Articles | Volume 12, issue 2
https://doi.org/10.5194/esd-12-367-2021
© Author(s) 2021. 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-12-367-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
14 Apr 2021
Research article | Highlight paper |
| 14 Apr 2021
| 14 Apr 2021
Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP6 models
Anja Katzenberger
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Department of Geography, Ludwig Maximilian University, Munich, Germany
Jacob Schewe
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Julia Pongratz
Department of Geography, Ludwig Maximilian University, Munich, Germany
Max Planck Institute for Meteorology, Hamburg, Germany
Anders Levermann
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research, Potsdam, Germany
LDEO, Columbia University, New York, NY, USA
Institute of Physics and Astronomy, Potsdam University, Potsdam, Germany
Related authors
Anja Katzenberger and Anders Levermann
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-40, https://doi.org/10.5194/esd-2024-40, 2025
Manuscript not accepted for further review
Short summary
Short summary
There is an ongoing societal discussion about speeding up the transition to net-zero carbon emissions. The faster emissions are reduced, the less carbon dioxide will accumulate in the atmosphere determining the level of global warming. In this study, we run simulations with an atmosphere model with different CO2 forcing rates to investigate whether the pace of the emissions itself (in addition to the resulting concentration) significantly influences climate and weather.
Anja Katzenberger and Anders Levermann
Earth Syst. Dynam., 15, 1137–1151, https://doi.org/10.5194/esd-15-1137-2024, https://doi.org/10.5194/esd-15-1137-2024, 2024
Short summary
Short summary
A fifth of the world's population lives in eastern China, whose climate is dominated by the East Asian Summer Monsoon (EASM). Therefore, it is important to know how the EASM will change under global warming. Here, we use the data of 34 climate models of the latest generation to understand how the EASM will change throughout the 21st century. The models project that the EASM will intensify and that variability between years will increase associated with an increase in extremely wet seasons.
Olivier Bouriaud, Ernst-Detlef Schulze, Konstantin Gregor, Issam Boukhris, Peter Högberg, Roland Irslinger, Phillip Papastefanou, Julia Pongratz, Anja Rammig, Riccardo Valentini, and Christian Körner
Biogeosciences, 22, 4729–4741, https://doi.org/10.5194/bg-22-4729-2025, https://doi.org/10.5194/bg-22-4729-2025, 2025
Short summary
Short summary
The impact of harvesting on forests' carbon sink capacities is debated. One view is that their sink strength is resilient to harvesting, and the other is that it disrupts these capacities. Our work shows that leaf area index (LAI) has been overlooked in this discussion. We found that temperate forests' carbon uptake is largely insensitive to variations in LAI beyond 4.5 m² m-² but that forests operate at higher levels.
Ida Bagus Mandhara Brasika, Pierre Friedlingstein, Stephen Sitch, Michael O'Sullivan, Maria Carolina Duran-Rojas, Thais Michele Rosan, Kees Klein Goldewijk, Julia Pongratz, Clemens Schwingshackl, Louise P. Chini, and George C. Hurtt
Biogeosciences, 22, 3547–3561, https://doi.org/10.5194/bg-22-3547-2025, https://doi.org/10.5194/bg-22-3547-2025, 2025
Short summary
Short summary
Indonesia is the world's third-highest carbon emitter from land use change. However, there are uncertainties in the carbon emissions of Indonesia. Our best estimate of carbon emissions from land use change in Indonesia is 0.12 ± 0.02 PgC/yr with a steady trend. Despite many uncertainties created by drivers, models, and products, we also found robust agreements between these models and products. All agree that Indonesian carbon emissions from LULCC (land use and land cover change) have had no decreasing trend for the last 2 decades.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
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.
Katja Frieler, Stefan Lange, Jacob Schewe, Matthias Mengel, Simon Treu, Christian Otto, Jan Volkholz, Christopher P. O. Reyer, Stefanie Heinicke, Colin Jones, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Ryan Heneghan, Derek P. Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Dánnell Quesada Chacón, Kerry Emanuel, Chia-Ying Lee, Suzana J. Camargo, Jonas Jägermeyr, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Lisa Novak, Inga J. Sauer, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, Michel Bechtold, Robert Reinecke, Inge de Graaf, Jed O. Kaplan, Alexander Koch, and Matthieu Lengaigne
EGUsphere, https://doi.org/10.5194/egusphere-2025-2103, https://doi.org/10.5194/egusphere-2025-2103, 2025
Short summary
Short summary
This paper describes the experiments and data sets necessary to run historic and future impact projections, and the underlying assumptions of future climate change as defined by the 3rd round of the ISIMIP Project (Inter-sectoral Impactmodel Intercomparison Project, isimip.org). ISIMIP provides a framework for cross-sectorally consistent climate impact simulations to contribute to a comprehensive and consistent picture of the world under different climate-change scenarios.
Suqi Guo, Felix Havermann, Steven J. De Hertog, Fei Luo, Iris Manola, Thomas Raddatz, Hongmei Li, Wim Thiery, Quentin Lejeune, Carl-Friedrich Schleussner, David Wårlind, Lars Nieradzik, and Julia Pongratz
Earth Syst. Dynam., 16, 631–666, https://doi.org/10.5194/esd-16-631-2025, https://doi.org/10.5194/esd-16-631-2025, 2025
Short summary
Short summary
Land cover and land management changes (LCLMCs) can alter climate even in intact areas, causing carbon changes in remote areas. This study is the first to assess these effects, finding they substantially alter global carbon dynamics, changing terrestrial stocks by up to dozens of gigatonnes. These results are vital for scientific and policy assessments, given the expected role of LCLMCs in achieving the Paris Agreement's goal to limit global warming below 1.5 °C.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-188, https://doi.org/10.5194/essd-2025-188, 2025
Preprint under review for ESSD
Short summary
Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
Robert Reinecke, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
EGUsphere, https://doi.org/10.5194/egusphere-2025-1181, https://doi.org/10.5194/egusphere-2025-1181, 2025
Short summary
Short summary
Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
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.
Anja Katzenberger and Anders Levermann
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-40, https://doi.org/10.5194/esd-2024-40, 2025
Manuscript not accepted for further review
Short summary
Short summary
There is an ongoing societal discussion about speeding up the transition to net-zero carbon emissions. The faster emissions are reduced, the less carbon dioxide will accumulate in the atmosphere determining the level of global warming. In this study, we run simulations with an atmosphere model with different CO2 forcing rates to investigate whether the pace of the emissions itself (in addition to the resulting concentration) significantly influences climate and weather.
Sabine Egerer, Stefanie Falk, Dorothea Mayer, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Biogeosciences, 21, 5005–5025, https://doi.org/10.5194/bg-21-5005-2024, https://doi.org/10.5194/bg-21-5005-2024, 2024
Short summary
Short summary
Using a state-of-the-art land model, we find that bioenergy plants can store carbon more efficiently than forests over long periods in the soil, in geological reservoirs, or by substituting fossil-fuel-based energy. Planting forests is more suitable for reaching climate targets by 2050. The carbon removal potential depends also on local environmental conditions. These considerations have important implications for climate policy, spatial planning, nature conservation, and agriculture.
Johannes Feldmann, Anders Levermann, and Ricarda Winkelmann
The Cryosphere, 18, 4011–4028, https://doi.org/10.5194/tc-18-4011-2024, https://doi.org/10.5194/tc-18-4011-2024, 2024
Short summary
Short summary
Here we show in simplified simulations that the (ir)reversibility of the retreat of instability-prone, Antarctica-type glaciers can strongly depend on the depth of the bed depression they rest on. If it is sufficiently deep, then the destabilized glacier does not recover from its collapsed state. Our results suggest that glaciers resting on a wide and deep bed depression, such as Antarctica's Thwaites Glacier, are particularly susceptible to irreversible retreat.
Anja Katzenberger and Anders Levermann
Earth Syst. Dynam., 15, 1137–1151, https://doi.org/10.5194/esd-15-1137-2024, https://doi.org/10.5194/esd-15-1137-2024, 2024
Short summary
Short summary
A fifth of the world's population lives in eastern China, whose climate is dominated by the East Asian Summer Monsoon (EASM). Therefore, it is important to know how the EASM will change under global warming. Here, we use the data of 34 climate models of the latest generation to understand how the EASM will change throughout the 21st century. The models project that the EASM will intensify and that variability between years will increase associated with an increase in extremely wet seasons.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Biogeosciences, 21, 1923–1960, https://doi.org/10.5194/bg-21-1923-2024, https://doi.org/10.5194/bg-21-1923-2024, 2024
Short summary
Short summary
We study the timescale dependence of airborne fraction and underlying feedbacks by a theory of the climate–carbon system. Using simulations we show the predictive power of this theory and find that (1) this fraction generally decreases for increasing timescales and (2) at all timescales the total feedback is negative and the model spread in a single feedback causes the spread in the airborne fraction. Our study indicates that those are properties of the system, independently of the scenario.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 15, 265–291, https://doi.org/10.5194/esd-15-265-2024, https://doi.org/10.5194/esd-15-265-2024, 2024
Short summary
Short summary
Changes in land use are crucial to achieve lower global warming. However, despite their importance, the effects of these changes on moisture fluxes are poorly understood. We analyse land cover and management scenarios in three climate models involving cropland expansion, afforestation, and irrigation. Results show largely consistent influences on moisture fluxes, with cropland expansion causing a drying and reduced local moisture recycling, while afforestation and irrigation show the opposite.
Wolfgang Alexander Obermeier, Clemens Schwingshackl, Ana Bastos, Giulia Conchedda, Thomas Gasser, Giacomo Grassi, Richard A. Houghton, Francesco Nicola Tubiello, Stephen Sitch, and Julia Pongratz
Earth Syst. Sci. Data, 16, 605–645, https://doi.org/10.5194/essd-16-605-2024, https://doi.org/10.5194/essd-16-605-2024, 2024
Short summary
Short summary
We provide and compare country-level estimates of land-use CO2 fluxes from a variety and large number of models, bottom-up estimates, and country reports for the period 1950–2021. Although net fluxes are small in many countries, they are often composed of large compensating emissions and removals. In many countries, the estimates agree well once their individual characteristics are accounted for, but in other countries, including some of the largest emitters, substantial uncertainties exist.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
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.
Benedikt Mester, Thomas Vogt, Seth Bryant, Christian Otto, Katja Frieler, and Jacob Schewe
Nat. Hazards Earth Syst. Sci., 23, 3467–3485, https://doi.org/10.5194/nhess-23-3467-2023, https://doi.org/10.5194/nhess-23-3467-2023, 2023
Short summary
Short summary
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use coastal flood modeling and satellite imagery to construct a counterfactual cyclone event without the effects of climate change. We show that 12 600–14 900 displacements can be attributed to sea level rise and the intensification of storm wind speeds due to global warming. Our impact attribution study is the first one on human displacement and one of very few for a low-income country.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
Short summary
Short summary
Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
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
Short summary
Short summary
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.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2023-953, https://doi.org/10.5194/egusphere-2023-953, 2023
Preprint archived
Short summary
Short summary
Land cover and management changes can affect the climate and water availability. In this study we use climate model simulations of extreme global land cover changes (afforestation, deforestation) and land management changes (irrigation) to understand the effects on the global water cycle and local to continental water availability. We show that cropland expansion generally leads to higher evaporation and lower amounts of precipitation and afforestation and irrigation expansion to the opposite.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
Short summary
Short summary
Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Hongmei Li, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz
Earth Syst. Dynam., 14, 101–119, https://doi.org/10.5194/esd-14-101-2023, https://doi.org/10.5194/esd-14-101-2023, 2023
Short summary
Short summary
For the first time, our decadal prediction system based on Max Planck Institute Earth System Model enables prognostic atmospheric CO2 with an interactive carbon cycle. The evolution of CO2 fluxes and atmospheric CO2 growth is reconstructed well by assimilating data products; retrospective predictions show high confidence in predicting changes in the next year. The Earth system predictions provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.
Johannes Feldmann and Anders Levermann
The Cryosphere, 17, 327–348, https://doi.org/10.5194/tc-17-327-2023, https://doi.org/10.5194/tc-17-327-2023, 2023
Short summary
Short summary
Here we present a scaling relation that allows the comparison of the timescales of glaciers with geometric similarity. According to the relation, thicker and wider glaciers on a steeper bed slope have a much faster timescale than shallower, narrower glaciers on a flatter bed slope. The relation is supported by observations and simplified numerical simulations. We combine the scaling relation with a statistical analysis of the topography of 13 instability-prone Antarctic outlet glaciers.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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., 13, 1305–1350, https://doi.org/10.5194/esd-13-1305-2022, https://doi.org/10.5194/esd-13-1305-2022, 2022
Short summary
Short summary
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 occurs and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Tanja Schlemm, Johannes Feldmann, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 16, 1979–1996, https://doi.org/10.5194/tc-16-1979-2022, https://doi.org/10.5194/tc-16-1979-2022, 2022
Short summary
Short summary
Marine cliff instability, if it exists, could dominate Antarctica's contribution to future sea-level rise. It is likely to speed up with ice thickness and thus would accelerate in most parts of Antarctica. Here, we investigate a possible mechanism that might stop cliff instability through cloaking by ice mélange. It is only a first step, but it shows that embayment geometry is, in principle, able to stop marine cliff instability in most parts of West Antarctica.
Johannes Feldmann, Ronja Reese, Ricarda Winkelmann, and Anders Levermann
The Cryosphere, 16, 1927–1940, https://doi.org/10.5194/tc-16-1927-2022, https://doi.org/10.5194/tc-16-1927-2022, 2022
Short summary
Short summary
We use a numerical model to simulate the flow of a simplified, buttressed Antarctic-type outlet glacier with an attached ice shelf. We find that after a few years of perturbation such a glacier responds much stronger to melting under the ice-shelf shear margins than to melting in the central fast streaming part of the ice shelf. This study explains the underlying physical mechanism which might gain importance in the future if melt rates under the Antarctic ice shelves continue to increase.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
Short summary
Short summary
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.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
Short summary
Short summary
We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
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
Short summary
Short summary
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.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
Short summary
Short summary
Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Nonlin. Processes Geophys., 28, 501–532, https://doi.org/10.5194/npg-28-501-2021, https://doi.org/10.5194/npg-28-501-2021, 2021
Short summary
Short summary
Linear response functions are a powerful tool to both predict and investigate the dynamics of a system when subjected to small perturbations. In practice, these functions must often be derived from perturbation experiment data. Nevertheless, current methods for this identification require a tailored perturbation experiment, often with many realizations. We present a method that instead derives these functions from a single realization of an experiment driven by any type of perturbation.
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Nonlin. Processes Geophys., 28, 533–564, https://doi.org/10.5194/npg-28-533-2021, https://doi.org/10.5194/npg-28-533-2021, 2021
Short summary
Short summary
We apply a new identification method to derive the response functions that characterize the sensitivity of the land carbon cycle to CO2 perturbations in an Earth system model. By means of these response functions, which generalize the usually employed single-valued sensitivities, we can reliably predict the response of the land carbon to weak perturbations. Further, we demonstrate how by this new method one can robustly derive and interpret internal spectra of timescales of the system.
Louise Chini, George Hurtt, Ritvik Sahajpal, Steve Frolking, Kees Klein Goldewijk, Stephen Sitch, Raphael Ganzenmüller, Lei Ma, Lesley Ott, Julia Pongratz, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 4175–4189, https://doi.org/10.5194/essd-13-4175-2021, https://doi.org/10.5194/essd-13-4175-2021, 2021
Short summary
Short summary
Carbon emissions from land-use change are a large and uncertain component of the global carbon cycle. The Land-Use Harmonization 2 (LUH2) dataset was developed as an input to carbon and climate simulations and has been updated annually for the Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2 updates and describe the 2019 version which used new cropland and grazing land data inputs for the globally important region of Brazil.
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
Short summary
Short summary
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.
Kerstin Hartung, Ana Bastos, Louise Chini, Raphael Ganzenmüller, Felix Havermann, George C. Hurtt, Tammas Loughran, Julia E. M. S. Nabel, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Earth Syst. Dynam., 12, 763–782, https://doi.org/10.5194/esd-12-763-2021, https://doi.org/10.5194/esd-12-763-2021, 2021
Short summary
Short summary
In this study, we model the relative importance of several contributors to the land-use and land-cover change (LULCC) flux based on a LULCC dataset including uncertainty estimates. The uncertainty of LULCC is as relevant as applying wood harvest and gross transitions for the cumulative LULCC flux over the industrial period. However, LULCC uncertainty matters less than the other two factors for the LULCC flux in 2014; historical LULCC uncertainty is negligible for estimates of future scenarios.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
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
Short summary
Short summary
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.
Tanja Schlemm and Anders Levermann
The Cryosphere, 15, 531–545, https://doi.org/10.5194/tc-15-531-2021, https://doi.org/10.5194/tc-15-531-2021, 2021
Short summary
Short summary
Ice loss from Greenland and Antarctica is often cloaked by a mélange of icebergs and sea ice. Here we provide a simple method to parametrize the resulting back stress on the ice flow for large-scale projection 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
Short summary
Short summary
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.
Lena R. Boysen, Victor Brovkin, Julia Pongratz, David M. Lawrence, Peter Lawrence, Nicolas Vuichard, Philippe Peylin, Spencer Liddicoat, Tomohiro Hajima, Yanwu Zhang, Matthias Rocher, Christine Delire, Roland Séférian, Vivek K. Arora, Lars Nieradzik, Peter Anthoni, Wim Thiery, Marysa M. Laguë, Deborah Lawrence, and Min-Hui Lo
Biogeosciences, 17, 5615–5638, https://doi.org/10.5194/bg-17-5615-2020, https://doi.org/10.5194/bg-17-5615-2020, 2020
Short summary
Short summary
We find a biogeophysically induced global cooling with strong carbon losses in a 20 million square kilometre idealized deforestation experiment performed by nine CMIP6 Earth system models. It takes many decades for the temperature signal to emerge, with non-local effects playing an important role. Despite a consistent experimental setup, models diverge substantially in their climate responses. This study offers unprecedented insights for understanding land use change effects in CMIP6 models.
Maria Zeitz, Anders Levermann, and Ricarda Winkelmann
The Cryosphere, 14, 3537–3550, https://doi.org/10.5194/tc-14-3537-2020, https://doi.org/10.5194/tc-14-3537-2020, 2020
Short summary
Short summary
The flow of ice drives mass losses in the large ice sheets. Sea-level rise projections rely on ice-sheet models, solving the physics of ice flow and melt. Unfortunately the parameters in the physics of flow are uncertain. Here we show, in an idealized setup, that these uncertainties can double flow-driven mass losses within the possible range of parameters. It is possible that this uncertainty carries over to realistic sea-level rise projections.
Ronja Reese, Anders Levermann, Torsten Albrecht, Hélène Seroussi, and Ricarda Winkelmann
The Cryosphere, 14, 3097–3110, https://doi.org/10.5194/tc-14-3097-2020, https://doi.org/10.5194/tc-14-3097-2020, 2020
Short summary
Short summary
We compare 21st century projections of Antarctica's future sea-level contribution simulated with the Parallel Ice Sheet Model submitted to ISMIP6 with projections following the LARMIP-2 protocol based on the same model configuration. We find that (1) a preceding historic simulation increases mass loss by 5–50 % and that (2) the order of magnitude difference in the ice loss in our experiments following the two protocols can be explained by the translation of ocean forcing to sub-shelf melting.
Cited articles
Acharya, P. and Sreekesh, S.: Seasonal variability in aerosol optical depth
over India: a spatio-temporal analysis using the MODIS aerosol product,
Int. J. Remote Sens., 34, 4832–4849, https://doi.org/10.1080/01431161.2013.782114, 2013. a
Allan, R., Barlow, M., Byrne, M. P., Cherchi, A., Douville, H., Fowler, H. J., Gan, T. Y., Pendergrass, A. G., Rosenfeld, D., Swann, A. L., Wilcox, L. J., and Zolina, O.: Advances in understanding large-scale responses of the water cycle to climate change, Ann. NY. Acad. Sci., 1472, 1–27, https://doi.org/10.1111/nyas.14337, 2020. a
Asharaf, S. and Ahrens, B.: Indian summer monsoon rainfall processes in climate change scenarios, J. Climate, 28, 5414–5429,
https://doi.org/10.1175/JCLI-D-14-00233.1, 2015. a
Ashfaq, M., Rastogi, D., Mei, R., Touma, D., and Leung, L. R.: Sources of
errors in the simulation of south Asian summer monsoon in the CMIP5 GCMs,
Clim. Dynam., 49, 193–223, https://doi.org/10.1007/s00382-016-3337-7, 2017. a
Azad, S. and Rajeevan, M.: Possible shift in the ENSO-Indian monsoon rainfall
relationship under future global warming, Scient. Rep., 6, 20145,
https://doi.org/10.1038/srep20145, 2016. a
Bollasina, M. A.: Hydrology: Probing the monsoon pulse, Nature Clim. Change, 4, 422–423, https://doi.org/10.1038/nclimate2243, 2014. a
Bollasina, M. A., Ming, Y., and Ramaswamy, V.: Anthropogenic aerosols and the
weakening of the South Asian summer monsoon, Science, 334, 502–505,
https://doi.org/10.1126/science.1204994, 2011. a
Boos, W. R. and Korty, R. L.: Regional energy budget control of the
intertropical convergence zone and application to mid-Holocene rainfall, Nat. Geosci., 9, 892–897, https://doi.org/10.1038/ngeo2833, 2016. a
Byrne, M. P. and Schneider, T.: Narrowing of the ITCZ in a warming climate:
Physical mechanisms, Geophys. Res. Lett., 43, 11–350, https://doi.org/10.1002/2016GL070396, 2016. a
CDS: Near surface meteorological variables from 1979 to 2018 derived from bias-corrected reanalysis, https://doi.org/10.24381/cds.20d54e34, 2021 a
Cherchi, A., Alessandri, A., Masina, S., and Navarra, A.: Effects of increased CO2 levels on monsoons, Clim. Dynam., 37, 83–101,
https://doi.org/10.1007/s00382-010-0801-7, 2011. a
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S.,
Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted
ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12,
2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020. a, b
D'Agostino, R., Bader, J., Bordoni, S., Ferreira, D., and Jungclaus, J.:
Northern Hemisphere Monsoon Response to Mid-Holocene Orbital Forcing and
Greenhouse Gas-Induced Global Warming, Geophys. Res. Lett., 46, 1591–1601, https://doi.org/10.1029/2018GL081589, 2019. a, b, c, d
Dai, A., Li, H., Sun, Y., Hong, L.-C., Chou, C., and Zhou, T.: The relative
roles of upper and lower tropospheric thermal contrasts and tropical
influences in driving Asian summer monsoons, J. Geophys. Res.-Atmos., 118, 7024–7045, https://doi.org/10.1002/jgrd.50565, 2013. a
Danielsen, E. F.: In situ evidence of rapid, vertical, irreversible transport
of lower tropospheric air into the lower tropical stratosphere by convective
cloud turrets and by larger-scale upwelling in tropical cyclones, J. Geophys. Res.-Atmos., 98, 8665–8681, https://doi.org/10.1029/92JD02954, 1993. a
DeFries, R., Mondal, P., Singh, D., Agrawal, I., Fanzo, J., Remans, R., and
Wood, S.: Synergies and trade-offs for sustainable agriculture: Nutritional
yields and climate-resilience for cereal crops in Central India, Global Food
Secur., 11, 44–53, https://doi.org/10.1016/j.gfs.2016.07.001, 2016. a
Deser, C., Phillips, A. S., and Alexander, M. A.: Twentieth century tropical
sea surface temperature trends revisited, Geophys. Res. Lett., 37, 1–6, https://doi.org/10.1029/2010GL043321, 2010. a
DIAS: Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions (Experiment 1), https://doi.org/10.20783/DIAS.501, 2021. a
Gadgil, S. and Gadgil, S.: The Indian monsoon, GDP and agriculture, Economic
and political weekly, Econ. Polit. Weekly, 41, 4887–4895, 2006. a
Herzschuh, U., Borkowski, J., Schewe, J., Mischke, S., and Tian, F.:
Moisture-advection feedback supports strong early-to-mid Holocene monsoon
climate on the eastern Tibetan Plateau as inferred from a pollen-based
reconstruction, Palaeogeogr. Palaeocl., 402, 44–54, https://doi.org/10.1016/j.palaeo.2014.02.022, 2014. a, b
Jalihal, C., Srinivasan, J., and Chakraborty, A.: Modulation of Indian monsoon by water vapor and cloud feedback over the past 22,000 years, Nat.
Commun., 10, 1–8, https://doi.org/10.1038/s41467-019-13754-6, 2019. a
Jayasankar, C., Surendran, S., and Rajendran, K.: Robust signals of future
projections of Indian summer monsoon rainfall by IPCC AR5 climate models:
Role of seasonal cycle and interannual variability, Geophys. Res. Lett., 42, 3513–3520, https://doi.org/10.1002/2015GL063659, 2015. a, b
Jin, Q. and Wang, C.: A revival of Indian summer monsoon rainfall since 2002,
Nat. Clim. Change, 7, 587–594, https://doi.org/10.1038/nclimate3348, 2017. a, b, c
Katzenberger, A.: CMIP6-Indian-Monsoon, GitHub, available at: https://github.com/AnjaKatzenberger/CMIP6-Indian-Monsoon.git, last access: 31 March 2021. a
Kim, H.: Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions
(Experiment 1) [Data set], Data Integration and Analysis System (DIAS),
https://doi.org/10.20783/DIAS.501, 2017. a
Kitoh, A.: The Asian monsoon and its future change in climate models: A review, J. Meteorol. Soc. Jpn. Ser. II, 95, 7–33, https://doi.org/10.2151/jmsj.2017-002, 2017. a, b
Kitoh, A., Yukimoto, S., Noda, A., and Motoi, T.: Simulated changes in the
Asian summer monsoon at times of increased atmospheric CO2, J.
Meteorol. Soc. Jpn. Ser. II, 75, 1019–1031, https://doi.org/10.2151/jmsj1965.75.6_1019, 1997. a, b
Knutti, R., Sedláček, J., Sanderson, B. M., Lorenz, R., Fischer,
E. M., and Eyring, V.: A climate model projection weighting scheme accounting
for performance and interdependence, Geophys. Res. Lett., 44, 1909–1918, https://doi.org/10.1002/2016GL072012, 2017. a
Krishna Moorthy, K., Suresh Babu, S., Manoj, M., and Satheesh, S.: Buildup of
aerosols over the Indian Region, Geophys. Res. Lett., 40, 1011–1014, https://doi.org/10.1002/grl.50165, 2013. a
Kumar, K. K., Rajagopalan, B., Hoerling, M., Bates, G., and Cane, M.:
Unraveling the mystery of Indian monsoon failure during El Niño, Science,
314, 115–119, https://doi.org/10.1126/science.1131152, 2006. a
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with
ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070,
https://doi.org/10.5194/gmd-12-3055-2019, 2019. a
Lee, J.-Y. and Wang, B.: Future change of global monsoon in the CMIP5, Clim. Dynam., 42, 101–119, https://doi.org/10.1007/s00382-012-1564-0, 2014. a, b, c
Levermann, A., Schewe, J., Petoukhov, V., and Held, H.: Basic mechanism for
abrupt monsoon transitions, P. Natl. Acad. Sci. USA, 106, 20572–20577, https://doi.org/10.1073/pnas.0901414106, 2009. a
Li, K., Liu, X., Wang, Y., Herzschuh, U., Ni, J., Liao, M., and Xiao, X.: Late Holocene vegetation and climate change on the southeastern Tibetan Plateau: Implications for the Indian Summer Monsoon and links to the Indian Ocean Dipole, Quaternary Sci. Rev., 177, 235–245,
https://doi.org/10.1016/j.quascirev.2017.10.020, 2017. a
Mei, R., Ashfaq, M., Rastogi, D., Leung, L. R., and Dominguez, F.: Dominating
controls for wetter South Asian summer monsoon in the twenty-first century, J. Climate, 28, 3400–3419, https://doi.org/10.1175/JCLI-D-14-00355.1, 2015. a, b, c, d
Ming, G., Zhou, W., Cheng, P., Wang, H., Xian, F., Fu, Y., Wu, S., and Du, H.: Lacustrine record from the eastern Tibetan Plateau associated with Asian
summer monsoon changes over the past 6 ka and its links with solar and ENSO
activity, Clim. Dynam., 55, 1075–1086, https://doi.org/10.1007/s00382-020-05312-4, 2020. a, b, c
Mishra, V., Smoliak, B. V., Lettenmaier, D. P., and Wallace, J. M.: A prominent pattern of year-to-year variability in Indian Summer Monsoon Rainfall, P. Natl. Acad. Sci. USA, 109, 7213–7217, https://doi.org/10.1073/pnas.1119150109, 2012. a
Mishra, V., Kumar, D., Ganguly, A. R., Sanjay, J., Mujumdar, M., Krishnan, R., and Shah, R. D.: Reliability of regional and global climate models to
simulate precipitation extremes over India, J. Geophys. Res.-Atmos., 119, 9301–9323, https://doi.org/10.1002/2014JD021636, 2014a. a
Mishra, V., Shah, R., and Thrasher, B.: Soil moisture droughts under the
retrospective and projected climate in India, J. Hydrometeorol., 15, 2267–2292, https://doi.org/10.1175/JHM-D-13-0177.1, 2014b. a
Ogata, T., Ueda, H., Inoue, T., Hayasaki, M., Yoshida, A., Watanabe, S., Kira, M., Ooshiro, M., and Kumai, A.: Projected future changes in the Asian
monsoon: a comparison of CMIP3 and CMIP5 model results, J. Meteorol. Soc. Jpn. Ser. II, 92, 207–225, https://doi.org/10.2151/jmsj.2014-302, 2014. a
O'Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K.,
Rothman, D. S., van Ruijven, B. J., Van Vuuren, D. P., Birkmann, J., Kok, K.,
Levy, M., and Solecki, W.: The roads ahead: Narratives for shared
socioeconomic pathways describing world futures in the 21st century, Global
Environ. Change, 42, 169–180, https://doi.org/10.1016/j.gloenvcha.2015.01.004, 2017. a, b
Prasanna, V.: Impact of monsoon rainfall on the total foodgrain yield over
India, J. Earth Syst. Sci., 123, 1129–1145, https://doi.org/10.1007/s12040-014-0444-x, 2014. a
Ramanathan, V., Chung, C., Kim, D., Bettge, T., Buja, L., Kiehl, J. T.,
Washington, W. M., Fu, Q., Sikka, D. R., and Wild, M.: Atmospheric brown
clouds: Impacts on South Asian climate and hydrological cycle, P. Natl. Acad. Sci. USA, 102, 5326–5333, https://doi.org/10.1073/pnas.0500656102, 2005. a
Ramesh, K. and Goswami, P.: Assessing reliability of regional climate
projections: the case of Indian monsoon, Scient. Rep., 4, 1–9, https://doi.org/10.1038/srep04071, 2014. a
Revadekar, J. and Preethi, B.: Statistical analysis of the relationship between summer monsoon precipitation extremes and foodgrain yield over India,
Int. J. Climatol., 32, 419–429, https://doi.org/10.1002/joc.2282, 2012. a
Roxy, M. K., Ritika, K., Terray, P., Murtugudde, R., Ashok, K., and Goswami,
B.: Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land-sea thermal gradient, Na. Commun., 6, 1–10, https://doi.org/10.1038/ncomms8423, 2015. a
Sabeerali, C., Rao, S. A., Dhakate, A., Salunke, K., and Goswami, B.: Why
ensemble mean projection of south Asian monsoon rainfall by CMIP5 models is
not reliable?, Clim. Dynam., 45, 161–174, https://doi.org/10.1007/s00382-014-2269-3, 2015. a
Saha, A., Ghosh, S., Sahana, A., and Rao, E.: Failure of CMIP5 climate models
in simulating post-1950 decreasing trend of Indian monsoon, Geophys. Res. Lett., 41, 7323–7330, https://doi.org/10.1002/2014GL061573, 2014. a
Schewe, J., Levermann, A., and Cheng, H.: A critical humidity threshold for
monsoon transitions, Clim.e Past, 8, 535–544, https://doi.org/10.5194/cp-8-535-2012, 2012. a
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., and Ziese, M.:
GPCC Full Data Monthly Product Version 2018 at 0.5∘: Monthly
land-surface precipitation from rain-gauges built on GTS-based and historical
data, https://doi.org/10.5676/DWD_GPCC/FD_M_V2018_050, 2018. a
Seth, A., Rauscher, S. A., Biasutti, M., Giannini, A., Camargo, S. J., and
Rojas, M.: CMIP5 projected changes in the annual cycle of precipitation in
monsoon regions, J. Climate, 26, 7328–7351, https://doi.org/10.1175/JCLI-D-12-00726.1, 2013. a
Shah, H. L. and Mishra, V.: Hydrologic changes in Indian subcontinental river
basins (1901–2012), J. Hydrometeorol., 17, 2667–2687,
https://doi.org/10.1175/JHM-D-15-0231.1, 2016. a
Sharmila, S., Joseph, S., Sahai, A. K., Abhilash, S., and Chattopadhyay, R.:
Future projection of Indian summer monsoon variability under climate change
scenario: An assessment from CMIP5 climate models, Global Planet. Change, 124, 62–78, https://doi.org/10.1016/j.gloplacha.2014.11.004, 2015. a, b, c, d, e, f
Shashikanth, K., Salvi, K., Ghosh, S., and Rajendran, K.: Do CMIP5 simulations of Indian summer monsoon rainfall differ from those of CMIP3?, Atmos. Sci. Lett., 15, 79–85, https://doi.org/10.1002/asl2.466, 2014. a
Singh, D., Ghosh, S., Roxy, M. K., and McDermid, S.: Indian summer monsoon:
Extreme events, historical changes, and role of anthropogenic forcings, Wiley
Interdisciplin. Rev.: Clim. Change, 10, 1–35, https://doi.org/10.1002/wcc.571, 2019. a, b, c, d
Sooraj, K., Terray, P., and Mujumdar, M.: Global warming and the weakening of
the Asian summer monsoon circulation: assessments from the CMIP5 models, Clim. Dynam., 45, 233–252, https://doi.org/10.1007/s00382-014-2257-7, 2015. a, b, c
Sperber, K. R., Annamalai, H., Kang, I.-S., Kitoh, A., Moise, A., Turner, A.,
Wang, B., and Zhou, T.: The Asian summer monsoon: an intercomparison of CMIP5
vs. CMIP3 simulations of the late 20th century, Clim. Dynam., 41, 2711–2744, https://doi.org/10.1007/s00382-012-1607-6, 2013. a
Tebaldi, C., Debeire, K., Eyring, V., Fischer, E., Fyfe, J., Friedlingstein, P., Knutti, R., Lowe, J., O'Neill, B., Sanderson, B., van Vuuren, D., Riahi, K., Meinshausen, M., Nicholls, Z., Tokarska, K. B., Hurtt, G., Kriegler, E., Lamarque, J.-F., Meehl, G., Moss, R., Bauer, S. E., Boucher, O., Brovkin, V., Byun, Y.-H., Dix, M., Gualdi, S., Guo, H., John, J. G., Kharin, S., Kim, Y., Koshiro, T., Ma, L., Olivié, D., Panickal, S., Qiao, F., Rong, X., Rosenbloom, N., Schupfner, M., Séférian, R., Sellar, A., Semmler, T., Shi, X., Song, Z., Steger, C., Stouffer, R., Swart, N., Tachiiri, K., Tang, Q., Tatebe, H., Voldoire, A., Volodin, E., Wyser, K., Xin, X., Yang, S., Yu, Y., and Ziehn, T.: Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6, Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, 2021. a
Turner, A. G. and Annamalai, H.: Climate change and the South Asian summer
monsoon, Nat. Clim. Change, 2, 587–595, https://doi.org/10.1038/nclimate1495, 2012. a
Turner, A. G. and Slingo, J. M.: Subseasonal extremes of precipitation and
active-break cycles of the Indian summer monsoon in a climate-change scenario, Q. J. Roy. Meteorol. Soc., 135, 549–567, https://doi.org/10.1002/qj.401, 2009. a
Ul Hasson, S., Pascale, S., Lucarini, V., and Böhner, J.: Seasonal cycle of precipitation over major river basins in South and Southeast Asia: a review of the CMIP5 climate models data for present climate and future climate projections, Atmos. Res., 180, 42–63,
https://doi.org/10.1016/j.atmosres.2016.05.008, 2016. a
Van Vuuren, D. P., Kriegler, E., O'Neill, B. C., Ebi, K. L., Riahi, K., Carter, T. R., Edmonds, J., Hallegatte, S., Kram, T., Mathur, R., et al.: A new scenario framework for climate change research: scenario matrix architecture, Climatic Change, 122, 373–386, 2014. a
Varghese, S. J., Surendran, S., Rajendran, K., and Kitoh, A.: Future
projections of Indian Summer Monsoon under multiple RCPs using a high
resolution global climate model multiforcing ensemble simulations, Clim.
Dynam., 54, 1315–1328, https://doi.org/10.1007/s00382-019-05059-7, 2020. a, b, c, d
Vecchi, G. A., Soden, B. J., Wittenberg, A. T., Held, I. M., Leetmaa, A., and
Harrison, M. J.: Weakening of tropical Pacific atmospheric circulation due to
anthropogenic forcing, Nature, 441, 73–76, https://doi.org/10.1038/nature04744, 2006. a
Wang, P., Clemens, S., Beaufort, L., Braconnot, P., Ganssen, G., Jian, Z.,
Kershaw, P., and Sarnthein, M.: Evolution and variability of the Asian
monsoon system: state of the art and outstanding issues, Quaternary Sci. Rev., 24, 595–629, https://doi.org/10.1016/j.quascirev.2004.10.002, 2005. a, b, c
Wang, Y., Cheng, H., Edwards, R. L., He, Y., Kong, X., An, Z., Wu, J., Kelly,
M. J., Dykoski, C. A., and Li, X.: The Holocene Asian monsoon: links to solar
changes and North Atlantic climate, Science, 308, 854–857,
https://doi.org/10.1126/science.1106296, 2005. a, b
Wang, Y., Cheng, H., Edwards, R. L., Kong, X., Shao, X., Chen, S., Wu, J.,
Jiang, X., Wang, X., and An, Z.: Millennial-and orbital-scale changes in the
East Asian monsoon over the past 224,000 years, Nature, 451, 1090–1093,
https://doi.org/10.1038/nature06692, 2008. a, b
Wang, Y., Bekeschus, B., Handorf, D., Liu, X., Dallmeyer, A., and Herzschuh,
U.: Coherent tropical-subtropical Holocene see-saw moisture patterns in the
Eastern Hemisphere monsoon systems, Quaternary Sci. Rev., 169, 231–242, https://doi.org/10.1016/j.quascirev.2017.06.006, 2017. a
Wang, Y., Shen, J., Wang, Y., Liu, X., Cao, X., and Herzschuh, U.: Abrupt
mid-Holocene decline in the Indian Summer Monsoon caused by tropical Indian
Ocean cooling, Clim. Dynam., 55, 1961–1977, https://doi.org/10.1007/s00382-020-05363-7, 2020. a, b
WCRP: CMIP6, available at: https://esgf-node.llnl.gov/search/cmip6/, last access: 31 March 2021. a
Wyser, K., van Noije, T., Yang, S., von Hardenberg, J., O'Donnell, D., and Döscher, R.: On the increased climate sensitivity in the EC-Earth model from CMIP5 to CMIP6, Geosci. Model Dev., 13, 3465–3474, https://doi.org/10.5194/gmd-13-3465-2020, 2020.
a
Zaveri, E., Grogan, D. S., Fisher-Vanden, K., Frolking, S., Lammers, R. B.,
Wrenn, D. H., Prusevich, A., and Nicholas, R. E.: Invisible water, visible
impact: groundwater use and Indian agriculture under climate change, Environ. Res. Lett., 11, 084005, https://doi.org/10.1088/1748-9326/11/8/084005, 2016. a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M.,
Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of higher climate
sensitivity in CMIP6 models, Geophys. Res. Lett., 47, e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020. a
Zhang, P., Cheng, H., Edwards, R. L., Chen, F., Wang, Y., Yang, X., Liu, J.,
Tan, M., Wang, X., Liu, J., An, C., Dai, Z., Zhou, J., Zhang, D., Jia, J.,
Jin, L., and Johnson, K. R.: A test of climate, sun, and culture
relationships from an 1810-year Chinese cave record, Science, 322, 940–942,
https://doi.org/10.1126/science.1163965, 2008. a, b
Zhang, W., Zhang, Z., Liao, Z., Wang, Y., Chen, S., Shao, Q., and Wang, Y.:
Changes in the Asian monsoon climate during the late last interglacial
recorded in oxygen isotopes of a stalagmite from the Yongxing Cave, central
China, J. Asian Earth Sci., 179, 211–218, https://doi.org/10.1016/j.jseaes.2019.04.024, 2019. a, b
Zhou, T., Yu, R., Li, H., and Wang, B.: Ocean forcing to changes in global
monsoon precipitation over the recent half-century, J. Climate, 21, 3833–3852, https://doi.org/10.1175/2008JCLI2067.1, 2008. a
Short summary
All state-of-the-art global climate models that contributed to the latest Coupled Model Intercomparison Project (CMIP6) show a robust increase in Indian summer monsoon rainfall that is even stronger than in the previous intercomparison (CMIP5). Furthermore, they show an increase in the year-to-year variability of this seasonal rainfall that crucially influences the livelihood of more than 1 billion people in India.
All state-of-the-art global climate models that contributed to the latest Coupled Model...
Altmetrics
Final-revised paper
Preprint