6rsta.royalsocietypublishing.orgP h i l .T r a n s .R .S o c .A376:20160452 ........................................................
0–0.2 0.2 0.4 0.6
vulnerability to food insecurity
0.8 1.0 1.2 1.4
Figure1. HungerandClimateVulnerabilityIndexfor1981–2010climate(ensemblemeanacrossthebias-correctedHadGEM3
ensemble).
Table2. ProxiesforfloodanddroughteventsusedintheHCVI.
extremeweatherevent descriptionofproxy
averagelengthoffloodevents numberofdaysinwhichthecumulativedailyrainfallexcessispositive,
comparedwiththe95thpercentileinthe1981–2010average
......................................... ............................................ .......................................... ..................................... ......................................
averagelengthofdroughtevents numberofdaysinwhichthecumulativedailyrainfalldeficitispositive,
comparedwiththe20thpercentileinthe1981–2010average
......................................... ............................................ .......................................... ..................................... ......................................
UN Food and Agriculture Organization, UN Development Programme and UN Population
Fund [ 22]. The exposure component comprised proxies for the average length of ﬂood and
drought events calculated with daily precipitation data [ 23]( table 2). These proxies were chosen
above other possible metrics as they were required to replace self-reported instances of ﬂood
and drought events used in the original HCVI, which correlate with undernutrition data at the
country-level [23]. The proxies were therefore masked to only include data where a signiﬁcant
proportion of people live and grow crops before aggregating to country level and combining to
comprise a measure of exposure [ 23]; nevertheless, it is recognized that precipitation data alone
may not always be adequate for representing ﬂood and drought events, so the current method is
regarded as preliminary.
The impacts of projected climate change, therefore, act through changes in these quantities. In
the current version of the HCVI, climate-change impacts on other quantities such as crop yield
are not considered. Socio-economic factors affecting sensitivity and adaptive capacity are ﬁxed at
present-day conditions.
The ensemble-mean baseline HCVI calculated with the high-resolution bias-corrected
HadGEM3 ensemble is shown in ﬁgure 1 . The spatial pattern is compatible with HCVI values
calculated using reanalysis data at the CMIP5 grid-scale resolution [ 23]; the most vulnerable
regions are sub-Saharan Africa and South Asia. This higher-resolution climate data enables
inclusion of additional countries which were not resolved in the lower-resolution CMIP5 data.