Mapping the impacts of climate change

The impacts of climate change will be experienced differently across the globe. Here’s how four key impacts will affect different regions of the world in 2100 under a 2°C scenario compared with a no-policy high emission scenario.

The maps below show the changing likelihood of the following thresholds being passed:

  • An over 25% increase in people exposed to heatwaves
  • An over 25% increase in people exposed to river flooding
  • An over 10% increase in people exposed to water stress
  • An over 20% increase in area of cropland degradation

(see footnote for further information).

What is the likelihood that the number of people affected by heatwaves will increase by over 25%?

Chances of an over 25% increase in people exposed to heatwaves occurring (%)

  • 0-9
  • 10-19
  • 20-29
  • 30-39
  • 40-49
  • 50-59
  • 60-69
  • 70-79
  • 80-89
  • 90-99
  • 100

If we limit global temperature rise to 2°C rather than allowing it to reach 5.2°C, 10.8 billion fewer people will exposed to heatwaves in 2100.

What is the likelihood that the number of people affected by river flooding will increase by over 25%?

Chances of an over 25% increase in people exposed to river flooding occurring (%)

  • 0-9
  • 10-19
  • 20-29
  • 30-39
  • 40-49
  • 50-59
  • 60-69
  • 70-79
  • 80-89
  • 90-99
  • 100

If we limit global temperature rise to 2°C rather than allowing it to reach 5.2°C, 85 million fewer people will be affected by river flooding in 2100.

What is the likelihood that the number of people affected by water stress will increase by over 10%?

Chances of an over 10% increase in people exposed to water stress occurring (%)

  • 0-9
  • 10-19
  • 20-29
  • 30-39
  • 40-49
  • 50-59
  • 60-69
  • 70-79
  • 80-89
  • 90-99
  • 100

If we limit global temperature rise to 2°C rather than allowing it to reach 5.2°C, 500 million fewer people will be exposed to increased water stress in 2100.

What is the likelihood that over 20% of cropland will experience a decline in suitability?

Chances of an over 20% increase in area of cropland degradation occurring (%)

  • 0-9
  • 10-19
  • 20-29
  • 30-39
  • 40-49
  • 50-59
  • 60-69
  • 70-79
  • 80-89
  • 90-99
  • 100

If we limit global temperature rise to 2°C rather than allowing it to reach 5.2°C, 3.1 million fewer km2 of cropland will become less suitable for farming in 2100.


 

In conclusion

  • In many parts of the world, limiting warming to 2°C rather 5.2°C than can avoid a sizeable proportion of climate impacts.
  • The benefits of mitigation vary geographically, with some regions seeing a greater reduction in impacts than others. This is because the sensitivity to a changing climate varies between regions, and in some regions for some indicators a small change in climate is sufficient for an impacts threshold to be crossed.
  • Under high emissions projections, global average temperature is projected to reach 5.2 degrees above pre-industrial levels by 2100. Limiting warming to less than 2 degrees involves climate action beyond that indicated by pledges proposed by countries to date.
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Footnote

The maps show the chance that regional-scale aggregated impacts exceed defined values: population exposed to river flooding increases by over 25%, population in water stress increases by over 10%, over 20% of cropland experiences a decline in suitability, and more than 25% of population is exposed to heatwaves. Chances are derived from the distribution of impacts in a given year and assume that all of the individual relationships between global mean temperature change and impact are equally plausible. The thresholds are arbitrarily defined, and are all expressed as percentages of some measure of exposure: – for the water and flood indicators they are the same as those used by King et al. (2015) Climate Change: A Risk Assessment . Percentage thresholds are used to enable comparisons between regions and therefore to illustrate the regional variation in impact, but the same percentage thresholds translate into different absolute thresholds in different regions. The chances are calculated assuming population follows SSP2 and the chances would be different under different scenarios. More information on this analysis