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. 2012 Jan 10;114(3-4):813-822.
doi: 10.1007/s10584-012-0570-x.

Climate change hotspots in the CMIP5 global climate model ensemble

Noah S Diffenbaugh  1 , Filippo Giorgi
Affiliations

Climate change hotspots in the CMIP5 global climate model ensemble

Noah S Diffenbaugh et al. Clim Change. .

Abstract

We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21st century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20th-century baseline), but not at the higher levels of global warming that occur in the late-21st-century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

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Figures

Fig. 1
Fig. 1
The relative aggregate climate change between the 1986–2005 period and the 2016–2035, 2046–2065 and 2080–2099 periods of RCP8.5 and RCP4.5. The aggregate climate change is calculated using the Standard Euclidean Distance (SED) across the 28-dimensional climate space formed by 7 climate indicators in each of 4 seasons. Prior to calculating the SED, the absolute values of change in each climate indicator are normalized to the maximum global absolute value in the 2080–2099 period of RCP8.5. Only land grid points north of 60°S are used in the normalization. The median global temperature change above the late 20th century baseline is given from Rogelj et al. (2012) in the lower left corner of each panel
Fig. 2
Fig. 2
The change in December-January-February (DJF) and June-July-August (JJA) surface air temperature and precipitation between the 1986–2005 period and the 2080–2099 period of RCP8.5 in the CMIP5 ensemble
Fig. 3
Fig. 3
The occurrence of the 1986–2005 maximum June-July-August (JJA) seasonal temperature in the 2016–2035, 2046–2065 and 2080–2099 periods of RCP8.5 (left) and RCP4.5 (right). The panels show the absolute occurrences as the percent of years in each 20-year period. The frequency of occurrence of the 1986–2005 maximum JJA seasonal temperature value is, by definition, 5 % at each grid point during the 20-year 1986–2005 period
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