18rsta.royalsocietypublishing.orgP h i l .T r a n s .R .S o c .A376:20160452 ........................................................
(b)
(d)
(a) TXx (°C)
CDD (days)
1.5°C 2°C
TX90p (% time)
RX5day (mm)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0
2.0
0.0
–2.0
–4.0
–6.0
IPSL-CM5A-LR IPSL-CM5A-MRGFDL-ESM2M
MIROC-ESM-CHEM
ACCESS1-0ensemble meanHadGEM2-ES IPSL-CM5A-LR IPSL-CM5A-MRGFDL-ESM2M
MIROC-ESM-CHEM
ACCESS1-0ensemble meanHadGEM2-ES
IPSL-CM5A-LR IPSL-CM5A-MRGFDL-ESM2M
MIROC-ESM-CHEM
ACCESS1-0ensemble meanHadGEM2-ES
IPSL-CM5A-LR IPSL-CM5A-MRGFDL-ESM2M
MIROC-ESM-CHEM
ACCESS1-0ensemble meanHadGEM2-ES
8.0
6.0
4.0
2.0
0
35
30
25
20
15
10
5
0
(c)
Figure 12.Comparison of global mean changes in climate extremes indices relative to 1981–2010 at 2°Ca n d1 . 5°Cg l o b a l
warming for individual ensemble members and ensemble mean. (a) Change in annual daily maximum temperature;
(b)percentageofdayswithmaximumtemperatureabove90thpercentilefor1981–2010;( c)changeinconsecutivedrydays;
(d)changeinannualmaximum5-dayrainfall.
For precipitation, generally similar changes are seen at 1.5°C global warming as at 2°C, but
smaller in magnitude (compare ﬁgures 16 and 4), suggesting that most of these changes are a
response to radiatively forced climate change as opposed to internal climate variability. However,
some localized changes do vary in sign between the GWLs, such as in South Australia, suggesting
a possible dominance of internal variability over the global warming signal in these places.
Where Rx5day increases, the increases are projected to be larger—in some cases approximately
double—at 2°C global warming than 1.5°C. Where Rx5day decreases, again the decreases are
projected to be larger at 2°C global warming than 1.5°C (ﬁgure 17).
Of the 122 countries assessed, 93 have smaller ensemble-mean HCVI calculated at 1.5°C global
warming than at 2°C, indicating an ensemble consensus that 76% of assessed countries would
see a smaller increase in vulnerability to food insecurity if global warming were limited to 1.5°C
(ﬁgures 18 and 19). Conversely, 24% of countries would, by this metric, see the same or higher
vulnerability to food insecurity at 1.5°C than 2°C. Of these, some are countries where HCVI
is projected to be lower at 2°C global warming than in the baseline. For example, in Mali the
ensemble-mean baseline HCVI of 0.83 increased slightly to 0.85 at 1.5°C then reduced to 0.81
at 2°C. In some countries, the ensemble-mean HCVI happened to be identical at both warming
levels. In Chad, for example, the baseline HCVI of 0.89 increased to 0.91 at both 1.5°C and 2°C.
As noted above, four countries saw ensemble-mean HCVI values at 2°C above any seen
in the baseline, and this number increased to seven at 1.5°C. The same four countries with
‘unprecedented’ HCVI values at 2°C also saw ‘unprecedented’ values at 1.5°C; these were Oman,
Bangladesh, Mauritania and Yemen. These were joined by Myanmar, India and Cambodia as
having ‘unprecedented’ values at 1.5°C. The role of internal climate variability in the HCVI
results needs to be assessed, as does the effect of potential nonlinear interactions between the
ﬂood and drought metric. Until the reasons behind these country-speciﬁc results are understood,