Articles | Volume 11, issue 3
https://doi.org/10.5194/esd-11-641-2020
© Author(s) 2020. 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-11-641-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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24 Jul 2020
Research article | Highlight paper |
| 24 Jul 2020
| 24 Jul 2020
Impact of environmental changes and land management practices on wheat production in India
Shilpa Gahlot
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, 110016, India
Tzu-Shun Lin
Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
Atul K. Jain
Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, 110016, India
Vinay K. Sehgal
Department of Agricultural Physics, Indian Agricultural Research
Institute, New Delhi, 110012, India
Rajkumar Dhakar
Department of Agricultural Physics, Indian Agricultural Research
Institute, New Delhi, 110012, India
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Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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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
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Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Tanvi Gupta and Somnath Baidya Roy
Adv. Geosci., 56, 129–139, https://doi.org/10.5194/adgeo-56-129-2021, https://doi.org/10.5194/adgeo-56-129-2021, 2021
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In this paper we study how the momentum extracted by wind turbines get replenished so that the wind farm can continue to function. We use a numerical model to simulate the dynamics of a hypothetical coastal wind farm in the Arabian Sea under sea breeze conditions. Results show that vertical turbulent eddies can replenish more than half of the lost momentum, but horizontal advection also plays a role near the wind farm edges especially in sparsely packed wind farms.
Aheli Das and Somnath Baidya Roy
Adv. Geosci., 56, 89–96, https://doi.org/10.5194/adgeo-56-89-2021, https://doi.org/10.5194/adgeo-56-89-2021, 2021
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In this study we evaluated subseasonal-seasonal scale forecasts of solar radiation, wind speed, temperature and relative humidity over India from 6 global models by comparing against observations. Results show that the overall quality of the forecasts are not good. However, they demonstrate enough skill suggesting that further improvement through calibration may make then useful for the renewable energy sector.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Tanvi Gupta and Somnath Baidya Roy
Wind Energ. Sci., 6, 1089–1106, https://doi.org/10.5194/wes-6-1089-2021, https://doi.org/10.5194/wes-6-1089-2021, 2021
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Wind turbines extract momentum from atmospheric flow and convert that to electricity. This study explores recovery processes in wind farms that replenish the momentum so that wind farms can continue to function. Experiments with a numerical model show that momentum transport by turbulent eddies from above the wind turbines is the major contributor to recovery except for strong wind conditions and low wind turbine density, where horizontal advection can also play a major role.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Narender Kangari Reddy and Somnath Baidya Roy
Adv. Geosci., 54, 79–87, https://doi.org/10.5194/adgeo-54-79-2020, https://doi.org/10.5194/adgeo-54-79-2020, 2020
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In this study, we apply the Genetic Algorithm technique that mimics the natural selection process observed in nature to design optimal layouts for massive wind farms off the southeastern coast of India using real wind data. Our results show that layout optimization leads to large improvements in power generation (up to 28 %), efficiency (up to 34 %), and cost (up to 25 %) due to the reduction in wake losses.
Tzu-Shun Lin, Yang Song, Atul K. Jain, Peter Lawrence, and Haroon S. Kheshgi
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-68, https://doi.org/10.5194/bg-2020-68, 2020
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ISAM model was used to estimate soybean and maize crop yields over 1901–2100 driven by changes in environmental factors and management factors. Over the 20th century, each of these factors contributes to the increase in global crop yield with increasing nitrogen fertilizer application the strongest of these drivers for maize and increasing [CO2] the strongest for soybean. Over the 21st century, changing climate drives yield lower, while rising [CO2] drives yield higher for both crops.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
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Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
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
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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.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Emily Ane Dionizio, Marcos Heil Costa, Andrea D. de Almeida Castanho, Gabrielle Ferreira Pires, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Eddie Lenza, Fernando Martins Pimenta, Xiaojuan Yang, and Atul K. Jain
Biogeosciences, 15, 919–936, https://doi.org/10.5194/bg-15-919-2018, https://doi.org/10.5194/bg-15-919-2018, 2018
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Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon–Cerrado border, followed by nutrient limitation and interannual climate variability. Although we simulated more than 80 % of the variability of biomass in the transition zone, in many places the simulated biomass clearly does not match observations. The accurate representation of the transition is important for understanding the savannization of the Amazon.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
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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.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
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We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
Y. Song, A. K. Jain, and G. F. McIsaac
Biogeosciences, 10, 8039–8066, https://doi.org/10.5194/bg-10-8039-2013, https://doi.org/10.5194/bg-10-8039-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
S. Jha, V. K. Sehgal, R. Raghava, and M. Sinha
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-4-429-2013, https://doi.org/10.5194/esdd-4-429-2013, 2013
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X. Yang, W. M. Post, P. E. Thornton, and A. Jain
Biogeosciences, 10, 2525–2537, https://doi.org/10.5194/bg-10-2525-2013, https://doi.org/10.5194/bg-10-2525-2013, 2013
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Impacts of future agricultural change on ecosystem service indicators
Biogeophysical impacts of forestation in Europe: first results from the LUCAS (Land Use and Climate Across Scales) regional climate model intercomparison
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems
Different response of surface temperature and air temperature to deforestation in climate models
Changes in crop yields and their variability at different levels of global warming
A global assessment of gross and net land change dynamics for current conditions and future scenarios
Quantification of the impacts of climate change and human agricultural activities on oasis water requirements in an arid region: a case study of the Heihe River basin, China
Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era
Managing fire risk during drought: the influence of certification and El Niño on fire-driven forest conversion for oil palm in Southeast Asia
Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments
Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions
Continuous and consistent land use/cover change estimates using socio-ecological data
Vulnerability to climate change and adaptation strategies of local communities in Malawi: experiences of women fish-processing groups in the Lake Chilwa Basin
Deforestation in Amazonia impacts riverine carbon dynamics
Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework
Ocean–atmosphere interactions modulate irrigation's climate impacts
Impacts of land-use history on the recovery of ecosystems after agricultural abandonment
Actors and networks in resource conflict resolution under climate change in rural Kenya
Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, Canada
The role of spatial scale and background climate in the latitudinal temperature response to deforestation
Potential impact of climate and socioeconomic changes on future agricultural land use in West Africa
Implications of land use change in tropical northern Africa under global warming
Quantifying differences in land use emission estimates implied by definition discrepancies
Inter-annual and seasonal trends of vegetation condition in the Upper Blue Nile (Abay) Basin: dual-scale time series analysis
Local sources of global climate forcing from different categories of land use activities
Effects of climate variability on savannah fire regimes in West Africa
Sustainable management of river oases along the Tarim River (SuMaRiO) in Northwest China under conditions of climate change
Terminology as a key uncertainty in net land use and land cover change carbon flux estimates
Towards decision-based global land use models for improved understanding of the Earth system
Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa
The impact of nitrogen and phosphorous limitation on the estimated terrestrial carbon balance and warming of land use change over the last 156 yr
A theoretical framework for the net land-to-atmosphere CO2 flux and its implications in the definition of "emissions from land-use change"
Spatio-temporal analysis of the urban–rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy)
Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations
Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use
The influence of vegetation on the ITCZ and South Asian monsoon in HadCM3
Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 14, 629–667, https://doi.org/10.5194/esd-14-629-2023, https://doi.org/10.5194/esd-14-629-2023, 2023
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Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occur and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Marcus Breil, Felix Krawczyk, and Joaquim G. Pinto
Earth Syst. Dynam., 14, 243–253, https://doi.org/10.5194/esd-14-243-2023, https://doi.org/10.5194/esd-14-243-2023, 2023
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We provide evidence that biogeophysical effects of afforestation can counteract the favorable biogeochemical climate effect of reduced CO2 concentrations. By changing the land surface characteristics, afforestation reduces vegetation surface temperatures, resulting in a reduced outgoing longwave radiation in summer, although CO2 concentrations are reduced. Since forests additionally absorb a lot of solar radiation due to their dark surfaces, afforestation has a total warming effect.
Ana Bastos, Kerstin Hartung, Tobias B. Nützel, Julia E. M. S. Nabel, Richard A. Houghton, and Julia Pongratz
Earth Syst. Dynam., 12, 745–762, https://doi.org/10.5194/esd-12-745-2021, https://doi.org/10.5194/esd-12-745-2021, 2021
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Fluxes from land-use change and management (FLUC) are a large source of uncertainty in global and regional carbon budgets. Here, we evaluate the impact of different model parameterisations on FLUC. We show that carbon stock densities and allocation of carbon following transitions contribute more to uncertainty in FLUC than response-curve time constants. Uncertainty in FLUC could thus, in principle, be reduced by available Earth-observation data on carbon densities at a global scale.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
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Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Sam S. Rabin, Peter Alexander, Roslyn Henry, Peter Anthoni, Thomas A. M. Pugh, Mark Rounsevell, and Almut Arneth
Earth Syst. Dynam., 11, 357–376, https://doi.org/10.5194/esd-11-357-2020, https://doi.org/10.5194/esd-11-357-2020, 2020
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We modeled how agricultural performance and demand will shift as a result of climate change and population growth, and how the resulting adaptations will affect aspects of the Earth system upon which humanity depends. We found that the impacts of land use and management can have stronger impacts than climate change on some such
ecosystem services. The overall impacts are strongest in future scenarios with more severe climate change, high population growth, and/or resource-intensive lifestyles.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
Matias Heino, Joseph H. A. Guillaume, Christoph Müller, Toshichika Iizumi, and Matti Kummu
Earth Syst. Dynam., 11, 113–128, https://doi.org/10.5194/esd-11-113-2020, https://doi.org/10.5194/esd-11-113-2020, 2020
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In this study, we analyse the impacts of three major climate oscillations on global crop production. Our results show that maize, rice, soybean, and wheat yields are influenced by climate oscillations to a wide extent and in several important crop-producing regions. We observe larger impacts if crops are rainfed or fully fertilized, while irrigation tends to mitigate the impacts. These results can potentially help to increase the resilience of the global food system to climate-related shocks.
Johannes Winckler, Christian H. Reick, Sebastiaan Luyssaert, Alessandro Cescatti, Paul C. Stoy, Quentin Lejeune, Thomas Raddatz, Andreas Chlond, Marvin Heidkamp, and Julia Pongratz
Earth Syst. Dynam., 10, 473–484, https://doi.org/10.5194/esd-10-473-2019, https://doi.org/10.5194/esd-10-473-2019, 2019
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For local living conditions, it matters whether deforestation influences the surface temperature, temperature at 2 m, or the temperature higher up in the atmosphere. Here, simulations with a climate model show that at a location of deforestation, surface temperature generally changes more strongly than atmospheric temperature. Comparison across climate models shows that both for summer and winter the surface temperature response exceeds the air temperature response locally by a factor of 2.
Sebastian Ostberg, Jacob Schewe, Katelin Childers, and Katja Frieler
Earth Syst. Dynam., 9, 479–496, https://doi.org/10.5194/esd-9-479-2018, https://doi.org/10.5194/esd-9-479-2018, 2018
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It has been shown that regional temperature and precipitation changes in future climate change scenarios often scale quasi-linearly with global mean temperature change (∆GMT). We show that an important consequence of these physical climate changes, namely changes in agricultural crop yields, can also be described in terms of ∆GMT to a large extent. This makes it possible to efficiently estimate future crop yield changes for different climate change scenarios without need for complex models.
Richard Fuchs, Reinhard Prestele, and Peter H. Verburg
Earth Syst. Dynam., 9, 441–458, https://doi.org/10.5194/esd-9-441-2018, https://doi.org/10.5194/esd-9-441-2018, 2018
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We analysed current global land change dynamics based on high-resolution (30–100 m) remote sensing products. We integrated these empirical data into a future simulation model to assess global land change dynamics in the future (2000 to 2040). The consideration of empirically derived land change dynamics in future models led globally to ca. 50 % more land changes than currently assumed in state-of-the-art models. This impacts the results of other global change studies (e.g. climate change).
Xingran Liu and Yanjun Shen
Earth Syst. Dynam., 9, 211–225, https://doi.org/10.5194/esd-9-211-2018, https://doi.org/10.5194/esd-9-211-2018, 2018
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The impacts of climate change and human activities on oasis water requirements in Heihe River basin were quantified with the methods of partial derivative and slope in this study. The results showed that the oasis water requirement increased sharply from 10.8 × 108 to 19.0 × 108 m3 during 1986–2013. Human activities were the dominant driving forces. Changes in climate, land scale and structure contributed to the increase in water requirement at rates of 6.9, 58.1, and 25.3 %, respectively.
Ben Parkes, Dimitri Defrance, Benjamin Sultan, Philippe Ciais, and Xuhui Wang
Earth Syst. Dynam., 9, 119–134, https://doi.org/10.5194/esd-9-119-2018, https://doi.org/10.5194/esd-9-119-2018, 2018
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We present an analysis of three crops in West Africa and their response to short-term climate change in a world where temperatures are 1.5 °C above the preindustrial levels. We show that the number of crop failures for all crops is due to increase in the future climate. We further show the difference in yield change across several West African countries and show that the yields are not expected to increase fast enough to prevent food shortages.
Praveen Noojipady, Douglas C. Morton, Wilfrid Schroeder, Kimberly M. Carlson, Chengquan Huang, Holly K. Gibbs, David Burns, Nathalie F. Walker, and Stephen D. Prince
Earth Syst. Dynam., 8, 749–771, https://doi.org/10.5194/esd-8-749-2017, https://doi.org/10.5194/esd-8-749-2017, 2017
Reinhard Prestele, Almut Arneth, Alberte Bondeau, Nathalie de Noblet-Ducoudré, Thomas A. M. Pugh, Stephen Sitch, Elke Stehfest, and Peter H. Verburg
Earth Syst. Dynam., 8, 369–386, https://doi.org/10.5194/esd-8-369-2017, https://doi.org/10.5194/esd-8-369-2017, 2017
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Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models. We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use–climate interactions and feedback.
Anita D. Bayer, Mats Lindeskog, Thomas A. M. Pugh, Peter M. Anthoni, Richard Fuchs, and Almut Arneth
Earth Syst. Dynam., 8, 91–111, https://doi.org/10.5194/esd-8-91-2017, https://doi.org/10.5194/esd-8-91-2017, 2017
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We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model. Different historical reconstructions yielded an uncertainty of ca. ±30 % in the mean annual land use emission over the last decades. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level (tropical shifting cultivation) substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017, https://doi.org/10.5194/esd-8-55-2017, 2017
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The transition of land from one cover type to another can adversely affect the Earth system. A growing body of research aims to map these transitions in space and time to better understand the impacts. Here we develop a statistical model that is parameterized by socio-ecological geospatial data and extensive aerial/ground surveys to visualize and interpret these transitions on an annual basis for 30 years in Kenya. Future work will use this method to project land suitability across Africa.
Hanne Jørstad and Christian Webersik
Earth Syst. Dynam., 7, 977–989, https://doi.org/10.5194/esd-7-977-2016, https://doi.org/10.5194/esd-7-977-2016, 2016
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This research is about climate change adaptation. It demonstrates how adaptation to climate change can avoid social tensions if done in a sustainable way. Evidence is drawn from Malawi in southern Africa.
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
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Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
Kerstin Engström, Stefan Olin, Mark D. A. Rounsevell, Sara Brogaard, Detlef P. van Vuuren, Peter Alexander, Dave Murray-Rust, and Almut Arneth
Earth Syst. Dynam., 7, 893–915, https://doi.org/10.5194/esd-7-893-2016, https://doi.org/10.5194/esd-7-893-2016, 2016
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The development of global cropland in the future depends on how many people there will be, how much meat and milk we will eat, how much food we will waste and how well farms will be managed. Uncertainties in these factors mean that global cropland could decrease from today's 1500 Mha to only 893 Mha in 2100, which would free land for biofuel production. However, if population rises towards 12 billion and global yields remain low, global cropland could also increase up to 2380 Mha in 2100.
Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, and Larissa Nazarenko
Earth Syst. Dynam., 7, 863–876, https://doi.org/10.5194/esd-7-863-2016, https://doi.org/10.5194/esd-7-863-2016, 2016
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We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
Andreas Krause, Thomas A. M. Pugh, Anita D. Bayer, Mats Lindeskog, and Almut Arneth
Earth Syst. Dynam., 7, 745–766, https://doi.org/10.5194/esd-7-745-2016, https://doi.org/10.5194/esd-7-745-2016, 2016
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We used a vegetation model to study the legacy effects of different land-use histories on ecosystem recovery in a range of environmental conditions. We found that recovery trajectories are crucially influenced by type and duration of former agricultural land use, especially for soil carbon. Spatially, we found the greatest sensitivity to land-use history in boreal forests and subtropical grasslands. These results are relevant for measurements, climate modeling and afforestation projects.
Grace W. Ngaruiya and Jürgen Scheffran
Earth Syst. Dynam., 7, 441–452, https://doi.org/10.5194/esd-7-441-2016, https://doi.org/10.5194/esd-7-441-2016, 2016
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Climate change complicates rural conflict resolution dynamics and institutions. There is urgent need for conflict-sensitive adaptation in Africa. The study of social network data reveals three forms of fused conflict resolution arrangements in Loitoktok, Kenya. Where, extension officers, council of elders, local chiefs and private investors are potential conduits of knowledge. Efficiency of rural conflict resolution can be enhanced by diversification in conflict resolution actors and networks.
Daniel Paradis, Harold Vigneault, René Lefebvre, Martine M. Savard, Jean-Marc Ballard, and Budong Qian
Earth Syst. Dynam., 7, 183–202, https://doi.org/10.5194/esd-7-183-2016, https://doi.org/10.5194/esd-7-183-2016, 2016
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According to groundwater flow and mass transport simulations, nitrate concentration for year 2050 would increase mainly due to the attainment of equilibrium conditions of the aquifer system related to actual nitrogen loadings, and to the increase in nitrogen loadings due to changes in agricultural practices. Impact of climate change on the groundwater recharge would contribute only slightly to that increase.
Yan Li, Nathalie De Noblet-Ducoudré, Edouard L. Davin, Safa Motesharrei, Ning Zeng, Shuangcheng Li, and Eugenia Kalnay
Earth Syst. Dynam., 7, 167–181, https://doi.org/10.5194/esd-7-167-2016, https://doi.org/10.5194/esd-7-167-2016, 2016
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The impact of deforestation is to warm the tropics and cool the extratropics, and the magnitude of the impact depends on the spatial extent and the degree of forest loss. That also means location matters for the impact of deforestation on temperature because such an impact is largely determined by the climate condition of that region. For example, under dry and wet conditions, deforestation can have quite different climate impacts.
Kazi Farzan Ahmed, Guiling Wang, Liangzhi You, and Miao Yu
Earth Syst. Dynam., 7, 151–165, https://doi.org/10.5194/esd-7-151-2016, https://doi.org/10.5194/esd-7-151-2016, 2016
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A prototype model LandPro was developed to study climate change impact on land use in West Africa. LandPro considers climate and socioeconomic factors in projecting anthropogenic future land use change (LULCC). The model projections reflect that relative impact of climate change on LULCC in West Africa is region dependent. Results from scenario analysis suggest that science-informed decision-making by the farmers in agricultural land use can potentially reduce crop area expansion in the region.
T. Brücher, M. Claussen, and T. Raddatz
Earth Syst. Dynam., 6, 769–780, https://doi.org/10.5194/esd-6-769-2015, https://doi.org/10.5194/esd-6-769-2015, 2015
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A major link between climate and humans in northern Africa, and the Sahel in particular, is land use. We assess possible feedbacks between the type of land use and harvest intensity and climate by analysing a series of idealized GCM experiments using the MPI-ESM. Our study suggests marginal feedback between land use changes and climate changes triggered by strong greenhouse gas emissions.
B. D. Stocker and F. Joos
Earth Syst. Dynam., 6, 731–744, https://doi.org/10.5194/esd-6-731-2015, https://doi.org/10.5194/esd-6-731-2015, 2015
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Estimates for land use change CO2 emissions (eLUC) rely on different approaches, implying conceptual differences of what eLUC represents. We use an Earth System Model and quantify differences between two commonly applied methods to be ~20% for historical eLUC but increasing under a future scenario. We decompose eLUC into component fluxes, quantify them, and discuss best practices for global carbon budget accountings and model-data intercomparisons relying on different methods to estimate eLUC.
E. Teferi, S. Uhlenbrook, and W. Bewket
Earth Syst. Dynam., 6, 617–636, https://doi.org/10.5194/esd-6-617-2015, https://doi.org/10.5194/esd-6-617-2015, 2015
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This study concludes that integrated analysis of course and fine-scale, inter-annual and intra-annual trends enables a more robust identification of changes in vegetation condition. Seasonal trend analysis was found to be very useful in identifying changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis were performed. The finer-scale intra-annual trend analysis revealed trends that were more linked to human activities.
D. S. Ward and N. M. Mahowald
Earth Syst. Dynam., 6, 175–194, https://doi.org/10.5194/esd-6-175-2015, https://doi.org/10.5194/esd-6-175-2015, 2015
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The radiative forcing of land use and land cover change activities has recently been computed for a set of forcing agents including long-lived greenhouse gases, short-lived agents (ozone and aerosols), and land surface albedo change. Here we address where the global forcing comes from and what land use activities, such as deforestation or agriculture, contribute the most forcing. We find that changes in forest and crop area can be used to predict the land use radiative forcing in some regions.
E. T. N'Datchoh, A. Konaré, A. Diedhiou, A. Diawara, E. Quansah, and P. Assamoi
Earth Syst. Dynam., 6, 161–174, https://doi.org/10.5194/esd-6-161-2015, https://doi.org/10.5194/esd-6-161-2015, 2015
C. Rumbaur, N. Thevs, M. Disse, M. Ahlheim, A. Brieden, B. Cyffka, D. Duethmann, T. Feike, O. Frör, P. Gärtner, Ü. Halik, J. Hill, M. Hinnenthal, P. Keilholz, B. Kleinschmit, V. Krysanova, M. Kuba, S. Mader, C. Menz, H. Othmanli, S. Pelz, M. Schroeder, T. F. Siew, V. Stender, K. Stahr, F. M. Thomas, M. Welp, M. Wortmann, X. Zhao, X. Chen, T. Jiang, J. Luo, H. Yimit, R. Yu, X. Zhang, and C. Zhao
Earth Syst. Dynam., 6, 83–107, https://doi.org/10.5194/esd-6-83-2015, https://doi.org/10.5194/esd-6-83-2015, 2015
J. Pongratz, C. H. Reick, R. A. Houghton, and J. I. House
Earth Syst. Dynam., 5, 177–195, https://doi.org/10.5194/esd-5-177-2014, https://doi.org/10.5194/esd-5-177-2014, 2014
M. D. A. Rounsevell, A. Arneth, P. Alexander, D. G. Brown, N. de Noblet-Ducoudré, E. Ellis, J. Finnigan, K. Galvin, N. Grigg, I. Harman, J. Lennox, N. Magliocca, D. Parker, B. C. O'Neill, P. H. Verburg, and O. Young
Earth Syst. Dynam., 5, 117–137, https://doi.org/10.5194/esd-5-117-2014, https://doi.org/10.5194/esd-5-117-2014, 2014
M. Lindeskog, A. Arneth, A. Bondeau, K. Waha, J. Seaquist, S. Olin, and B. Smith
Earth Syst. Dynam., 4, 385–407, https://doi.org/10.5194/esd-4-385-2013, https://doi.org/10.5194/esd-4-385-2013, 2013
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
T. Gasser and P. Ciais
Earth Syst. Dynam., 4, 171–186, https://doi.org/10.5194/esd-4-171-2013, https://doi.org/10.5194/esd-4-171-2013, 2013
G. Modica, M. Vizzari, M. Pollino, C. R. Fichera, P. Zoccali, and S. Di Fazio
Earth Syst. Dynam., 3, 263–279, https://doi.org/10.5194/esd-3-263-2012, https://doi.org/10.5194/esd-3-263-2012, 2012
A. J. Pitman, N. de Noblet-Ducoudré, F. B. Avila, L. V. Alexander, J.-P. Boisier, V. Brovkin, C. Delire, F. Cruz, M. G. Donat, V. Gayler, B. van den Hurk, C. Reick, and A. Voldoire
Earth Syst. Dynam., 3, 213–231, https://doi.org/10.5194/esd-3-213-2012, https://doi.org/10.5194/esd-3-213-2012, 2012
M. Cerreta and P. De Toro
Earth Syst. Dynam., 3, 157–171, https://doi.org/10.5194/esd-3-157-2012, https://doi.org/10.5194/esd-3-157-2012, 2012
M. P. McCarthy, J. Sanjay, B. B. B. Booth, K. Krishna Kumar, and R. A. Betts
Earth Syst. Dynam., 3, 87–96, https://doi.org/10.5194/esd-3-87-2012, https://doi.org/10.5194/esd-3-87-2012, 2012
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Short summary
Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing environmental and management factors. Using a new spring wheat model, we find that over the 1980–2016 period elevated CO2 levels, irrigation, and nitrogen fertilizers led to an increase of 30 %, 12 %, and 15 % in countrywide production, respectively. In contrast, rising temperatures have reduced production by 18 %. These effects vary across the country, thereby affecting production at regional scales.
Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing...
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