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Global warming: °C
Actions
Affected
Impacts

2100

The state as of the year 2100 according to a reference scenario, which projects a global warming of 3.3°C – or less, if appropriate actions are taken. Also see sources [7-15].

Shut down coal and gas power plants

Coal and gas power plants are responsible for a large part of CO₂ emissions. Here it is assumed that of the total emissions from now until 2100 according to the reference scenario, 80% are avoided. Also see sources [7-15].

Decarbonize industry

CO₂ emissions by industry, e.g. during steel production. Of course, we are indirectly responsible for these emissions through our consumption behaviour as well. The assignment of CO₂ emissions to different sectors is not always easy. Also see sources [7-15].

Take freight and short distance traffic off the road

Traffic in total is responsible for about 20% of CO₂ emissions. Here it is assumed that freight traffic on the road and short distance car traffic (less than about 15 km) are reduced by 80% each. Also see sources [7-15].

Further actions for 1.5° target

In order to limit global warming to 1.5 degrees Celsius, many more issues need to be acted on. For instance heating of buildings, cement production, agriculture, and consumption of animal products. Also see sources [7-15].

Population

If the population toggle is enabled, impacts will be multiplied by the population density. That is, the size of areas on the map is proportional to the impact on people living in these areas. The population density for the year 2100 is projected using the estimated population growth on a per-country level. Also see sources [18-20].

Wildfires

Depicted on the map is a measure of cumulative yearly wildfire risk. Due to climate change, both the frequency and the wildfire season length increase in many regions around the world. Also see sources [31-34].

Sea level rise

On this map, areas that disappear are not submerged by water, they are on the contrary not impacted by sea level rise. Those areas that are shown lie below sea level or, statistically speaking, experience flooding at least once a year, for instance due to storm surges. Already today, some areas of land lie below sea level. Due to climate change, the sea level will probably rise by more than one meter. This increases the danger of erosion, flooding and salinization and makes preventive measures like levees increasingly difficult. Also see sources [21-23].

Unbearable heat

Humans sweat to avoid overheating. When the air is not only hot, but also very humid, that doesn't work anymore. The sweat cannot evaporate, the body can't cool itself anymore. A so-called wet-bulb temperature of 35°C is the theoretical limit that a human can survive without air conditioning – even in the shade and with enough water. 30°C are already dangerous. Places that reach wet-bulb temperatures of more than 35°C multiple times a year are shown on the map. Also see sources [24-30].

About this map

Video walkthrough

This map does not show geographic reality, but the reality of climate change. Depending on what you select, it shows the areas or people that will be most affected by wildfires, sea level rise and unbearable heat. Places are enlarged or shrinked relative to how affected they are. Like that, regional effects that may however impact a lot of people are made visible on a world map. In a perfect world without negative impacts, this map would thus be empty.

Please bear in mind that the exact impacts of climate change are difficult to predict, even more so on a regional level. This map might exaggerate them, but more likely it might underestimate them. There are many tipping points and feedback loops that are poorly understood, and if triggered, they might lead to even more extreme, self-amplifying impacts. Please also note that there are many more effects of climate change that are not (yet) represented on this map.

Sources

The idea for this project has been inspired and influenced by sources [1-5]. See the respective links for other takes on these so-called cartograms. Furthermore, for this project, data and algorithms from sources [6-34] have been used. For more details on data sources and preparation, please see the source code repository of this project at https://github.com/traines-source/climate-change-cartograms

  1. https://www.carbonmap.org/
  2. https://worldmapper.org/
  3. Hennig, Benjamin. Rediscovering the world: Map transformations of human and physical space. Springer Science & Business Media, 2012.
  4. Döll, Petra. "Cartograms facilitate communication of climate change risks and responsibilities." Earth's Future 5.12 (2017): 1182-1195.
  5. https://go-cart.io/
  6. Gastner, Michael T., and Mark EJ Newman. "Diffusion-based method for producing density-equalizing maps." Proceedings of the National Academy of Sciences 101.20 (2004): 7499-7504.
  7. https://github.com/JGCRI/gcam-core
  8. GCAM reference scenario, see https://github.com/traines-source/climate-change-cartograms/tree/master/generate/emissions
  9. Calvin, K., Patel, P., Clarke, L., Asrar, G., Bond-Lamberty, B., Cui, R. Y., Di Vittorio, A., Dorheim, K., Edmonds, J., Hartin, C., Hejazi, M., Horowitz, R., Iyer, G., Kyle, P., Kim, S., Link, R., McJeon, H., Smith, S. J., Snyder, A., Waldhoff, S., and Wise, M.: GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems, Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, 2019.
  10. https://ourworldindata.org/emissions-by-sector
  11. https://www.solarjourneyusa.com/EVdistanceAnalysis.php
  12. IPCC, 2013: Annex II: Climate System Scenario Tables [Prather, M., G. Flato, P. Friedlingstein, C. Jones, J.-F. Lamarque, H. Liao and P. Rasch (eds.)]. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https://www.ipcc.ch/site/assets/uploads/2017/09/WG1AR5_AnnexII_FINAL.pdf
  13. Simon Dietz, Frank Venmans, Cumulative carbon emissions and economic policy: In search of general principles, Journal of Environmental Economics and ;Management, Volume 96, 2019, Pages 108-129, ISSN 0095-0696 https://doi.org/10.1016/j.jeem.2019.04.003
  14. Rogelj, Joeri, et al. "Differences between carbon budget estimates unravelled." Nature Climate Change 6.3 (2016): 245-252.
  15. Rogelj, J., D. Shindell, K. Jiang, S. Fifita, P. Forster, V. Ginzburg, C. Handa, H. Kheshgi, S. Kobayashi, E. Kriegler, L. Mundaca, R. Séférian, and M.V.Vilariño, 2018: Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. https://www.ipcc.ch/site/assets/uploads/sites/2/2019/02/SR15_Chapter2_Low_Res.pdf
  16. Stöckli, Reto, et al. "The Blue Marble Next Generation-A true color earth dataset including seasonal dynamics from MODIS." Published by the NASA Earth Observatory (2005). For image data see https://neo.gsfc.nasa.gov/archive/bluemarble/
  17. Pareto Software, LLC, SimpleMaps.com. World Cities Database. 2021. https://simplemaps.com/data/world-cities Data licensed under CC-BY-4.0 http://creativecommons.org/licenses/by/4.0.
  18. Center for International Earth Science Information Network - CIESIN - Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density Adjusted to Match 2015 Revision UN WPP Country Totals, Revision 11. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4F47M65. Accessed 2022-02-19. Data licensed under CC-BY-4.0 http://creativecommons.org/licenses/by/4.0.
  19. Center for International Earth Science Information Network - CIESIN - Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): National Identifier Grid, Revision 11. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4TD9VDP. Accessed 2022-02-19. Data licensed under CC-BY-4.0 http://creativecommons.org/licenses/by/4.0.
  20. https://ourworldindata.org/grapher/population-past-future, Gapminder (v6), HYDE (v3.2), United Nations Population Division (2019). Accessed 2022-02-19. Data licensed under CC-BY-4.0 http://creativecommons.org/licenses/by/4.0
  21. Kopp, Robert E., et al. "Evolving understanding of Antarctic ice‐sheet physics and ambiguity in probabilistic sea‐level projections." Earth's Future 5.12 (2017): 1217-1233. https://doi.org/10.1002/2017EF000663
  22. Kulp, Scott A., and Benjamin H. Strauss. "New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding." Nature communications 10.1 (2019): 1-12. https://doi.org/10.1038/s41467-019-12808-z Supplementary Data 1. Data licensed under CC-BY-4.0 http://creativecommons.org/licenses/by/4.0
  23. Jarvis A., H.I. Reuter, A. Nelson, E. Guevara, 2008, Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), available from https://srtm.csi.cgiar.org.
  24. Coffel, Ethan D., Radley M. Horton, and Alex De Sherbinin. "Temperature and humidity based projections of a rapid rise in global heat stress exposure during the 21st century." Environmental Research Letters 13.1 (2017): 014001.
  25. Dufresne, J-L., et al. "Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5." Climate dynamics 40.9 (2013): 2123-2165. Obtained from https://cds.climate.copernicus.eu/cdsapp#!/dataset/projections-cmip5-daily-single-levels?tab=form
  26. GTOPO30 http://www.webgis.com/terr_world.html Worldwide DEM. U.S. Geological Survey (USGS). Public Domain.
  27. Chavaillaz, Yann, et al. "Exposure to excessive heat and impacts on labour productivity linked to cumulative CO2 emissions." Scientific reports 9.1 (2019): 1-11.
  28. Buzan, J. R., K. Oleson, and M. Huber. "Implementation and comparison of a suite of heat stress metrics within the Community Land Model version 4.5." Geoscientific Model Development 8.2 (2015): 151-170.
  29. Newth, David, and Don Gunasekera. "Projected changes in wet-bulb globe temperature under alternative climate scenarios." Atmosphere 9.5 (2018): 187.
  30. Raymond, Colin, Tom Matthews, and Radley M. Horton. "The emergence of heat and humidity too severe for human tolerance." Science Advances 6.19 (2020): eaaw1838. https://github.com/cr2630git/raymondmatthewshorton2020_sciadv
  31. Gannon, Colin S., and Nik C. Steinberg. "A global assessment of wildfire potential under climate change utilizing Keetch-Byram drought index and land cover classifications." Environmental Research Communications 3.3 (2021): 035002. https://doi.org/10.1088/2515-7620/abd836
  32. Noble, I. R., A. M. Gill, and G. A. V. Bary. "McArthur's fire‐danger meters expressed as equations." Australian Journal of Ecology 5.2 (1980): 201-203. https://doi.org/10.1111/j.1442-9993.1980.tb01243.x
  33. Sun, Qiaohong, et al. "Global heat stress on health, wildfires, and agricultural crops under different levels of climate warming." Environment international 128 (2019): 125-136. https://doi.org/10.1016/j.envint.2019.04.025
  34. Garcia-Prats, Alberto, Fernandes JG Tarcísio, and Molina J. Antonio. "Development of a Keetch and Byram—based drought index sensitive to forest management in Mediterranean conditions." Agricultural and Forest Meteorology 205 (2015): 40-50. http://dx.doi.org/10.1016/j.agrformet.2015.02.009