India vs Sudan

India vs Sudan: Days above 35 °C

Days above 35 °C in 2014: 80.6 days in India and 184 days in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 103.4 days, or 2.28 times that in India.

days a year · CMIP6

India vs Sudan: Days above 35 °CDays above 35 °C in 2014: 80.6 days in India and 184 days in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 103.4 days, or 2.28 times that in India.
IndiaSudanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Sudan has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts India at 111.9 days and Sudan at 230.7 days in 2100.

Every year

days a year · CMIP6

YearIndiaSudan
201480.6184
201379.2179.8
201281.3180.9
201179.9183.5
201080.8181.3
200978.4175.7
200877173.9
200779171.9
200676.2171.2
200579.9169.5
200480.1171.6
200376.9172.7
200279.2173.6
200180.1177.8
200076.6170.3
199977.1170.7
199876.9166
199775.4169.3
199672.1165.5
199575.4165.1
199476.3162.2
199372.3154.5
199268.7154.3
199178.1165.3
199076.7166.6
198975.5164.1
198873.9164.2
198775.3163.3
198676.8166.1
198573159.7
198475.9158
198374.1157
198276.1155.1
198176.3162.1
198075.3161.1
197974.4160.4
197874.4155.5
197774.6157.9
197676157.3
197571153.9
197475.8155.3
197377.9161.4
197271.1156.2
197174.1153.4
197073.7156.8
196973.3153.8
196872.2154.6
196771.3148.4
196675.3153
196573.7154.2
196468.9148.7
196370.4146.1
196274.2155.9
196175.4158.5
196075.4161.3
195977.9158.4
195874.8156.7
195775.5159.4
195675.6157.7
195574.8154.7
195475.3158.7
195375.2156.3
195276156.1
195176.3158.9
195076.5155.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIndiaSudan
201581.664.7–96183.4158.5–201.6
20168063.1–96.1179.1156.3–200.8
201779.461.7–95.3184.1159.3–204.4
201882.461.5–95.7178.9156–204.1
201979.160.2–95.2181.9158.3–204.8
202082.262.4–99182.3159.2–205.5
202182.167.7–96.4183.1159.4–206.8
202283.962.8–100.3187.9165.4–207.6
202383.164–99.3185.3162.7–207.9
202484.766.4–100.3192.2168–211.3
202581.662.4–97.1188.6166.8–209.3
202684.866.1–101.3188.5157.9–211.8
202783.563.7–102189.2157–211.6
202882.862.9–99.9189.6162.9–211.3
202989.566–105.9190.4166.6–209.3
203084.265.7–100.2191.6170.8–214.6
203185.466.7–103.4192.2167.3–218
203285.665.5–105.3191.2169.9–210.3
203383.865.8–99.8195.3172.4–216.8
203485.467.4–104.8197.1168.8–222.4
203585.766.6–105.3196.4168.7–221.2
203684.565.5–101.8191.3171.4–213.6
203789.772.2–107.5198173.5–220.2
203890.269.1–107.1200.4179.8–221.2
203987.168.5–107.4199.5171.5–218.6
204087.566.6–106196.3172.7–217.9
204189.171.2–107.8202.2174.1–221.8
204295.475.7–112.9201.6175.8–224.1
204391.270.1–111.1198.7169.7–224.3
204490.471.6–110.9198.3173.4–222.2
204591.772–108.5203.4179.1–224.6
204695.469.1–117210.2177.8–229.9
204794.272.6–113.5206.2180.9–228.4
204897.673.2–120.5204.6180–231.3
204995.173.8–117.5204.3178.2–227.3
205094.474.5–117205.3180.8–234.5
205194.775.8–114.7206.2186–229.8
205296.876.1–116.5209182–231.9
205394.673.9–116.7208.7181.2–230.7
205496.574.3–117211180.1–231.4
205599.175.7–118212.3184–233.5
205699.173.7–118.2208.5182.4–235.7
2057100.371.9–123.9213.2186.4–240.1
205897.775.1–121.5213.4183–233.4
2059102.380.5–127.4214.6189.2–242.4
206010380.3–124.4213.7189.1–241.7
2061100.978.4–122.6214.5186.1–239.4
2062100.175.4–126.5214.4187–241.2
2063100.678.3–122.1212.5181.1–235.9
206410081–123.3214.9189.9–242.2
2065103.580.5–128.2217.2195.4–238.5
2066100.780.7–124.6217.1190.9–246.3
206799.678.4–126216.5188.1–243.9
2068102.780.1–130.1216.7193.9–247.6
206910477.5–128.1216.1187.6–243.2
2070101.179.7–125.6219.4189.5–241.3
2071105.581.4–132.1224.1190.5–247.8
2072104.384.4–128.2222.3196.2–245.1
2073108.485.4–130221.8196.1–246.8
2074105.182.9–126.8218.1183.5–249
2075102.578.8–126221.9188.6–243.6
2076105.582.2–134.6222.4196.4–250.8
2077107.484.1–132.6225.8194.6–252.8
2078107.382.8–127.7224.1196.8–250.7
2079105.379.7–127.2220.7194.1–245.3
2080109.784.5–135.9225.9191.3–250
2081108.986.2–134.4225.1197.7–250.3
2082105.783.4–133.6222.6195.3–249.8
2083110.287.8–135.8228.1199.6–251.9
2084111.582.3–138.1224.5194.9–252.9
2085112.381.2–143.6226.3199.3–251.5
2086107.882.8–141.1225.2193.1–258.3
2087107.980.1–134222.9190.2–250.1
2088107.984.4–143.1220.4194.2–256.8
2089107.981.7–137.3227195.7–249.8
2090108.883.9–136.6229198.7–254.5
2091113.486.9–144227196.4–254.1
2092113.587.1–142.8227.2200.5–253.1
2093108.482.7–144.8227.5203–252.1
2094111.386.8–139.5231.9201.3–256
2095114.186.4–143.6228.4202.1–255
209610880.4–140.3226.4198.4–255.9
2097110.385–137.8225.9196.5–255.7
2098113.687.7–141.1227.8194.4–253.4
2099112.585.3–137.7229.5200.7–257.4
2100111.986.8–138.7230.7199.7–256.7

Each country on its own

Good to know

  • Days in a year whose highest temperature passes 35 °C, averaged over the country.
  • Source: World Bank Climate Change Knowledge Portal, CMIP6 multi-model median.
  • The dashed line is the CMIP6 model median (SSP2-4.5, middle of the road), a scenario rather than a forecast; the band is its models’ 10th–90th percentile.
  • Climate model values are the median of the CMIP6 models, run on past emissions to 2014 and on SSP2-4.5, a middle-of-the-road path, after: they are not measurements.

How the layers work, where their data comes from and what they can’t tell you: Countries through time

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