Iran vs Yemen

Iran vs Yemen: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 85 nights, or 1.94 times that in Iran.

nights a year · CMIP6

Iran vs Yemen: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 85 nights, or 1.94 times that in Iran.
IranYemenCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Yemen has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Iran at 124.4 nights and Yemen at 225.7 nights in 2100.

Every year

nights a year · CMIP6

YearIranYemen
201490.8175.8
201390.6176.9
201290.3178.4
201189.8178.3
201087174.9
200987.2173.4
200888174
200787.9173.9
200688.2173.6
200587.1172.4
200486.4174.3
200385.9173.5
200287.7171.8
200186.6172.7
200086.5167.9
199985.1168.6
199883.8168.7
199784.3168.8
199682.4166
199581.6164.3
199480.6161.6
199377.7161.2
199277157.2
199181.9166.5
199083.1168.3
198981.7164.3
198880.4163.7
198779.8160.7
198680.1162.3
198579.7158.2
198478.8159.8
198375.5155.4
198277.9161.5
198180.2161.7
198079.4158.5
197980.2160.1
197878.1158.9
197777.8161.2
197677.2157.5
197576.6156.9
197476.4157.8
197376.9158.1
197277.4157.5
197175156.7
197075.3156.9
196975.6157.5
196876.3154.5
196776.1152.1
196675.5155.1
196575.3153.5
196475.3154
196376.4154.7
196277.5155.9
196177.7158.7
196077.6160.1
195976.8156.1
195878.4158.5
195778.2158.1
195676.2156.2
195576.5157.4
195477.6156.1
195377.3155.1
195278.2157
195176.6155.4
195077.7157.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranYemen
201594.482.7–106180.9163.8–197.8
201694.183.1–105.3178.4162.7–194.6
201793.981.7–104179.8162.3–196.8
201894.183–106.3183.2165.3–198.6
201995.183.4–105.8179162–200.4
202095.985.5–107.5181.5163.1–195.9
202197.286–107.7184.6170.2–202.6
202296.285.2–108.3184.1167.5–203.7
202398.485.7–110.6186.8170.1–200.5
20249885.1–110.5185.3168.8–206.4
202598.787.2–110.5186.5164.7–211.8
202699.186.7–111.7187.8167.9–208.8
2027100.288.7–112.1186.5167.9–205.3
202899.686.2–111.6188.2172.3–203.6
202999.386.7–109.9193175.7–211.5
2030100.889.8–111.6189.4171.6–207.4
2031102.990.1–114.8193.4176.6–211.5
2032101.289–113.9192.7173.2–213.2
2033102.889.9–115.1191.2173–209.1
2034104.690.7–117.3193.1172.1–214.9
203510592.1–116.2193.1174.5–214.1
2036103.591.4–115.2194177.6–213.5
203710693.1–119.4195.9180.3–212.8
2038105.993.2–116.5197.6178.5–217.1
2039104.392.9–116.6194.8179.8–215.4
2040105.592.3–118.4196.4178.8–220.1
2041104.892.5–116.4198.5176.5–216.9
2042107.793.4–120.7197.3174.4–225.8
204310692.9–118.8198.3179.3–221
2044106.893.6–121.2198.7180.5–221.9
2045108.795.1–121.8199.8181.6–220.3
2046109.296.1–121.9202.2181.7–229.3
2047110.596.9–123.3205182.7–229.8
2048111.498.6–124207.4188.8–229.5
204911095.7–123.4203.6186.1–222.5
2050112.199.6–125.1202.8186.2–226.3
2051111.797.6–124.1204.6185.1–229.1
205211298.3–126207.2186.9–227.7
2053111.597.5–124203.9186.1–226.9
2054111.899–126.3208.4188.3–234.9
2055114.6101.4–128208.3190.7–228
2056113.1100.2–126.2208.6188.5–236.3
2057113.899.9–128.9208.4190.1–233.1
2058114.2100–127.7207.2184.7–236
2059113.498.9–126.3213.3191.6–239.3
2060116.3100.3–129.5215194.1–235.3
2061115100.5–127.6209.8189.8–233.3
2062115.799.7–131.1211.4189.6–246.5
2063117103.7–130.3215.9193.5–239.5
2064115.1101.7–130.3212.6194.7–231.7
2065117.3102.8–132.3212.5191.7–241.4
2066117.7103.7–132.1215.6196.9–241.3
2067119103–133.5214.6192.2–242.5
2068118.1104.3–131.4217192.5–243.8
2069118.4103.8–133.2216.7196.5–240.8
2070118.2104.9–132.9214.6189–244.5
2071119.3105.1–135.3221.2192.7–244.8
2072119103.2–135.1217.5194.7–239.4
2073120.6104.9–137.7220.5197.7–248.2
2074119.1104.4–134.5215.3193.3–240.1
2075119.7105.9–135.5220.7195.5–247.6
2076118.9102.6–137219.5196.2–243.5
2077120.3104.3–135.3220.8193.8–249.9
2078119.2105.3–136220.7198.9–246.9
2079120.1103.2–135.6219.4195.2–249.3
2080120.4106.1–139.5221.7197.8–246
2081120.5104.3–137.1222.4199.1–247
2082122.5107.5–137.7220.1198.5–243
2083122.6105.8–140.4217.4195.3–258.9
2084123.7107.6–139.1223.7195.6–246
2085121.3106.6–140.6225.1203.3–254.4
2086122.1107.9–139.8223.1196.5–256
2087123.7108–140.7225.8201.1–255.8
2088124106.5–142.2224197.1–259.9
2089124.1109–139.7225.6200.2–255.2
2090122.5105.4–141.9225.1201.5–253
2091124.3108–140.5228.1201.9–261.8
2092125.5110.1–140227.3200.1–261.6
2093124.5109–139.3223.6200.9–258.9
2094125108.7–142.9223200.3–250.5
2095125.3108.5–141228205.2–255.9
2096125.8109–142.4225.1201.6–257.9
2097123.6106.9–141.8222.6200.1–251.1
2098125.8109.4–143.8225.6199.6–261
2099123.1107.8–140.1223.2200.6–251.1
2100124.4107.9–143.7225.7204.7–259.7

Each country on its own

Good to know

  • Nights in a year when the temperature stays above 20 °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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