Israel vs Yemen

Israel vs Yemen: Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 77.9 nights, or 1.8 times that in Israel.

nights a year · CMIP6

Israel vs Yemen: Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 77.9 nights, or 1.8 times that in Israel.
IsraelYemenCMIP6 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 Israel at 149.4 nights and Yemen at 225.7 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelYemen
201497.9175.8
201398176.9
201296.3178.4
201196.1178.3
201095.5174.9
200992.5173.4
200894.1174
200792.7173.9
200692173.6
200592.3172.4
200490.7174.3
200393.9173.5
200289.5171.8
200191172.7
200089.5167.9
199986.2168.6
199884.8168.7
199784.2168.8
199683.7166
199579.3164.3
199480.1161.6
199371.6161.2
199274.9157.2
199178.4166.5
199080.2168.3
198976.9164.3
198876.5163.7
198775.1160.7
198678.3162.3
198574158.2
198469.4159.8
198368.9155.4
198273.5161.5
198173.5161.7
198075.3158.5
197968.7160.1
197871.6158.9
197772.3161.2
197673.2157.5
197570.9156.9
197472.5157.8
197371.9158.1
197269.9157.5
197173.1156.7
197071.6156.9
196970.6157.5
196869.6154.5
196766.9152.1
196668.8155.1
196563.5153.5
196466.1154
196370.9154.7
196273155.9
196171.5158.7
196074.9160.1
195975156.1
195873158.5
195774.8158.1
195674.3156.2
195572.8157.4
195471.4156.1
195373.7155.1
195272157
195175.1155.4
195069.5157.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelYemen
2015105.988.4–122.7180.9163.8–197.8
2016104.186.9–120.1178.4162.7–194.6
2017107.892.2–121.4179.8162.3–196.8
201810993.8–124.2183.2165.3–198.6
201910989.1–124.5179162–200.4
2020111.594.8–123.5181.5163.1–195.9
202111097.7–128.4184.6170.2–202.6
2022111.493.6–130.2184.1167.5–203.7
2023117.297.9–130.5186.8170.1–200.5
2024114.5100.4–127.3185.3168.8–206.4
2025116.698.3–129.2186.5164.7–211.8
2026115.9104.9–126.2187.8167.9–208.8
2027115.699–127.1186.5167.9–205.3
2028116.3100.2–127.9188.2172.3–203.6
2029117103.1–129.2193175.7–211.5
2030118.6102.1–131.2189.4171.6–207.4
2031116.8104.4–132.8193.4176.6–211.5
2032121.4106.5–134.7192.7173.2–213.2
2033122.1108.9–134.7191.2173–209.1
2034119.7103.1–133.4193.1172.1–214.9
2035122.8105.8–138.8193.1174.5–214.1
2036120.2105.5–136.2194177.6–213.5
2037121.6106.3–139.4195.9180.3–212.8
2038126.5105.7–142.1197.6178.5–217.1
2039127.7110.5–147.1194.8179.8–215.4
2040124.2109.7–144.9196.4178.8–220.1
2041126108.4–141.5198.5176.5–216.9
2042128.5105.8–144.3197.3174.4–225.8
2043126.5111.8–144.3198.3179.3–221
2044125.9108.5–142.9198.7180.5–221.9
2045130.9117.5–148.6199.8181.6–220.3
2046131114.4–147.2202.2181.7–229.3
2047132.3116.1–145.4205182.7–229.8
2048129.9118.5–146.9207.4188.8–229.5
2049127.9108.7–143.9203.6186.1–222.5
2050133.3114.3–147202.8186.2–226.3
2051130.3116.7–143.9204.6185.1–229.1
2052130.3119.9–143.5207.2186.9–227.7
2053135120.4–149.7203.9186.1–226.9
2054134.1118.8–149.3208.4188.3–234.9
2055134.1115.2–150.3208.3190.7–228
2056136110.1–151.1208.6188.5–236.3
2057132.7110.9–155208.4190.1–233.1
2058135.7119.1–155.4207.2184.7–236
2059138.8118.5–156.7213.3191.6–239.3
2060136.1116.3–159.2215194.1–235.3
2061136119–150.7209.8189.8–233.3
2062139118.7–156211.4189.6–246.5
2063137.4120.1–151.2215.9193.5–239.5
2064139.3121–154.3212.6194.7–231.7
2065139.6122.3–154.3212.5191.7–241.4
2066137.3119.6–153.7215.6196.9–241.3
2067142.8126–157.8214.6192.2–242.5
2068141.2122.8–156.4217192.5–243.8
2069141.5123.7–157.6216.7196.5–240.8
2070141.8120.5–157.5214.6189–244.5
2071142.9124.3–161.8221.2192.7–244.8
2072144.3127–158.5217.5194.7–239.4
2073143.6127.3–159.2220.5197.7–248.2
2074138.8123–162.2215.3193.3–240.1
2075138.1120.8–154.6220.7195.5–247.6
2076143.2126.8–161.5219.5196.2–243.5
2077142.8120.5–161.6220.8193.8–249.9
2078143.6128.2–160.6220.7198.9–246.9
2079148.6123.7–160.2219.4195.2–249.3
2080145.5123.5–163.7221.7197.8–246
2081143.7128.1–161.2222.4199.1–247
2082145.8129.5–160.6220.1198.5–243
2083149.4126–163.1217.4195.3–258.9
2084148128.2–164223.7195.6–246
2085149127.9–162.4225.1203.3–254.4
2086148127.4–167.1223.1196.5–256
2087146.4123.7–165.7225.8201.1–255.8
2088147.6133.5–165.3224197.1–259.9
2089148.4131.4–169.1225.6200.2–255.2
2090147.6132.4–168.8225.1201.5–253
2091151.9131.7–170.6228.1201.9–261.8
2092148.2132–167.4227.3200.1–261.6
2093154.1135.3–172.2223.6200.9–258.9
2094153.2133.6–170.3223200.3–250.5
2095148.2131.4–164.1228205.2–255.9
2096150.5130.5–172.6225.1201.6–257.9
2097149.8134.4–172.7222.6200.1–251.1
2098150.9131.3–170.1225.6199.6–261
2099149.5129–166.6223.2200.6–251.1
2100149.4130.1–168.5225.7204.7–259.7

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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