The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
Global exposure and vulnerability to multi-sector development and climate change hotspots
Open accessAbstract
Understanding the interplay between multiple climate change risks and socioeconomic development is increasingly required to inform effective actions to manage these risks and pursue sustainable development. We calculate a set of 14 impact indicators at different levels of global mean temperature (GMT) change and socioeconomic development covering water, energy and land sectors from an ensemble of global climate, integrated assessment and impact models. The analysis includes changes in drought intensity and water stress index, cooling demand change and heat event exposure, habitat degradation and crop yield, amongst others. To investigate exposure to multi-sector climate impacts, these are combined with gridded socioeconomic projections of population and those 'vulnerable to poverty' from three Shared Socioeconomic Pathways (SSP) (income <$10/day, currently 4.2 billion people). We show that global exposure to multi-sector risks approximately doubles between 1.5 °C and 2 °C GMT change, doubles again with 3 °C GMT change and is ~6x between the best and worst cases (SSP1/1.5 °C vs SSP3/3 °C, 0.8–4.7bi). For populations vulnerable to poverty, the exposure is an order of magnitude greater (8–32x) in the high poverty and inequality scenarios (SSP3) compared to sustainable socioeconomic development (SSP1). Whilst 85%–95% of global exposure falls to Asian and African regions, they have 91%–98% of the exposed and vulnerable population (depending on SSP/GMT combination), approximately half of which in South Asia. In higher warming scenarios, African regions have growing proportion of the global exposed and vulnerable population, ranging from 7%–17% at 1.5 °C, doubling to 14%–30% at 2 °C and again to 27%–51% at 3 °C. Finally, beyond 2 °C and at higher risk thresholds, the world's poorest are disproportionately impacted, particularly in cases (SSP3) of high inequality in Africa and southern Asia. Sustainable development that reduces poverty, mitigates emissions and meets targets in the water, energy and land sectors has the potential for order-of-magnitude scale reductions in multi-sector climate risk for the most vulnerable.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Projections show that under the Shared Socioeconomic Pathway (SSP) SSP2 (a “middle of the road” scenario), by 2050 approximately 1,152 million people in dryland areas alone will be exposed to higher drought intensity and water stress at 2°C warming, whereas this number would be reduced to 974 million people under SSP1 (“sustainable” scenario) and increased to 1,267 million people in an SSP3 (“frag”
From Restoring Degraded Lands (2021) · cites this paper as [70]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Higher temperature increases result in higher projected numbers of people exposed to, and vulnerable to, water scarcity and droughts (70,71).”
From Restoring Degraded Lands (2021) · cites this paper as [70]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Projections show that under the Shared Socioeconomic Pathway (SSP) SSP2 (a “middle of the road” scenario), by 2050 approximately 1,152 million people in dryland areas alone will be exposed to higher drought intensity and water stress at 2°C warming, whereas this number would be reduced to 974 million people under SSP1 (“sustainable” scenario) and increased to 1,267 million people in an SSP3 (“frag”
From Restoring Degraded Lands (2021) · cites this paper as [70]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Projections show that under the Shared Socioeconomic Pathway (SSP) SSP2 (a “middle of the road” scenario), by 2050 approximately 1,152 million people in dryland areas alone will be exposed to higher drought intensity and water stress at 2°C warming, whereas this number would be reduced to 974 million people under SSP1 (“sustainable” scenario) and increased to 1,267 million people in an SSP3 (“frag”
From Restoring Degraded Lands (2021) · cites this paper as [70]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
The representative concentration pathways: an overview
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., et al. (2011) · Climatic Change · doi:10.1007/s10584-011-0148-z · Cited by 7,741
Self-citationRiahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., et al. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.05.009 · Cited by 6,607
Self-citationThe next generation of scenarios for climate change research and assessment
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., et al. (2010) · Nature · doi:10.1038/nature08823 · Cited by 6,467
Self-citationO’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., et al. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.01.004 · Cited by 3,359
Self-citationField, C. B., Barros, V. R., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G., Allen, S., et al. (2012) · Cambridge University Press eBooks · Cited by 3,037
Self-citationGreenhouse-gas emission targets for limiting global warming to 2 °C
Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C. B., Frieler, K., Knutti, R., Frame, D. J., & Allen, M. R. (2009) · Nature · doi:10.1038/nature08017 · Cited by 2,775
Giorgi, F. M. (2006) · Geophysical Research Letters · doi:10.1029/2006gl025734 · Cited by 2,755
The potential to narrow uncertainty in regional climate predictions.
Hawkins, E., & Sutton, R. (2009) · Bulletin of the American Meteorological Society · doi:10.1175/2009bams2607.1 · Cited by 2,732
A new scenario framework for climate change research: the concept of shared socioeconomic pathways
O’Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter, T. R., Mathur, R., & van Vuuren, D. P. (2014) · Climatic Change · doi:10.1007/s10584-013-0905-2 · Cited by 2,716
Self-citationRosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222463110 · Cited by 2,319
Multimodel assessment of water scarcity under climate change
Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark, D. B., Dankers, R., Eisner, S., Fekete, B. M., Colón‐González, F. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222460110 · Cited by 1,927
Self-citationThe economics of poverty traps and persistent poverty: An asset-based approach
Carter, M. R., & Barrett, C. B. (2006) · The Journal of Development Studies · doi:10.1080/00220380500405261 · Cited by 1,634
Robustness and uncertainties in the new CMIP5 climate model projections
Knutti, R., & Sedláček, J. (2013) · Nature Climate Change · doi:10.1038/nclimate1716 · Cited by 1,569
xarray: N-D labeled Arrays and Datasets in Python
Hoyer, S., & Hamman, J. (2017) · Journal of Open Research Software · doi:10.5334/jors.148 · Cited by 1,540
Projected distributions of novel and disappearing climates by 2100 AD
Williams, J. W., Jackson, S. T., & Kutzbach, J. E. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606292104 · Cited by 1,385
KC, S., & Lutz, W. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2014.06.004 · Cited by 1,337
The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., & Schewe, J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312330110 · Cited by 1,253
A trend-preserving bias correction – the ISI-MIP approach
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., & Piontek, F. (2013) · Earth System Dynamics · doi:10.5194/esd-4-219-2013 · Cited by 1,238 · cited 1×
“5◦, bias-corrected [65] to observed data [66], and were selected for coverage of the uncertainty range in temperature and precipitation variables from the CMIP5 models [23].”
MethodFricko, O., Havlik, P., Rogelj, J., Klimont, Z., Gusti, M., Johnson, N., Kolp, P., Strubegger, M., Valin, H., Amann, M., et al. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.06.004 · Cited by 1,075
Self-citationDependence of drivers affects risks associated with compound events
Jakob Zscheischler, A., & Seneviratne, S. I. (2017) · Science Advances · doi:10.1126/sciadv.1700263 · Cited by 953
Long-term economic growth projections in the Shared Socioeconomic Pathways
Dellink, R., Chateau, J., Lanzi, E., & Magné, B. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.06.004 · Cited by 893 · cited 1×
“New, socioeconomic projections with consistent 21st Century narratives are available for the SSPs for population [38], urbanization [39] and gross domestic product [40].”
BackgroundMeinshausen, M., Raper, S. C. B., & Wigley, T. M. L. (2011) · Atmospheric Chemistry and Physics · doi:10.5194/acp-11-1417-2011 · Cited by 876
Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E., Österle, H., Adam, J. C., Bellouin, N., Boucher, O., & Best, M. J. (2011) · Journal of Hydrometeorology · doi:10.1175/2011jhm1369.1 · Cited by 832
Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways
Jones, B., & O’Neill, B. C. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/8/084003 · Cited by 817 · cited 1×
“Additional methodological information In this study, gridded projections of population and GDP for SSP 1-3 spanning 2010 to 2050 [48] at 0.”
MethodGlobal urbanization projections for the Shared Socioeconomic Pathways
Jiang, L., & O’Neill, B. C. (2015) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.03.008 · Cited by 733
Wada, Y., Flörke, M., Hanasaki, N., Eisner, S., Fischer, G., Tramberend, S., Satoh, Y., van Vliet, M. T. H., Yillia, P. T., Ringler, C., et al. (2016) · Geoscientific model development · doi:10.5194/gmd-9-175-2016 · Cited by 690
Self-citationSchleussner, C.-F., Lissner, T. K., Fischer, E. M., Wohland, J., Perrette, M., Golly, A., Rogelj, J., Childers, K., Schewe, J., Frieler, K., et al. (2016) · Earth System Dynamics · doi:10.5194/esd-7-327-2016 · Cited by 680
Self-citationClimate change hotspots in the CMIP5 global climate model ensemble
Diffenbaugh, N. S., & Giorgi, F. (2012) · Climatic Change · doi:10.1007/s10584-012-0570-x · Cited by 663
SSP3: AIM implementation of Shared Socioeconomic Pathways
Fujimori, S., Hasegawa, T., Masui, T., Takahashi, K., Herran, D. S., Dai, H., Hijioka, Y., & Kainuma, M. (2016) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.06.009 · Cited by 650
Climate change mitigation through livestock system transitions
Havlík, P., Valin, H., Herrero, M., Obersteiner, M. H., Schmid, E., Rufino, M. C., Mosnier, A., Thornton, P. K., Böttcher, H., Conant, R. T., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308044111 · Cited by 639
Self-citationRobust spatially aggregated projections of climate extremes
Fischer, E. M., Beyerle, U., & Knutti, R. (2013) · Nature Climate Change · doi:10.1038/nclimate2051 · Cited by 583
A guide to SDG interactions: from science to implementation
Nilsson, M., Griggs, D., McCollum, D., & Stevance, A. (2017) · doi:10.24948/2017.01 · Cited by 568
Climate change through a poverty lens
Hallegatte, S., & Rozenberg, J. (2017) · Nature Climate Change · doi:10.1038/nclimate3253 · Cited by 545
Sustainability of global water use: past reconstruction and future projections
Wada, Y., & Bierkens, M. F. P. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/10/104003 · Cited by 512
Self-citationComprehensive Assessment of the Freshwater Resources of the World
Kirshen, P., & Strzepek, K. M. (1997) · Managing Water: Coping with Scarcity and Abundance · Cited by 485
IPCC reasons for concern regarding climate change risks
O’Neill, B. C., Oppenheimer, M., Warren, R., Stéphane Hallegatte, A., Kopp, R. E., Pörtner, H., Scholes, R. J., Birkmann, J., Foden, W., Licker, R., et al. (2017) · Nature Climate Change · doi:10.1038/nclimate3179 · Cited by 454
Connecting the sustainable development goals by their energy inter-linkages
McCollum, D. L., Echeverri, L. G., Busch, S., Pachauri, S., Parkinson, S., Rogelj, J., Krey, V., Minx, J. C., Nilsson, M., Stevance, A.-S., et al. (2018) · Environmental Research Letters · doi:10.1088/1748-9326/aaafe3 · Cited by 448
Self-citationHuman and climate impacts on the 21st century hydrological drought
Wanders, N., & Wada, Y. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.10.047 · Cited by 380
Self-citationA vulnerability approach to the definition of the middle class
López-Calva, L. F., & Ortiz-Juárez, E. (2013) · The Journal of Economic Inequality · doi:10.1007/s10888-012-9240-5 · Cited by 355
van Vuuren, D. P., Riahi, K., Calvin, K., Dellink, R., Emmerling, J., Fujimori, S., KC, S., Kriegler, E., & O’Neill, B. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.10.009 · Cited by 330
Self-citationDankers, R., Arnell, N. W., Clark, D. B., Falloon, P., Fekete, B. M., Gosling, S. N., Heinke, J., Kim, H., Masaki, Y., Satoh, Y., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1302078110 · Cited by 326
Self-citationJames, R., Washington, R., Schleussner, C., Rogelj, J., & Conway, D. (2017) · Wiley Interdisciplinary Reviews Climate Change · doi:10.1002/wcc.457 · Cited by 286
Self-citationAssessing the land resource–food price nexus of the Sustainable Development Goals
Obersteiner, M. H., Walsh, B., Frank, S., Havlík, P., Cantele, M., Liu, J., Palazzo, A., Herrero, M., Lü, Y., Mosnier, A., et al. (2016) · Science Advances · doi:10.1126/sciadv.1501499 · Cited by 276
Self-citationPrestele, R., Alexander, P. M., Rounsevell, M., Arneth, A., Calvin, K., Doelman, J., Eitelberg, D. A., Engström, K., Fujimori, S., Hasegawa, T., et al. (2016) · Global Change Biology · doi:10.1111/gcb.13337 · Cited by 269
Climate change hotspots in the United States
Diffenbaugh, N. S., Giorgi, F., & Pal, J. S. (2008) · Geophysical Research Letters · doi:10.1029/2008gl035075 · Cited by 253
Valin, H., Havlík, P., Mosnier, A., Herrero, M., Schmid, E., & Obersteiner, M. H. (2013) · Environmental Research Letters · doi:10.1088/1748-9326/8/3/035019 · Cited by 227
Self-citation2 °C and SDGs: united they stand, divided they fall?
von Stechow, C., Minx, J. C., Riahi, K., Jewell, J., McCollum, D. L., Callaghan, M., Bertram, C., Luderer, G., & Baiocchi, G. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/3/034022 · Cited by 224
Self-citationEnergy Pathways for Sustainable Development
Riahi, K., Dentener, F. J., Gielen, D. J., Grübler, A., Jewell, J., Klimont, Z., Krey, V., McCollum, D. L., Pachauri, S., Rao, S., et al. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9780511793677.023 · Cited by 205
Self-citationCoping with the curse of freshwater variability
Hall, J. W., Grey, D., Garrick, D. E., Fung, F., Brown, C., Dadson, S., & Sadoff, C. (2014) · Science · doi:10.1126/science.1257890 · Cited by 203
Self-citationRaskin, P. D., Gleick, P. H., Kirshen, P., Pontius, G., & Strzepek, K. M. (1997) · Cited by 197
Poorest countries experience earlier anthropogenic emergence of daily temperature extremes
Harrington, L. J., Frame, D. J., Fischer, E. M., Hawkins, E., Joshi, M., & JONES, C. D. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/5/055007 · Cited by 196
Bank, W. (2013) · doi:10.1596/978-0-8213-9903-3 · Cited by 195
Pathways to achieve universal household access to modern energy by 2030
Pachauri, S., van Ruijven, B. J., Nagai, Y., Riahi, K., van Vuuren, D. P., Brew-Hammond, A., & Nakićenović, N. (2013) · Environmental Research Letters · doi:10.1088/1748-9326/8/2/024015 · Cited by 182
Self-citationMultisectoral climate impact hotspots in a warming world
Piontek, F., Müller, C., Pugh, T., Clark, D., Deryng, D., Elliott, J., González, F. D. J. C., Flörke, M., Folberth, C., Franssen, W., et al. (2013) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1222471110 · Cited by 181
Balkovič, J., van der Velde, M., Skalský, R., Xiong, W., Folberth, C., Khabarov, N., Смирнов, А. В., Mueller, N. D., & Obersteiner, M. H. (2014) · Global and Planetary Change · doi:10.1016/j.gloplacha.2014.08.010 · Cited by 174
Self-citationA climate change index: Where climate change may be most prominent in the 21st century
Bättig, M. B., Wild, M., & Imboden, D. M. (2007) · Geophysical Research Letters · doi:10.1029/2006gl028159 · Cited by 158
Meeting the Sustainable Development Goals leads to lower world population growth
Abel, G., Barakat, B. F., Samir, K. C., & Lutz, W. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1611386113 · Cited by 153
A Vulnerability Approach to the Definition of the Middle Class
Ortiz-Juárez, E., & López-Calva, L. F. (2011) · The World Bank Open Knowledge Repository (World Bank) · doi:10.1596/1813-9450-5902 · Cited by 151
The impacts of climate change across the globe: A multi-sectoral assessment
Arnell, N. W., Brown, S. A., Gosling, S. N., Gottschalk, P., Hinkel, J., Huntingford, C., Lloyd‐Hughes, B., Lowe, J. A., Nicholls, R. J., Osborn, T. J., et al. (2014) · Climatic Change · doi:10.1007/s10584-014-1281-2 · Cited by 144
van Vuuren, D. P., Isaac, M., Kundzewicz, Z. W., Arnell, N. W., Barker, T., Patrick Criqui, A., Berkhout, F., Hilderink, H. B. M., Hinkel, J., Hof, A. F., et al. (2010) · Global Environmental Change · doi:10.1016/j.gloenvcha.2010.11.003 · Cited by 137
Importance of the pre-industrial baseline for likelihood of exceeding Paris goals
Schurer, A., MANN, M. E., Hawkins, E., Tett, S. F. B., & Hegerl, G. C. (2017) · Nature Climate Change · doi:10.1038/nclimate3345 · Cited by 127
Assessing inter-sectoral climate change risks: the role of ISIMIP
Rosenzweig, C., Arnell, N. W., Ebi, K. L., Lotze‐Campen, H., elisabeth, R. F. P., Rapley, C. G., Stafford‐Smith, M., Crämer, W., Frieler, K., Reyer, C., et al. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/12/1/010301 · Cited by 124
Self-citationClimate change induced transformations of agricultural systems: insights from a global model
Leclère, D., Havlík, P., Fuss, S., Schmid, E., Mosnier, A., Walsh, S., Valin, H., Herrero, M., Khabarov, N., & Obersteiner, M. H. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/12/124018 · Cited by 112
Self-citationChang, K. M., Hess, J. J., Balbus, J. M., Buonocore, J. J., Cleveland, D. A., Grabow, M., Neff, R., Saari, R. K., Tessum, C. W., Wilkinson, P., et al. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa8f7b · Cited by 84
Self-citationHerrero, M., Havlík, P., McIntire, J. M., Palazzo, A., & Valin, H. (2014) · IIASA PURE (International Institute of Applied Systems Analysis) · Cited by 82
Self-citationDemographic scenarios by age, sex and education corresponding to the SSP narratives
Samir, K. C., & Lutz, W. (2014) · Population and Environment · doi:10.1007/s11111-014-0205-4 · Cited by 81
Indicators of 21st century socioclimatic exposure
Diffenbaugh, N. S., Giorgi, F., Raymond, L., & Bi, X. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706680105 · Cited by 79
Harrington, L. J., & Otto, F. E. L. (2018) · Environmental Research Letters · doi:10.1088/1748-9326/aaaa99 · Cited by 78
Satoh, Y., Kahil, T., Byers, E. A., Burek, P., Fischer, G., Tramberend, S., Greve, P., Flörke, M., Eisner, S., Hanasaki, N., et al. (2017) · Earth s Future · doi:10.1002/2016ef000503 · Cited by 73
Self-citationThe elephant, the blind, and the intersectoral intercomparison of climate impacts
Schellnhuber, H. J., Frieler, K., & Kabat, P. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1321791111 · Cited by 57
Raptis, C., & Pfister, S. (2016) · Energy · doi:10.1016/j.energy.2015.12.107 · Cited by 54
Hayashi, A., Akimoto, K., Sano, F., Mori, S., & Tomoda, T. (2009) · Climatic Change · doi:10.1007/s10584-009-9663-6 · Cited by 41
Half of the world’s population experience robust changes in the water cycle for a 2 °C warmer world
Sedláčék, J., & Knutti, R. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/4/044008 · Cited by 31
Global Energy Demand in a Warming ClimatePreprint
Cian, E. D., & Wing, I. S. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2744532 · Cited by 18
Towards indicators for water security - A global hydro-economic classification of water challenges
Fischer, G., Hizsnyik, E., Tramberend, S., & Wiberg, D. A. (2015) · IIASA PURE (International Institute of Applied Systems Analysis) · Cited by 10
Research works printed but not linked: 13
- Tramberend S, 2017, Earth’s Future
- Lavell A ed Field C B, 2012, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), 25
- World Bank, 2017, PovcalNet
- Hallegatte S, 2016, Climate Change and Development Serie
- Gidden M J, 2017, Nat. Sustain.
- Jones B, 2016, Environ. Res. Lett., 11
- Platts ed Platts, 2014, World Electric Power Plants Database
- Ummel K, 2012, Carbon Monitoring for Action (CARMA) Database
- Seneviratne S I, 2018, Nature
- IIASA, 2014, IAMC AR5 Scenario Database
- Chang K M, 2017, Environ. Res. Lett., 12
- ICSU ed Griggs D, 2017, A Guide to SDG Interactions: From Science to Implementation
- Johnson N, 2017, Glob. Env. Change
Cited by
Sorted by citations
Hot weather and heat extremes: health risks
Ebi, K. L., Capon, A., Berry, P., Broderick, C., de Dear, R., Havenith, G., Honda, Y., Kovats, R. S., Ma, W., Malik, A., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)01208-3 · Cited by 2,172
Self-citationBending the Curve of Global Freshwater Biodiversity Loss: An Emergency Recovery Plan
Tickner, D., Opperman, J. J., Abell, R., Acreman, M., Arthington, A. H., Bunn, S. E., Cooke, S. J., Dalton, J., Darwall, W., Edwards, G., et al. (2020) · BioScience · doi:10.1093/biosci/biaa002 · Cited by 1,241
Self-citationThe emergence of heat and humidity too severe for human tolerance
Raymond, C., Matthews, T. K. R., & Horton, R. (2020) · Science Advances · doi:10.1126/sciadv.aaw1838 · Cited by 875
Achievements and needs for the climate change scenario framework
O’Neill, B. C., Carter, T. R., Ebi, K. L., Harrison, P. A., Kemp-Benedict, E. J., Kok, K. I., Kriegler, E., Preston, B. L., Riahi, K., Sillmann, J., et al. (2020) · Nature Climate Change · doi:10.1038/s41558-020-00952-0 · Cited by 666
Self-citationExtreme weather impacts of climate change: an attribution perspective
Clarke, B. J., Otto, F. E. L., Stuart-Smith, R. F., & Harrington, L. J. (2022) · Environmental Research Climate · doi:10.1088/2752-5295/ac6e7d · Cited by 727
Metadata
- Authors
- Byers, E., Gidden, M., Leclère, D., Balkovic, J., Burek, P., Ebi, K., Greve, P., Grey, D., Havlik, P., Hillers, A., Johnson, N., Kahil, T., Krey, V., Langan, S., Nakicenovic, N., Novak, R., Obersteiner, M., Pachauri, S., Palazzo, A., Parkinson, S., Rao, N. D., Rogelj, J., Satoh, Y., Wada, Y., Willaarts, B., & Riahi, K.
- Affiliations
- International Institute for Applied Systems Analysis (AT)
- University of Washington (US)
- University of Oxford (GB)
- Global Environment Facility (US)
- United Nations Industrial Development Organization (AT)
- Corresponding author
- Byers, Edward
- ORCID
- Venue
- Environmental Research Letters
- Publisher
- IOP Publishing
- Published
- 2018-05-01
- Volume
- 13
- Issue
- 5
- Pages
- 055012
- ISSN
- 1748-9326 (ISSN-L)
- OpenAlex
- W2802086350
- Cited by
- 295
- References
- 78
- Citations by year
- 2026: 27 · 2025: 34 · 2024: 46 · 2023: 39 · 2022: 51 · 2021: 50 · 2020: 28 · 2019: 17 · 2018: 3
- FWCI
- 37.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Environmental Research Letters (publishedVersion, cc-by)
- IIASA PURE (International Institute of Applied Systems Analysis) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by)
- Funders
- Global Environment Facility (6993)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Keywords
- climate change exposure, climate change vulnerability, Shared Socioeconomic Pathways, global mean temperature change, poverty, water stress, drought severity, cooling demand, heat events, habitat degradation, crop yield, population projections, sustainable development, South Asia, Africa
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review