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As demonstrated in these analyses, the mean response of the intensity of temperature extremes in climate models to changes in the global mean temperature is approximately linear and independent of the considered emissions scenario Seneviratne et al. Nonetheless, in the case of changes in the number of days exceeding a given threshold, changes are approximately exponential, with higher increases for rare events Fischer and Knutti, ; Kharin et al. This behaviour is consistent with a linear increase in absolute temperature for extreme threshold exceedances Whan et al.

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As mentioned in Section 3. As highlighted in Seneviratne et al. For differences in regional temperature extremes at a mean global warming of 1. For hot extremes, the strongest warming is found in central and eastern North America, central and southern Europe, the Mediterranean, western and central Asia, and southern Africa Figures 3. These regions are all characterized by a strong soil-moisture—temperature coupling and projected increased dryness Vogel et al.

Some of these regions also show a wide range of responses to temperature extremes, in particular central Europe and central North America, owing to discrepancies in the representation of the underlying processes in current climate models Vogel et al. For mean temperature and cold extremes, the strongest warming is found in the northern high-latitude regions high confidence. This is due to substantial ice-snow-albedo-temperature feedbacks Figure 3. Maps of changes in the number of frost days FD can be found in Supplementary Material 3.

These analyses reveal clear patterns of changes between the two warming levels, which are consistent with analysed changes in heatwave occurrence e. For the NHD, the largest differences are found in the tropics high confidence , owing to the low interannual temperature variability there Mahlstein et al. Extreme heatwaves are thus projected to emerge earliest in the tropics and to become widespread in these regions already at 1. These results are consistent with other recent assessments.


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The considered regions follow the classification used in Figure 3. Based on these analyses, the following can be stated: significant changes in responses are found in all regions for most temperature indices, with the exception of i the diurnal temperature range DTR in most regions, ii ice days ID , frost days FD and growing season length GSL mostly in regions where differences are zero, because, e.

In terms of the sign of the changes, warm extremes display an increase in intensity, frequency and duration e. Hence, while warm extremes are intensified, cold extremes become less intense in affected regions. Overall, large increases in hot extremes occur in many densely inhabited regions Figure 3. For instance, Dosio et al. They also concluded that limiting global warming to 1. However, changes in vulnerability were not considered in their study.

For this reason, we assess that there is medium confidence in their conclusions. In summary, there is high confidence that there are robust and statistically significant differences in the projected temperature means and extremes at 1. Further, the observational record reveals that substantial changes due to a 0. The strongest increases in the frequency of hot extremes are projected for the rarest events very likely. On the other hand, cold extremes would become less intense and less frequent, and cold spells would be shorter very likely.

Temperature extremes on land would generally increase more than the global average temperature very likely. The highest levels of warming for extreme hot days are expected to occur in central and eastern North America, central and southern Europe, the Mediterranean, western and central Asia, and southern Africa medium confidence.

These regions have a strong soil-moisture-temperature coupling in common as well as increased dryness and, consequently, a reduction in evaporative cooling. However, there is a substantial range in the representation of these processes in models, in particular in central Europe and central North America medium confidence.


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The coldest nights in high latitudes warm by as much as 1. NHD shows the largest differences between 1. For analyses for other regions from Figure 3. The stippling indicates significance of the differences in changes between 1. See Supplementary Material 3. The underlying methodology and the data basis are the same as for Figure 3.

Chapter 3 — Global Warming of ºC

Columns indicate analysed regions and global land see Figure 3. White shading indicates when an index is the same at the two global warming levels i.

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This section addresses regional changes in precipitation on land, with a focus on heavy precipitation and consideration of changes to the key features of monsoons. Observed global changes in the water cycle, including precipitation, are more uncertain than observed changes in temperature Hartmann et al. There is high confidence that mean precipitation over the mid-latitude land areas of the Northern Hemisphere has increased since Hartmann et al.

For other latitudinal zones, area-averaged long-term positive or negative trends have low confidence because of poor data quality, incomplete data or disagreement amongst available estimates Hartmann et al. There is, in particular, low confidence regarding observed trends in precipitation in monsoon regions, according to the SREX report Seneviratne et al. For heavy precipitation, AR5 Hartmann et al. In addition, for land regions where observational coverage is sufficient for evaluation, it was assessed that there is medium confidence that anthropogenic forcing has contributed to a global-scale intensification of heavy precipitation over the second half of the 20th century Bindoff et al.

Regarding changes in precipitation associated with global warming of 0. Both warming levels display robust differences in mean precipitation compared to the pre-industrial period. The results, however, are less robust across models than for mean temperature.

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For Europe, recent studies Vautard et al. Regarding changes in heavy precipitation, Figure 3.

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Further analyses are available in Supplementary Material 3. These analyses show that projected changes in heavy precipitation are more uncertain than those for temperature extremes. However, the mean response of model simulations is generally robust and linear see also Fischer et al. As observed for temperature extremes, this response is also mostly independent of the considered emissions scenario e. This feature appears to be specific to heavy precipitation, possibly due to a stronger coupling with temperature, as the scaling of projections of mean precipitation changes with global warming shows some scenario dependency Pendergrass et al.

Robust changes in heavy precipitation compared to pre-industrial conditions are found at both 1. This is also consistent with results for, for example, the European continent, although different indices for heavy precipitation changes have been analysed. Based on regional climate simulations, Vautard et al.

Their findings are consistent with those of Jacob et al. There is consistent agreement in the direction of change in heavy precipitation at 1. Differences in heavy precipitation are generally projected to be small between 1. Some regions display substantial increases, for instance southern Asia, but generally in less than two-thirds of the CMIP5 models Figure 3. Wartenburger et al. AR5 assessed that the global monsoon, aggregated over all monsoon systems, is likely to strengthen, with increases in its area and intensity, while the monsoon circulation weakens Christensen et al.

A few publications provide more recent evaluations of projections of changes in monsoons for high-emission scenarios e. However, scenarios at 1. Consequently, the current assessment is that there is low confidence regarding changes in monsoons at these lower global warming levels, as well as regarding differences in monsoon responses at 1. Similar to Figure 3. Hotspots displaying statistically significant changes in heavy precipitation at 1.

Results are less consistent for other regions. Note that analyses for meteorological drought lack of precipitation are provided in Section 3. In summary, observations and projections for mean and heavy precipitation are less robust than for temperature means and extremes high confidence. Several large regions display statistically significant differences in heavy precipitation at 1.

Overall, regions that display statistically significant changes in heavy precipitation between 1. There is low confidence in projected changes in heavy precipitation in other regions. The underlying methodology and the data basis are the same as in Figure 3. The IPCC AR5 assessed that there was low confidence in the sign of drought trends since at the global scale, but that there was high confidenc e in observed trends in some regions of the world, including drought increases in the Mediterranean and West Africa and drought decreases in central North America and northwest Australia Hartmann et al.

AR5 assessed that there was low confidence in the attribution of global changes in droughts and did not provide assessments for the attribution of regional changes in droughts Bindoff et al. The recent literature does not suggest that the SREX and AR5 assessment of drought trends should be revised, except in the Mediterranean region.

Recent publications based on observational and modelling evidence suggest that human emissions have substantially increased the probability of drought years in the Mediterranean region Gudmundsson and Seneviratne, ; Gudmundsson et al. Based on this evidence, there is medium confidence that enhanced greenhouse forcing has contributed to increased drying in the Mediterranean region including southern Europe, northern Africa and the Near East and that this tendency will continue to increase under higher levels of global warming.

There is medium confidence in projections of changes in drought and dryness. However, given this medium confidence , the current assessment does not include a likelihood statement, thereby maintaining consistency with the IPCC uncertainty guidance document Mastrandrea et al. The technical summary of AR5 Stocker et al. However, more recent assessments have highlighted uncertainties in dryness projections due to a range of factors, including variations between the drought and dryness indices considered, and the effects of enhanced CO 2 concentrations on plant water-use efficiency Orlowsky and Seneviratne, ; Roderick et al.

Overall, projections of changes in drought and dryness for high-emissions scenarios e. Uncertainty is expected to be even larger for conditions with a smaller signal-to-noise ratio, such as for global warming levels of 1. Some published literature is now available on the evaluation of differences in drought and dryness occurrence at 1. These analyses have produced consistent findings overall, despite the known sensitivity of drought assessments to chosen drought indices see above paragraph.

These analyses suggest that increases in drought, dryness or precipitation deficits are projected at 1. Generally, the clearest signals are found for the Mediterranean region medium confidence.

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Greve et al. The simulations analysed span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear dependencies on global temperature changes while thoroughly addressing associated uncertainties via resampling methods.