Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-153-2018
© 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/esd-9-153-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2018
Research article |
| 21 Feb 2018
| 21 Feb 2018
Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties
Jean-François Exbrayat
CORRESPONDING AUTHOR
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of
Technology, Pasadena, California, USA
Pete Falloon
Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
Akihiko Ito
National Institute for Environmental Studies, Tsukuba,
Japan
T. Luke Smallman
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
Mathew Williams
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
Related authors
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
Short summary
Short summary
We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
Short summary
Short summary
The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Efrén López-Blanco, Magnus Lund, Mathew Williams, Mikkel P. Tamstorf, Andreas Westergaard-Nielsen, Jean-François Exbrayat, Birger U. Hansen, and Torben R. Christensen
Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, https://doi.org/10.5194/bg-14-4467-2017, 2017
Short summary
Short summary
An improvement in our process-based understanding of CO2 exchanges in the Arctic and their climate sensitivity is critical. With continued warming temperatures and longer growing seasons, tundra systems will likely increase rates of C cycling, although shifts in sink strength could take place, challenging the forecast of upcoming C states. In this context, we investigated the functional responses of C exchange to environmental characteristics across 8 consecutive years in West Greenland.
Nina Hinko-Najera, Peter Isaac, Jason Beringer, Eva van Gorsel, Cacilia Ewenz, Ian McHugh, Jean-François Exbrayat, Stephen J. Livesley, and Stefan K. Arndt
Biogeosciences, 14, 3781–3800, https://doi.org/10.5194/bg-14-3781-2017, https://doi.org/10.5194/bg-14-3781-2017, 2017
Short summary
Short summary
We undertook a 3-year study (2010–2012) of eddy covariance measurements in a dry temperate eucalypt (broadleaf evergreen) forest in southeastern Australia. The forest was a large and constant carbon sink, with the greatest uptake in early spring and summer. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited.
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, https://doi.org/10.5194/gmd-10-2651-2017, 2017
J.-F. Exbrayat, N. R. Viney, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 6, 117–125, https://doi.org/10.5194/gmd-6-117-2013, https://doi.org/10.5194/gmd-6-117-2013, 2013
Yosuke Niwa, Yasunori Tohjima, Yukio Terao, Tazu Saeki, Akihiko Ito, Taku Umezawa, Kyohei Yamada, Motoki Sasakawa, Toshinobu Machida, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Hitoshi Mukai, Yukio Yoshida, Shinji Morimoto, Shinya Takatsuji, Kazuhiro Tsuboi, Yousuke Sawa, Hidekazu Matsueda, Kentaro Ishijima, Ryo Fujita, Daisuke Goto, Xin Lan, Kenneth Schuldt, Michal Heliasz, Tobias Biermann, Lukasz Chmura, Jarsolaw Necki, Irène Xueref-Remy, and Damiano Sferlazzo
Atmos. Chem. Phys., 25, 6757–6785, https://doi.org/10.5194/acp-25-6757-2025, https://doi.org/10.5194/acp-25-6757-2025, 2025
Short summary
Short summary
This study estimated regional and sectoral emission contributions to the unprecedented surge of atmospheric methane for 2020–2022. The methane is the second most important greenhouse gas, and its emissions reduction is urgently required to mitigate global warming. Numerical modeling-based estimates with three different sets of atmospheric observations consistently suggested large contributions of biogenic emissions from South Asia and Southeast Asia to the surge of atmospheric methane.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
Earth Syst. Dynam., 16, 803–840, https://doi.org/10.5194/esd-16-803-2025, https://doi.org/10.5194/esd-16-803-2025, 2025
Short summary
Short summary
Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the Land Use Model Intercomparison Project (LUMIP) and the Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that LUC-induced carbon emissions contribute to a BGC warming of 0.21 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasize the need for improved representations of LUC processes.
Konstantin Gregor, Benjamin F. Meyer, Tillmann Gaida, Victor Justo Vasquez, Karina Bett-Williams, Matthew Forrest, João P. Darela-Filho, Sam Rabin, Marcos Longo, Joe R. Melton, Johan Nord, Peter Anthoni, Vladislav Bastrikov, Thomas Colligan, Christine Delire, Michael C. Dietze, George Hurtt, Akihiko Ito, Lasse T. Keetz, Jürgen Knauer, Johannes Köster, Tzu-Shun Lin, Lei Ma, Marie Minvielle, Stefan Olin, Sebastian Ostberg, Hao Shi, Reiner Schnur, Urs Schönenberger, Qing Sun, Peter E. Thornton, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2025-1733, https://doi.org/10.5194/egusphere-2025-1733, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Liang Feng, Paul Palmer, Luke Smallman, Jingfeng Xiao, Paulo Cristofanelli, Ove Hermansen, John Lee, Casper Labuschagne, Simonetta Montaguti, Steffen Noe, Stephen Platt, Xinrong Ren, Martin Steinbacher, and Irene Xueref-Remy
EGUsphere, https://doi.org/10.5194/egusphere-2025-1793, https://doi.org/10.5194/egusphere-2025-1793, 2025
Short summary
Short summary
2023 saw an unexpectedly high global atmospheric CO2 growth. Satellite data reveal a role for increased emissions over the tropics. Larger emissions over eastern Brazil can be explained by warmer temperatures, while changes in rainfall and soil moisture play more of a role in emission increases elsewhere in the tropics.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
Short summary
Short summary
Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Mathew Williams, David T. Milodowski, T. Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
Biogeosciences, 22, 1597–1614, https://doi.org/10.5194/bg-22-1597-2025, https://doi.org/10.5194/bg-22-1597-2025, 2025
Short summary
Short summary
Southern African woodlands are important in both regional and global carbon cycles. A new carbon analysis created by combining satellite data with ecosystem modelling shows that the region has a neutral C balance overall but with important spatial variations. Patterns of biomass and C balance across the region are the outcome of climate controls on production and vegetation–fire interactions, which determine the mortality of vegetation and spatial variations in vegetation function.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris D. Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
Biogeosciences, 22, 1447–1473, https://doi.org/10.5194/bg-22-1447-2025, https://doi.org/10.5194/bg-22-1447-2025, 2025
Short summary
Short summary
This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations (CO2 concentration- and emission-driven experiments). We successfully identified problems with regard to the global carbon budget in each model. We also found urgent issues with regard to land use change CO2 emissions that should be solved in the latest generation of models.
Nikolina Mileva, Julia Pongratz, Vivek K. Arora, Akihiko Ito, Sebastiaan Luyssaert, Sonali S. McDermid, Paul A. Miller, Daniele Peano, Roland Séférian, Yanwu Zhang, and Wolfgang Buermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-979, https://doi.org/10.5194/egusphere-2025-979, 2025
Short summary
Short summary
Despite forests being so important for mitigating climate change, there are still uncertainties about how much the changes in forest cover contribute to the cooling/warming of the climate. Climate models and real-world observations often disagree about the magnitude and even the direction of these changes. We constrain climate models scenarios of widespread deforestation with satellite and in-situ data and show that models still have difficulties representing the movement of heat and water.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, 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, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). 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.
Marcos B. Sanches, Manoel Cardoso, Celso von Randow, Chris Jones, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2025-942, https://doi.org/10.5194/egusphere-2025-942, 2025
Preprint archived
Short summary
Short summary
This study examines South America's role in the global carbon cycle using flux and stock analyses from CMIP6 Earth System Models. We discuss the continent’s relevance, model-observation agreement, and the impacts of dry and wet years on major biomes. Additionally, we assess model results indicating that parts of South America could shift from carbon sinks to emitters, significantly affecting the global carbon balance.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
Short summary
Short summary
This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
Short summary
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). 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.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
Short summary
Short summary
The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
Short summary
Short summary
Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
Short summary
Short summary
This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
Short summary
Short summary
This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
Naveen Chandra, Prabir K. Patra, Yousuke Niwa, Akihiko Ito, Yosuke Iida, Daisuke Goto, Shinji Morimoto, Masayuki Kondo, Masayuki Takigawa, Tomohiro Hajima, and Michio Watanabe
Atmos. Chem. Phys., 22, 9215–9243, https://doi.org/10.5194/acp-22-9215-2022, https://doi.org/10.5194/acp-22-9215-2022, 2022
Short summary
Short summary
This paper is intended to accomplish two goals: (1) quantify mean and uncertainty in non-fossil-fuel CO2 fluxes estimated by inverse modeling and (2) provide in-depth analyses of regional CO2 fluxes in support of emission mitigation policymaking. CO2 flux variability and trends are discussed concerning natural climate variability and human disturbances using multiple lines of evidence.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
Short summary
Short summary
Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
Short summary
Short summary
Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
Short summary
Short summary
We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
Short summary
Short summary
Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Yosuke Niwa, Yousuke Sawa, Hideki Nara, Toshinobu Machida, Hidekazu Matsueda, Taku Umezawa, Akihiko Ito, Shin-Ichiro Nakaoka, Hiroshi Tanimoto, and Yasunori Tohjima
Atmos. Chem. Phys., 21, 9455–9473, https://doi.org/10.5194/acp-21-9455-2021, https://doi.org/10.5194/acp-21-9455-2021, 2021
Short summary
Short summary
Fires in Equatorial Asia release a large amount of carbon into the atmosphere. Extensively using high-precision atmospheric carbon dioxide (CO2) data from a commercial aircraft observation project, we estimated fire carbon emissions in Equatorial Asia induced by the big El Niño event in 2015. Additional shipboard measurement data elucidated the validity of the analysis and the best estimate indicated 273 Tg C for fire emissions during September–October 2015.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
Short summary
Short summary
Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471, https://doi.org/10.5194/gmd-14-437-2021, https://doi.org/10.5194/gmd-14-437-2021, 2021
Short summary
Short summary
Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
Short summary
Short summary
We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Tokuta Yokohata, Tsuguki Kinoshita, Gen Sakurai, Yadu Pokhrel, Akihiko Ito, Masashi Okada, Yusuke Satoh, Etsushi Kato, Tomoko Nitta, Shinichiro Fujimori, Farshid Felfelani, Yoshimitsu Masaki, Toshichika Iizumi, Motoki Nishimori, Naota Hanasaki, Kiyoshi Takahashi, Yoshiki Yamagata, and Seita Emori
Geosci. Model Dev., 13, 4713–4747, https://doi.org/10.5194/gmd-13-4713-2020, https://doi.org/10.5194/gmd-13-4713-2020, 2020
Short summary
Short summary
The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balances, human water management, and crop growth incorporates a land-use decision-making model based on economic activities. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Abigail Snyder, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Karina Williams, Ziwei Wang, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, https://doi.org/10.5194/gmd-13-3995-2020, 2020
Short summary
Short summary
Improving our understanding of the impacts of climate change on crop yields will be critical for global food security in the next century. The models often used to study the how climate change may impact agriculture are complex and costly to run. In this work, we describe a set of global crop model emulators (simplified models) developed under the Agricultural Model Intercomparison Project. Crop model emulators make agricultural simulations more accessible to policy or decision makers.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
Short summary
Short summary
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Juraj Balkovic, Philippe Ciais, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, Munir Hoffmann, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Nikolay Khabarov, Marian Koch, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Xuhui Wang, Karina Williams, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 2315–2336, https://doi.org/10.5194/gmd-13-2315-2020, https://doi.org/10.5194/gmd-13-2315-2020, 2020
Short summary
Short summary
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Crop models, which represent plant biology, are necessary tools for this purpose since they allow representing future climate, farmer choices, and new agricultural geographies. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, under the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to evaluate and improve crop models.
Tomohiro Hajima, Michio Watanabe, Akitomo Yamamoto, Hiroaki Tatebe, Maki A. Noguchi, Manabu Abe, Rumi Ohgaito, Akinori Ito, Dai Yamazaki, Hideki Okajima, Akihiko Ito, Kumiko Takata, Koji Ogochi, Shingo Watanabe, and Michio Kawamiya
Geosci. Model Dev., 13, 2197–2244, https://doi.org/10.5194/gmd-13-2197-2020, https://doi.org/10.5194/gmd-13-2197-2020, 2020
Short summary
Short summary
We developed a new Earth system model (ESM) named MIROC-ES2L. This model is based on a state-of-the-art climate model and includes carbon–nitrogen cycles for the land and multiple biogeochemical cycles for the ocean. The model's performances on reproducing historical climate and biogeochemical changes are confirmed to be reasonable, and the new model is likely to be an
optimisticmodel in projecting future climate change among ESMs in the Coupled Model Intercomparison Project Phase 6.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
Short summary
Short summary
We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Sophie Flack-Prain, Patrick Meir, Yadvinder Malhi, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 16, 4463–4484, https://doi.org/10.5194/bg-16-4463-2019, https://doi.org/10.5194/bg-16-4463-2019, 2019
Short summary
Short summary
Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Akihiko Ito
Earth Syst. Dynam., 10, 685–709, https://doi.org/10.5194/esd-10-685-2019, https://doi.org/10.5194/esd-10-685-2019, 2019
Short summary
Short summary
Various minor carbon flows such as trace gas emissions, disturbance-induced emissions, and subsurface exports can affect the carbon budget of terrestrial ecosystems in complicated ways. This study assessed how much these minor flows influence the carbon budget using a process-based model. It was found that the minor flows, though small in magnitude, could significantly affect net carbon budget at as much strengths as major flows, implying their long-term importance in Earth's climate system.
R. Cong, M. Saito, R. Hirata, and A. Ito
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 75–81, https://doi.org/10.5194/isprs-archives-XLII-2-W16-75-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W16-75-2019, 2019
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.
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.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
Short summary
Short summary
The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Vasileios Myrgiotis, Mathew Williams, Robert M. Rees, and Cairistiona F. E. Topp
Biogeosciences, 16, 1641–1655, https://doi.org/10.5194/bg-16-1641-2019, https://doi.org/10.5194/bg-16-1641-2019, 2019
Short summary
Short summary
This study focuses on a northwestern European cropland region and shows that the type of crop growing on a soil has notable effects on the emission of nitrous oxide (N2O – a greenhouse gas) from that soil. It was found that N2O emissions from soils under oilseed cultivation are significantly higher than soils under cereal cultivation. This variation is mostly explained by the fact that oilseeds require more nitrogen (fertiliser) than cereals, especially at early crop growth stages.
Anne Sofie Lansø, Thomas Luke Smallman, Jesper Heile Christensen, Mathew Williams, Kim Pilegaard, Lise-Lotte Sørensen, and Camilla Geels
Biogeosciences, 16, 1505–1524, https://doi.org/10.5194/bg-16-1505-2019, https://doi.org/10.5194/bg-16-1505-2019, 2019
Short summary
Short summary
Although coastal regions only amount to 7 % of the global oceans, their contribution to the global oceanic surface exchange of CO2 is much greater. In this study, we gain detailed insight into how these coastal marine fluxes compare to CO2 exchange from coastal land regions. Annually, the coastal marine exchanges are smaller than the total uptake of CO2 from the land surfaces within the study area but comparable in size to terrestrial fluxes from individual land cover classes of the region.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
Short summary
Short summary
Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
R. Cong, M. Saito, R. Hirata, A. Ito, and S. Maksyutov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 115–119, https://doi.org/10.5194/isprs-archives-XLII-4-115-2018, https://doi.org/10.5194/isprs-archives-XLII-4-115-2018, 2018
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.
Camilla Mathison, Chetan Deva, Pete Falloon, and Andrew J. Challinor
Earth Syst. Dynam., 9, 563–592, https://doi.org/10.5194/esd-9-563-2018, https://doi.org/10.5194/esd-9-563-2018, 2018
Short summary
Short summary
Sowing and harvest dates are a significant source of uncertainty within crop models. South Asia is one region with a large uncertainty. We aim to provide more accurate sowing and harvest dates than currently available and that are relevant for climate impact assessments. This method reproduces the present day sowing and harvest dates for most parts of India and when applied to two future periods provides a useful way of modelling potential growing season adaptations to changes in future climate.
Mary C. Ockenden, Wlodek Tych, Keith J. Beven, Adrian L. Collins, Robert Evans, Peter D. Falloon, Kirsty J. Forber, Kevin M. Hiscock, Michael J. Hollaway, Ron Kahana, Christopher J. A. Macleod, Martha L. Villamizar, Catherine Wearing, Paul J. A. Withers, Jian G. Zhou, Clare McW. H. Benskin, Sean Burke, Richard J. Cooper, Jim E. Freer, and Philip M. Haygarth
Hydrol. Earth Syst. Sci., 21, 6425–6444, https://doi.org/10.5194/hess-21-6425-2017, https://doi.org/10.5194/hess-21-6425-2017, 2017
Short summary
Short summary
This paper describes simple models of phosphorus load which are identified for three catchments in the UK. The models use new hourly observations of phosphorus load, which capture the dynamics of phosphorus transfer in small catchments that are often missed by models with a longer time step. Unlike more complex, process-based models, very few parameters are required, leading to low parameter uncertainty. Interpretation of the dominant phosphorus transfer modes is made based solely on the data.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
Short summary
Short summary
This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Efrén López-Blanco, Magnus Lund, Mathew Williams, Mikkel P. Tamstorf, Andreas Westergaard-Nielsen, Jean-François Exbrayat, Birger U. Hansen, and Torben R. Christensen
Biogeosciences, 14, 4467–4483, https://doi.org/10.5194/bg-14-4467-2017, https://doi.org/10.5194/bg-14-4467-2017, 2017
Short summary
Short summary
An improvement in our process-based understanding of CO2 exchanges in the Arctic and their climate sensitivity is critical. With continued warming temperatures and longer growing seasons, tundra systems will likely increase rates of C cycling, although shifts in sink strength could take place, challenging the forecast of upcoming C states. In this context, we investigated the functional responses of C exchange to environmental characteristics across 8 consecutive years in West Greenland.
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.
Nina Hinko-Najera, Peter Isaac, Jason Beringer, Eva van Gorsel, Cacilia Ewenz, Ian McHugh, Jean-François Exbrayat, Stephen J. Livesley, and Stefan K. Arndt
Biogeosciences, 14, 3781–3800, https://doi.org/10.5194/bg-14-3781-2017, https://doi.org/10.5194/bg-14-3781-2017, 2017
Short summary
Short summary
We undertook a 3-year study (2010–2012) of eddy covariance measurements in a dry temperate eucalypt (broadleaf evergreen) forest in southeastern Australia. The forest was a large and constant carbon sink, with the greatest uptake in early spring and summer. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited.
Darren Slevin, Simon F. B. Tett, Jean-François Exbrayat, A. Anthony Bloom, and Mathew Williams
Geosci. Model Dev., 10, 2651–2670, https://doi.org/10.5194/gmd-10-2651-2017, https://doi.org/10.5194/gmd-10-2651-2017, 2017
Yosuke Niwa, Yosuke Fujii, Yousuke Sawa, Yosuke Iida, Akihiko Ito, Masaki Satoh, Ryoichi Imasu, Kazuhiro Tsuboi, Hidekazu Matsueda, and Nobuko Saigusa
Geosci. Model Dev., 10, 2201–2219, https://doi.org/10.5194/gmd-10-2201-2017, https://doi.org/10.5194/gmd-10-2201-2017, 2017
Short summary
Short summary
A new 4D-Var inversion system based on the icosahedral grid model, NICAM, is introduced and tested. Adding to the offline forward and adjoint models, this study has introduced the optimization method of POpULar; it does not require difficult decomposition of a matrix that establishes the correlation among the prior flux errors. In identical twin experiments of atmospheric CO2 inversion, the system successfully reproduces the spatiotemporal variations of the surface fluxes.
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, https://doi.org/10.5194/gmd-10-2141-2017, 2017
Short summary
Short summary
Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Kazuya Nishina, Akihiko Ito, Naota Hanasaki, and Seiji Hayashi
Earth Syst. Sci. Data, 9, 149–162, https://doi.org/10.5194/essd-9-149-2017, https://doi.org/10.5194/essd-9-149-2017, 2017
Short summary
Short summary
Available historical global N fertilizer map as an input data to global biogeochemical model is still limited and existing maps were not considered NH4+ and NO3− in the fertilizer application rates. In our products, by utilizing national fertilizer species consumption data in FAOSTAT database, we succeeded to estimate the ratio of NH4+ to NO3− in the N fertilizer map. The products could be widely utilized for global N cycling studies.
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.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
Short summary
Short summary
Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
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.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
Short summary
Short summary
In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
K. E. Williams and P. D. Falloon
Geosci. Model Dev., 8, 3987–3997, https://doi.org/10.5194/gmd-8-3987-2015, https://doi.org/10.5194/gmd-8-3987-2015, 2015
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.
S. Miyazaki, K. Saito, J. Mori, T. Yamazaki, T. Ise, H. Arakida, T. Hajima, Y. Iijima, H. Machiya, T. Sueyoshi, H. Yabuki, E. J. Burke, M. Hosaka, K. Ichii, H. Ikawa, A. Ito, A. Kotani, Y. Matsuura, M. Niwano, T. Nitta, R. O'ishi, T. Ohta, H. Park, T. Sasai, A. Sato, H. Sato, A. Sugimoto, R. Suzuki, K. Tanaka, S. Yamaguchi, and K. Yoshimura
Geosci. Model Dev., 8, 2841–2856, https://doi.org/10.5194/gmd-8-2841-2015, https://doi.org/10.5194/gmd-8-2841-2015, 2015
Short summary
Short summary
The paper provides an overall outlook and the Stage 1 experiment (site simulations) protocol of GTMIP, an open model intercomparison project for terrestrial Arctic, conducted as an activity of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA). Models are driven by 34-year data created with the GRENE-TEA observations at four sites in Finland, Siberia and Alaska, and evaluated for physico-ecological key processes: energy budgets, snow, permafrost, phenology, and carbon budget.
K. Frieler, A. Levermann, J. Elliott, J. Heinke, A. Arneth, M. F. P. Bierkens, P. Ciais, D. B. Clark, D. Deryng, P. Döll, P. Falloon, B. Fekete, C. Folberth, A. D. Friend, C. Gellhorn, S. N. Gosling, I. Haddeland, N. Khabarov, M. Lomas, Y. Masaki, K. Nishina, K. Neumann, T. Oki, R. Pavlick, A. C. Ruane, E. Schmid, C. Schmitz, T. Stacke, E. Stehfest, Q. Tang, D. Wisser, V. Huber, F. Piontek, L. Warszawski, J. Schewe, H. Lotze-Campen, and H. J. Schellnhuber
Earth Syst. Dynam., 6, 447–460, https://doi.org/10.5194/esd-6-447-2015, https://doi.org/10.5194/esd-6-447-2015, 2015
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
Short summary
Short summary
Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
Short summary
Short summary
In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
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.
A. Ghosh, P. K. Patra, K. Ishijima, T. Umezawa, A. Ito, D. M. Etheridge, S. Sugawara, K. Kawamura, J. B. Miller, E. J. Dlugokencky, P. B. Krummel, P. J. Fraser, L. P. Steele, R. L. Langenfelds, C. M. Trudinger, J. W. C. White, B. Vaughn, T. Saeki, S. Aoki, and T. Nakazawa
Atmos. Chem. Phys., 15, 2595–2612, https://doi.org/10.5194/acp-15-2595-2015, https://doi.org/10.5194/acp-15-2595-2015, 2015
Short summary
Short summary
Atmospheric CH4 increased from 900ppb to 1800ppb during the period 1900–2010 at a rate unprecedented in any observational records. We use bottom-up emissions and a chemistry-transport model to simulate CH4. The optimized global total CH4 emission, estimated from the model–observation differences, increased at fastest rate during 1940–1990. Using δ13C of CH4 measurements we attribute this emission increase to biomass burning. Total CH4 lifetime is shortened by 4% over the simulation period.
A. A. Bloom and M. Williams
Biogeosciences, 12, 1299–1315, https://doi.org/10.5194/bg-12-1299-2015, https://doi.org/10.5194/bg-12-1299-2015, 2015
D. Slevin, S. F. B. Tett, and M. Williams
Geosci. Model Dev., 8, 295–316, https://doi.org/10.5194/gmd-8-295-2015, https://doi.org/10.5194/gmd-8-295-2015, 2015
G. B. Bonan, M. Williams, R. A. Fisher, and K. W. Oleson
Geosci. Model Dev., 7, 2193–2222, https://doi.org/10.5194/gmd-7-2193-2014, https://doi.org/10.5194/gmd-7-2193-2014, 2014
R. Hirata, K. Takagi, A. Ito, T. Hirano, and N. Saigusa
Biogeosciences, 11, 5139–5154, https://doi.org/10.5194/bg-11-5139-2014, https://doi.org/10.5194/bg-11-5139-2014, 2014
R. Q. Thomas and M. Williams
Geosci. Model Dev., 7, 2015–2037, https://doi.org/10.5194/gmd-7-2015-2014, https://doi.org/10.5194/gmd-7-2015-2014, 2014
M. Saito, A. Ito, and S. Maksyutov
Geosci. Model Dev., 7, 1829–1840, https://doi.org/10.5194/gmd-7-1829-2014, https://doi.org/10.5194/gmd-7-1829-2014, 2014
G. Xenakis and M. Williams
Geosci. Model Dev., 7, 1519–1533, https://doi.org/10.5194/gmd-7-1519-2014, https://doi.org/10.5194/gmd-7-1519-2014, 2014
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
T. L. Smallman, M. Williams, and J. B. Moncrieff
Biogeosciences, 11, 735–747, https://doi.org/10.5194/bg-11-735-2014, https://doi.org/10.5194/bg-11-735-2014, 2014
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, https://doi.org/10.5194/gmd-6-2121-2013, 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. Maksyutov, H. Takagi, V. K. Valsala, M. Saito, T. Oda, T. Saeki, D. A. Belikov, R. Saito, A. Ito, Y. Yoshida, I. Morino, O. Uchino, R. J. Andres, and T. Yokota
Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, https://doi.org/10.5194/acp-13-9351-2013, 2013
T. L. Smallman, J. B. Moncrieff, and M. Williams
Geosci. Model Dev., 6, 1079–1093, https://doi.org/10.5194/gmd-6-1079-2013, https://doi.org/10.5194/gmd-6-1079-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
J.-F. Exbrayat, N. R. Viney, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 6, 117–125, https://doi.org/10.5194/gmd-6-117-2013, https://doi.org/10.5194/gmd-6-117-2013, 2013
P. K. Patra, J. G. Canadell, R. A. Houghton, S. L. Piao, N.-H. Oh, P. Ciais, K. R. Manjunath, A. Chhabra, T. Wang, T. Bhattacharya, P. Bousquet, J. Hartman, A. Ito, E. Mayorga, Y. Niwa, P. A. Raymond, V. V. S. S. Sarma, and R. Lasco
Biogeosciences, 10, 513–527, https://doi.org/10.5194/bg-10-513-2013, https://doi.org/10.5194/bg-10-513-2013, 2013
Related subject area
Earth system interactions with the biosphere: biogeochemical cycles
How does the phytoplankton–light feedback affect the marine N2O inventory?
Time-varying changes and uncertainties in the CMIP6 ocean carbon sink from global to local scale
Interannual global carbon cycle variations linked to atmospheric circulation variability
Contrasting projections of the ENSO-driven CO2 flux variability in the equatorial Pacific under high-warming scenario
Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products
Indian Ocean marine biogeochemical variability and its feedback on simulated South Asia climate
Impact of bioenergy crop expansion on climate–carbon cycle feedbacks in overshoot scenarios
Biogeochemical functioning of the Baltic Sea
Process-based analysis of terrestrial carbon flux predictability
Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century
Resolving ecological feedbacks on the ocean carbon sink in Earth system models
Disequilibrium of terrestrial ecosystem CO2 budget caused by disturbance-induced emissions and non-CO2 carbon export flows: a global model assessment
Ocean phosphorus inventory: large uncertainties in future projections on millennial timescales and their consequences for ocean deoxygenation
Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system
Hazards of decreasing marine oxygen: the near-term and millennial-scale benefits of meeting the Paris climate targets
The biomass burning contribution to climate–carbon-cycle feedback
Earth system model simulations show different feedback strengths of the terrestrial carbon cycle under glacial and interglacial conditions
Nitrogen leaching from natural ecosystems under global change: a modelling study
Structure and functioning of the acid–base system in the Baltic Sea
The potential of using remote sensing data to estimate air–sea CO2 exchange in the Baltic Sea
Effects of the 2014 major Baltic inflow on methane and nitrous oxide dynamics in the water column of the central Baltic Sea
Evapotranspiration seasonality across the Amazon Basin
Seasonal effects of irrigation on land–atmosphere latent heat, sensible heat, and carbon fluxes in semiarid basin
Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis
Effect of various climate databases on the results of dendroclimatic analysis
The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks
Comment on: "Recent revisions of phosphate rock reserves and resources: a critique" by Edixhoven et al. (2014) – clarifying comments and thoughts on key conceptions, conclusions and interpretation to allow for sustainable action
Climate and carbon cycle dynamics in a CESM simulation from 850 to 2100 CE
The ocean carbon sink – impacts, vulnerabilities and challenges
Recent revisions of phosphate rock reserves and resources: a critique
The sensitivity of carbon turnover in the Community Land Model to modified assumptions about soil processes
Comment on "Carbon farming in hot, dry coastal areas: an option for climate change mitigation" by Becker et al. (2013)
Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes
Soil temperature response to 21st century global warming: the role of and some implications for peat carbon in thawing permafrost soils in North America
Thermodynamic dissipation theory for the origin of life
Sarah Berthet, Julien Jouanno, Roland Séférian, Marion Gehlen, and William Llovel
Earth Syst. Dynam., 14, 399–412, https://doi.org/10.5194/esd-14-399-2023, https://doi.org/10.5194/esd-14-399-2023, 2023
Short summary
Short summary
Phytoplankton absorbs the solar radiation entering the ocean surface and contributes to keeping the associated energy in surface waters. This natural effect is either not represented in the ocean component of climate models or its representation is simplified. An incomplete representation of this biophysical interaction affects the way climate models simulate ocean warming, which leads to uncertainties in projections of oceanic emissions of an important greenhouse gas (nitrous oxide).
Parsa Gooya, Neil C. Swart, and Roberta C. Hamme
Earth Syst. Dynam., 14, 383–398, https://doi.org/10.5194/esd-14-383-2023, https://doi.org/10.5194/esd-14-383-2023, 2023
Short summary
Short summary
We report on the ocean carbon sink and sources of uptake uncertainty from the latest version of the Coupled Model Intercomparison Project. We diagnose the highly active regions for the sink and show how knowledge about historical regions of uptake will provide information about future regions of uptake change and uncertainty. We evaluate the dependence of uncertainty on the location and integration scale. Our results help make useful suggestions for both modeling and observational communities.
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022, https://doi.org/10.5194/esd-13-1505-2022, 2022
Short summary
Short summary
Quantifying the imprint of large-scale atmospheric circulation dynamics and associated carbon cycle responses is key to improving our understanding of carbon cycle dynamics. Using a statistical model that relies on spatiotemporal sea level pressure as a proxy for large-scale atmospheric circulation, we quantify the fraction of interannual variability in atmospheric CO2 growth rate and the land CO2 sink that are driven by atmospheric circulation variability.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
Short summary
Short summary
The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han
Earth Syst. Dynam., 13, 833–849, https://doi.org/10.5194/esd-13-833-2022, https://doi.org/10.5194/esd-13-833-2022, 2022
Short summary
Short summary
We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022, https://doi.org/10.5194/esd-13-809-2022, 2022
Short summary
Short summary
The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. When the biogeochemical coupling is included, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.
Irina Melnikova, Olivier Boucher, Patricia Cadule, Katsumasa Tanaka, Thomas Gasser, Tomohiro Hajima, Yann Quilcaille, Hideo Shiogama, Roland Séférian, Kaoru Tachiiri, Nicolas Vuichard, Tokuta Yokohata, and Philippe Ciais
Earth Syst. Dynam., 13, 779–794, https://doi.org/10.5194/esd-13-779-2022, https://doi.org/10.5194/esd-13-779-2022, 2022
Short summary
Short summary
The deployment of bioenergy crops for capturing carbon from the atmosphere facilitates global warming mitigation via generating negative CO2 emissions. Here, we explored the consequences of large-scale energy crops deployment on the land carbon cycle. The land-use change for energy crops leads to carbon emissions and loss of future potential increase in carbon uptake by natural ecosystems. This impact should be taken into account by the modeling teams and accounted for in mitigation policies.
Karol Kuliński, Gregor Rehder, Eero Asmala, Alena Bartosova, Jacob Carstensen, Bo Gustafsson, Per O. J. Hall, Christoph Humborg, Tom Jilbert, Klaus Jürgens, H. E. Markus Meier, Bärbel Müller-Karulis, Michael Naumann, Jørgen E. Olesen, Oleg Savchuk, Andreas Schramm, Caroline P. Slomp, Mikhail Sofiev, Anna Sobek, Beata Szymczycha, and Emma Undeman
Earth Syst. Dynam., 13, 633–685, https://doi.org/10.5194/esd-13-633-2022, https://doi.org/10.5194/esd-13-633-2022, 2022
Short summary
Short summary
The paper covers the aspects related to changes in carbon, nitrogen, and phosphorus (C, N, P) external loads; their transformations in the coastal zone; changes in organic matter production (eutrophication) and remineralization (oxygen availability); and the role of sediments in burial and turnover of C, N, and P. Furthermore, this paper also focuses on changes in the marine CO2 system, the structure of the microbial community, and the role of contaminants for biogeochemical processes.
István Dunkl, Aaron Spring, Pierre Friedlingstein, and Victor Brovkin
Earth Syst. Dynam., 12, 1413–1426, https://doi.org/10.5194/esd-12-1413-2021, https://doi.org/10.5194/esd-12-1413-2021, 2021
Short summary
Short summary
The variability in atmospheric CO2 is largely controlled by terrestrial carbon fluxes. These land–atmosphere fluxes are predictable for around 2 years, but the mechanisms providing the predictability are not well understood. By decomposing the predictability of carbon fluxes into individual contributors we were able to explain the spatial and seasonal patterns and the interannual variability of CO2 flux predictability.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
Short summary
Short summary
Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
David I. Armstrong McKay, Sarah E. Cornell, Katherine Richardson, and Johan Rockström
Earth Syst. Dynam., 12, 797–818, https://doi.org/10.5194/esd-12-797-2021, https://doi.org/10.5194/esd-12-797-2021, 2021
Short summary
Short summary
We use an Earth system model with two new ocean ecosystem features (plankton size traits and temperature-sensitive nutrient recycling) to revaluate the effect of climate change on sinking organic carbon (the
biological pump) and the ocean carbon sink. These features lead to contrary pump responses to warming, with a combined effect of a smaller sink despite a more resilient pump. These results show the importance of including ecological dynamics in models for understanding climate feedbacks.
Akihiko Ito
Earth Syst. Dynam., 10, 685–709, https://doi.org/10.5194/esd-10-685-2019, https://doi.org/10.5194/esd-10-685-2019, 2019
Short summary
Short summary
Various minor carbon flows such as trace gas emissions, disturbance-induced emissions, and subsurface exports can affect the carbon budget of terrestrial ecosystems in complicated ways. This study assessed how much these minor flows influence the carbon budget using a process-based model. It was found that the minor flows, though small in magnitude, could significantly affect net carbon budget at as much strengths as major flows, implying their long-term importance in Earth's climate system.
Tronje P. Kemena, Angela Landolfi, Andreas Oschlies, Klaus Wallmann, and Andrew W. Dale
Earth Syst. Dynam., 10, 539–553, https://doi.org/10.5194/esd-10-539-2019, https://doi.org/10.5194/esd-10-539-2019, 2019
Short summary
Short summary
Oceanic deoxygenation is driven by climate change in several areas of the global ocean. Measurements indicate that ocean volumes with very low oxygen levels expand, with consequences for marine organisms and fishery. We found climate-change-driven phosphorus (P) input in the ocean is hereby an important driver for deoxygenation on longer timescales with effects in the next millennia.
Efrén López-Blanco, Jean-François Exbrayat, Magnus Lund, Torben R. Christensen, Mikkel P. Tamstorf, Darren Slevin, Gustaf Hugelius, Anthony A. Bloom, and Mathew Williams
Earth Syst. Dynam., 10, 233–255, https://doi.org/10.5194/esd-10-233-2019, https://doi.org/10.5194/esd-10-233-2019, 2019
Short summary
Short summary
The terrestrial CO2 exchange in Arctic ecosystems plays an important role in the global carbon cycle and is particularly sensitive to the ongoing warming experienced in recent years. To improve our understanding of the atmosphere–biosphere interplay, we evaluated the state of the terrestrial pan-Arctic carbon cycling using a promising data assimilation system in the first 15 years of the 21st century. This is crucial when it comes to making predictions about the future state of the carbon cycle.
Gianna Battaglia and Fortunat Joos
Earth Syst. Dynam., 9, 797–816, https://doi.org/10.5194/esd-9-797-2018, https://doi.org/10.5194/esd-9-797-2018, 2018
Short summary
Short summary
Human-caused, climate change hazards in the ocean continue to aggravate over a very long time. For business as usual, we project the ocean oxygen content to decrease by 40 % over the next thousand years. This would likely have severe consequences for marine life. Global warming and oxygen loss are linked, and meeting the warming target of the Paris Climate Agreement effectively limits related marine hazards. Developments over many thousands of years should be considered to assess marine risks.
Sandy P. Harrison, Patrick J. Bartlein, Victor Brovkin, Sander Houweling, Silvia Kloster, and I. Colin Prentice
Earth Syst. Dynam., 9, 663–677, https://doi.org/10.5194/esd-9-663-2018, https://doi.org/10.5194/esd-9-663-2018, 2018
Short summary
Short summary
Temperature affects fire occurrence and severity. Warming will increase fire-related carbon emissions and thus atmospheric CO2. The size of this feedback is not known. We use charcoal records to estimate pre-industrial fire emissions and a simple land–biosphere model to quantify the feedback. We infer a feedback strength of 5.6 3.2 ppm CO2 per degree of warming and a gain of 0.09 ± 0.05 for a climate sensitivity of 2.8 K. Thus, fire feedback is a large part of the climate–carbon-cycle feedback.
Markus Adloff, Christian H. Reick, and Martin Claussen
Earth Syst. Dynam., 9, 413–425, https://doi.org/10.5194/esd-9-413-2018, https://doi.org/10.5194/esd-9-413-2018, 2018
Short summary
Short summary
Computer simulations show that during an ice age a strong atmospheric CO2 increase would have resulted in stronger carbon uptake of the continents than today. Causes are the larger potential of glacial vegetation to increase its photosynthetic efficiency under increasing CO2 and the smaller amount of carbon in extratropical soils during an ice age that can be released under greenhouse warming. Hence, for different climates the Earth system is differently sensitive to carbon cycle perturbations.
Maarten C. Braakhekke, Karin T. Rebel, Stefan C. Dekker, Benjamin Smith, Arthur H. W. Beusen, and Martin J. Wassen
Earth Syst. Dynam., 8, 1121–1139, https://doi.org/10.5194/esd-8-1121-2017, https://doi.org/10.5194/esd-8-1121-2017, 2017
Short summary
Short summary
Nitrogen input in natural ecosystems usually has a positive effect on plant growth. However, too much N causes N leaching, which contributes to water pollution. Using a global model we estimated that N leaching from natural lands has increased by 73 % during the 20th century, mainly due to rising N deposition from the atmosphere caused by emissions from fossil fuels and agriculture. Climate change and increasing CO2 concentration had positive and negative effects (respectively) on N leaching.
Karol Kuliński, Bernd Schneider, Beata Szymczycha, and Marcin Stokowski
Earth Syst. Dynam., 8, 1107–1120, https://doi.org/10.5194/esd-8-1107-2017, https://doi.org/10.5194/esd-8-1107-2017, 2017
Short summary
Short summary
This review describes the general knowledge of the marine acid–base system as well as the peculiarities identified and reported for the Baltic Sea specifically. We discuss issues such as dissociation constants in the brackish water, the structure of the total alkalinity in the Baltic Sea, long-term changes in total alkalinity, and the acid–base effects of biomass production and mineralization. We identify research gaps and specify bottlenecks concerning the Baltic Sea acid–base system.
Gaëlle Parard, Anna Rutgersson, Sindu Raj Parampil, and Anastase Alexandre Charantonis
Earth Syst. Dynam., 8, 1093–1106, https://doi.org/10.5194/esd-8-1093-2017, https://doi.org/10.5194/esd-8-1093-2017, 2017
Short summary
Short summary
Coastal environments and shelf sea represent 7.6 % of the total oceanic surface area. They are, however, biogeochemically more dynamic and probably more vulnerable to climate change than the open ocean. Whatever the responses of the open ocean to climate change, they will propagate to the coastal ocean. We used the self-organizing multiple linear output (SOMLO) method to estimate the ocean surface pCO2 in the Baltic Sea from remotely sensed measurements and we estimated the air–sea CO2 flux.
Jukka-Pekka Myllykangas, Tom Jilbert, Gunnar Jakobs, Gregor Rehder, Jan Werner, and Susanna Hietanen
Earth Syst. Dynam., 8, 817–826, https://doi.org/10.5194/esd-8-817-2017, https://doi.org/10.5194/esd-8-817-2017, 2017
Short summary
Short summary
The deep waters of the Baltic Sea host an expanding
dead zone, where low-oxygen conditions favour the natural production of two strong greenhouse gases, methane and nitrous oxide. Oxygen is introduced into the deeps only during rare
salt pulses. We studied the effects of a recent salt pulse on Baltic greenhouse gas production. We found that where oxygen was introduced, methane was largely removed, while nitrous oxide production increased, indicating strong effects on greenhouse gas dynamics.
Eduardo Eiji Maeda, Xuanlong Ma, Fabien Hubert Wagner, Hyungjun Kim, Taikan Oki, Derek Eamus, and Alfredo Huete
Earth Syst. Dynam., 8, 439–454, https://doi.org/10.5194/esd-8-439-2017, https://doi.org/10.5194/esd-8-439-2017, 2017
Short summary
Short summary
The Amazon River basin continuously transfers massive volumes of water from the land surface to the atmosphere, thereby having massive influence on global climate patterns. Nonetheless, the characteristics of ET across the Amazon basin, as well as the relative contribution of the multiple drivers to this process, are still uncertain. This study carries out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers across the Amazon Basin.
Yujin Zeng, Zhenghui Xie, and Shuang Liu
Earth Syst. Dynam., 8, 113–127, https://doi.org/10.5194/esd-8-113-2017, https://doi.org/10.5194/esd-8-113-2017, 2017
Short summary
Short summary
Irrigation constitutes 70 % of human water consumption. In this study, using the improved CLM4.5 with an active crop model, two 1 km simulations investigating the effects of irrigation on latent heat, sensible heat, and carbon fluxes in the Heihe River basin in northwestern China were conducted using a high-quality irrigation dataset compiled from 1981 to 2013. The results revealed the key role of irrigation in the control of land–atmosphere water, energy, and carbon fluxes in semiarid basin.
Rashid Rafique, Jianyang Xia, Oleksandra Hararuk, Ghassem R. Asrar, Guoyong Leng, Yingping Wang, and Yiqi Luo
Earth Syst. Dynam., 7, 649–658, https://doi.org/10.5194/esd-7-649-2016, https://doi.org/10.5194/esd-7-649-2016, 2016
Short summary
Short summary
Traceability analysis was used to diagnose the causes of differences in simulating ecosystem carbon storage capacity between two land models: CLMA-CASA and CABLE. Results showed that the simulated ecosystem carbon storage capacity is largely influenced by the photosynthesis parameterization, residence time and organic matter decomposition.
Roman Sitko, Jaroslav Vido, Jaroslav Škvarenina, Viliam Pichler, Ĺubomír Scheer, Jana Škvareninová, and Paulína Nalevanková
Earth Syst. Dynam., 7, 385–395, https://doi.org/10.5194/esd-7-385-2016, https://doi.org/10.5194/esd-7-385-2016, 2016
A. Kessler and J. Tjiputra
Earth Syst. Dynam., 7, 295–312, https://doi.org/10.5194/esd-7-295-2016, https://doi.org/10.5194/esd-7-295-2016, 2016
Short summary
Short summary
The uncertainty of ocean carbon uptake in ESMs is projected to grow 2-fold by the end of the 21st century. We found that models that take up anomalously low (high) CO2 in the Southern Ocean (SO) today project low (high) cumulative CO2 uptake in the 21st century; thus the SO can be used to constrain future global uptake uncertainty. Inter-model spread in the SO carbon sink arises from variations in the pCO2 seasonality, specifically bias in the simulated timing and amplitude of NPP and SST.
R. W. Scholz and F.-W. Wellmer
Earth Syst. Dynam., 7, 103–117, https://doi.org/10.5194/esd-7-103-2016, https://doi.org/10.5194/esd-7-103-2016, 2016
Short summary
Short summary
The 2014 USGS data could decrease from 67 Gt phosphate rock (PR) reserves to 58.5 Gt marketable PR (PR-M) if data on PR-ore are transferred to PR-M. The 50 Gt PR-M estimate for Moroccan reserves is reasonable. Geoeconomics suggests that large parts of resources and geopotential become future reserves. As phosphate is essential for food production and reserve data alone are unsufficient for assessing long-run supply security, an international standing committee may assess future PR accessibility.
F. Lehner, F. Joos, C. C. Raible, J. Mignot, A. Born, K. M. Keller, and T. F. Stocker
Earth Syst. Dynam., 6, 411–434, https://doi.org/10.5194/esd-6-411-2015, https://doi.org/10.5194/esd-6-411-2015, 2015
Short summary
Short summary
We present the first last-millennium simulation with the Community Earth System Model (CESM) including an interactive carbon cycle in both ocean and land component. Volcanic eruptions emerge as the strongest forcing factor for the preindustrial climate and carbon cycle. We estimate the climate-carbon-cycle feedback in CESM to be at the lower bounds of empirical estimates (1.3ppm/°C). The time of emergence for interannual global land and ocean carbon uptake rates are 1947 and 1877, respectively.
C. Heinze, S. Meyer, N. Goris, L. Anderson, R. Steinfeldt, N. Chang, C. Le Quéré, and D. C. E. Bakker
Earth Syst. Dynam., 6, 327–358, https://doi.org/10.5194/esd-6-327-2015, https://doi.org/10.5194/esd-6-327-2015, 2015
Short summary
Short summary
Rapidly rising atmospheric CO2 concentrations caused by human actions over the past 250 years have raised cause for concern that changes in Earth’s climate system may progress at a much faster pace and larger extent than during the past 20,000 years. Questions that yet need to be answered are what the carbon uptake kinetics of the oceans will be in the future and how the increase in oceanic carbon inventory will affect its ecosystems. Major future ocean carbon research challenges are discussed.
J. D. Edixhoven, J. Gupta, and H. H. G. Savenije
Earth Syst. Dynam., 5, 491–507, https://doi.org/10.5194/esd-5-491-2014, https://doi.org/10.5194/esd-5-491-2014, 2014
Short summary
Short summary
Phosphate rock is a finite resource required for fertilizer production. Following a debate over the PR depletion timeline, global PR reserves were recently increased 4-fold based mainly on a restatement of Moroccan reserves. We review whether this restatement is methodologically compatible with resource terminology used in major resource classifications, whether resource classification nomenclature is sufficiently understood in the literature, and whether the recent restatements are reliable.
B. Foereid, D. S. Ward, N. Mahowald, E. Paterson, and J. Lehmann
Earth Syst. Dynam., 5, 211–221, https://doi.org/10.5194/esd-5-211-2014, https://doi.org/10.5194/esd-5-211-2014, 2014
M. Heimann
Earth Syst. Dynam., 5, 41–42, https://doi.org/10.5194/esd-5-41-2014, https://doi.org/10.5194/esd-5-41-2014, 2014
R. Séférian, L. Bopp, D. Swingedouw, and J. Servonnat
Earth Syst. Dynam., 4, 109–127, https://doi.org/10.5194/esd-4-109-2013, https://doi.org/10.5194/esd-4-109-2013, 2013
D. Wisser, S. Marchenko, J. Talbot, C. Treat, and S. Frolking
Earth Syst. Dynam., 2, 121–138, https://doi.org/10.5194/esd-2-121-2011, https://doi.org/10.5194/esd-2-121-2011, 2011
K. Michaelian
Earth Syst. Dynam., 2, 37–51, https://doi.org/10.5194/esd-2-37-2011, https://doi.org/10.5194/esd-2-37-2011, 2011
Cited articles
Ahlström, A., Schurgers, G., Arneth, A., and Smith, B.: Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections, Environ. Res. Lett., 7, 044008, https://doi.org/10.1088/1748-9326/7/4/044008, 2012.
Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A., Jung, M., Reichstein, M., Canadell, J. G., Friedlingstein, P., Jain, A. K., Kato, E., Poulter, B., Sitch, S., Stocker, B. D., Viovy, N., Wang, Y. P., Wiltshire, A., Zaehle, S., and Zeng, N.: Carbon cycle. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink, Science, 348, 895–899, https://doi.org/10.1126/science.aaa1668, 2015.
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D., Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., Cadule, P., Hajima, T., Ilyina, T., Lindsay, K., Tjiputra, J. F., and Wu, T.: Carbon–concentration and carbon–climate feedbacks in CMIP5 earth system models, J. Climate, 26, 5289–5314, https://doi.org/10.1175/JCLI-D-12-00494.1, 2013.
Baldocchi, D., Falge, E., Gu, L. H., Olson, R., Hollinger, D.,
Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R.,
Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X. H., Malhi, Y.,
Meyers, T., Munger, W., Oechel, W., U, Paw, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: a new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:fantts>2.3.co;2, 2001.
Bastos, A., Running, S. W., Gouveia, C., and Trigo, R. M.: The global NPP dependence on ENSO: La Niña and the extraordinary year of 2011, J. Geophys. Res.-Biogeo., 118, 1247–1255, https://doi.org/10.1002/jgrg.20100, 2013.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate Earth paradigm, Clim. Dynam., 41, 885–900, https://doi.org/10.1007/s00382-012-1610-y, 2012.
Bloom, A. A. and Williams, M.: Constraining ecosystem carbon dynamics in a
data-limited world: integrating ecological ”common sense” in a model–data
fusion framework, Biogeosciences, 12, 1299–1315,
https://doi.org/10.5194/bg-12-1299-2015, 2015a.
Bloom, A. and Williams, M.: CARDAMOM 2001–2010 global carbon Model–Data
Fusion (MDF) analysis, 2001–2010, [dataset], University of Edinburgh, School
of GeoSciences, available at: https://doi.org/10.7488/ds/316 (last access:
17 November 2016), 2015b.
Bloom, A. A., Exbrayat, J.-F., van der Velde, I. R., Feng, L., and Williams, M.: The decadal state of the terrestrial carbon cycle: global retrievals of terrestrial carbon allocation, pools, and residence times., P. Natl. Acad. Sci. USA, 113, 1285–1290, https://doi.org/10.1073/pnas.1515160113, 2016.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001.
Canadell, J. G., Le Quéré, C., Raupach, M. R., Field, C. B.,
Buitenhuis, E. T., Ciais, P., Conway, T. J., Gillett, N. P.,
Houghton, R. A., and Marland, G.: Contributions to accelerating
atmospheric CO2 growth from economic activity, carbon
intensity, and efficiency of natural sinks, P. Natl. Acad. Sci. USA, 104, 18866–18870, https://doi.org/10.1073/pnas.0702737104, 2007.
Chen, M., Rafique, R., Asrar, G. R., Bond-Lamberty, B., Ciais, P., Zhao, F.,
Reyer, C. P. O., Ostberg, S., Chang, J., Ito, A., Yang, J., Zeng, N.,
Kalnay, E., West, T., Leng, G., Francois, L., Munhoven, G., Henrot, A.,
Tian, H., Pan, S., Nishina, K., Viovy, N., Morfopoulos, C., Betts, R.,
Schaphoff, S., Steinkamp, J., and Hickler, T.: Regional contribution to
variability and trends of global gross primary productivity, Environ. Res.
Lett., 12, 105005, https://doi.org/10.1088/1748-9326/aa8978, 2017.
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.
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin, G., O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire, A., and Woodward, S.: Development and evaluation of an Earth-System model – HadGEM2, Geosci. Model Dev., 4, 1051–1075, https://doi.org/10.5194/gmd-4-1051-2011, 2011.
Cox, P. M., Pearson, D., Booth, B. B., Friedlingstein, P., Huntingford, C.,
Jones, C. D., and Luke, C. M.: Sensitivity of tropical carbon to climate
change constrained by carbon dioxide variability, Nature, 494, 341–344,
https://doi.org/10.1038/nature11882, 2013.
De Kauwe, M. G., Keenan, T. F., Medlyn, B. E., Prentice, I. C., and Terrer., C.: Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity, Nat. Clim. Change, 6, 892–893, https://doi.org/10.1038/nclimate3105, 2016.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont,
O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp,
L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic,
A., Cugnet, D., Noblet, N., Duvel, J.-P., Ethé, C., Fairhead, L., Fichefet,
T., Flavoni, S., Friedlingstein, P., Grandpeix, J.-Y., Guez, L., Guilyardi,
E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J., Joussaume, S.,
Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A., Lefebvre, M.-P.,
Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F., Madec, G., Mancip, M.,
Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J., Musat, I., Parouty, S.,
Polcher, J., Rio, C., Schulz, M., Swingedouw, D., Szopa, S., Talandier, C.,
Terray, P., Viovy, N. and Vuichard, N.: Climate change projections using the
IPSL-CM5 Earth System Model: from CMIP3 to CMIP5, Clim. Dynam., 40,
2123–2165, https://doi.org/10.1007/s00382-012-1636-1, 2013.
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W.,
Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J.,
Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman,
L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and
Zadeh, N.: GFDL's ESM2 global coupled climate–carbon earth system models.
Part I: Physical formulation and baseline simulation characteristics,
J. Climate, 25, 6646–6665, https://doi.org/10.1175/JCLI-D-11-00560.1, 2012.
Ellsworth, D. S., Anderson, I. C., Crous, K. Y., Cooke, J., Drake, J. E., Gherlenda, A. N., Gimeno, T. E., Macdonald, C. A., Medlyn, B. E., Powell, J. R., Tjoelker, M. G., and Reich, P. B.: Elevated CO2 does not increase eucalypt forest productivity on a low-phosphorus soil, Nat. Clim. Change, 7, 279–282, https://doi.org/10.1038/nclimate3235, 2017.
Exbrayat, J.-F., Viney, N. R., Seibert, J., Wrede, S., Frede, H.-G., and Breuer, L.: Ensemble modelling of nitrogen fluxes: data fusion for a Swedish meso-scale catchment, Hydrol. Earth Syst. Sci., 14, 2383–2397, https://doi.org/10.5194/hess-14-2383-2010, 2010.
Exbrayat, J.-F., Pitman, A. J., Zhang, Q., Abramowitz, G., and Wang, Y.-P.: Examining soil carbon uncertainty in a global model: response of microbial decomposition to temperature, moisture and nutrient limitation, Biogeosciences, 10, 7095–7108, https://doi.org/10.5194/bg-10-7095-2013, 2013a.
Exbrayat, J.-F., Viney, N. R., Frede, H.-G., and Breuer, L.: Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions, Geosci. Model Dev., 6, 117–125, https://doi.org/10.5194/gmd-6-117-2013, 2013b.
Exbrayat, J.-F., Pitman, A. J., and Abramowitz, G.: Response of microbial
decomposition to spin-up explains CMIP5 soil carbon range until 2100, Geosci.
Model Dev., 7, 2683–2692, https://doi.org/10.5194/gmd-7-2683-2014, 2014.
Exbrayat, J.-F. and Williams, M.: Reliability Ensemble Averaging of ISIMIP
NPP projections for 2095–2099 under RCP8.5, [dataset], School of
GeoSciences, University of Edinburgh, available at: https://doi.org/10.7488/ds/2304,
last access: 19 February 2018.
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database (version 1.21), FAO, Rome, Italy and IIASA, Laxenburg, Austria, 2012.
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results, Remote Sens. Environ., 83, 287–302, https://doi.org/10.1016/S0034-4257(02)00078-0, 2002.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate–carbon cycle feedback analysis: results from the C4MIP Model intercomparison, J. Climate, 19, 3337–3353, https://doi.org/10.1175/JCLI3800.1, 2006.
Friend, A. D. and White, A.: Evaluation and analysis of a dynamic terrestrial ecosystem model under preindustrial conditions at the global scale, Global Biogeochem. Cy., 14, 1173–1190, https://doi.org/10.1029/1999GB900085, 2000.
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, https://doi.org/10.1073/pnas.1222477110, 2014.
Georgakakos, K. P., Seo, D.-J., Gupta, H., Schaake, J., and Butts, M. B.: Towards the characterization of streamflow simulation uncertainty through multimodel ensembles, J. Hydrol., 298, 222–241, https://doi.org/10.1016/j.jhydrol.2004.03.037, 2004.
Giglio, L., Randerson, J. T., and van der 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, https://doi.org/10.1002/jgrg.20042, 2013.
Giorgi, F. and Mearns, L. O.: Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “Reliability Ensemble Averaging” (REA) method, J. Climate, 15, 1141–1158, https://doi.org/10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2, 2002.
Goll, D. S., Brovkin, V., Parida, B. R., Reick, C. H., Kattge, J., Reich, P.
B., van Bodegom, P. M., and Niinemets, Ü.: Nutrient limitation reduces
land carbon uptake in simulations with a model of combined carbon, nitrogen
and phosphorus cycling, Biogeosciences, 9, 3547–3569,
https://doi.org/10.5194/bg-9-3547-2012, 2012.
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F.: A trend-preserving bias correction – the ISIMIP approach, Earth Syst. Dynam., 4, 219–236, https://doi.org/10.5194/esd-4-219-2013, 2013.
Huisman, J. A., Breuer, L., Bormann, H., Bronstert, A., Croke, B. F. W., Frede, H.-G., Gräff, T., Hubrechts, L., Jakeman, A. J., Kite, G., Lanini, J., Leavesley, G., Lettenmaier, D. P., Lindström, G., Seibert, J., Sivapalan, M., Viney, N. R., and Willems, P.: Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: scenario analysis, Adv. Water Resour., 32, 159–170, https://doi.org/10.1016/j.advwatres.2008.06.009, 2009.
Huntzinger, D. N., Schwalm, C., Michalak, A. M., Schaefer, K., King, A. W., Wei, Y., Jacobson, A., Liu, S., Cook, R. B., Post, W. M., Berthier, G., Hayes, D., Huang, M., Ito, A., Lei, H., Lu, C., Mao, J., Peng, C. H., Peng, S., Poulter, B., Riccuito, D., Shi, X., Tian, H., Wang, W., Zeng, N., Zhao, F., and Zhu, Q.: The North American Carbon Program Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design, Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, 2013.
Huntzinger, D. N., Michalak, A. M., Schwalm, C., Ciais, P., King, A. W., Fang, Y., Schaefer, K., Wei, Y., Cook, R. B., Fisher, J. B., Hayes, D., Huang, M., Ito, A., Jain, A. K., Lei, H., Lu, C., Maignan, F., Mao, J., Parazoo, N., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tian, H., Wang, W., Zeng, N., and Zhao, F.: Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions, Sci. Rep.-UK, 7, 4765, https://doi.org/10.1038/s41598-017-03818-2, 2017.
Ito, A. and Inatomi, M.: Water-use efficiency of the terrestrial biosphere: a model analysis focusing on interactions between the global carbon and water cycles, J. Hydrometeorol., 13, 681–694, https://doi.org/10.1175/JHM-D-10-05034.1, 2012.
Jung, M.: FLUXCOM (RS+METEO) Global Land Carbon Fluxes using CRUNCEP climate
data, [dataset], Max Planck Institute for Biogeochemistry, available at:
https://doi.org/10.17871/FLUXCOM_RS_METEO_CRUNCEPv6_1980_2013_v1 (last
access: 28 July 2017), 2016.
Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001–2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D., Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D., Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A., Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M., Vaccari, F., and Williams, C.: Global patterns of land–atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations, J. Geophys. Res.-Biogeo., 116, G00J07, https://doi.org/10.1029/2010JG001566, 2011.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S., Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B., Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y.-P., Weber, U., Zaehle, S., and Zeng, N.: Compensatory water effects link yearly global land CO2 sink changes to temperature, Nature, 541, 516–520, https://doi.org/10.1038/nature20780, 2017.
Knutti, R., Masson, D., and Gettelman, A.: Climate model genealogy: generation CMIP5 and how we got there, Geophys. Res. Lett., 40, 1194–1199, https://doi.org/10.1002/grl.50256, 2013.
Krishnamurti, T. N., Kishtawal, C. M., LaRow, T. E., Bachiochi, D. R., Zhang, Z., Williford, C. E., Gadgil, S., and Surendran, S.: Improved weather and seasonal climate forecasts from multimodel superensemble, Science, 80, 1548–1550, https://doi.org/10.1126/science.285.5433.1548, 1999.
Lasslop, G., Reichstein, M., Papale, D., Richardson, A. D., Arneth, A., Barr, A., Stoy, P., and Wohlfahrt, G.: Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation, Glob. Change Biol., 16, 187–208, https://doi.org/10.1111/j.1365-2486.2009.02041.x, 2009.
Le Quéré, C., Raupach, M. R., Canadell, J. G., Marland, G., Bopp, L., Ciais, P., Conway, T. J., Doney, S. C., Feely, R. A., Foster, P., Friedlingstein, P., Gurney, K., Houghton, R. A., House, J. I., Huntingford, C., Levy, P. E., Lomas, M. R., Majkut, J., Metzl, N., Ometto, J. P., Peters, G. P., Prentice, I. C., Randerson, J. T., Running, S. W., Sarmiento, J. L., Schuster, U., Sitch, S., Takahashi, T., Viovy, N., van der Werf, G. R., and Woodward, F. I.: Trends in the sources and sinks of carbon dioxide, Nat. Geosci., 2, 831–836, https://doi.org/10.1038/ngeo689, 2009.
Lovenduski, N. S. and Bonan, G. B.: Reducing uncertainty in projections of
terrestrial carbon uptake, Environ. Res. Lett., 12, 44020,
https://doi.org/10.1088/1748-9326/aa66b8, 2017.
Moncrieff, G. R., Scheiter, S., Langan, L., Trabucco, A., and Higgins, S. I.: The future distribution of the savannah biome: model-based and biogeographic contingency, Philos. T. R. Soc. B, 371, 20150311, https://doi.org/10.1098/rstb.2015.0311, 2016.
Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J. L., Glassy, J., Tian, Y., Wang, Y., Song, X., Zhang, Y., Smith, G. R., Lotsch, A., Friedl, M., Morisette, J. T., Votava, P., Nemani, R. R., and Running, S. W.: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data, Remote Sens. Environ., 83, 214–231, 2002.
Nishina, K., Ito, A., Beerling, D. J., Cadule, P., Ciais, P., Clark, D. B., Falloon, P., Friend, A. D., Kahana, R., Kato, E., Keribin, R., Lucht, W., Lomas, M., Rademacher, T. T., Pavlick, R., Schaphoff, S., Vuichard, N., Warszawaski, L., and Yokohata, T.: Quantifying uncertainties in soil carbon responses to changes in global mean temperature and precipitation, Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, 2014.
Nishina, K., Ito, A., Falloon, P., Friend, A. D., Beerling, D. J., Ciais, P., Clark, D. B., Kahana, R., Kato, E., Lucht, W., Lomas, M., Pavlick, R., Schaphoff, S., Warszawaski, L., and Yokohata, T.: Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISIMIP results, Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, 2015.
Norby, R. J., Warren, J. M., Iversen, C. M., Medlyn, B. E., and McMurtrie, R. E.: CO2 enhancement of forest productivity constrained by limited nitrogen availability, P. Natl. Acad. Sci. USA, 107, 19368–19373, https://doi.org/10.1073/pnas.1006463107, 2010.
Pavlick, R., Drewry, D. T., Bohn, K., Reu, B., and Kleidon, A.: The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs, Biogeosciences, 10, 4137–4177, https://doi.org/10.5194/bg-10-4137-2013, 2013.
Poulter, B., Frank, D., Ciais, P., Myneni, R. B., Andela, N., Bi, J., Broquet, G., Canadell, J. G., Chevallier, F., Liu, Y. Y., Running, S. W., Sitch, S., and van der Werf, G. R.: Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle, Nature, 509, 600–603, https://doi.org/10.1038/nature13376, 2014.
Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M.: Using bayesian model averaging to calibrate forecast ensembles, Mon. Weather Rev., 133, 1155–1174, https://doi.org/10.1175/MWR2906.1, 2005.
Rammig, A., Jupp, T., Thonicke, K., Tietjen, B., Heinke, J., Ostberg, S., Lucht, W., Cramer, W., and Cox, P.: Estimating the risk of Amazonian forest dieback, New Phytol., 187, 694–706, https://doi.org/10.1111/j.1469-8137.2010.03318.x, 2010.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier,
P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T.,
Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila,
A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M.,
Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G.,
Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of
net ecosystem exchange into assimilation and ecosystem respiration: review
and improved algorithm, Glob. Change Biol., 11, 1424–1439, 2005.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and Hashimoto, H.: A continuous satellite-derived measure of global terrestrial primary production, Bioscience, 54, 547, https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2, 2004.
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, https://doi.org/10.1073/pnas.1019576108, 2011.
Schwalm, C. R., Huntzinger, D. N., Fisher, J. B., Michalak, A. M., Bowman, K., Ciais, P., Cook, R., El-Masri, B., Hayes, D., Huang, M., Ito, A., Jain, A., King, A. W., Lei, H., Liu, J., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Schaefer, K., Shi, X., Tao, B., Tian, H., Wang, W., Wei, Y., Yang, J., and Zeng, N.: Toward “optimal” integration of terrestrial biosphere models, Geophys. Res. Lett., 42, 4418–4428, https://doi.org/10.1002/2015GL064002, 2015.
Shamseldin, A. Y., O'Connor, K. M., and Liang, G. C.: Methods for combining the outputs of different rainfall–runoff models, J. Hydrol., 197, 203–229, https://doi.org/10.1016/S0022-1694(96)03259-3, 1997.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Smallman, T. L., Exbrayat, J.-F., Mencuccini, M., Bloom, A. A., and Williams, M.: Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests, J. Geophys. Res.-Biogeo., 122, 528–545, https://doi.org/10.1002/2016JG003520, 2017.
Smith, W. K., Reed, S. C., Cleveland, C. C., Ballantyne, A. P., Anderegg, W. R. L., Wieder, W. R., Liu, Y. Y., and Running, S. W.: Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization, Nat. Clim. Change, 6, 306–310, https://doi.org/10.1038/nclimate2879, 2015.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experiment design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Thornton, P. E., Doney, S. C., Lindsay, K., Moore, J. K., Mahowald, N., Randerson, J. T., Fung, I., Lamarque, J.-F., Feddema, J. J., and Lee, Y.-H.: Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: results from an atmosphere-ocean general circulation model, Biogeosciences, 6, 2099–2120, https://doi.org/10.5194/bg-6-2099-2009, 2009.
Tjoelker, M. G., Oleksyn, J., and Reich, P. B.: Modelling respiration of
vegetation: Evidence for a general temperature-dependent Q10, Glob. Chang.
Biol., 7, 223–230, https://doi.org/10.1046/j.1365-2486.2001.00397.x, 2001.
Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, 2016.
Viney, N. R., Bormann, H., Breuer, L., Bronstert, A., Croke, B. F. W., Frede, H., Gräff, T., Hubrechts, L., Huisman, J. A., Jakeman, A. J., Kite, G. W., Lanini, J., Leavesley, G., Lettenmaier, D. P., Lindström, G., Seibert, J., Sivapalan, M., and Willems, P.: Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: ensemble combinations and predictions, Adv. Water Resour., 32, 147–158, https://doi.org/10.1016/j.advwatres.2008.05.006, 2009.
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and Schewe, J.: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP): project framework, P. Natl. Acad. Sci. USA, 111, 3228–32, https://doi.org/10.1073/pnas.1312330110, 2014.
Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., Nozawa, T., Kawase, H., Abe, M., Yokohata, T., Ise, T., Sato, H., Kato, E., Takata, K., Emori, S., and Kawamiya, M.: MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments, Geosci. Model Dev., 4, 845–872, https://doi.org/10.5194/gmd-4-845-2011, 2011.
Wieder, W. R., Cleveland, C. C., Smith, W. K., and Todd-Brown, K. E. O.: Future productivity and carbon storage limited by terrestrial nutrient availability, Nat. Geosci., 8, 441–444, https://doi.org/10.1038/ngeo2413, 2015.
Williams, M., Schwarz, P. A., Law, B. E., Irvine, J., and Kurpius, M. R.: An improved analysis of forest carbon dynamics using data assimilation, Glob. Change Biol., 11, 89–105, https://doi.org/10.1111/j.1365-2486.2004.00891.x, 2005.
Woodward, F., Smith, T., and Emanuel, W.: A global land primary productivity and phytogeography model, Global Biogeochem. Cy., 9, 471–490, 1995.
Zhang, Q., Wang, Y. P., Pitman, A. J., and Dai, Y. J.: Limitations of
nitrogen and phosphorous on the terrestrial carbon uptake in the
20th century, Geophys. Res. Lett., 38, L22701, https://doi.org/10.1029/2011GL049244,
2011.
Zhang, Q., Wang, Y. P., Matear, R. J., Pitman, A. J., and Dai, Y. J.:
Nitrogen and phosphorous limitations significantly reduce future allowable
CO2 emissions, Geophys. Res. Lett., 41, 632–637,
https://doi.org/10.1002/2013GL058352, 2013.
Zhao, M. and Running, S. W.: Drought-induced reduction in global, Science,
329, 940–943, https://doi.org/10.1126/science.1192666, 2010 (data available at:
http://files.ntsg.umt.edu/data/NTSG_Products/MOD17/GeoTIFF/MOD17A3/,
last access: 17 August 2017).
Zhao, M., Heinsch, F. A., Nemani, R. R., and Running, S. W.: Improvements of
the MODIS terrestrial gross and net primary production global data set,
Remote Sens. Environ., 95, 164–176, https://doi.org/10.1016/j.rse.2004.12.011, 2005
(data available at:
http://files.ntsg.umt.edu/data/NTSG_Products/MOD17/GeoTIFF/MOD17A3/,
last access: 17 August 2017).
Short summary
We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
We use global observations of current terrestrial net primary productivity (NPP) to constrain...
Altmetrics
Final-revised paper
Preprint