Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-2995-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-2995-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
27 Jul 2018
Model description paper |
| 27 Jul 2018
| 27 Jul 2018
A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis
Vanessa Haverd
CORRESPONDING AUTHOR
CSIRO Oceans and Atmosphere, Canberra, 2601, Australia
Benjamin Smith
CSIRO Oceans and Atmosphere, Canberra, 2601, Australia
Dept. of Physical Geography and Ecosystem Science, Lund University,
Sölvegatan 12, 22362 Lund, Sweden
Lars Nieradzik
Centre for Environmental and Climate Research (CEC), Lund University
Sölvegatan 37, 22362 Lund, Sweden
Peter R. Briggs
CSIRO Oceans and Atmosphere, Canberra, 2601, Australia
William Woodgate
CSIRO Land & Water, Canberra, 2601, Australia
Cathy M. Trudinger
CSIRO Oceans and Atmosphere, Melbourne, 3195, Australia
Josep G. Canadell
CSIRO Oceans and Atmosphere, Canberra, 2601, Australia
Matthias Cuntz
INRA, Université de Lorraine, AgroParisTech, UMR Silva, 54000
Nancy, France
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We report on a 3000-year record of carbon monoxide (CO) levels in the Southern Hemisphere's high latitudes by combining ice core and firn air measurements with modern direct atmospheric samples. Antarctica [CO] remained stable (–835 to 1500 CE), decreased during the Little Ice Age, and peaked around 1985 CE. Such evolution reflects stable biomass burning CO emissions before industrialization, followed by growth from CO anthropogenic sources, which decline after 1985 due to improved combustion.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
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This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
H. E. Markus Meier, Marcus Reckermann, Joakim Langner, Ben Smith, and Ira Didenkulova
Earth Syst. Dynam., 14, 519–531, https://doi.org/10.5194/esd-14-519-2023, https://doi.org/10.5194/esd-14-519-2023, 2023
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The Baltic Earth Assessment Reports summarise the current state of knowledge on Earth system science in the Baltic Sea region. The 10 review articles focus on the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Some highlights of the results are presented here.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, and Bo Zheng
Atmos. Chem. Phys., 23, 789–807, https://doi.org/10.5194/acp-23-789-2023, https://doi.org/10.5194/acp-23-789-2023, 2023
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The large uncertainties in OH simulated by atmospheric chemistry models hinder accurate estimates of CH4 chemical loss through the bottom-up method. This study presents a new approach based on OH precursor observations and a chemical box model to improve the tropospheric OH distributions simulated by atmospheric chemistry models. Through this approach, both the global OH burden and the corresponding methane chemical loss reach consistency with the top-down method based on MCF inversions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Luke M. Western, Alison L. Redington, Alistair J. Manning, Cathy M. Trudinger, Lei Hu, Stephan Henne, Xuekun Fang, Lambert J. M. Kuijpers, Christina Theodoridi, David S. Godwin, Jgor Arduini, Bronwyn Dunse, Andreas Engel, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Michela Maione, Jens Mühle, Simon O'Doherty, Hyeri Park, Sunyoung Park, Stefan Reimann, Peter K. Salameh, Daniel Say, Roland Schmidt, Tanja Schuck, Carolina Siso, Kieran M. Stanley, Isaac Vimont, Martin K. Vollmer, Dickon Young, Ronald G. Prinn, Ray F. Weiss, Stephen A. Montzka, and Matthew Rigby
Atmos. Chem. Phys., 22, 9601–9616, https://doi.org/10.5194/acp-22-9601-2022, https://doi.org/10.5194/acp-22-9601-2022, 2022
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The production of ozone-destroying gases is being phased out. Even though production of one of the main ozone-depleting gases, called HCFC-141b, has been declining for many years, the amount that is being released to the atmosphere has been increasing since 2017. We do not know for sure why this is. A possible explanation is that HCFC-141b that was used to make insulating foams many years ago is only now escaping to the atmosphere, or a large part of its production is not being reported.
Jacob D. Morgan, Christo Buizert, Tyler J. Fudge, Kenji Kawamura, Jeffrey P. Severinghaus, and Cathy M. Trudinger
The Cryosphere, 16, 2947–2966, https://doi.org/10.5194/tc-16-2947-2022, https://doi.org/10.5194/tc-16-2947-2022, 2022
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The composition of air bubbles in Antarctic ice cores records information about past changes in properties of the snowpack. We find that, near the South Pole, thinner snowpack in the past is often due to steeper surface topography, in which faster winds erode the snow and deposit it in flatter areas. The slope and wind seem to also cause a seasonal bias in the composition of air bubbles in the ice core. These findings will improve interpretation of other ice cores from places with steep slopes.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 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.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Adrian Gustafson, Paul A. Miller, Robert G. Björk, Stefan Olin, and Benjamin Smith
Biogeosciences, 18, 6329–6347, https://doi.org/10.5194/bg-18-6329-2021, https://doi.org/10.5194/bg-18-6329-2021, 2021
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We performed model simulations of vegetation change for a historic period and a range of climate change scenarios at a high spatial resolution. Projected treeline advance continued at the same or increased rates compared to our historic simulation. Temperature isotherms advanced faster than treelines, revealing a lag in potential vegetation shifts that was modulated by nitrogen availability. At the year 2100 projected treelines had advanced by 45–195 elevational metres depending on the scenario.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
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Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021, https://doi.org/10.5194/gmd-14-6071-2021, 2021
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Forests play an important role in the global carbon cycle and for carbon storage. In Europe, forests are intensively managed. To understand how management influences carbon storage in European forests, we implement detailed forest management into the dynamic vegetation model LPJ-GUESS. We test the model by comparing model output to typical forestry measures, such as growing stock and harvest data, for different countries in Europe.
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021, https://doi.org/10.5194/gmd-14-5891-2021, 2021
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We have proposed and evaluated the use of four benchmarks that leverage tree-ring width observations to provide more nuanced verification targets for land-surface models (LSMs), which currently lack a long-term benchmark for forest ecosystem functioning. Using relatively unbiased European biomass network datasets, we identify the extent to which presumed biases in the much larger International Tree-Ring Data Bank might degrade the validation of LSMs.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Weidong Guo, Sanaa Hobeichi, and Peter R. Briggs
Earth Syst. Dynam., 12, 919–938, https://doi.org/10.5194/esd-12-919-2021, https://doi.org/10.5194/esd-12-919-2021, 2021
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Groundwater can buffer the impacts of drought and heatwaves on ecosystems, which is often neglected in model studies. Using a land surface model with groundwater, we explained how groundwater sustains transpiration and eases heat pressure on plants in heatwaves during multi-year droughts. Our results showed the groundwater’s influences diminish as drought extends and are regulated by plant physiology. We suggest neglecting groundwater in models may overstate projected future heatwave intensity.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
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Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
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, Sebastian 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, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 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.
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.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Antoine Berchet, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, Makoto Deushi, Patrick Jöckel, Douglas Kinnison, Ole Kirner, Sarah Strode, Simone Tilmes, Edward J. Dlugokencky, and Bo Zheng
Atmos. Chem. Phys., 20, 13011–13022, https://doi.org/10.5194/acp-20-13011-2020, https://doi.org/10.5194/acp-20-13011-2020, 2020
Short summary
Short summary
Decadal trends and variations in OH are critical for understanding atmospheric CH4 evolution. We quantify the impacts of OH trends and variations on the CH4 budget by conducting CH4 inversions on a decadal scale with an ensemble of OH fields. We find the negative OH anomalies due to enhanced fires can reduce the optimized CH4 emissions by up to 10 Tg yr−1 during El Niño years and the positive OH trend from 1986 to 2010 results in a ∼ 23 Tg yr−1 additional increase in optimized CH4 emissions.
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
Cited articles
Ainsworth, E. A. and Rogers, A.: The response of photosynthesis and stomatal
conductance to rising [CO2]: mechanisms and environmental interactions,
Plant, Cell Environ., 30, 258–270, 2007.
Ali, A. A., Xu, C., Rogers, A., Fisher, R. A., Wullschleger, S. D., Massoud,
E. C., Vrugt, J. A., Muss, J. D., McDowell, N. G., Fisher, J. B., Reich, P.
B., and Wilson, C. J.: A global scale mechanistic model of photosynthetic
capacity (LUNA V1.0), Geosci. Model Dev., 9, 587–606,
https://doi.org/10.5194/gmd-9-587-2016, 2016.
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D.,
Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., and Cadule, P.:
Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system
models, J. Climate, 26, 5289–5314, 2013.
Atkin, O. K., Evans, J. R., and Siebke, K.: Relationship between the
inhibition of leaf respiration by light and enhancement of leaf dark
respiration following light treatment, Aust. J. Plant Physiol., 25, 437–443,
https://doi.org/10.1071/PP97159, 1998.
Atkin, O. K., Evans, J. R., Ball, M. C., Lambers, H., and Pons, T. L.: Leaf
respiration of snow gum in the light and dark. Interactions between
temperature and irradiance, Plant Physiol., 122, 915–924,
https://doi.org/10.1104/pp.122.3.915, 2000.
Atkin, O., Bloomfield, K., Reich, P., Tjoelker, M., Asner, G., Bonal, D.,
Bonisch, G., Bradford, M., Cernusak, L., and Cosio, E.: Global variability in
leaf respiration in relation to climate, plant functional types and leaf
traits, New Phytol., 211, 1142–1142, 2016.
Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O.
L., Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N.
J., Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley,
E., Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A.,
Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry,
S. J. W., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R.,
Verbeeck, H., Wijaya, A., and Willcock, S.: An integrated pan-tropical
biomass map using multiple reference datasets, Glob. Change Biol., 22,
1406–1420, 2016.
Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M.,
Sulla-Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A.,
Samanta, S., and Houghton, R. A.: Estimated carbon dioxide emissions from
tropical deforestation improved by carbon-density maps, Nat. Clim. Change, 2,
182–185, 2012.
Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., and
Houghton, R. A.: Tropical forests are a net carbon source based on
aboveground measurements of gain and loss, Science, 358, 230–234, 2017.
Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global land
cover mapping from Earth observation data, Int. J. Remote Sens., 26,
1959–1977, 2005.
Bergh, J., McMurtrie, R. E., and Linder, S.: Climatic factors controlling the
productivity of Norway spruce: a model-based analysis, Forest Ecol. Manage.,
110, 127–139, 1998.
Best, M. J., Abramowitz, G., Johnson, H. R., Pitman, A. J., Balsamo, G.,
Boone, A., Cuntz, M., Decharme, B., Dirmeyer, P. A., Dong, J., Ek, M., Guo,
Z., Haverd, V., van den Hurk, B. J. J., Nearing, G. S., Pak, B.,
Peters-Lidard, C., Santanello, J. A., Stevens, L., and Vuichard, N.: The
plumbing of land surface models: Benchmarking model performance, J.
Hydrometeorol., 16, 1425–1442, 2015.
Brooks, A. and Farquhar, G. D.: Effect of temperature on the CO2-O2
specificity of ribulose-1,5-biphosphate carboxylase/oxygenase and the rate of
respiration in the light: estimates from gas exchange measurements on
spinach, Planta, 165, 397–406, https://doi.org/10.1007/BF00392238, 1985.
Campbell, J. E., Berry, J. A., Seibt, U., Smith, S. J., Montzka, S. A.,
Launois, T., Belviso, S., Bopp, L., and Laine, M.: Large historical growth in
global terrestrial gross primary production, Nature, 544, 84–87, 2017.
Cannell, M. G. R.: World Forest Biomass and Primary Production Data, Academic
Press, London, UK, 391 pp., 1982.
Chen, J.-L., Reynolds, J. F., Harley, P. C., and Tenhunen, J. D.:
Coordination theory of leaf nitrogen distribution in a canopy, Oecologia, 93,
63–69, 1993.
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.
Collatz, G., Ribas-Carbo, M., and Berry, J.: Coupled Photosynthesis-Stomatal
Conductance Model for Leaves of C4 Plants, Funct. Plant Biol., 19,
519–538, 1992.
De Kauwe, M. G., Kala, J., Lin, Y.-S., Pitman, A. J., Medlyn, B. E., Duursma,
R. A., Abramowitz, G., Wang, Y.-P., and Miralles, D. G.: A test of an optimal
stomatal conductance scheme within the CABLE land surface model, Geosci.
Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, 2015.
Decker, M.: Development and evaluation of a new soil moisture and runoff
parameterization for the CABLE LSM including subgrid-scale processes, J. Adv.
Model. Earth Sy., 7, 1788–1809, 2015.
Dlugokencky, E. and Tans, P.: Trends in atmospheric carbon dioxide, National
Oceanic & Atmospheric Administration, Earth System Research Laboratory
(NOAA/ESRL), available at:
http://www.esrl.noaa.gov/gmd/ccgg/trends/global.html, last access: June
2017.
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database (version 1.2).
FAO, Rome, Italy and IIASA, Laxenburg, Austria, available at:
http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/ (last access: 16 February 2016), 2009.
Farquhar, G. and Wong, S.: An Empirical Model of Stomatal Conductance, Funct.
Plant Biol., 11, 191–210, 1984.
Farquhar, G. V., Caemmerer, S. V., and Berry, J.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149,
78–90, 1980.
Friend, A. D., Lucht, W., Rademacher, T. T., Keribin, R., Betts, R., Cadule,
P., Ciais, P., Clark, D. B., Dankers, R., Falloon, P. D., Ito, A., Kahana,
R., Kleidon, A., Lomas, M. R., Nishina, K., Ostberg, S., Pavlick, R., Peylin,
P., Schaphoff, S., Vuichard, N., Warszawski, L., Wiltshire, A., and Woodward,
F. I.: Carbon residence time dominates uncertainty in terrestrial vegetation
responses to future climate and atmospheric CO2, P. Natl. Acad. Sci. USA,
111, 3280–3285, 2014.
Goudriaan, J. and van Laar, H. H.: Modelling potential crop growth processes:
textbook with exercises, Kluwer Academic Publishers, Dordrecht, 1994.
Hansis, E., Davis, S. J., and Pongratz, J.: Relevance of methodological
choices for accounting of land use change carbon fluxes, Global Biogeochem.
Cy., 29, 1230–1246, 2015.
Haverd, V., Lovell, J. L., Cuntz, M., Jupp, D. L. B., Newnham, G. J., and
Sea, W.: The Canopy Semi-analytic Pgap And Radiative Transfer (CanSPART)
model: Formulation and application, Agr. Forest Meteorol., 160, 14–35, 2012.
Haverd, V., Raupach, M. R., Briggs, P. R., Canadell, J. G., Isaac, P.,
Pickett-Heaps, C., Roxburgh, S. H., van Gorsel, E., Viscarra Rossel, R. A.,
and Wang, Z.: Multiple observation types reduce uncertainty in Australia's
terrestrial carbon and water cycles, Biogeosciences, 10, 2011–2040,
https://doi.org/10.5194/bg-10-2011-2013, 2013a.
Haverd, V., Smith, B., Cook, G., Briggs, P. R., Nieradzik, L., Roxburgh, S.
R., Liedloff, A., Meyer, C. P., and Canadell, J. G.: A stand-alone tree
demography and landscape structure module for Earth system models., Geophys.
Res. Lett., 40, 1–6, 2013b.
Haverd, V., Smith, B., Cook, G. D., Briggs, P. R., Nieradzik, L., Roxburgh,
S. H., Liedloff, A., Meyer, C. P., and Canadell, J. G.: A stand-alone tree
demography and landscape structure module for Earth system models, Geophys.
Res. Lett., 40, 5234–5239, 2013c.
Haverd, V., Smith, B., Nieradzik, L. P., and Briggs, P. R.: A stand-alone
tree demography and landscape structure module for Earth system models:
integration with inventory data from temperate and boreal forests,
Biogeosciences, 11, 4039–4055, https://doi.org/10.5194/bg-11-4039-2014,
2014.
Haverd, V., Cuntz, M., Nieradzik, L. P., and Harman, I. N.: Improved
representations of coupled soil–canopy processes in the CABLE land surface
model (Subversion revision 3432), Geosci. Model Dev., 9, 3111–3122,
https://doi.org/10.5194/gmd-9-3111-2016, 2016a.
Haverd, V., Smith, B., Raupach, M., Briggs, P., Nieradzik, L., Beringer, J.,
Hutley, L., Trudinger, C. M., and Cleverly, J.: Coupling carbon allocation
with leaf and root phenology predicts tree–grass partitioning along a
savanna rainfall gradient, Biogeosciences, 13, 761–779,
https://doi.org/10.5194/bg-13-761-2016, 2016b.
Haverd, V., Smith, B., and Trudinger, C. M.: Process contributions of
Australian ecosystems to interannual variations in the carbon cycle, Environ.
Res. Lett., 11, 054013, https://doi.org/10.1088/1748-9326/11/5/054013, 2016c.
Haverd, V., Smith, B., Nieradzik, L., Briggs, P. R., Woodgate, W., Trudinger,
C. M., Canadell, J. G., and Cuntz, M.: CABLE land surface model software
(Subversion revision r4601, 26 September 2017), available at:
https://trac.nci.org.au/trac/cable/log/branches/Users/vxh599/trunk_checks_extract_sli_optimise_JVratio_crop_harvest/core,
2017.
Hoefnagel, M. H. N., Atkin, O. K., and Wiskich, J. T.: Interdependence
between chloroplasts and mitochondria in the light and the dark, Biochim.
Biophys. Acta, 1366, 235–255, https://doi.org/10.1016/s0005-2728(98)00126-1, 1998.
Hoffman, F. M., Koven, C. D., Keppel-Aleks, G., Lawrence, D. M., Riley, W.
J., Randerson, J. T., Ahlström, A., Abramowitz, G., Baldocchi, D. D.,
Best, M. J., Bond-Lamberty, B., De Kauwe, M. G., Denning, A. S., Desai, A.
R., Eyring, V., Fisher, J. B., Fisher, R. A., Gleckler, P. J., Huang, M.,
Hugelius, G., Jain, A. K., Kiang, N. Y., Kim, H., Koster, R. D., Kumar, S.
V., Li, H., Luo, Y., Mao, J., McDowell, N. G., Mishra, U., Moorcroft, P. R.,
Pau, G. S. H., Ricciuto, D. M., Schaefer, K., Schwalm, C. R., Serbin, S. P.,
Shevliakova, E., Slater, A. G., Tang, J., Williams, M., Xia, J., Xu, C.,
Joseph, R., and Koch, D.: 2016 International Land Model Benchmarking (ILAMB)
Workshop Report, USDOE Office of Science, Washington, DC, USA, DOE/SC-0186,
https://doi.org/10.2172/1330803, 2017.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer,
G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones, C. D.,
Kindermann, G., Kinoshita, T., Klein Goldewijk, K., Riahi, K., Shevliakova,
E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., Vuuren, D. P., and
Wang, Y. P.: 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, Clim. Change, 109, 117–161, 2011.
Hurtt, G. C., Chini, L., Frolking, S., and Sahajpal, R.: Land Use
Harmonisation 2 (LUH2) v2h available at: http://luh.umd.edu/data.shtml
(last access: June 2017) 2016.
IPCC: Climate Change 2014: Synthesis Report, Contribution of Working Groups
I, II and III to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Core Writing Team, Pachauri, R. K., and Meyer,
L. A., IPCC, Geneva, Switzerland, 151 pp., 2014.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J.,
Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A. J.,
Eugster, W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball, J.,
Law, B. E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D.,
Richardson, A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N.,
Weber, U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline
in the global land evapotranspiration trend due to limited moisture supply,
Nature, 467, 951–954, 2010.
Kowalczyk, E., Wang, Y. P., Law, R. M., Davies, H. L., McGregor, J. L.,
and Abramowitz, G.: The CSIRO Atmosphere Biosphere Land Exchange (CABLE)
model for use in climate models and as an offline model, 013, 42 pp., 2006.
Kowalczyk, E., Stevens, L., Law, R., Dix, M., Wang, Y., Harman, I., Haynes,
K., Srbinovsky, J., Pak, B., and Ziehn, T.: The land surface model component
of ACCESS: description and impact on the simulated surface climatology, Aust.
Meteorol. Oceanogr. J., 63, 65–82, 2013.
Lamarque, J.-F., Kyle, G. P., Meinshausen, M., Riahi, K., Smith, S. J., van
Vuuren, D. P., Conley, A. J., and Vitt, F.: Global and regional evolution of
short-lived radiatively-active gases and aerosols in the Representative
Concentration Pathways, Clim. Change, 109, 191,
https://doi.org/10.1007/s10584-011-0155-0, 2011.
Law, R. M., Ziehn, T., Matear, R. J., Lenton, A., Chamberlain, M. A.,
Stevens, L. E., Wang, Y.-P., Srbinovsky, J., Bi, D., Yan, H., and Vohralik,
P. F.: The carbon cycle in the Australian Community Climate and Earth System
Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial
simulation, Geosci. Model Dev., 10, 2567–2590,
https://doi.org/10.5194/gmd-10-2567-2017, 2017.
Lawrence, D. M., Hurtt, G. C., Arneth, A., Brovkin, V., Calvin, K. V., Jones,
A. D., Jones, C. D., Lawrence, P. J., de Noblet-Ducoudré, N., Pongratz,
J., Seneviratne, S. I., and Shevliakova, E.: The Land Use Model
Intercomparison Project (LUMIP) contribution to CMIP6: rationale and
experimental design, Geosci. Model Dev., 9, 2973–2998,
https://doi.org/10.5194/gmd-9-2973-2016, 2016.
Lawrence, P. J., Feddema, J. J., Bonan, G. B., Meehl, G. A., O'Neill, B. C.,
Oleson, K. W., Levis, S., Lawrence, D. M., Kluzek, E., and Lindsay, K.:
Simulating the biogeochemical and biogeophysical impacts of transient land
cover change and wood harvest in the Community Climate System Model (CCSM4)
from 1850 to 2100, J. Climate, 25, 3071–3095, 2012.
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.
Leuning, R.: Modelling Stomatal Behaviour and Photosynthesis of
Eucalyptus grandis, Funct. Plant Biol., 17, 159–175, 1990.
Leuning, R.: Temperature dependence of two parameters in a photosynthesis
model, Plant, Cell Environ., 25, 1205–1210, 2002.
Lin, Y.-S., Medlyn, B. E., Duursma, R. A., Prentice, I. C., Wang, H., Baig,
S., Eamus, D., de Dios, V. R., Mitchell, P., and Ellsworth, D. S.: Optimal
stomatal behaviour around the world, Nat. Clim. Change, 5, 459–464, 2015.
Lindeskog, M., Arneth, A., Bondeau, A., Waha, K., Seaquist, J., Olin, S., and
Smith, B.: Implications of accounting for land use in simulations of
ecosystem carbon cycling in Africa, Earth Syst. Dynam., 4, 385–407,
https://doi.org/10.5194/esd-4-385-2013, 2013.
Lloyd, J. and Taylor, J. A.: On the Temperature Dependence of Soil
Respiration, Funct. Ecol., 8, 315–323, 1994.
Lloyd, J., Grace, J., Miranda, A. C., Meir, P., Wong, S. C., Miranda, H. S.,
Wright, I. R., Gash, J. H. C., and McIntyre J.: A simple calibrated model for
Amazon rainforest productivity based on leaf biochemical properties, Plant
Cell Environ., 18, 1129–1145, https://doi.org/10.1111/j.1365-3040.1995.tb00624.x,
1995.
Maire, V., Martre, P., Kattge, J., Gastal, F., Esser, G., Fontaine, S., and
Soussana, J.-F.: The Coordination of Leaf Photosynthesis Links C and N Fluxes
in C3 Plant Species, PLoS ONE, 7, e38345,
https://doi.org/10.1371/journal.pone.0038345, 2012.
Massad, R., Tuzet, A., and Bethenod, O.: The effect of temperature on
C4-type leaf photosynthesis parameters, Plant, Cell Environ., 30,
1191–1204, 2007.
Mercado, L. M., Huntingford, C., Gash, J. H. C., Cox, P. M., and Jogireddy,
V.: Improving the representation of radiation interception and photosynthesis
for climate model applications, Tellus B, 59, 553–565, 2007.
Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A.
J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G.,
McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang,
Y., and Seneviratne, S. I.: Benchmark products for land evapotranspiration:
LandFlux-EVAL multi-data set synthesis, Hydrol. Earth Syst. Sci., 17,
3707–3720, https://doi.org/10.5194/hess-17-3707-2013, 2013.
Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X.,
Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung,
M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y.,
Ma, Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S.,
and Zeng, N.: Evaluation of terrestrial carbon cycle models for their
response to climate variability and to CO2 trends, Global Change Biol.,
19, 2117–2132, 2013.
Poorter, H., Niklas, K. J., Reich, P. B., Oleksyn, J., Poot, P., and Mommer,
L.: Biomass allocation to leaves, stems and roots: meta-analyses of
interspecific variation and environmental control, New Phytol., 193, 30–50,
2012.
Prentice, I. C., Cramer, W., Harrison, S. P., Leemans, R., Monserud, R. A.,
and Solomon, A. M.: Special Paper: A Global Biome Model Based on Plant
Physiology and Dominance, Soil Properties and Climate, J. Biogeogr., 19,
117–134, 1992.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.:
Numerical Recipes in FORTRAN; The Art of Scientific Computing, Cambridge
University Press, 1993.
Purves, D. and Pacala, S.: Predictive Models of Forest Dynamics, Science,
320, 1452–1453, 2008.
Raupach, M.: Simplified expressions for vegetation roughness length and
zero-plane displacement as functions of canopy height and area index,
Bound.-Lay. Meteorol., 71, 211–216, 1994.
Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T. A.,
Salas, W., Zutta, B. R., Buermann, W., Lewis, S. L., Hagen, S., Petrova, S.,
White, L., Silman, M., and Morel, A.: Benchmark map of forest carbon stocks
in tropical regions across three continents, P. Natl. Acad. Sci. USA, 108,
9899–9904, 2011.
Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. E. S., Hall, R.
J., Pathe, C., Schmullius, C., Schepaschenko, D., Shvidenko, A., Thurner, M.,
and Wegmüller, U.: Forest growing stock volume of the northern
hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR,
Remote Sens. Environ., 168, 316–334, 2015.
Schimel, D., Stephens, B. B., and Fisher, J. B.: Effect of increasing CO2
on the terrestrial carbon cycle, P. Natl. Acad. Sci. USA, 112, 436–441,
2015.
Shevliakova, E., Pacala, S. W., Malyshev, S., Hurtt, G. C., Milly, P. C. D.,
Caspersen, J. P., Sentman, L. T., Fisk, J. P., Wirth, C., and Crevoisier, C.:
Carbon cycling under 300 years of land use change: Importance of the
secondary vegetation sink, Global Biogeochem. Cy., 23, GB2022,
https://doi.org/10.1029/2007GB003176, 2009.
Shinozaki, K., Yoda, K., Hozumi, K., and Kira, T.: A Quantitative Analysis of
Plant Form – The Pipe Model Theory I. Basic Analyses, Jap. J. Ecol., 14,
97–105, 1964.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W.,
Kaplan, J., Levis, S., Lucht, W., and Sykes, M. T.: Evaluation of ecosystem
dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic
global vegetation model, Glob. Change Biol., 9, 161–185, 2003.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation
dynamics in the modelling of terrestrial ecosystems: comparing two
contrasting approaches within European climate space, Global Ecol. Biogeogr.,
10, 621–637, 2001.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg,
J., and Zaehle, S.: Implications of incorporating N cycling and N limitations
on primary production in an individual-based dynamic vegetation model,
Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014,
2014.
Stocker, B. D., Feissli, F., Strassmann, K. M., Spahni, R., and Joos, F.:
Past and future carbon fluxes from land use change, shifting cultivation and
wood harvest, Tellus B, 66, 23188, https://doi.org/10.3402/tellusb.v66.23188, 2014.
Sykes, M. T., Prentice, I. C., and Cramer, W.: A bioclimatic model for the
potential distributions of north European tree species under present and
future climates, J. Biogeogr., 23, 203–233, 1996.
Teobaldelli, M.: The Biomass Compartments Database, available at:
http://afoludata.jrc.it/DS_Free/AF_Bio.cfm (last access: 2014), 2008.
Teobaldelli, M., Somogyi, Z., Migliavacca, M., and Usoltsev, V. A.:
Generalized functions of biomass expansion factors for conifers and broadleaved by stand age,
growing stock and site index, For. Ecol. Manag., 257, 3, 1004–1013,https://doi.org/10.1016/j.foreco.2008.11.002, 2009.
Tjoelker, M. G., Oleksyn, J., and Reich, P. B.: Modelling respiration of
vegetation: Evidence for a general temperature-dependent Q10, Glob. Change
Biol., 7, 223–230, 2001.
Trudinger, C. M., Haverd, V., Briggs, P. R., and Canadell, J. G.: Interannual
variability in Australia's terrestrial carbon cycle constrained by multiple
observation types, Biogeosciences, 13, 6363–6383,
https://doi.org/10.5194/bg-13-6363-2016, 2016.
Usoltsev, V. A.: Forest biomass of northern Eurasia: database and geography,
Russian Academy of Sciences, Ural Branch, Yekarinenburg, 2001.
van der Laan-Luijkx, I. T., van der Velde, I. R., van der Veen, E., Tsuruta,
A., Stanislawska, K., Babenhauserheide, A., Zhang, H. F., Liu, Y., He, W.,
Chen, H., Masarie, K. A., Krol, M. C., and Peters, W.: The CarbonTracker Data
Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance
2001–2015, Geosci. Model Dev., 10, 2785–2800,
https://doi.org/10.5194/gmd-10-2785-2017, 2017.
Viovy, N.: CRUNCEP Version 7 – Atmospheric Forcing Data for the Community
Land Model, available at:
ftp://nacp.ornl.gov/synthesis/2009/frescati/temp/land_use_change/original/readme.htm,
last access: 24 May 2016.
Viscarra Rossel, R. A., Webster, R., Bui, E. N., and Baldock, J. A.: Baseline
map of organic carbon in Australian soil to support national carbon
accounting and monitoring under climate change, Glob. Change Biol., 20,
2953–2970, 2014.
Walker, A. P., Beckerman, A. P., Gu, L., Kattge, J., Cernusak, L. A.,
Domingues, T. F., Scales, J. C., Wohlfahrt, G., Wullschleger, S. D., and
Woodward, F. I.: The relationship of leaf photosynthetic traits – Vcmax and
Jmax – to leaf nitrogen, leaf phosphorus, and specific leaf area: a
meta-analysis and modeling study, Ecol. Evol., 4, 3218–3235, 2014.
Wang, H., Prentice, I. C., Keenan, T. F., Davis, T. W., Wright, I. J.,
Cornwell, W. K., Evans, B. J., and Peng, C.: Towards a universal model for
carbon dioxide uptake by plants, Nat. Plants, 3, 734–741, 2017.
Wang, Y.-P. and Leuning, R.: A two-leaf model for canopy conductance,
photosynthesis and partitioning of available energy I: Model description and
comparison with a multi-layered model, Agr. Forest Meteorol., 91, 89–111,
1998.
Wang, Y. P., Law, R. M., and Pak, B.: A global model of carbon, nitrogen and
phosphorus cycles for the terrestrial biosphere, Biogeosciences, 7,
2261–2282, https://doi.org/10.5194/bg-7-2261-2010, 2010.
Wang, Y. P., Kowalczyk, E., Leuning, R., Abramowitz, G., Raupach, M. R., Pak,
B., van Gorsel, E., and Luhar, A.: Diagnosing errors in a land surface model
(CABLE) in the time and frequency domains, J. Geophys. Res., 116, G01034,
https://doi.org/10.1029/2010JG001385, 2011.
Wilkenskjeld, S., Kloster, S., Pongratz, J., Raddatz, T., and Reick, C. H.:
Comparing the influence of net and gross anthropogenic land-use and
land-cover changes on the carbon cycle in the MPI-ESM, Biogeosciences, 11,
4817–4828, https://doi.org/10.5194/bg-11-4817-2014, 2014.
Wolf, A., Ciais, P., Bellassen, V., Delbart, N., Field, C. B., and Berry, J.
A.: Forest biomass allometry in global land surface models, Global
Biogeochem. Cy., 25, GB3015, https://doi.org/10.1029/2010gb003917, 2011.
Xia, J. Y., Luo, Y. Q., Wang, Y.-P., Weng, E. S., and Hararuk, O.: A
semi-analytical solution to accelerate spin-up of a coupled carbon and
nitrogen land model to steady state, Geosci. Model Dev., 5, 1259–1271,
https://doi.org/10.5194/gmd-5-1259-2012, 2012.
Xu, C., Fisher, R., Wullschleger, S. D., Wilson, C. J., Cai, M., and
McDowell, N. G.: Toward a Mechanistic Modeling of Nitrogen Limitation on
Vegetation Dynamics, PLoS ONE, 7, e37914, https://doi.org/10.1371/journal.pone.0037914,
2012.
Zhang, H., Pak, B., Wang, Y. P., Zhou, X., Zhang, Y., and Zhang, L.:
Evaluating surface water cycle simulated by the Australian community land
surface model (CABLE) across different spatial and temporal domains, J.
Hydrometeorol., 14, 1119–1138, https://doi.org/10.1175/JHM-D-12-0123.1, 2013.
Zhou, X. Y., Zhang, Y. Q., Wang, Y. P., Zhang, H. Q., Zhang, L., Vaze, J.,
Yang, Y. H., and Zhou, Y. C.: Benchmarking global land surface models against
the observed mean annual runoff from 150 large basins, J. Hydrol., 470,
269–279, https://doi.org/10.1016/j.jhydrol.2012.09.002, 2012.
Ziehn, T., Lenton, A., Law, R. M., Matear, R. J., and Chamberlain, M. A.: The
carbon cycle in the Australian Community Climate and Earth System Simulator
(ACCESS-ESM1) – Part 2: Historical simulations, Geosci. Model Dev., 10,
2591–2614, https://doi.org/10.5194/gmd-10-2591-2017, 2017.
Short summary
CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface–atmosphere exchange within a climate model. We extend CABLE for regional and global carbon–climate simulations, accounting for land use and land cover change mediated by tree demography. A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.
CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land...
