looks in detail at how well the crop model within the Joint UK Land Environment Simulator (JULES), a community land-surface model, is able to simulate irrigated maize in Nebraska. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties.
Sam S. Rabin, Joe R. Melton, Gitta Lasslop, Dominique Bachelet, Matthew Forrest, Stijn Hantson, Jed O. Kaplan, Fang Li, Stéphane Mangeon, Daniel S. Ward, Chao Yue, Vivek K. Arora, Thomas Hickler, Silvia Kloster, Wolfgang Knorr, Lars Nieradzik, Allan Spessa, Gerd A. Folberth, Tim Sheehan, Apostolos Voulgarakis, Douglas I. Kelley, I. Colin Prentice, Stephen Sitch, Sandy Harrison, and Almut Arneth
Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, https://doi.org/10.5194/gmd-10-1175-2017, 2017
Short summary
Short summary
Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include. A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance. It also includes equations for all models.
Finn Müller-Hansen, Manoel F. Cardoso, Eloi L. Dalla-Nora, Jonathan F. Donges, Jobst Heitzig, Jürgen Kurths, and Kirsten Thonicke
Nonlin. Processes Geophys., 24, 113–123, https://doi.org/10.5194/npg-24-113-2017, https://doi.org/10.5194/npg-24-113-2017, 2017
Short summary
Short summary
Deforestation and subsequent land uses in the Brazilian Amazon have huge impacts on greenhouse gas emissions, local climate and biodiversity. To better understand these land-cover changes, we apply complex systems methods uncovering spatial patterns in regional transition probabilities between land-cover types, which we estimate using maps derived from satellite imagery. The results show clusters of similar land-cover dynamics and thus complement studies at the local scale.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
Short summary
Short summary
An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Doug McNeall, Jonny Williams, Ben Booth, Richard Betts, Peter Challenor, Andy Wiltshire, and David Sexton
Earth Syst. Dynam., 7, 917–935, https://doi.org/10.5194/esd-7-917-2016, https://doi.org/10.5194/esd-7-917-2016, 2016
Short summary
Short summary
We compare simulated with observed forests to constrain uncertain input parameters of the land surface component of a climate model.
We find that the model is unlikely to be able to simulate the Amazon and other major forests simultaneously at any one parameter set, suggesting a bias in the model's representation of the Amazon.
We find we cannot constrain parameters individually, but we can rule out large areas of joint parameter space.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
Short summary
Short summary
The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
Short summary
Short summary
The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
David M. Lawrence, George C. Hurtt, Almut Arneth, Victor Brovkin, Kate V. Calvin, Andrew D. Jones, Chris D. Jones, Peter J. Lawrence, Nathalie de Noblet-Ducoudré, Julia Pongratz, Sonia I. Seneviratne, and Elena Shevliakova
Geosci. Model Dev., 9, 2973–2998, https://doi.org/10.5194/gmd-9-2973-2016, https://doi.org/10.5194/gmd-9-2973-2016, 2016
Short summary
Short summary
Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The goal of LUMIP is to take the next steps in land-use change science, and enable, coordinate, and ultimately address the most important land-use science questions in more depth and sophistication than possible in a multi-model context to date.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
Short summary
Short summary
How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Stéphane Mangeon, Apostolos Voulgarakis, Richard Gilham, Anna Harper, Stephen Sitch, and Gerd Folberth
Geosci. Model Dev., 9, 2685–2700, https://doi.org/10.5194/gmd-9-2685-2016, https://doi.org/10.5194/gmd-9-2685-2016, 2016
Short summary
Short summary
To understand the role of fires in the Earth system, global fire models are required. In this paper we describe the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO). It follows a reduced complexity approach using mainly temperature, humidity and precipitation. INFERNO was found to perform well on a global scale and to maintain regional patterns over the 1997–2011 period of study, despite regional biases particularly linked to fuel consumption.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
Short summary
Short summary
Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
Short summary
Short summary
Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
Short summary
Short summary
We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
C. Mathison, A. J. Wiltshire, P. Falloon, and A. J. Challinor
Hydrol. Earth Syst. Sci., 19, 4783–4810, https://doi.org/10.5194/hess-19-4783-2015, https://doi.org/10.5194/hess-19-4783-2015, 2015
Short summary
Short summary
South Asia is a highly variable region where there is concern over water and food security. The simulations presented suggest an increasing trend in water resources, in some cases almost doubling by the end of the century although this is masked by the large annual variability of river flows for this region. Future peak river flows still occur during the monsoon period, with a tendency for reduced frequency of lowest flows and increased magnitude of highest flows across the selected locations.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
Short summary
Short summary
Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
J. Lloyd, T. F. Domingues, F. Schrodt, F. Y. Ishida, T. R. Feldpausch, G. Saiz, C. A. Quesada, M. Schwarz, M. Torello-Raventos, M. Gilpin, B. S. Marimon, B. H. Marimon-Junior, J. A. Ratter, J. Grace, G. B. Nardoto, E. Veenendaal, L. Arroyo, D. Villarroel, T. J. Killeen, M. Steininger, and O. L. Phillips
Biogeosciences, 12, 6529–6571, https://doi.org/10.5194/bg-12-6529-2015, https://doi.org/10.5194/bg-12-6529-2015, 2015
Short summary
Short summary
Across tropical South America, forest soils are typically of a higher cation status than their savanna equivalents with soil exchangeable potassium a key soil nutrient differentiating these two vegetation types. Differences in soil water storage capacity are also important – interacting with both potassium availability and precipitation regimes in a relatively complex manner.
C. D. Koven, J. Q. Chambers, K. Georgiou, R. Knox, R. Negron-Juarez, W. J. Riley, V. K. Arora, V. Brovkin, P. Friedlingstein, and C. D. Jones
Biogeosciences, 12, 5211–5228, https://doi.org/10.5194/bg-12-5211-2015, https://doi.org/10.5194/bg-12-5211-2015, 2015
Short summary
Short summary
Terrestrial carbon feedbacks are a large uncertainty in climate change. We separate modeled feedback responses into those governed by changed carbon inputs (productivity) and changed outputs (turnover). The disaggregated responses show that both are important in controlling inter-model uncertainty. Interactions between productivity and turnover are also important, and research must focus on these interactions for more accurate projections of carbon cycle feedbacks.
G. Saiz, M. Bird, C. Wurster, C. A. Quesada, P. Ascough, T. Domingues, F. Schrodt, M. Schwarz, T. R. Feldpausch, E. Veenendaal, G. Djagbletey, G. Jacobsen, F. Hien, H. Compaore, A. Diallo, and J. Lloyd
Biogeosciences, 12, 5041–5059, https://doi.org/10.5194/bg-12-5041-2015, https://doi.org/10.5194/bg-12-5041-2015, 2015
Short summary
Short summary
We demonstrate and explain differential patterns in SOM dynamics in C3/C4 mixed ecosystems at various spatial scales across contrasting climate and soils. This study shows that the interdependence between biotic and abiotic factors ultimately determines whether SOM dynamics of C3- and C4-derived vegetation are at variance in ecosystems where both vegetation types coexist. The results also highlight the far-reaching implications that vegetation thickening may have for the stability of deep SOM.
B. Poulter, N. MacBean, A. Hartley, I. Khlystova, O. Arino, R. Betts, S. Bontemps, M. Boettcher, C. Brockmann, P. Defourny, S. Hagemann, M. Herold, G. Kirches, C. Lamarche, D. Lederer, C. Ottlé, M. Peters, and P. Peylin
Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, https://doi.org/10.5194/gmd-8-2315-2015, 2015
Short summary
Short summary
Land cover is an essential variable in earth system models and determines conditions driving biogeochemical, energy and water exchange between ecosystems and the atmosphere. A methodology is presented for mapping plant functional types used in global vegetation models from a updated land cover classification system and open-source conversion tool, resulting from a consultative process among map producers and modelers engaged in the European Space Agency’s Land Cover Climate Change Initiative.
P. R. Halloran, B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker
Biogeosciences, 12, 4497–4508, https://doi.org/10.5194/bg-12-4497-2015, https://doi.org/10.5194/bg-12-4497-2015, 2015
Short summary
Short summary
The oceans currently take up around a quarter of the carbon dioxide (CO2) emitted by human activity. While stored in the ocean, this CO2 is not causing global warming. Here we explore high latitude North Atlantic CO2 uptake across a set of climate model simulations, and find that the models show a peak in ocean CO2 uptake around the middle of the century after which time CO2 uptake begins to decline. We identify the causes of this long-term change and interannual variability in the models.
E. M. Veenendaal, M. Torello-Raventos, T. R. Feldpausch, T. F. Domingues, F. Gerard, F. Schrodt, G. Saiz, C. A. Quesada, G. Djagbletey, A. Ford, J. Kemp, B. S. Marimon, B. H. Marimon-Junior, E. Lenza, J. A. Ratter, L. Maracahipes, D. Sasaki, B. Sonké, L. Zapfack, D. Villarroel, M. Schwarz, F. Yoko Ishida, M. Gilpin, G. B. Nardoto, K. Affum-Baffoe, L. Arroyo, K. Bloomfield, G. Ceca, H. Compaore, K. Davies, A. Diallo, N. M. Fyllas, J. Gignoux, F. Hien, M. Johnson, E. Mougin, P. Hiernaux, T. Killeen, D. Metcalfe, H. S. Miranda, M. Steininger, K. Sykora, M. I. Bird, J. Grace, S. Lewis, O. L. Phillips, and J. Lloyd
Biogeosciences, 12, 2927–2951, https://doi.org/10.5194/bg-12-2927-2015, https://doi.org/10.5194/bg-12-2927-2015, 2015
Short summary
Short summary
When nearby forest and savanna stands are compared, they are not as structurally different as first seems. Moreover, savanna-forest transition zones typically occur at higher rainfall for South America than for Africa but with coexistence confined to a well-defined edaphic-climate envelope. With interacting soil cation-soil water storage–precipitations effects on canopy cover also observed we argue that both soils and climate influence the location of the two major tropical vegetation types.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
Short summary
Short summary
Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
T. Osborne, J. Gornall, J. Hooker, K. Williams, A. Wiltshire, R. Betts, and T. Wheeler
Geosci. Model Dev., 8, 1139–1155, https://doi.org/10.5194/gmd-8-1139-2015, https://doi.org/10.5194/gmd-8-1139-2015, 2015
L. Rowland, A. Harper, B. O. Christoffersen, D. R. Galbraith, H. M. A. Imbuzeiro, T. L. Powell, C. Doughty, N. M. Levine, Y. Malhi, S. R. Saleska, P. R. Moorcroft, P. Meir, and M. Williams
Geosci. Model Dev., 8, 1097–1110, https://doi.org/10.5194/gmd-8-1097-2015, https://doi.org/10.5194/gmd-8-1097-2015, 2015
Short summary
Short summary
This study evaluates the capability of five vegetation models to simulate the response of forest productivity to changes in temperature and drought, using data collected from an Amazonian forest. This study concludes that model consistencies in the responses of net canopy carbon production to temperature and precipitation change were the result of inconsistently modelled leaf-scale process responses and substantial variation in modelled leaf area responses.
R. A. Betts, N. Golding, P. Gonzalez, J. Gornall, R. Kahana, G. Kay, L. Mitchell, and A. Wiltshire
Biogeosciences, 12, 1317–1338, https://doi.org/10.5194/bg-12-1317-2015, https://doi.org/10.5194/bg-12-1317-2015, 2015
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
A. J. Wiltshire
The Cryosphere, 8, 941–958, https://doi.org/10.5194/tc-8-941-2014, https://doi.org/10.5194/tc-8-941-2014, 2014
K. E. O. Todd-Brown, J. T. Randerson, F. Hopkins, V. Arora, T. Hajima, C. Jones, E. Shevliakova, J. Tjiputra, E. Volodin, T. Wu, Q. Zhang, and S. D. Allison
Biogeosciences, 11, 2341–2356, https://doi.org/10.5194/bg-11-2341-2014, https://doi.org/10.5194/bg-11-2341-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
J. C. S. Davie, P. D. Falloon, R. Kahana, R. Dankers, R. Betts, F. T. Portmann, D. Wisser, D. B. Clark, A. Ito, Y. Masaki, K. Nishina, B. Fekete, Z. Tessler, Y. Wada, X. Liu, Q. Tang, S. Hagemann, T. Stacke, R. Pavlick, S. Schaphoff, S. N. Gosling, W. Franssen, and N. Arnell
Earth Syst. Dynam., 4, 359–374, https://doi.org/10.5194/esd-4-359-2013, https://doi.org/10.5194/esd-4-359-2013, 2013
S. Hagemann, C. Chen, D. B. Clark, S. Folwell, S. N. Gosling, I. Haddeland, N. Hanasaki, J. Heinke, F. Ludwig, F. Voss, and A. J. Wiltshire
Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, https://doi.org/10.5194/esd-4-129-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Related subject area
Biogeosciences
Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14
Modeling the impacts of diffuse light fraction on photosynthesis in ORCHIDEE (v5453) land surface model
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
A multi-isotope model for simulating soil organic carbon cycling in eroding landscapes (WATEM_C v1.0)
One-dimensional models of radiation transfer in heterogeneous canopies: a review, re-evaluation, and improved model
An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)
Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)
FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence
The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage
Evaluation of CH4MODwetland and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands
Simulating stable carbon isotopes in the ocean component of the FAMOUS general circulation model with MOSES1 (XOAVI)
Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
Marine biogeochemical cycling and oceanic CO2 uptake simulated by the NUIST Earth System Model version 3 (NESM v3)
Soil carbon estimates by Yasso15 model improved with state data assimilation
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance
Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation-fire model SSiB4/TRIFFID-Fire v1.0
Calibrating soybean parameters in JULES5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O3 experiment
Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0
HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)
BPOP-v1 model: exploring the impact of changes in the biological pump on the shelf sea and ocean nutrient and redox state
P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production
HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 2: Phenology and water cycle
Dynamic upscaling of decomposition kinetics for carbon cycling models
CE-DYNAM (v1): a spatially explicit process-based carbon erosion scheme for use in Earth system models
A coupled pelagic–benthic–sympagic biogeochemical model for the Bering Sea: documentation and validation of the BESTNPZ model (v2019.08.23) within a high-resolution regional ocean model
FORests and HYdrology under Climate Change in Switzerland v1.0: a spatially distributed model combining hydrology and forest dynamics
ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 2: Model evaluation over the Lena River basin
GLOBAL-FATE (version 1.0.0): A geographical information system (GIS)-based model for assessing contaminants fate in the global river network
A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?
Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data
Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production
A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996)
Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED)
A lattice-automaton bioturbation simulator with coupled physics, chemistry, and biology in marine sediments (eLABS v0.2)
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)
Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH
Evaluation of leaf-level optical properties employed in land surface models
ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 1: Rationale, model description, and simulation protocol
Modelling northern peatland area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488)
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1
The quasi-equilibrium framework revisited: analyzing long-term CO2 enrichment responses in plant–soil models
Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy
CO2 drawdown due to particle ballasting by glacial aeolian dust: an estimate based on the ocean carbon cycle model MPIOM/HAMOCC version 1.6.2p3
Towards end-to-end (E2E) modelling in a consistent NPZD-F modelling framework (ECOSMO E2E_v1.0): application to the North Sea and Baltic Sea
Evaluating the E3SM land model version 0 (ELMv0) at a temperate forest site using flux and soil water measurements
The [simple carbon project] model v1.0
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
Short summary
Short summary
We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
Short summary
Short summary
We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
Short summary
Short summary
The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
Zhengang Wang, Jianxiu Qiu, and Kristof Van Oost
Geosci. Model Dev., 13, 4977–4992, https://doi.org/10.5194/gmd-13-4977-2020, https://doi.org/10.5194/gmd-13-4977-2020, 2020
Short summary
Short summary
This study developed a spatially distributed carbon cycling model applicable in an eroding landscape. It includes all three carbon isotopes so that it is able to represent the carbon isotopic compositions. The model is able to represent the observations that eroding area is enriched in 13C and depleted of 14C compared to depositional area. Our simulations show that the spatial variability of carbon isotopic properties in an eroding landscape is mainly caused by the soil redistribution.
Brian N. Bailey, María A. Ponce de León, and E. Scott Krayenhoff
Geosci. Model Dev., 13, 4789–4808, https://doi.org/10.5194/gmd-13-4789-2020, https://doi.org/10.5194/gmd-13-4789-2020, 2020
Short summary
Short summary
Numerous models of plant radiation interception based on a range of assumptions are available in the literature, but the importance of each assumption is not well understood. In this work, we evaluate several assumptions common in simple models of radiation interception in canopies with widely spaced plants by comparing against a detailed 3-D model. This yielded a simple model based on readily measurable parameters that could accurately predict interception for a wide range of architectures.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020, https://doi.org/10.5194/gmd-13-4459-2020, 2020
Short summary
Short summary
Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Emily Kyker-Snowman, William R. Wieder, Serita D. Frey, and A. Stuart Grandy
Geosci. Model Dev., 13, 4413–4434, https://doi.org/10.5194/gmd-13-4413-2020, https://doi.org/10.5194/gmd-13-4413-2020, 2020
Short summary
Short summary
Microbes drive carbon (C) and nitrogen (N) transformations in soil, and soil models have started to include explicit microbial physiology and functioning to try to reduce uncertainty in soil–climate feedbacks. Here, we add N cycling to a microbially explicit soil C model and reproduce C and N dynamics in soil during litter decomposition across a range of sites. We discuss model-generated hypotheses about soil C and N cycling and highlight the need for landscape-scale model evaluation data.
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev., 13, 4091–4106, https://doi.org/10.5194/gmd-13-4091-2020, https://doi.org/10.5194/gmd-13-4091-2020, 2020
Short summary
Short summary
One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020, https://doi.org/10.5194/gmd-13-4041-2020, 2020
Short summary
Short summary
Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. The canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind SIF emission from complex forest canopies.
Femke Lutz, Stephen Del Grosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 13, 3905–3923, https://doi.org/10.5194/gmd-13-3905-2020, https://doi.org/10.5194/gmd-13-3905-2020, 2020
Short summary
Short summary
Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analyses on global estimates of tillage effects on N2O emissions. By comparing model results with observational data of four experimental sites and outputs from field-scale DayCent model simulations, we show that advancing information on agricultural management, as well as the representation of soil moisture dynamics, improves LPJmL5.0-tillage and the estimates of tillage effects on N2O emissions.
Tingting Li, Yanyu Lu, Lingfei Yu, Wenjuan Sun, Qing Zhang, Wen Zhang, Guocheng Wang, Zhangcai Qin, Lijun Yu, Hailing Li, and Ran Zhang
Geosci. Model Dev., 13, 3769–3788, https://doi.org/10.5194/gmd-13-3769-2020, https://doi.org/10.5194/gmd-13-3769-2020, 2020
Short summary
Short summary
Reliable models are required to estimate global wetland CH4 emissions, which are the largest and most uncertain source of atmospheric CH4. This paper evaluated CH4MODwetland and TEM models against CH4 measurements from different continents and wetland types. Based on best-model performance, we estimated 117–125 Tg yr−1 of global CH4 emissions from wetlands for the period 2000–2010. Efforts should be made to reduce estimate uncertainties for different wetland types and regions.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, and Laura F. Robinson
Geosci. Model Dev., 13, 3529–3552, https://doi.org/10.5194/gmd-13-3529-2020, https://doi.org/10.5194/gmd-13-3529-2020, 2020
Short summary
Short summary
We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model captures the large-scale spatial pattern of observations but the simulated values are consistently higher than observed. In the first instance, our new tracer is therefore useful for recalibrating the physical and biogeochemical components of the model.
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
Short summary
Short summary
Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020, https://doi.org/10.5194/gmd-13-3119-2020, 2020
Short summary
Short summary
NESM v3 is one of the CMIP6 registered Earth system models. We evaluate its ocean carbon cycle component and present its present-day and future oceanic CO2 uptake based on the CMIP6 historical and SSP5–8.5 scenarios. We hope that this paper can serve as a documentation of the marine biogeochemical cycle in NESM v3. Also, the model defects found and their underlying causes analyzed in this paper could help users and further model development.
Toni Viskari, Maisa Laine, Liisa Kulmala, Jarmo Mäkela, Istem Fer, and Jari Liski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-141, https://doi.org/10.5194/gmd-2020-141, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The research here established if a Bayesian statistical method called state data assimilation could be used to improve soil organic carbon (SOC) forecasts. Our test case was a Fallow experiment where SOC content was measured over several decades from a plot where all vegetation was removed. Our results showed that state data assimilation improved projections and allowed for the detailed model state be updated with coarse total carbon measurements.
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, https://doi.org/10.5194/gmd-13-2825-2020, 2020
Short summary
Short summary
We transitioned the CLASS-CTEM land surface model to an open-source community model format by modernizing the code base to make the model easier to use and understand, providing a complete software environment to run the model within, developing a benchmarking suite for model evaluation, and creating an infrastructure to support community involvement. The new model, the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC), is now available for the community to use and develop.
Huilin Huang, Yongkang Xue, Fang Li, and Ye Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-122, https://doi.org/10.5194/gmd-2020-122, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Fire is a major disturbance to the world’s biomes and influences the surface fluxes and climate. To assess the long-term fire impact on ecosystem and climate, we developed a fire-coupled dynamic vegetation model that captures the spatial distribution and temporal variability of fire regime. We find fire is an important determinant of the structure and functions of the savanna. By changing the vegetation distribution and ecosystem characteristics, fire causes an increase in surface temperature.
Felix Leung, Karina Williams, Stephen Sitch, Amos P.K. Tai, Andy Wiltshire, Jemma Gornall, Elizabeth A. Ainsworth, Timiothy Arkebauer, and David Scoby
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-97, https://doi.org/10.5194/gmd-2020-97, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Ground-level ozone (O3) is detrimental to plant productivity and crop yield. Currently the Joint UK Land Environment Simulator (JULES) includes a representation of crops (JULES-crop). The parameters for O3 damage in soybean in JULES-crop were calibrated against photosynthesis measurements from the Soybean Free-Air-Concentration-Enrichment (SoyFACE). The result shows good performance for yield and it helps contribute to understanding of the impacts of climate and air pollution on food production.
Virginie Moreaux, Simon Martel, Alexandre Bosc, Delphine Picart, David Achat, Christophe Moisy, Raphael Aussenac, Christophe Chipeaux, Jean-Marc Bonnefond, Pierre Trichet, Rémi Vezy, Vincent Badeau, Bernard Longdoz, André Granier, Olivier Roupsard, Manuel Nicolas, Kim Pilegaard, Giorgio Matteucci, Claudy Jolivet, Andrew T. Black, Olivier Picard, and Denis Loustau
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-66, https://doi.org/10.5194/gmd-2020-66, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The model GO+ describes the functioning of managed forests based upon biophysical and biogeochemical processes. GO+ accounts for the impacts of forest operations on energy, water and carbon exchanges within the soil-vegetation-atmosphere continuum. It includes versatile descriptions of management operations. Its sensitivity and uncertainty are detailed and predictions are compared with observations about mass and energy exchanges, hydrological and tree growth variables from different sites.
Giovanni Denaro, Daniela Salvagio Manta, Alessandro Borri, Maria Bonsignore, Davide Valenti, Enza Quinci, Andrea Cucco, Bernardo Spagnolo, Mario Sprovieri, and Andrea De Gaetano
Geosci. Model Dev., 13, 2073–2093, https://doi.org/10.5194/gmd-13-2073-2020, https://doi.org/10.5194/gmd-13-2073-2020, 2020
Short summary
Short summary
The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in seawater and marine sediments, of three mercury species (elemental, inorganic, and organic mercury) in a highly polluted marine environment (Augusta Bay, southern Italy). The model shows fair agreement with the experimental data collected during six different oceanographic cruises and can possibly be used for a detailed exploration of the effects of climate change on mercury distribution.
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
Short summary
Short summary
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.
Benjamin D. Stocker, Han Wang, Nicholas G. Smith, Sandy P. Harrison, Trevor F. Keenan, David Sandoval, Tyler Davis, and I. Colin Prentice
Geosci. Model Dev., 13, 1545–1581, https://doi.org/10.5194/gmd-13-1545-2020, https://doi.org/10.5194/gmd-13-1545-2020, 2020
Short summary
Short summary
Estimating terrestrial photosynthesis relies on satellite data of vegetation cover and models simulating the efficiency by which light absorbed by vegetation is used for CO2 assimilation. This paper presents the P-model, a light use efficiency model derived from a carbon–water optimality principle, and evaluates its predictions of ecosystem-level photosynthesis against globally distributed observations. The model is implemented and openly accessible as an R package (rpmodel).
Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
Short summary
Short summary
Given their key role in the simulation of climate impacts on tree growth, phenological and water balance processes must be integrated in models simulating forest dynamics under a changing environment. Here, we describe these processes integrated in HETEROFOR, a model accounting simultaneously for the functional, structural and spatial complexity to explore the forest response to forestry practices. The model evaluation using phenological and soil water content observations is quite promising.
Arjun Chakrawal, Anke M. Herrmann, John Koestel, Jerker Jarsjö, Naoise Nunan, Thomas Kätterer, and Stefano Manzoni
Geosci. Model Dev., 13, 1399–1429, https://doi.org/10.5194/gmd-13-1399-2020, https://doi.org/10.5194/gmd-13-1399-2020, 2020
Short summary
Short summary
Soils are heterogeneous, which results in a nonuniform spatial distribution of substrates and the microorganisms feeding on them. Our results show that the variability in the spatial distribution of substrates and microorganisms at the pore scale is crucial because it affects how fast substrates are used by microorganisms and thus the decomposition rate observed at the soil core scale. This work provides a methodology to include microscale heterogeneity in soil carbon cycling models.
Victoria Naipal, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, and Yilong Wang
Geosci. Model Dev., 13, 1201–1222, https://doi.org/10.5194/gmd-13-1201-2020, https://doi.org/10.5194/gmd-13-1201-2020, 2020
Short summary
Short summary
In this study we present the Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the soil carbon cycle along a cascade of hillslopes, floodplains, and rivers. The model can simulate the removal of soil and carbon from eroding areas and their destination at regional scale. We calibrated and validated the model for the Rhine catchment, and we show that soil erosion is a potential large net carbon sink over the period 1850–2005.
Kelly Kearney, Albert Hermann, Wei Cheng, Ivonne Ortiz, and Kerim Aydin
Geosci. Model Dev., 13, 597–650, https://doi.org/10.5194/gmd-13-597-2020, https://doi.org/10.5194/gmd-13-597-2020, 2020
Short summary
Short summary
We describe an ecosystem model for the Bering Sea. Biological components in the Bering Sea can be found in the water column, on and within the bottom sediments, and within the porous lower layer of seasonal sea ice. This model simulates the exchange of material between nutrients and plankton within all three environments. Here, we thoroughly document the model and assess its skill in capturing key biophysical features across the Bering Sea.
Matthias J. R. Speich, Massimiliano Zappa, Marc Scherstjanoi, and Heike Lischke
Geosci. Model Dev., 13, 537–564, https://doi.org/10.5194/gmd-13-537-2020, https://doi.org/10.5194/gmd-13-537-2020, 2020
Short summary
Short summary
Climate change is expected to substantially affect natural processes, and simulation models are a valuable tool to anticipate these changes. In this study, we combine two existing models that each describe one aspect of the environment: forest dynamics and the terrestrial water cycle. The coupled model better described observed patterns in vegetation structure. We also found that including the effect of water availability on tree height and rooting depth improved the model.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Pierre Regnier, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 13, 507–520, https://doi.org/10.5194/gmd-13-507-2020, https://doi.org/10.5194/gmd-13-507-2020, 2020
Short summary
Short summary
In this second part of the study, we performed simulations of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. We compare simulations using this model to existing data sources to show that it is capable of reproducing dissolved carbon fluxes of potentially great importance for the future of the global permafrost.
Carme Font, Francesco Bregoli, Vicenç Acuña, Sergi Sabater, and Rafael Marcé
Geosci. Model Dev., 12, 5213–5228, https://doi.org/10.5194/gmd-12-5213-2019, https://doi.org/10.5194/gmd-12-5213-2019, 2019
Short summary
Short summary
GLOBAL-FATE is an open-source, multiplatform, and flexible model that simulates the fate of pharmaceutical-like compounds in the global river network. The model considers the consumption of pharmaceuticals by humans, differentiates between pharmaceutical load treated in wastewater treatment plants from that directly delivered to streams and rivers, and integrates lakes and reservoirs in calculations. GLOBAL-FATE is a powerful tool for pollutant impact studies at the global scale.
Luke Gregor, Alice D. Lebehot, Schalk Kok, and Pedro M. Scheel Monteiro
Geosci. Model Dev., 12, 5113–5136, https://doi.org/10.5194/gmd-12-5113-2019, https://doi.org/10.5194/gmd-12-5113-2019, 2019
Short summary
Short summary
The ocean plays a vital role in mitigating climate change by taking up atmospheric carbon dioxide (CO2). Historically sparse ship-based measurements of surface ocean CO2 make direct estimates of CO2 exchange changes unreliable. We introduce a machine-learning ensemble approach to fill these observational gaps. Our method performs incrementally better relative to past methods, leading to our hypothesis that we are perhaps reaching the limitation of machine-learning algorithms' capability.
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
Short summary
Short summary
This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
Short summary
Short summary
In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
Short summary
Short summary
To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Dave van Wees and Guido R. van der Werf
Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, https://doi.org/10.5194/gmd-12-4681-2019, 2019
Short summary
Short summary
For this paper, a novel high spatial-resolution fire emission model based on the Global Fire Emissions Database (GFED) modelling framework was developed and compared to a coarser-resolution version of the same model. Our findings highlight the importance of fine spatial resolution when modelling global-scale fire emissions, especially considering the comparison of model pixels to individual field measurements and the model representation of heterogeneity in the landscape.
Yoshiki Kanzaki, Bernard P. Boudreau, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 12, 4469–4496, https://doi.org/10.5194/gmd-12-4469-2019, https://doi.org/10.5194/gmd-12-4469-2019, 2019
Short summary
Short summary
This paper provides eLABS, an extension of the lattice-automaton bioturbation simulator LABS. In our new model, the benthic animal behavior interacts and changes dynamically with oxygen and organic matter concentrations and the water flows caused by benthic animals themselves, in a 2-D marine-sediment grid. The model can address the mechanisms behind empirical observations of bioturbation based on the interactions between physical, chemical and biological aspects of marine sediment.
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, https://doi.org/10.5194/gmd-12-4309-2019, 2019
Short summary
Short summary
Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, https://doi.org/10.5194/gmd-12-4347-2019, 2019
Short summary
Short summary
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Elias C. Massoud, Chonggang Xu, Rosie A. Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, and Jasper A. Vrugt
Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, https://doi.org/10.5194/gmd-12-4133-2019, 2019
Short summary
Short summary
We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model 5000 times with changing input parameter values, we found that (1) the photosynthetic capacity controls carbon fluxes, (2) the allometry is important for tree growth, and (3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
Short summary
Short summary
We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
Titta Majasalmi and Ryan M. Bright
Geosci. Model Dev., 12, 3923–3938, https://doi.org/10.5194/gmd-12-3923-2019, https://doi.org/10.5194/gmd-12-3923-2019, 2019
Short summary
Short summary
Many land surface models rely on solutions derived from two-stream approximations utilizing leaf-level optical properties, many of which have not been formally reviewed or published. Using plant functional type groupings of the Community Land Model (CLM), we found large deviations between measured and CLM default near-infrared optical properties, implying that the modeled shortwave radiation budget including surface albedo may be expected to change after updating the biased parameters.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 12, 3503–3521, https://doi.org/10.5194/gmd-12-3503-2019, https://doi.org/10.5194/gmd-12-3503-2019, 2019
Short summary
Short summary
Few Earth system models represent permafrost soil biogeochemistry, contributing to uncertainty in estimating its response and that of the planet to warming. Because the permafrost contains over double the carbon in the present atmosphere, its fate as it is
unlockedby warming is globally significant. One way it can be mobilised is into rivers, the sea, or the atmosphere: a vector previously ignored in climate modelling. We present a model scheme for resolving this vector at a global scale.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie
Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019, https://doi.org/10.5194/gmd-12-2961-2019, 2019
Short summary
Short summary
We present a model that can simulate the dynamics of peatland area extent and the vertical buildup of peat. The model is validated across a range of northern peatland sites and over the Northern Hemisphere (> 30° N). It is able to reproduce the spatial extent of northern peatlands and peat carbon accumulation over the Holocene.
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019, https://doi.org/10.5194/gmd-12-2419-2019, 2019
Short summary
Short summary
Tillage practices are under-represented in global biogeochemical models so that assessments of agricultural greenhouse gas emissions and climate mitigation options are hampered. We describe the implementation of tillage modules into the model LPJmL5.0, including multiple feedbacks between soil water, nitrogen, and productivity. By comparing simulation results with observational data, we show that the model can reproduce reported tillage effects on carbon and water dynamics and crop yields.
Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019, https://doi.org/10.5194/gmd-12-2227-2019, 2019
Short summary
Short summary
Photosynthesis and evapotranspiration are processes with global significance for climate, carbon and water cycling. Process-orientated simulation of these processes and their interactions have till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement, with a typical R2 value of ~ 0.60.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
Short summary
Short summary
Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
Ahmed S. Elshall, Ming Ye, Guo-Yue Niu, and Greg A. Barron-Gafford
Geosci. Model Dev., 12, 2009–2032, https://doi.org/10.5194/gmd-12-2009-2019, https://doi.org/10.5194/gmd-12-2009-2019, 2019
Short summary
Short summary
The assumptions that the residuals are independent, identically distributed, and have constant variance tend to simplify the underlying mathematics of data models for Bayesian inference. We relax these three assumptions step-wise, resulting in eight data models. Using three mechanistic soil respiration models with different levels of model discrepancy, we discuss the impacts of data models on parameter estimation and predictive performance, and provide recommendations for data model selection.
Malte Heinemann, Joachim Segschneider, and Birgit Schneider
Geosci. Model Dev., 12, 1869–1883, https://doi.org/10.5194/gmd-12-1869-2019, https://doi.org/10.5194/gmd-12-1869-2019, 2019
Short summary
Short summary
Ocean CO2 uptake played a crucial role for the global cooling during ice ages. Dust formation, e.g. by ice scraping over bedrock, potentially contributed to this CO2 uptake because (1) the iron in the dust is a fertilizer and (2) the heavy dust particles can accelerate sinking organic matter (ballasting hypothesis). This study tests the glacial dust ballasting hypothesis for the first time, using an ocean model. It turns out, however, that the ballasting effect probably played a minor role.
Ute Daewel, Corinna Schrum, and Jed I. Macdonald
Geosci. Model Dev., 12, 1765–1789, https://doi.org/10.5194/gmd-12-1765-2019, https://doi.org/10.5194/gmd-12-1765-2019, 2019
Short summary
Short summary
Here we propose a novel modelling approach that includes an extended food web in a functional-group-type marine ecosystem model (ECOSMO E2E) by formulating new groups for macrobenthos and fish. This enables the estimation of the dynamics of the higher-trophic-level production potential and constitutes a more consistent closure term for the lower-trophic-level ecosystem. Thus, the model allows for the study of the control mechanisms for marine ecosystems at a high spatial and temporal resolution.
Junyi Liang, Gangsheng Wang, Daniel M. Ricciuto, Lianhong Gu, Paul J. Hanson, Jeffrey D. Wood, and Melanie A. Mayes
Geosci. Model Dev., 12, 1601–1612, https://doi.org/10.5194/gmd-12-1601-2019, https://doi.org/10.5194/gmd-12-1601-2019, 2019
Short summary
Short summary
Soil respiration, the second largest carbon fluxes between the atmosphere and land, is not well represented in global land models. In this study, using long-term observations at a temperate forest, we identified a solution for using better soil water potential simulations to improve predictions of soil respiration in the E3SM land model. In addition, parameter calibration further improved model performance.
Cameron M. O'Neill, Andrew McC. Hogg, Michael J. Ellwood, Stephen M. Eggins, and Bradley N. Opdyke
Geosci. Model Dev., 12, 1541–1572, https://doi.org/10.5194/gmd-12-1541-2019, https://doi.org/10.5194/gmd-12-1541-2019, 2019
Short summary
Short summary
The [simple carbon project] model v1.0 (SCP-M) was constructed for simulations of the paleo and modern carbon cycle. In this paper we show its application to the carbon cycle transition from the Last Glacial Maximum to the Holocene period. Our model–data experiment uses SCP-M's fast run time to cover a large range of possible inputs. The results highlight the role of varying the strength of ocean circulation to account for large fluctuations in atmospheric CO2 across the two periods.
Cited articles
Alonso-Canas, I. and Chuvieco, E.: Global burned area mapping from
ENVISAT-MERIS and MODIS active fire data, Remote Sens. Environ., 163,
140–152, https://doi.org/10.1016/j.rse.2015.03.011, 2015.
Andela, N., Morton, D., Giglio, L., Chen, Y., van der Werf, G., Kasibhatla,
P., DeFries, R., Collatz, G., Hantson, S., Kloster, S., Bachelet, D.,
Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J., Yue, C., and
Randerson, J.: A human-driven decline in global burned area, Science, 356,
1356–1361, 2017.
Aragão, L. and Shimabukuro, Y.: The Incidence of Fire in Amazonian
Forests with Implications for REDD, Science, 328, 1275–1278, 2010.
Aragão, L., Malhi, Y., Barbier, N., Lima, A., Shimabukuro, Y., Anderson,
L., and Saatchi, S.: Interactions between rainfall, deforestation and fires
during recent years in the Brazilian Amazonia, Philos. T. Roy. Soc. B, 363,
1779–1785, 2008.
Aragão, L., Anderson, L. O., Fonseca, M. G., Rosan, T. M., Vedovato, L.
B., Wagner, F. H., Silva, C. V. J., Silva, C. H. L., Arai, E., Aguiar, A. P.,
Barlow, J., Berenguer, E., Deeter, M. N., Domingues, L. G., Gatti, L., Gloor,
M., Malhi, Y., Marengo, J. A., Miller, J. B., Phillips O. L., and Saatchi,
S.: 21st Century drought-related fires counteract the decline of Amazon
deforestation carbon emissions, Nat. Commun., 9, 536,
https://doi.org/10.1038/s41467-017-02771-y, 2018.
Archibald, S., Lehmann, C. E. R., Gomez-Dans, J. L., and Bradstock, R. A.:
Defining pyromes and global syndromes of fire regimes, P. Natl. Acad. Sci.
USA, 110, 6442–6447, https://doi.org/10.1073/pnas.1211466110, 2013.
Arneth, A., Sitch, S., Pongratz, J., Stocker, B. D., Ciais, P., Poulter, B.,
Bayer, A. D., Bondeau, A., Calle, L., Chini, L. P., Gasser, T., Fader, M.,
Friedlingstein, P., Kato, E., Li, W., Lindeskog, M., Nabel, J. E. M. S.,
Pugh, T. A. M., Robertson, E., Viovy, N., Yue, C., and Zaehle, S.: Historical
carbon dioxide emissions caused by land-use changes are possibly larger than
assumed, Nat. Geosci.,10, 79–84, https://doi.org/10.1038/ngeo2882, 2017.
Bagley, J., Desai, A., Harding, K., Snyder, P., and Foley, J.: Drought and
Deforestation: Has Land Cover Change Influenced Recent Precipitation Extremes
in the Amazon?, J. Climate, 27, 345–361, 2014.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H.,
Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N.,
Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C.
S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES),
model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4,
677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Betts, R.: Integrated approaches to climate-crop modelling: needs and
challenges, Philos. T. Roy. Soc. B, 360, 2049–2065, 2005.
Betts, R. A., Golding, N., Gonzalez, P., Gornall, J., Kahana, R., Kay, G.,
Mitchell, L., and Wiltshire, A.: Climate and land use change impacts on
global terrestrial ecosystems and river flows in the HadGEM2-ES Earth system
model using the representative concentration pathways, Biogeosciences, 12,
1317–1338, https://doi.org/10.5194/bg-12-1317-2015, 2015.
Bistinas, I., Harrison, S. P., Prentice, I. C., and Pereira, J. M. C.: Causal
relationships versus emergent patterns in the global controls of fire
frequency, Biogeosciences, 11, 5087–5101,
https://doi.org/10.5194/bg-11-5087-2014, 2014.
Bond, W. J., Woodward, F. I., and Midgley, G. F.: The global distribution of
ecosystems in a world without fire, New Phytol., 165, 525–537,
https://doi.org/10.1111/j.1469-8137.2004.01252.x, 2005.
Brando, P., Balch, J., Nepstad, D., Morton, D., Putz, F., Coe, M., Silverio,
D., Macedo, M., Davidson, E., Nobrega, C., Alencar, A., and Soares, B.:
Abrupt increases in Amazonian tree mortality due to drought-fire
interactions, P. Natl. Acad. Sci. USA, 111, 6347–6352, 2014.
Burton, C., Betts, R. A., Jones, C. D., and Williams, K.: Will fire danger be
reduced by using Solar Radiation Management to limit global warming to
1.5 ∘C compared to 2.0 ∘C?, Geophys. Res. Lett., 45,
3644–3652, 2018.
Cano-Crespo, A., Oliveira, P., Boit, A., Cardoso, M., and Thonicke, K.:
Forest edge burning in the Brazilian Amazon promoted by escaping fires from
managed pastures, J. Geophys. Res.-Biogeo., 120, 2095–2107, 2015.
Cardoso, M., Hurtt, G., Moore, B., Nobrem C., and Prins, E.: Projecting
future fire activity in Amazonia, Glob. Change Biol., 9, 656–669, 2003.
Cardoso, M., Nobre, C., Lapola, D., Oyama, M., and Sampaio, G.: Long-term
potential for fires in estimates of the occurrence of savannas in the
tropics, Global Ecol. Biogeogr., 17, 222–235,
https://doi.org/10.1111/j.1466-8238.2007.00356.x, 2008.
Castello, L. and Macedo, M. N.: Large-scale degradation of Amazonian
freshwater ecosystems, Glob. Change Biol., 22, 990–1007, 2016.
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J.,
Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le
Quéré, C., Myneni, R. B., Piao, S., and Thornton, P.: Carbon and
Other Biogeochemical Cycles, in: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia,
Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK
and New York, NY, USA, 2013.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M.
J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O.,
Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land
Environment Simulator (JULES), model description – Part 2: Carbon fluxes and
vegetation dynamics, Geosci. Model Dev., 4, 701–722,
https://doi.org/10.5194/gmd-4-701-2011, 2011.
Cochrane, M. A.: Fire Science for Rainforests, Nature, 421, 913–919,
https://doi.org/10.1038/nature01437, 2003.
Cochrane, M. A. and Laurance, W. F.: Synergisms among Fire, Land Use, and
Climate Change in the Amazon, Ambio, 37, 522–527, 2008.
Coe, M., Marthews, T., Costa, M., Galbraith, D., Greenglass, N., Imbuzeiro,
H., Levine, N., Malhi, Y., Moorcroft, P., Muza, M., Powell, T., Saleska, S.,
Solorzano, L., and Wang, J.: Deforestation and climate feedbacks threaten the
ecological integrity of south-southeastern Amazonia, Philos. T. Roy. Soc. B,
368, 1619, https://doi.org/10.1098/rstb.2012.0155, 2013.
Cox, P. M.: Description of the “TRIFFID” Dynamic Global Vegetation Model,
Tech. Note 24, Hadley Centre, Met Office, Bracknell, UK, 16 pp. 2001.
Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., and Totterdell, I. J.:
Acceleration of global warming due to carbon-cycle feedbacks in a coupled
climate model, Nature, 408, 184–187, 2000.
Cruzten, P. J., Heidt, L. E., Krasnec, J. P., Pollock, W. H., and Seiler, W.
G.: Biomass burning as a source of atmospheric gases CO, H2,
N2O, NO, CH3, Cl and COS, Nature, 282, 253–256, 1979.
Davies-Barnard, T., Valdes, P. J., Singarayer, J. S., Wiltshire, A. J., and
Jones, C. D.: Quantifying the relative importance of land cover change from
climate and land use in the representative concentration pathways, Global
Biogeochem. Cy., 29, 842–853, https://doi.org/10.1002/2014GB004949, 2015.
ESA CCI: https://maps.elie.ucl.ac.be/CCI/viewer/ (last access:
4 January 2019), 2010.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins,
W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.:
Evaluation of Climate Models, in: Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia,
Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK
and New York, NY, USA, 2013.
Giglio, L., Randerson, J. T., and Werf, G. R.: Analysis of daily, monthly,
and annual burned area using the fourth generation global fire emissions
database (GFED4), J. Geophys. Res.-Biogeo., 118, 317–328, 2013.
Hantson, S., Arneth, A., Harrison, S. P., Kelley, D. I., Prentice, I. C.,
Rabin, S. S., Archibald, S., Mouillot, F., Arnold, S. R., Artaxo, P.,
Bachelet, D., Ciais, P., Forrest, M., Friedlingstein, P., Hickler, T.,
Kaplan, J. O., Kloster, S., Knorr, W., Lasslop, G., Li, F., Mangeon, S.,
Melton, J. R., Meyn, A., Sitch, S., Spessa, A., van der Werf, G. R.,
Voulgarakis, A., and Yue, C.: The status and challenge of global fire
modelling, Biogeosciences, 13, 3359–3375,
https://doi.org/10.5194/bg-13-3359-2016, 2016.
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C.
D., Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J.,
Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü.,
Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., Soudzilovskaia,
N. A., and Bodegom, P. V.: Improved representation of plant functional types
and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using
plant trait information, Geosci. Model Dev., 9, 2415–2440,
https://doi.org/10.5194/gmd-9-2415-2016, 2016.
Harper, A. B., Wiltshire, A. J., Cox, P. M., Friedlingstein, P., Jones, C.
D., Mercado, L. M., Sitch, S., Williams, K., and Duran-Rojas, C.: Vegetation
distribution and terrestrial carbon cycle in a carbon cycle configuration of
JULES4.6 with new plant functional types, Geosci. Model Dev., 11, 2857–2873,
https://doi.org/10.5194/gmd-11-2857-2018, 2018.
Hartley, A., MacBean, N., Georgievski, G., and Bontempts, S.: Uncertainty in
plant functional type distributions and its impact on land surface models,
Remote Sens. Environ., 203, 71–89, https://doi.org/10.1016/j.rse.2017.07.037, 2017.
Hurtt, G. C., Frolking, S., Fearon, M. G., Moore, B., Shevliakova, E.,
Malyshev, S., Pacala, S. W., and Houghton, R. A.: The underpinnings of
land-use history: three centuries of global gridded land-use transitions,
wood harvest activity, and resulting secondary lands, Glob. Change Biol., 12,
1208–1229, 2006.
Hurtt, G. C., Chini, L., Frolking, S., Betts, R., Feddema, J., Fischer, G.,
Fisk, J., Hibbard, K., Houghton, R., Janetos, A., Jones, C., Kindermann, G.,
Kinoshita, T., Goldewijk, K., Riahi, K., Shevliakova, E., Smith, S.,
Stehfest, E., Thomson, A., Thornton, P., van Vuuren, D., and Wang, Y.:
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, 2011.
Johnson, E. A.: Fire and the vegetation dynamics: studies from the North
American boreal forest. Cambridge studies in ecology, Cambridge University
Press, Cambridge, UK, 1992.
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S.,
Knight, J., Liddicoat, S., O'Connor, F. M., Andres, R. J., Bell, C., Boo,
K.-O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D., Doutriaux-Boucher,
M., Friedlingstein, P., Gornall, J., Gray, L., Halloran, P. R., Hurtt, G.,
Ingram, W. J., Lamarque, J.-F., Law, R. M., Meinshausen, M., Osprey, S.,
Palin, E. J., Parsons Chini, L., Raddatz, T., Sanderson, M. G., Sellar, A.
A., Schurer, A., Valdes, P., Wood, N., Woodward, S., Yoshioka, M., and
Zerroukat, M.: The HadGEM2-ES implementation of CMIP5 centennial simulations,
Geosci. Model Dev., 4, 543–570, https://doi.org/10.5194/gmd-4-543-2011,
2011.
Kelley, D. I., Prentice, I. C., Harrison, S. P., Wang, H., Simard, M.,
Fisher, J. B., and Willis, K. O.: A comprehensive benchmarking system for
evaluating global vegetation models, Biogeosciences, 10, 3313–3340,
https://doi.org/10.5194/bg-10-3313-2013, 2013.
Kelley, D. I., Harrison, S. P., and Prentice, I. C.: Improved simulation of
fire–vegetation interactions in the Land surface Processes and eXchanges
dynamic global vegetation model (LPX-Mv1), Geosci. Model Dev., 7, 2411–2433,
https://doi.org/10.5194/gmd-7-2411-2014, 2014.
Klein Goldewijk, K., Beusen, A., de Vos, M., and van Drecht, G.: The HYDE 3.1
spatially explicit database of human induced land use change over the past
12,000 years, Global Ecol. Biogeogr., 20, 73–86,
https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2011.
Kloster, S. and Lasslop, G.: Historical and future fire occurrence (1850 to
2100) simulated in CMIP5 Earth System Models, Global Planet. Change, 150,
58–69, 2017.
Lasslop, G., Kirsten T., and Kloster, S.: SPITFIRE within the MPI Earth
system model: Model development and evaluation, J. Adv. Model. Earth Sy.,
6.3, 740–755, 2014.
Lasslop, G., Brovkin. V., Reick, C. H., Bathiany, S., and Kloster, S.:
Multiple stable states of tree cover in a global land surface model due to a
fire-vegetation feedback, Geophys. Res. Lett., 43, 6324–6331, 2016.
Laurance, W. F., Vasconcelos, H. L., and Lovejoy, T. E.: Forest loss and
fragmentation in the Amazon: implications for wildlife conservation, Oryx,
34, 39–45, https://doi.org/10.1046/j.1365-3008.2000.00094.x, 2000.
Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken,
J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R.
A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp,
L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney,
S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V.,
Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A.,
Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi,
D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R.,
Nabel, J. E. M. S., Nakaoka, S.-I., O'Brien, K., Olsen, A., Omar, A. M., Ono,
T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U.,
Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A.
J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van
der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., and Zaehle, S.:
Global Carbon Budget 2016, Earth Syst. Sci. Data, 8, 605-649,
https://doi.org/10.5194/essd-8-605-2016, 2016.
Li, F., Zeng, X. D., and Levis, S.: A process-based fire parameterization of
intermediate complexity in a Dynamic Global Vegetation Model, Biogeosciences,
9, 2761–2780, https://doi.org/10.5194/bg-9-2761-2012, 2012.
López-Saldaña, G., Bistinas, I., and Pereira, J. M. C.: Global
analysis of radiative forcing from fire-induced shortwave albedo change,
Biogeosciences, 12, 557–565, https://doi.org/10.5194/bg-12-557-2015, 2015.
Mangeon, S., Voulgarakis, A., Gilham, R., Harper, A., Sitch, S., and
Folberth, G.: INFERNO: a fire and emissions scheme for the UK Met Office's
Unified Model, Geosci. Model Dev., 9, 2685–2700,
https://doi.org/10.5194/gmd-9-2685-2016, 2016.
Mooney, H. A. (Ed.): Convergent in Chile and California Mediterranean Climate
Ecosystems, Dowden, Hutchinson and Ross, Inc. Stroudsberg, Penn., USA, 1977.
Ogden, J., Basher, L., and McGlone, M.: Botanical Briefing: Fire, Forest
Regeneration and Links with Early Human Habitation: Evidence from New
Zealand, Ann. Bot.-London, 81, 687–696, https://doi.org/10.1006/anbo.1998.0637, 1998.
Pellegrini, A. F. A., Anderegg, W. R. L., Paine, C. E. T., Hoffmann, W. A.,
Kartzinel, T., Rabin, S. S., Sheil, D., Franco, A. C., and Pacala, S. W.:
Convergence of bark investment according to fire and climate structures
ecosystem vulnerability to future change, Ecol. Lett., 20, 307–316,
https://doi.org/10.1111/ele.12725, 2017.
Pfeiffer, M., Spessa, A., and Kaplan, J. O.: A model for global biomass
burning in preindustrial time: LPJ-LMfire (v1.0), Geosci. Model Dev., 6,
643–685, https://doi.org/10.5194/gmd-6-643-2013, 2013.
Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R.,
Bontemps, S., Boettcher, M., Brockmann, C., Defourny, P., Hagemann, S.,
Herold, M., Kirches, G., Lamarche, C., Lederer, D., Ottlé, C., Peters,
M., and Peylin, P.: Plant functional type classification for earth system
models: results from the European Space Agency's Land Cover Climate Change
Initiative, Geosci. Model Dev., 8, 2315–2328,
https://doi.org/10.5194/gmd-8-2315-2015, 2015.
Prentice, I. C., Kelley, D., Foster, P., Friedlingstein, P., Harrison, S.,
and Bartlein, P.: Modeling fire and the terrestrial carbon balance, Global
Biogeochem. Cy., 25, GB3005, https://doi.org/10.1029/2010GB003906, 2011.
Pugh, T., Jones, C., Huntingford, C., Burton, C., Arneth, A., Brovkin, V.,
Ciais, P., Lomas, M., Robertson, E., Piao, S., and Sitch, S.: A large
committed long-term sink of carbon due to vegetation dynamics, Earth's
Future, 6, 1413–1432, https://doi.org/10.1029/2018EF000935, 2018.
Rabin, S. S., Melton, J. R., Lasslop, G., Bachelet, D., Forrest, M., Hantson,
S., Kaplan, J. O., Li, F., Mangeon, S., Ward, D. S., Yue, C., Arora, V. K.,
Hickler, T., Kloster, S., Knorr, W., Nieradzik, L., Spessa, A., Folberth, G.
A., Sheehan, T., Voulgarakis, A., Kelley, D. I., Prentice, I. C., Sitch, S.,
Harrison, S., and Arneth, A.: The Fire Modeling Intercomparison Project
(FireMIP), phase 1: experimental and analytical protocols with detailed model
descriptions, Geosci. Model Dev., 10, 1175–1197,
https://doi.org/10.5194/gmd-10-1175-2017, 2017.
Rabin, S. S., Ward, D. S., Malyshev, S. L., Magi, B. I., Shevliakova, E., and
Pacala, S. W.: A fire model with distinct crop, pasture, and non-agricultural
burning: use of new data and a model-fitting algorithm for FINAL.1, Geosci.
Model Dev., 11, 815–842, https://doi.org/10.5194/gmd-11-815-2018, 2018.
Randerson, J., Chen, Y., van der Werf, G., Rogers, B., and Morton, D.: Global
burned area and biomass burning emissions from small fires, J. Geophys. Res.,
117, G04012, https://doi.org/10.1029/2012JG002128, 2012.
Senior, C. A., Andrews, T., Burton, C., Chadwick, R., Copsey, D., Graham, T.,
Hyder, P., Jackson, L., McDonald, R., Ridley, J., Ringer, J., and Tsushima,
Y.: Idealized climate change simulations with a high-resolution physical
model: HadGEM3-GC2, J. Adv. Model. Earth Sy., 8, 813–830,
https://doi.org/10.1002/2015MS000614, 2016.
Seo, H. and Kim, Y.: Interactive Impacts of Fire and Vegetation Dynamics on
Global Carbon and Water Budgets using Community Land Model version 4.5,
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-231, in review,
2018.
Settele, J., Scholes, R., Betts, R., Bunn, S., Leadley, P., Nepstad, D.,
Overpeck, J. T., and Taboada, M. A.: Terrestrial and inland water systems,
in: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A:
Global and Sectoral Aspects. Contribution of Working Group II to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J., Mastrandrea, M.
D., Bilir, T. E., Hatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C.,
Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R.,
and White, L. L., Cambridge University Press, Cambridge, UK and New York, NY,
USA, 271–359, 2014.
Shakesby, R. A. and Doerr, S. H.: Wildfire as a hydrological and
geomorphological agent, Earth-Sci. Rev., 74, 269–307, 2006.
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo,
G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C.,
Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng,
N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais,
P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C.,
Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional
sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679,
https://doi.org/10.5194/bg-12-653-2015, 2015.
Soares, B., Silvestrini, R., Nepstad, D., Brando, P., Rodrigues, H., Alencar,
A., Coe, M., Locks, C., Lima, L., Hissa, L., and Stickler, C.: Forest
fragmentation, climate change and understory fire regimes on the Amazonian
landscapes of the Xingu headwaters, Landscape Ecol., 27, 585–598, 2012.
Staver, A. C., Archibald, S., and Levin, S. A.: The global extent and
determinants of savanna and forest as alternative biome states, Science,
334, 230–232, https://doi.org/10.1126/science.1210465, 2011.
Turner, B. L., Skole, D. L., Sanderson, S., Fischer, G., Fresco, L. O., and
Leemans, R.: Land-use and land-cover change. Science/Research Plan, IGBP
Report No. 35 and HDP Report No. 7, 132 pp., Stockholm, Sweden and Geneva,
Switzerland, 1995.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen,
Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G.
J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates
during 1997–2016, Earth Syst. Sci. Data, 9, 697–720,
https://doi.org/10.5194/essd-9-697-2017, 2017.
Veraverbeke, S., Rogers, B. M., Goulden, M. L., Jandt, R. R., Miller, C. E.,
Wiggins, E. B., and Randerson, J. T.: Lightning as a major driver of recent
large fire years in North American boreal forests, Nat. Clim. Change, 7,
529–534, https://doi.org/10.1038/nclimate3329, 2017.
Watson, R. T., Noble, I. R., Bolin, B., Ravindranath, N. H., Verardo, D. J.,
and Dokkenm D. J. (Eds.): IPCC, Cambridge University Press, Cambridge, UK,
375 pp., 2000.
Search articles
Short summary
Fire and land-use change are important disturbances within the Earth system, and their inclusion in models is critical to enable the correct simulation of vegetation cover. Here we describe developments to the land surface model JULES to represent explicit land-use change and fire and to assess the effects of each process on present day vegetation compared to observations. Using historical land-use data and the fire model INFERNO, overall model results are improved by the developments.
Fire and land-use change are important disturbances within the Earth system, and their inclusion...
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 4.0 License.