Articles | Volume 16, issue 5
https://doi.org/10.5194/essd-16-2333-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2333-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 May 2024
Data description paper |
| 14 May 2024
| 14 May 2024
A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015
Kanishka B. Narayan
CORRESPONDING AUTHOR
Joint Global Change Research Institute (JGCRI), Pacific Northwest National Lab (PNNL), College Park, Maryland, USA
Brian C. O'Neill
Joint Global Change Research Institute (JGCRI), Pacific Northwest National Lab (PNNL), College Park, Maryland, USA
Stephanie Waldhoff
Joint Global Change Research Institute (JGCRI), Pacific Northwest National Lab (PNNL), College Park, Maryland, USA
Claudia Tebaldi
Joint Global Change Research Institute (JGCRI), Pacific Northwest National Lab (PNNL), College Park, Maryland, USA
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Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 15, 1055–1071, https://doi.org/10.5194/esd-15-1055-2024, https://doi.org/10.5194/esd-15-1055-2024, 2024
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Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Kanishka B. Narayan, Alan V. Di Vittorio, Evan Margiotta, Seth A. Spawn-Lee, and Holly K. Gibbs
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In this paper we present a new dataset of grid cell level spatially explicit carbon harmonized with land types in a global Multisector Dynamics Model. This dataset can be used to define an initial condition of terrestrial carbon in MSD models. Our harmonized dataset presents carbon values for 3 pools (topsoil, above ground biomass and below ground biomass) for six statistical states across land use types. Our dataset is available at a pixel level (5 arcmin) and aggregated to 699 land regions.
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022, https://doi.org/10.5194/gmd-15-2533-2022, 2022
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GCAM-USA v5.3_water_dispatch is an open-source model that represents key interactions across economic, energy, water, and land systems in a global framework, with subnational detail in the United States. GCAM-USA can be used to explore future changes in demand for (and production of) energy, water, and crops at the state and regional level in the US. This paper describes GCAM-USA and provides four illustrative scenarios to demonstrate the model's capabilities and potential applications.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
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Abigail Snyder, Noah Prime, Claudia Tebaldi, and Kalyn Dorheim
Earth Syst. Dynam., 15, 1301–1318, https://doi.org/10.5194/esd-15-1301-2024, https://doi.org/10.5194/esd-15-1301-2024, 2024
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From running climate models to using their outputs to identify impacts, modeling the integrated human–Earth system is expensive. This work presents a method to identify a smaller subset of models from the full set that preserves the uncertainty characteristics of the full set. This results in a smaller number of runs that an impact modeler can use to assess how uncertainty propagates from the Earth to the human system, while still capturing the range of outcomes provided by climate models.
Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
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Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Kanishka B. Narayan, Alan V. Di Vittorio, Evan Margiotta, Seth A. Spawn-Lee, and Holly K. Gibbs
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-251, https://doi.org/10.5194/essd-2023-251, 2023
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Claudia Tebaldi, Abigail Snyder, and Kalyn Dorheim
Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, https://doi.org/10.5194/esd-13-1557-2022, 2022
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Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meets these demands in a comprehensive way and may thus support a fully integrated impact research effort and save resources for the climate modeling enterprise.
Mari R. Tye, Katherine Dagon, Maria J. Molina, Jadwiga H. Richter, Daniele Visioni, Ben Kravitz, and Simone Tilmes
Earth Syst. Dynam., 13, 1233–1257, https://doi.org/10.5194/esd-13-1233-2022, https://doi.org/10.5194/esd-13-1233-2022, 2022
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We examined the potential effect of stratospheric aerosol injection (SAI) on extreme temperature and precipitation. SAI may cause daytime temperatures to cool but nighttime to warm. Daytime cooling may occur in all seasons across the globe, with the largest decreases in summer. In contrast, nighttime warming may be greatest at high latitudes in winter. SAI may reduce the frequency and intensity of extreme rainfall. The combined changes may exacerbate drying over parts of the global south.
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
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Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
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Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
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The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise
Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, https://doi.org/10.5194/gmd-12-677-2019, 2019
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Nathan P. Gillett, Hideo Shiogama, Bernd Funke, Gabriele Hegerl, Reto Knutti, Katja Matthes, Benjamin D. Santer, Daithi Stone, and Claudia Tebaldi
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Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
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Related subject area
Domain: ESSD – Global | Subject: Energy and Emissions
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Zhe Jin, Xiangjun Tian, Yilong Wang, Hongqin Zhang, Min Zhao, Tao Wang, Jinzhi Ding, and Shilong Piao
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Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
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Simon Schulte, Arthur Jakobs, and Stefan Pauliuk
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The following study was undertaken to provide a continuous open access dataset for 2010-2020 from country to local level. In order to understand the reliability of the final dataset and to enable further use, the modelled data were validated against statistics, which is a novelty in this field. The dataset has been shown to be in good agreement with the statistical data. Biomass potentials modelled in this study are published in an open access database.
Lehui Cui, Yunting Xiao, Wei Hu, Lei Song, Yujue Wang, Chao Zhang, Pingqing Fu, and Jialei Zhu
Earth Syst. Sci. Data, 15, 5403–5425, https://doi.org/10.5194/essd-15-5403-2023, https://doi.org/10.5194/essd-15-5403-2023, 2023
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Earth Syst. Sci. Data, 15, 2179–2187, https://doi.org/10.5194/essd-15-2179-2023, https://doi.org/10.5194/essd-15-2179-2023, 2023
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Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Nadine Borduas-Dedekind, Karen C. Short, and Samuel P. Carlson
Earth Syst. Sci. Data, 15, 1437–1440, https://doi.org/10.5194/essd-15-1437-2023, https://doi.org/10.5194/essd-15-1437-2023, 2023
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This article describes the use of the open-discussion manuscript review process as an educational exercise for early career scientists.
Can Cui, Shuping Li, Weichen Zhao, Binyuan Liu, Yuli Shan, and Dabo Guan
Earth Syst. Sci. Data, 15, 1317–1328, https://doi.org/10.5194/essd-15-1317-2023, https://doi.org/10.5194/essd-15-1317-2023, 2023
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Emerging economies face challenges regarding net-zero targets: inconsistencies in accounting calibers, missing raw data, non-transparent accounting methods, and a lack of detail about emissions. The authors established an accounting framework and compiled detailed inventories of energy-related CO2 emissions in 40 emerging economies, covering 47 sectors and eight energy types. The dataset will support emission reduction policymaking at global, national, and subnational levels.
Chuanlong Zhou, Biqing Zhu, Steven J. Davis, Zhu Liu, Antoine Halff, Simon Ben Arous, Hugo de Almeida Rodrigues, and Philippe Ciais
Earth Syst. Sci. Data, 15, 949–961, https://doi.org/10.5194/essd-15-949-2023, https://doi.org/10.5194/essd-15-949-2023, 2023
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Our work aims to analyze sectoral and country-based daily natural gas supply–storage–consumption based on ENTSOG, Eurostat, and multiple datasets in the EU27 and UK. We estimated the magnitude of the Russian gas gap if Russian gas imports were to stop as well as potential short-term solutions to fill this gap. Our datasets could be important in various fields, such as gas/energy consumption and market modeling, carbon emission and climate change research, and policy decision-making.
Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
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Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
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Short summary
Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. We also present another version of this dataset aggregated from the country level to 32 geographical regions.
Here, we present a consistent dataset of income distributions across 190 countries from 1958 to...
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