Editing IPCC:AR6/SR15/Chapter-3 (section)

== 3.3 Global and Regional Climate Changes and Associated Hazards ==

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This section provides the assessment of changes in climate at 1.5°C of global warming relative to changes at higher global mean temperatures. Section 3.3.1 provides a brief overview of changes to global climate. Sections 3.3.2–3.3.11 provide assessments for specific aspects of the climate system, including regional assessments for temperature (Section 3.3.2) and precipitation (Section 3.3.3) means and extremes. Analyses of regional changes are based on the set of regions displayed in Figure 3.2. A synthesis of the main conclusions of this section is provided in Section 3.3.11. The section builds upon assessments from the IPCC AR5 WGI report (Bindoff et al., 2013a; Christensen et al., 2013; Collins et al., 2013; Hartmann et al., 2013; IPCC, 2013) <sup>[[#fn:r40|40]]</sup> and Chapter 3 of the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX; Seneviratne et al., 2012) <sup>[[#fn:r41|41]]</sup> , as well as a substantial body of new literature related to projections of climate at 1.5°C and 2°C of warming above the pre-industrial period (e.g., Vautard et al., 2014; Fischer and Knutti, 2015; Schleussner et al., 2016b, 2017; Seneviratne et al., 2016, 2018c; Déqué et al., 2017; Maule et al., 2017; Mitchell et al., 2017, 2018a; Wartenburger et al., 2017; Zaman et al., 2017; Betts et al., 2018; Jacob et al., 2018; Kharin et al., 2018; Wehner et al., 2018b) <sup>[[#fn:r42|42]]</sup> . The main assessment methods are as already detailed in Section 3.2.

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'''Figure 3.2'''

<span id="regions-used-for-regional-analyses-provided-in-section-3.3.-the-choice-of-regions-is-based-on-the-ipcc-fifth-assessment-report-ar5-chapter-14-christensen-et-al.-2013-and-annex-1-atlas-and-the-special-report-on-managing-the-risks-of-extreme-events-and-disasters-to-advance-climate-change-adaptation-srex-chapter-3-seneviratne-et"></span>
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'''Regions used for regional analyses provided in Section 3.3. The choice of regions is based on the IPCC Fifth Assessment Report (AR5, Chapter 14, Christensen et al., 2013 and Annex 1: Atlas) and the Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX, Chapter 3, Seneviratne et […]'''
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[[File:5309df6dca2530bbd4822676a65ca03c Figure-3.2-1024x795.jpg]]

Regions used for regional analyses provided in Section 3.3. The choice of regions is based on the IPCC Fifth Assessment Report (AR5, Chapter 14, Christensen et al., 2013 <sup>[[#fn:r43|43]]</sup> and Annex 1: Atlas) and the Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX, Chapter 3, Seneviratne et al., 2012) <sup>[[#fn:r44|44]]</sup> , with seven additional regions in the Arctic, Antarctic and islands not included in the IPCC SREX report (indicated with asterisks). Analyses for regions with asterisks are provided in the Supplementary Material 3.SM.2

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=== 3.3.1 Global Changes in Climate ===

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There is ''high confidence'' that the increase in global mean surface temperature (GMST) has reached 0.87°C (±0.10°C ''likely'' range) above pre-industrial values in the 2006–2015 decade (Chapter 1). AR5 assessed that the globally averaged temperature (combined over land and ocean) displayed a warming of about 0.85°C [0.65°C to 1.06°C] during the period 1880–2012, with a large fraction of the detected global warming being attributed to anthropogenic forcing (Bindoff et al., 2013a; Hartmann et al., 2013; Stocker et al., 2013) <sup>[[#fn:r45|45]]</sup> . While new evidence has highlighted that sampling biases and the choice of approaches used to estimate GMST (e.g., using water versus air temperature over oceans and using model simulations versus observations-based estimates) can affect estimates of GMST increase (Richardson et al., 2016; <sup>[[#fn:r46|46]]</sup> see also Supplementary Material 3.SM.2), the present assessment is consistent with that of AR5 regarding a detectable and dominant effect of anthropogenic forcing on observed trends in global temperature (also confirmed in Ribes et al., 2017) <sup>[[#fn:r47|47]]</sup> . As highlighted in Chapter 1, human-induced warming reached approximately 1°C (±0.2°C ''likely'' range) in 2017. More background on recent observed trends in global climate is provided in the Supplementary Material 3.SM.2.

A global warming of 1.5°C implies higher mean temperatures compared to during pre-industrial times in almost all locations, both on land and in oceans ( ''high confidence'' ) (Figure 3.3). In addition, a global warming of 2°C versus 1.5°C results in robust differences in the mean temperatures in almost all locations, both on land and in the ocean ( ''high confidence'' ). The land–sea contrast in warming is important and implies particularly large changes in temperature over land, with mean warming of more than 1.5°C in most land regions ( ''high confidence'' ; see Section 3.3.2 for more details). The largest increase in mean temperature is found in the high latitudes of the Northern Hemisphere ( ''high confidence'' ; Figure 3.3, see Section 3.3.2 for more details). Projections for precipitation are more uncertain, but they highlight robust increases in mean precipitation in the Northern Hemisphere high latitudes at 1.5ºC global warming versus pre-industrial conditions, as well as at 2ºC global warming versus pre-industrial conditions ( ''high confidence)'' (Figure 3.3). There are consistent but less robust signals when comparing changes in mean precipitation at 2ºC versus 1.5°C of global warming. Hence, it is assessed that there is ''medium confidence'' in an increase of mean precipitation in high-latitudes at 2ºC versus 1.5ºC of global warming (Figure 3.3). For droughts, changes in evapotranspiration and precipitation timing are also relevant (see Section 3.3.4). Figure 3.4 displays changes in temperature extremes (the hottest daytime temperature of the year, TXx, and the coldest night-time temperature of the year, TNn) and heavy precipitation (the annual maximum 5-day precipitation, Rx5day). These analyses reveal distinct patterns of changes, with the largest changes in TXx occurring on mid-latitude land and the largest changes in TNn occurring at high latitudes (both on land and in oceans). Differences in TXx and TNn compared to pre-industrial climate are robust at both global warming levels. Differences in TXx and TNn at 2°C versus 1.5°C of global warming are robust across most of the globe. Changes in heavy precipitation are less robust, but particularly strong increases are apparent at high latitudes as well as in the tropics at both 1.5°C and 2°C of global warming compared to pre-industrial conditions. The differences in heavy precipitation at 2ºC versus 1.5ºC global warming are generally not robust at grid-cell scale, but they display consistent increases in most locations (Figure 3.4). However, as addressed in Section 3.3.3, statistically significant differences are found in several large regions and when aggregated over the global land area. We thus assess that there is ''high confidence'' regarding global-scale differences in temperature means and extremes at 2°C versus 1.5°C global warming, and ''medium confidence'' regarding global-scale differences in precipitation means and extremes. Further analyses, including differences at 1.5°C and 2°C global warming versus 1°C (i.e., present-day) conditions are provided in the Supplementary Material 3.SM.2.

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'''Figure 3.3'''

<span id="projected-changes-in-mean-temperature-top-and-mean-precipitation-bottom-at-1.5c-left-and-2c-middle-of-global-warming-compared-to-the-pre-industrial-period-18611880-and-the-difference-between-1.5c-and-2c-of-global-warming-right."></span>
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'''Projected changes in mean temperature (top) and mean precipitation (bottom) at 1.5°C (left) and 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of global warming (right).'''
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[[File:428f98820d0ddabd99c0c17501450cc4 Figure-3.3-1-1024x528.jpg]]

Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26). Values were assessed from the transient response over a 10-year period at a given warming level, based on Representative Concentration Pathway (RCP)8.5 Coupled Model Intercomparison Project Phase 5 (CMIP5) model simulations (adapted from Seneviratne et al., 2016 <sup>[[#fn:r48|48]]</sup> and Wartenburger et al., 2017 <sup>[[#fn:r49|49]]</sup> , see Supplementary Material 3.SM.2 for more details). Note that the responses at 1.5°C of global warming are similar for RCP2.6 simulations (see Supplementary Material 3.SM.2). Differences compared to 1°C of global warming are provided in the Supplementary Material 3.SM.2.

Original Creation for this Report using CMIP5 multi-model ensemble output data.

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'''Figure 3.4'''

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'''Projected changes in extremes at 1.5°C (left) and 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of global warming (right).'''
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[[File:30449f014aa3614940a5105effb5397a figure-3.4-2-1024x746.jpg]]

Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26): T: temperature of annual hottest day (maximum temperature), TXx (top), and temperature of annual coldest night (minimum temperature), TNn (middle), and annual maximum 5-day precipitation, Rx5day (bottom). The underlying methodology and data basis are the same as for Figure 3.3 (see Supplementary Material 3.SM.2 for more details). Note that the responses at 1.5°C of global warming are similar for Representative Concentration Pathway (RCP) 2.6 simulations (see Supplementary Material 3.SM.2). Differences compared to 1°C of global warming are provided in the Supplementary Material 3.SM.2.

Original Creation for this Report using CMIP5 multi-model ensemble output data.

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These projected changes at 1.5°C and 2°C of global warming are consistent with the attribution of observed historical global trends in temperature and precipitation means and extremes (Bindoff et al., 2013a) <sup>[[#fn:r50|50]]</sup> , as well as with some observed changes under the recent global warming of 0.5°C (Schleussner et al., 2017) <sup>[[#fn:r51|51]]</sup> . These comparisons are addressed in more detail in Sections 3.3.2 and 3.3.3. Attribution studies have shown that there is ''high confidence'' that anthropogenic forcing has had a detectable influence on trends in global warming ( ''virtually certain'' since the mid-20th century), in land warming on all continents except Antarctica ( ''likely'' since the mid-20th century), in ocean warming since 1970 ( ''very likely'' ), and in increases in hot extremes and decreases in cold extremes since the mid-20th century ( ''very likely'' ) (Bindoff et al., 2013a) <sup>[[#fn:r52|52]]</sup> . In addition, there is ''medium confidence'' that anthropogenic forcing has contributed to increases in mean precipitation at high latitudes in the Northern Hemisphere since the mid-20th century and to global-scale increases in heavy precipitation in land regions with sufficient observations over the same period (Bindoff et al., 2013a) <sup>[[#fn:r53|53]]</sup> . Schleussner et al. (2017) <sup>[[#fn:r54|54]]</sup> showed, through analyses of recent observed tendencies, that changes in temperature extremes and heavy precipitation indices are detectable in observations for the 1991–2010 period compared with those for 1960–1979, with a global warming of approximately 0.5°C occurring between these two periods ( ''high confidence'' ). The observed tendencies over that time frame are thus consistent with attributed changes since the mid-20th century ( ''high confidence'' ).

The next sections assess changes in several different types of climate-related hazards. It should be noted that the different types of hazards are considered in isolation but some regions are projected to be affected by collocated and/or concomitant changes in several types of hazards ( ''high confidence'' ). Two examples are sea level rise and heavy precipitation in some regions, possibly leading together to more flooding, and droughts and heatwaves, which can together increase the risk of fire occurrence. Such events, also called compound events, may substantially increase risks in some regions (e.g., AghaKouchak et al., 2014; Van Den Hurk et al., 2015; Martius et al., 2016; Zscheischler et al., 2018) <sup>[[#fn:r55|55]]</sup> . A detailed assessment of physically-defined compound events was not possible as part of this report, but aspects related to overlapping multi-sector risks are highlighted in Sections 3.4 and 3.5.

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=== 3.3.2 Regional Temperatures on Land, Including Extremes ===

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==== 3.3.2.1 Observed and attributed changes in regional temperature means and extremes ====

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While the quality of temperature measurements obtained through ground observational networks tends to be high compared to that of measurements for other climate variables (Seneviratne et al., 2012) <sup>[[#fn:r56|56]]</sup> , it should be noted that some regions are undersampled. Cowtan and Way (2014) <sup>[[#fn:r57|57]]</sup> highlighted issues regarding undersampling, which is most problematic at the poles and over Africa, and which may lead to biases in estimated changes in GMST (see also Supplementary Material 3.SM.2 and Chapter 1). This undersampling also affects the confidence of assessments regarding regional observed and projected changes in both mean and extreme temperature. Despite this partly limited coverage, the attribution chapter of AR5 (Bindoff et al., 2013a) <sup>[[#fn:r58|58]]</sup> and recent papers (e.g., Sun et al., 2016; Wan et al., 2018) <sup>[[#fn:r59|59]]</sup> assessed that, over every continental region and in many sub-continental regions, anthropogenic influence has made a substantial contribution to surface temperature increases since the mid-20th century.

Based on the AR5 and SREX, as well as recent literature (see Supplementary Material 3.SM), there is ''high confidence'' ( ''very likely'' ) that there has been an overall decrease in the number of cold days and nights and an overall increase in the number of warm days and nights at the global scale on land. There is also ''high confidence'' ( ''likely'' ) that consistent changes are detectable on the continental scale in North America, Europe and Australia. There is ''high confidence'' that these observed changes in temperature extremes can be attributed to anthropogenic forcing (Bindoff et al., 2013a) <sup>[[#fn:r60|60]]</sup> . As highlighted in Section 3.2, the observational record can be used to assess past changes associated with a global warming of 0.5°C. Schleussner et al. (2017) <sup>[[#fn:r61|61]]</sup> used this approach to assess observed changes in extreme indices for the 1991–2010 versus the 1960–1979 period, which corresponds to just about a 0.5°C GMST difference in the observed record (based on the Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) dataset, Hansen et al., 2010) <sup>[[#fn:r62|62]]</sup> . They found that substantial changes due to 0.5°C of warming are apparent for indices related to hot and cold extremes, as well as for the Warm Spell Duration Indicator (WSDI). In particular, they identified that one-quarter of the land has experienced an intensification of hot extremes (maximum temperature on the hottest day of the year, TXx) by more than 1°C and a reduction in the intensity of cold extremes by at least 2.5°C (minimum temperature on the coldest night of the year, TNn). In addition, the same study showed that half of the global land mass has experienced changes in WSDI of more than six days, as well as an emergence of extremes outside the range of natural variability (Schleussner et al., 2017) <sup>[[#fn:r63|63]]</sup> . Analyses from Schleussner et al. (2017) <sup>[[#fn:r64|64]]</sup> for temperature extremes are provided in the Supplementary Material 3.SM, Figure 3.SM.6. It should be noted that assessments of attributed changes in the IPCC SREX and AR5 reports were generally provided since 1950, for time frames also approximately corresponding to a 0.5°C global warming (3.SM).

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==== 3.3.2.2 Projected changes in regional temperature means and extremes at 1.5°C versus 2°C of global warming ====

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There are several lines of evidence available for providing a regional assessment of projected changes in temperature means and extremes at 1.5°C versus 2°C of global warming (see Section 3.2). These include: analyses of changes in extremes as a function of global warming based on existing climate simulations using the empirical scaling relationship (ESR) and variations thereof (e.g., Schleussner et al., 2017; Dosio and Fischer, 2018; Seneviratne et al., 2018c <sup>[[#fn:r65|65]]</sup> ; see Section 3.2 for details about the methodology); dedicated simulations of 1.5°C versus 2°C of global warming, for instance based on the Half a degree additional warming, prognosis and projected impacts (HAPPI) experiment (Mitchell et al., 2017) <sup>[[#fn:r66|66]]</sup> or other model simulations (e.g., Dosio et al., 2018; Kjellström et al., 2018) <sup>[[#fn:r67|67]]</sup> ; and analyses based on statistical pattern scaling approaches (e.g., Kharin et al., 2018) <sup>[[#fn:r68|68]]</sup> . These different lines of evidence lead to qualitatively consistent results regarding changes in temperature means and extremes at 1.5°C of global warming compared to the pre-industrial climate and 2°C of global warming.

There are statistically significant differences in temperature means and extremes at 1.5°C versus 2°C of global warming, both in the global average (Schleussner et al., 2016b; Dosio et al., 2018; Kharin et al., 2018) <sup>[[#fn:r69|69]]</sup> , as well as in most land regions ( ''high confidence'' ) (Wartenburger et al., 2017; Seneviratne et al., 2018c; Wehner et al., 2018b) <sup>[[#fn:r70|70]]</sup> . Projected temperatures over oceans display significant increases in means and extremes between 1.5°C and 2°C of global warming (Figures 3.3 and 3.4). A general background on the available evidence on regional changes in temperature means and extremes at 1.5°C versus 2°C of global warming is provided in the Supplementary Material 3.SM.2. As an example, Figure 3.5 shows regionally-based analyses for the IPCC SREX regions (see Figure 3.2) of changes in the temperature of hot extremes as a function of global warming (corresponding analyses for changes in the temperature of cold extremes are provided in the Supplementary Material 3.SM.2). 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., 2016; Wartenburger et al., 2017) <sup>[[#fn:r71|71]]</sup> . 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, 2015; Kharin et al., 2018) <sup>[[#fn:r72|72]]</sup> ; see also Figure 3.6. This behaviour is consistent with a linear increase in absolute temperature for extreme threshold exceedances (Whan et al., 2015) <sup>[[#fn:r73|73]]</sup> .

As mentioned in Section 3.3.1, there is an important land–sea warming contrast, with stronger warming on land (see also Christensen et al., 2013; Collins et al., 2013; Seneviratne et al., 2016) <sup>[[#fn:r74|74]]</sup> , which implies that regional warming on land is generally more than 1.5°C even when mean global warming is at 1.5°C. As highlighted in Seneviratne et al. (2016) <sup>[[#fn:r75|75]]</sup> , this feature is generally stronger for temperature extremes (Figures 3.4 and 3.5; Supplementary Material 3.SM.2 ). For differences in regional temperature extremes at a mean global warming of 1.5°C versus 2°C, that is, a difference of 0.5ºC in global warming, this implies differences of as much as 1°C–1.5°C in some locations, which are two to three times larger than the differences in global mean temperature. 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 3.4 and 3.5) ( ''medium confidence'' ). These regions are all characterized by a strong soil-moisture–temperature coupling and projected increased dryness (Vogel et al., 2017) <sup>[[#fn:r76|76]]</sup> , which leads to a reduction in evaporative cooling in the projections. 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., 2017) <sup>[[#fn:r77|77]]</sup> . 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 3.3 and Figure 3.4, middle) related to the known ‘polar amplification’ mechanism (e.g., IPCC, 2013; Masson-Delmotte et al., 2013) <sup>[[#fn:r78|78]]</sup> .

Figure 3.7 displays maps of changes in the number of hot days (NHD) at 1.5°C and 2°C of GMST increase. Maps of changes in the number of frost days (FD) can be found in Supplementary Material 3.SM.2. These analyses reveal clear patterns of changes between the two warming levels, which are consistent with analysed changes in heatwave occurrence (e.g., Dosio et al., 2018) <sup>[[#fn:r79|79]]</sup> . For the NHD, the largest differences are found in the tropics ( ''high confidence'' ), owing to the low interannual temperature variability there (Mahlstein et al., 2011) <sup>[[#fn:r80|80]]</sup> , although absolute changes in hot temperature extremes tended to be largest at mid-latitudes ( ''high confidence'' ) (Figures 3.4 and 3.5). Extreme heatwaves are thus projected to emerge earliest in the tropics and to become widespread in these regions already at 1.5°C of global warming ( ''high confidence'' ). These results are consistent with other recent assessments. Coumou and Robinson (2013) <sup>[[#fn:r81|81]]</sup> found that 20% of the global land area, centred in low-latitude regions, is projected to experience highly unusual monthly temperatures during Northern Hemisphere summers at 1.5°C of global warming, with this number nearly doubling at 2°C of global warming.

Figure 3.8 features an objective identification of ‘hotspots’ / key risks in temperature indices subdivided by region, based on the ESR approach applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations (Wartenburger et al., 2017) <sup>[[#fn:r82|82]]</sup> . Note that results based on the HAPPI multimodel experiment (Mitchell et al., 2017) <sup>[[#fn:r83|83]]</sup> are similar (Seneviratne et al., 2018c) <sup>[[#fn:r84|84]]</sup> . The considered regions follow the classification used in Figure 3.2 and also include the global land areas. 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.g., there are no ice or frost days), iii) the minimum yearly value of the maximum daily temperature (TXn) in very few regions. In terms of the sign of the changes, warm extremes display an increase in intensity, frequency and duration (e.g., an increase in the temperature of the hottest day of the year (TXx) in all regions, an increase in the proportion of days with a maximum temperature above the 90th percentile of Tmax (TX90p) in all regions, and an increase in the length of the WSDI in all regions), while cold extremes display a decrease in intensity, frequency and duration (e.g., an increase in the temperature of the coldest night of the year (TNn) in all regions, a decrease in the proportion of days with a minimum temperature below the 10th percentile of Tmin (TN10p), and a decrease in the cold spell duration index (CSDI) in all regions). 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 3.5), for both warming scenarios compared to pre-industrial and present-day climate, as well as for 2°C versus 1.5°C GMST warming. For instance, Dosio et al. (2018) <sup>[[#fn:r85|85]]</sup> concluded, based on a modelling study, that 13.8% of the world population would be exposed to ‘severe heatwaves’ at least once every 5 years under 1.5°C of global warming, with a threefold increase (36.9%) under 2°C of GMST warming, corresponding to a difference of about 1.7 billion people between the two global warming levels. They also concluded that limiting global warming to 1.5°C would result in about 420 million fewer people being frequently exposed to extreme heatwaves, and about 65 million fewer people being exposed to ‘exceptional heatwaves’ compared to conditions at 2ºC GMST warming. 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 1.5°C versus 2°C of global warming, both in the global average and in nearly all land regions <sup>[[#fn:6|6]]</sup> ( ''likely'' ). Further, the observational record reveals that substantial changes due to a 0.5°C GMST warming are apparent for indices related to hot and cold extremes, as well as for the WSDI ( ''likely'' ). A global warming of 2°C versus 1.5°C would lead to more frequent and more intense hot extremes in all land regions <sup>[[#fn:7|7]]</sup> , as well as longer warm spells, affecting many densely inhabited regions ( ''very likely'' ). 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'' ). Temperature increases of extreme hot days in mid-latitudes are projected to be up to two times the increase in GMST, that is, 3ºC at 1.5ºC GMST warming ( ''high confidence'' ). 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'' ). The coldest nights in high latitudes warm by as much as 1.5°C for a 0.5°C increase in GMST, corresponding to a threefold stronger warming ( ''high confidence'' ). NHD shows the largest differences between 1.5°C and 2°C in the tropics, because of the low interannual temperature variability there ( ''high confidence'' ); extreme heatwaves are thus projected to emerge earliest in these regions, and they are expected to become widespread already at 1.5°C of global warming ( ''high confidence'' ). Limiting global warming to 1.5°C instead of 2°C could result in around 420 million fewer people being frequently exposed to extreme heatwaves, and about 65 million fewer people being exposed to exceptional heatwaves, assuming constant vulnerability ( ''medium confidence'' ).

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'''Figure 3.5'''

<span id="projected-changes-in-annual-maximum-daytime-temperature-txx-as-a-function-of-global-warming-for-ipcc-special-report-on-managing-the-risk-of-extreme-events-and-disasters-to-advance-climate-change-adaptation-srex-regions-see-figure-3.2-based-on-an-empirical-scaling-relationship-applied-to-coupled-model-intercomparison-project-phase-5-cmip5-data-adapted-from-seneviratne-et-al.-2016-86-and-wartenburger-et-al.-2017-87-together-with-projected-changes-from-the-half-a-degree-additional-warming-prognosis-and-projected-impacts-happi-multimodel-experiment-mitchell-et-al.-2017-88-based-on-analyses-in-seneviratne-et-al.-2018c-89-bar-plots-on-regional-analyses-and-central-plot-respectively."></span>
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'''Projected changes in annual maximum daytime temperature (TXx) as a function of global warming for IPCC Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions (see Figure 3.2), based on an empirical scaling relationship applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) data (adapted from Seneviratne et al., 2016 <sup>[[#fn:r86|86]]</sup> and Wartenburger et al., 2017) <sup>[[#fn:r87|87]]</sup> together with projected changes from the Half a degree additional warming, prognosis and projected impacts (HAPPI) multimodel experiment (Mitchell et al., 2017 <sup>[[#fn:r88|88]]</sup> ; based on analyses in Seneviratne et al., 2018c) <sup>[[#fn:r89|89]]</sup> (bar plots on regional analyses and central plot, respectively).'''
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[[File:9252f14e93b2d56d039676325a83d65b Figure_3_small-1024x717.jpg]]

For analyses for other regions from Figure 3.2 (with asterisks), see Supplementary Material 3.SM.2. (The stippling indicates significance of the differences in changes between 1.5°C and 2°C of global warming based on all model simulations, using a two-sided paired Wilcoxon test (P = 0.01, after controlling the false discovery rate according to Benjamini and Hochberg, 1995) <sup>[[#fn:r90|90]]</sup> . See Supplementary Material 3.SM.2 for details.

<!-- END IMG -->
<div id="section-3-3-2-2-block-3"></div>

<span id="figure-3.6"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.6'''

<span id="probability-ratio-pr-of-exceeding-extreme-temperature-thresholds."></span>
<!-- IMG CAPTION -->
'''Probability ratio (PR) of exceeding extreme temperature thresholds.'''
<!-- IMG FILE -->
[[File:6baf6de9f8862a37c500c13b51df12df Figure_3.6-small-1024x576.jpg]]

(a) PR of exceeding the 99th (blue) and 99.9th (red) percentile of pre-industrial daily temperatures at a given warming level, averaged across land (from Fischer and Knutti, 2015) <sup>[[#fn:r91|91]]</sup> . (b) PR for the hottest daytime temperature of the year (TXx). (c) PR for the coldest night of the year (TNn) for different event probabilities (with RV indicating return values) in the current climate (1°C of global warming). Shading shows the interquartile (25–75%) range (from Kharin et al., 2018) <sup>[[#fn:r92|92]]</sup> .

<!-- END IMG -->
<div id="section-3-3-2-2-block-4"></div>

<span id="figure-3.7"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.7'''

<span id="projected-changes-in-the-number-of-hot-days-nhd-10-warmest-days-at-1.5c-left-and-at-2c-middle-of-global-warming-compared-to-the-pre-industrial-period-18611880-and-the-difference-between-1.5c-and-2c-of-warming-right."></span>
<!-- IMG CAPTION -->
'''Projected changes in the number of hot days (NHD; 10% warmest days) at 1.5°C (left) and at 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of warming (right).'''
<!-- IMG FILE -->
[[File:4bf94f95131bf1bea5e0596fe9177107 Figure_3-small-1024x257.jpg]]

Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26). The underlying methodology and the data basis are the same as for Figure 3.2 (see Supplementary Material 3.SM.2 for more details). Differences compared to 1°C global warming are provided in the Supplementary Material 3.SM.2.

Original Creation for this Report using CMIP5 multi-model ensemble output data.

<!-- END IMG -->
<div id="section-3-3-2-2-block-5"></div>

<span id="figure-3.8"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.8'''

<span id="significance-of-differences-in-regional-mean-temperature-and-range-of-temperature-indices-between-the-1.5c-and-2c-global-mean-temperature-targets-rows."></span>
<!-- IMG CAPTION -->
'''Significance of differences in regional mean temperature and range of temperature indices between the 1.5°C and 2°C global mean temperature targets (rows).'''
<!-- IMG FILE -->
[[File:0c0469ed81921bcdf461eab1024baf70 Figure_3.8-new.jpg]]

Definitions of indices: T: mean temperature; CSDI: cold spell duration index; DTR: diurnal temperature range; FD: frost days; GSL: growing season length; ID: ice days; SU: summer days; TN10p: proportion of days with a minimum temperature (TN) lower than the 10th percentile of TN; TN90p: proportion of days with TN higher than the 90th percentile of TN; TNn: minimum yearly value of TN; TNx: maximum yearly value of TN; TR: tropical nights; TX10p: proportion of days with a maximum temperature (TX) lower than the 10th percentile of TX; TX90p: proportion of days with TX higher than the 90th percentile of TX; TXn: minimum yearly value of TX; TXx: maximum yearly value of TX; WSDI: warm spell duration index. Columns indicate analysed regions and global land (see Figure 3.2 for definitions). Significant differences are shown in red shading, with increases indicated with + and decreases indicated with –, while non-significant differences are shown in grey shading. White shading indicates when an index is the same at the two global warming levels (i.e., zero changes). Note that decreases in CSDI, FD, ID, TN10p and TX10p are linked to increased temperatures on cold days or nights. Significance was tested using a two-sided paired Wilcoxon test (P=0.01, after controlling the false discovery rate according to Benjamini and Hochberg, 1995) <sup>[[#fn:r93|93]]</sup> (adapted from Wartenburger et al., 2017) <sup>[[#fn:r94|94]]</sup> .

Original Creation for this Report using CMIP5 multi-model ensemble output data.

<!-- END IMG -->
<span id="regional-precipitation-including-heavy-precipitation-and-monsoons"></span>
=== 3.3.3 Regional Precipitation, Including Heavy Precipitation and Monsoons ===

<div id="section-3-3-3-block-1"></div>

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.

<div id="section-3-3-3-1"></div>

<span id="observed-and-attributed-changes-in-regional-precipitation"></span>
==== 3.3.3.1 Observed and attributed changes in regional precipitation ====

<div id="section-3-3-3-1-block-1"></div>

Observed global changes in the water cycle, including precipitation, are more uncertain than observed changes in temperature (Hartmann et al., 2013; Stocker et al., 2013) <sup>[[#fn:r95|95]]</sup> . There is ''high confidence'' that mean precipitation over the mid-latitude land areas of the Northern Hemisphere has increased since 1951 (Hartmann et al., 2013) <sup>[[#fn:r96|96]]</sup> . 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., 2013) <sup>[[#fn:r97|97]]</sup> . There is, in particular, ''low confidence'' regarding observed trends in precipitation in monsoon regions, according to the SREX report (Seneviratne et al., 2012) <sup>[[#fn:r98|98]]</sup> and AR5 (Hartmann et al., 2013) <sup>[[#fn:r99|99]]</sup> , as well as more recent publications (Singh et al., 2014; Taylor et al., 2017; Bichet and Diedhiou, 2018; <sup>[[#fn:r100|100]]</sup> see Supplementary Material 3.SM.2).

For heavy precipitation, AR5 (Hartmann et al., 2013) <sup>[[#fn:r101|101]]</sup> assessed that observed trends displayed more areas with increases than decreases in the frequency, intensity and/or amount of heavy precipitation ( ''likely'' ). 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., 2013a) <sup>[[#fn:r102|102]]</sup> .

Regarding changes in precipitation associated with global warming of 0.5°C, the observed record suggests that increases in precipitation extremes can be identified for annual maximum 1-day precipitation (RX1day) and consecutive 5-day precipitation (RX5day) for GMST changes of this magnitude (Supplementary Material 3.SM.2, Figure 3.SM.7; Schleussner et al., 2017) <sup>[[#fn:r103|103]]</sup> . It should be noted that assessments of attributed changes in the IPCC SREX and AR5 reports were generally provided since 1950, for time frames also approximately corresponding to a 0.5°C global warming (3.SM).

<div id="section-3-3-3-2"></div>

<span id="projected-changes-in-regional-precipitation-at-1.5c-versus-2c-of-global-warming"></span>
==== 3.3.3.2 Projected changes in regional precipitation at 1.5°C versus 2°C of global warming ====

<div id="section-3-3-3-2-block-1"></div>

Figure 3.3 in Section 3.3.1 summarizes the projected changes in mean precipitation at 1.5°C and 2°C of global warming. Both warming levels display robust differences in mean precipitation compared to the pre-industrial period. Regarding differences at 2°C vs 1.5°C global warming, some regions are projected to display changes in mean precipitation at 2°C compared with that at 1.5°C of global warming in the CMIP5 multimodel average, such as decreases in the Mediterranean area, including southern Europe, the Arabian Peninsula and Egypt, or increases in high latitudes. The results, however, are less robust across models than for mean temperature. For instance, Déqué et al. (2017) <sup>[[#fn:r104|104]]</sup> investigated the impact of 2°C of global warming on precipitation over tropical Africa and found that average precipitation does not show a significant response, owing to two phenomena: (i) the number of days with rain decreases whereas the precipitation intensity increases, and (ii) the rainy season occurs later during the year, with less precipitation in early summer and more precipitation in late summer. The results from Déqué et al. (2017) <sup>[[#fn:r105|105]]</sup> regarding insignificant differences between 1.5°C and 2°C scenarios for tropical Africa are consistent with the results presented in Figure 3.3. For Europe, recent studies (Vautard et al., 2014; Jacob et al., 2018; Kjellström et al., 2018) <sup>[[#fn:r106|106]]</sup> have shown that 2°C of global warming was associated with a robust increase in mean precipitation over central and northern Europe in winter but only over northern Europe in summer, and with decreases in mean precipitation in central/southern Europe in summer. Precipitation changes reaching 20% have been projected for the 2°C scenario (Vautard et al., 2014) <sup>[[#fn:r107|107]]</sup> and are overall more pronounced than with 1.5°C of global warming (Jacob et al., 2018; Kjellström et al., 2018) <sup>[[#fn:r108|108]]</sup> .

Regarding changes in heavy precipitation, Figure 3.9 displays projected changes in the 5-day maximum precipitation (Rx5day) as a function of global temperature increase, using a similar approach as in Figure 3.5. Further analyses are available in Supplementary Material 3.SM.2. 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., 2014; Seneviratne et al., 2016) <sup>[[#fn:r109|109]]</sup> . As observed for temperature extremes, this response is also mostly independent of the considered emissions scenario (e.g., RCP2.6 versus RCP8.5; see also Section 3.2). 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., 2015) <sup>[[#fn:r110|110]]</sup> .

Robust changes in heavy precipitation compared to pre-industrial conditions are found at both 1.5°C and 2°C global warming (Figure 3.4). 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. (2014) <sup>[[#fn:r111|111]]</sup> found a robust increase in heavy precipitation everywhere in Europe and in all seasons, except southern Europe in summer at 2°C versus 1971–2000. Their findings are consistent with those of Jacob et al. (2014) <sup>[[#fn:r112|112]]</sup> , who used more recent downscaled climate scenarios (EURO-CORDEX) and a higher resolution (12 km), but the change is not so pronounced in Teichmann et al. (2018) <sup>[[#fn:r113|113]]</sup> . There is consistent agreement in the direction of change in heavy precipitation at 1.5°C of global warming over much of Europe, compared to 1971–2000 (Jacob et al., 2018) <sup>[[#fn:r114|114]]</sup> .

Differences in heavy precipitation are generally projected to be small between 1.5°C and 2°C GMST warming (Figure 3.4 and 3.9 and Supplementary Material 3.SM.2, Figure 3.SM.10). Some regions display substantial increases, for instance southern Asia, but generally in less than two-thirds of the CMIP5 models (Figure 3.4, Supplementary Material 3.SM.2, Figure 3.SM.10). Wartenburger et al. (2017) <sup>[[#fn:r115|115]]</sup> suggested that there are substantial differences in heavy precipitation in eastern Asia at 1.5°C versus 2°C. Overall, while there is variation among regions, the global tendency is for heavy precipitation to increase at 2°C compared with at 1.5°C (see e.g., Fischer and Knutti, 2015 <sup>[[#fn:r116|116]]</sup> and Kharin et al., 2018 <sup>[[#fn:r117|117]]</sup> , as illustrated in Figure 3.10 from this chapter; see also Betts et al., 2018) <sup>[[#fn:r118|118]]</sup> .

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., 2013) <sup>[[#fn:r119|119]]</sup> . A few publications provide more recent evaluations of projections of changes in monsoons for high-emission scenarios (e.g., Jiang and Tian, 2013; Jones and Carvalho, 2013; Sylla et al., 2015, 2016 <sup>[[#fn:r120|120]]</sup> ; Supplementary Material 3.SM.2 ). However, scenarios at 1.5°C or 2°C global warming would involve a substantially smaller radiative forcing than those assessed in AR5 and these more recent studies, and there appears to be no specific assessment of changes in monsoon precipitation at 1.5°C versus 2°C of global warming in the literature. 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 1.5°C versus 2°C.

Similar to Figure 3.8, Figure 3.11 features an objective identification of ‘hotspots’ / key risks outlined in heavy precipitation indices subdivided by region, based on the approach by Wartenburger et al. (2017) <sup>[[#fn:r121|121]]</sup> . The considered regions follow the classification used in Figure 3.2 and also include global land areas. Hotspots displaying statistically significant changes in heavy precipitation at 1.5°C versus 2°C global warming are located in high-latitude (Alaska/western Canada, eastern Canada/Greenland/Iceland, northern Europe, northern Asia) and high-elevation (e.g., Tibetan Plateau) regions, as well as in eastern Asia (including China and Japan) and in eastern North America. Results are less consistent for other regions. Note that analyses for meteorological drought (lack of precipitation) are provided in Section 3.3.4.

In summary, observations and projections for mean and heavy precipitation are less robust than for temperature means and extremes ( ''high confidence'' ). Observations show that there are more areas with increases than decreases in the frequency, intensity and/or amount of heavy precipitation ''(high confidence'' ). Several large regions display statistically significant differences in heavy precipitation at 1.5°C versus 2°C GMST warming, with stronger increases at 2°C global warming, and there is a global tendency towards increases in heavy precipitation on land at 2°C compared with 1.5°C warming ( ''high confidence'' ). Overall, regions that display statistically significant changes in heavy precipitation between 1.5°C and 2°C of global warming are located in high latitudes (Alaska/western Canada, eastern Canada/Greenland/Iceland, northern Europe, northern Asia) and high elevation (e.g., Tibetan Plateau), as well as in eastern Asia (including China and Japan) and in eastern North America ( ''medium confidence'' ). There is ''low confidence'' in projected changes in heavy precipitation in other regions.

<div id="section-3-3-3-2-block-2"></div>

<span id="figure-3.9"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.9'''

<span id="projected-changes-in-annual-5-day-maximum-precipitation-rx5day-as-a-function-of-global-warming-for-ipcc-special-report-on-the-risk-of-extreme-events-and-disasters-to-advance-climate-change-adaptation-srex-regions-see-figure-3.2-based-on-an-empirical-scaling-relationship-applied-to-coupled-model-intercomparison-project-phase-5-cmip5-data-together-with-projected-changes-from-the-happi-multimodel-experiment-bar-plots-on-regional-analyses-and-central-plot."></span>
<!-- IMG CAPTION -->
'''Projected changes in annual 5-day maximum precipitation (Rx5day) as a function of global warming for IPCC Special Report on the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions (see Figure 3.2), based on an empirical scaling relationship applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) data together with projected changes from the HAPPI multimodel experiment (bar plots on regional analyses and central plot).'''
<!-- IMG FILE -->
[[File:afca31b63df59751f076ed3ca3f77b21 Figure_3.9-1024x733.jpg]]

The underlying methodology and data basis are the same as for Figure 3.5 (see Supplementary Material 3.SM.2 for more details).

Original Creation for this Report using CMIP5 multi-model ensemble output, HAPPI Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) model intercomparison project

<!-- END IMG -->
<div id="section-3-3-3-2-block-3"></div>

<span id="figure-3.10"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.10'''

<span id="probability-ratio-pr-of-exceeding-heavy-precipitation-thresholds."></span>
<!-- IMG CAPTION -->
'''Probability ratio (PR) of exceeding (heavy precipitation) thresholds.'''
<!-- IMG FILE -->
[[File:01d5a0bd8735a97d388ee703a9c79a2f Figure_3.10-1024x576.jpg]]

(a) PR of exceeding the 99th (blue) and 99.9th (red) percentile of pre-industrial daily precipitation at a given warming level, averaged across land (from Fischer and Knutti, 2015) <sup>[[#fn:r122|122]]</sup> . (b) PR for precipitation extremes (RX1day) for different event probabilities (with RV indicating return values) in the current climate (1°C of global warming). Shading shows the interquartile (25–75%) range (from Kharin et al., 2018) <sup>[[#fn:r123|123]]</sup> .

<!-- END IMG -->
<div id="section-3-3-3-2-block-4"></div>

<span id="figure-3.11"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.11'''

<span id="significance-of-differences-in-regional-mean-precipitation-and-range-of-precipitation-indices-between-the-1.5c-and-2c-global-mean-temperature-targets-rows."></span>
<!-- IMG CAPTION -->
'''Significance of differences in regional mean precipitation and range of precipitation indices between the 1.5°C and 2°C global mean temperature targets (rows).'''
<!-- IMG FILE -->
[[File:288b54c4bcd6a693ddf27e40e1992eb4 Figure_3.11-1024x452.png]]

Definition of indices: PRCPTOT: mean precipitation; CWD: consecutive wet days; R10mm: number of days with precipitation &gt;10 mm; R1mm: number of days with precipitation &gt;1 mm; R20mm: number of days with precipitation &gt;20 mm; R95ptot: proportion of rain falling as 95th percentile or higher; R99ptot: proportion of rain falling as 99th percentile or higher; RX1day: intensity of maximum yearly 1-day precipitation; RX5day: intensity of maximum yearly 5-day precipitation; SDII: Simple Daily Intensity Index. Columns indicate analysed regions and global land (see Figure 3.2 for definitions). Significant differences are shown in light blue (wetting tendency) or brown (drying tendency) shading, with increases indicated with ‘+’ and decreases indicated with ‘–’, while non-significant differences are shown in grey shading. The underlying methodology and the data basis are the same as in Figure 3.8 (see Supplementary Material 3.SM.2 for more details).

Original Creation for this Report using CMIP5 multi-model ensemble output data.

<!-- END IMG -->
<span id="drought-and-dryness"></span>
=== 3.3.4 Drought and Dryness ===

<div id="section-3-3-4-1"></div>

<span id="observed-and-attributed-changes"></span>
==== 3.3.4.1 Observed and attributed changes ====

<div id="section-3-3-4-1-block-1"></div>

The IPCC AR5 assessed that there was ''low confidence'' in the sign of drought trends since 1950 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., 2013; Stocker et al., 2013) <sup>[[#fn:r124|124]]</sup> . 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., 2013a) <sup>[[#fn:r125|125]]</sup> .

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, 2016; Gudmundsson et al., 2017) <sup>[[#fn:r126|126]]</sup> . 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.

<div id="section-3-3-4-1-block-2" class="box"></div>

<span id="box-3.1-sub-saharan-africa-changes-in-temperature-and-precipitation-extremes"></span>