Israel vs Jordan

Israel vs Jordan: Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 74.7 nights in Jordan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Israel, by 23.3 nights, or 1.31 times that in Jordan.

nights a year · CMIP6

Israel vs Jordan: Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 74.7 nights in Jordan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Israel, by 23.3 nights, or 1.31 times that in Jordan.
IsraelJordanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Israel 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 Jordan at 131.7 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelJordan
201497.974.7
20139872.2
201296.371.9
201196.171.4
201095.571.4
200992.566.9
200894.169.4
200792.764.6
20069267.7
200592.366.2
200490.767.4
200393.968.2
200289.563
20019168.3
200089.563.8
199986.262.2
199884.861.8
199784.259.2
199683.756.6
199579.354.1
199480.154.6
199371.645.2
199274.948.3
199178.452.3
199080.257.7
198976.953.4
198876.550.5
198775.149.5
198678.352
19857447.1
198469.444.2
198368.941.5
198273.547.4
198173.548.3
198075.349.2
197968.741.8
197871.645.1
197772.346.7
197673.245.6
197570.943
197472.545.1
197371.944.6
197269.944.8
197173.147.2
197071.644.3
196970.646.3
196869.642.6
196766.941.5
196668.843
196563.536.8
196466.137.7
196370.943
19627345
196171.545.4
196074.946.3
19597546.3
19587347.2
195774.848.7
195674.348.4
195572.845.5
195471.442.7
195373.747.8
19527245.7
195175.145
195069.541.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelJordan
2015105.988.4–122.781.862.6–98.9
2016104.186.9–120.179.261.3–95.2
2017107.892.2–121.482.466.3–96.6
201810993.8–124.284.868.8–102.1
201910989.1–124.587.467.5–100.7
2020111.594.8–123.586.866.8–102.2
202111097.7–128.488.273.8–101.1
2022111.493.6–130.288.170–103.7
2023117.297.9–130.592.474.7–106.4
2024114.5100.4–127.390.776.3–107.1
2025116.698.3–129.294.173.1–105.2
2026115.9104.9–126.291.678.6–106.9
2027115.699–127.194.475.7–108.4
2028116.3100.2–127.992.675.9–106.3
2029117103.1–129.295.381.2–107.3
2030118.6102.1–131.296.381.5–111.7
2031116.8104.4–132.893.876.5–110.6
2032121.4106.5–134.710086.4–110.9
2033122.1108.9–134.7100.683.6–113.6
2034119.7103.1–133.498.882.4–112.3
2035122.8105.8–138.8101.883.2–115.2
2036120.2105.5–136.297.885.1–116.2
2037121.6106.3–139.410384.6–117.8
2038126.5105.7–142.1102.386.1–122.6
2039127.7110.5–147.1107.190.5–125.7
2040124.2109.7–144.9106.387.8–125.5
2041126108.4–141.5103.787.8–123.2
2042128.5105.8–144.3108.586.5–122.3
2043126.5111.8–144.3105.791–124.9
2044125.9108.5–142.9105.682.8–125.1
2045130.9117.5–148.611298.8–128
2046131114.4–147.211395.5–127.5
2047132.3116.1–145.4112.293–125.7
2048129.9118.5–146.9111.893.7–129.7
2049127.9108.7–143.9110.384.7–125.6
2050133.3114.3–147112.495.9–127.2
2051130.3116.7–143.9112.397–125.6
2052130.3119.9–143.5110.697.4–125.9
2053135120.4–149.7113.798.2–129.9
2054134.1118.8–149.3115.492.5–130.9
2055134.1115.2–150.3115.794.8–130.2
2056136110.1–151.1115.394.2–130.5
2057132.7110.9–155115.496.7–135.6
2058135.7119.1–155.4116.196.6–136.8
2059138.8118.5–156.7120.998.5–137.1
2060136.1116.3–159.2115.898.7–138.7
2061136119–150.7118.897.1–132.3
2062139118.7–15612091.6–136.4
2063137.4120.1–151.2118.7101.7–135.9
2064139.3121–154.3121.4103.3–135.9
2065139.6122.3–154.3120.2100.4–134.9
2066137.3119.6–153.7120.498.5–135
2067142.8126–157.8124106.1–139.5
2068141.2122.8–156.4123.2105.3–138.1
2069141.5123.7–157.6118.8105.4–137.2
2070141.8120.5–157.5123104–140.8
2071142.9124.3–161.8123.6103.8–144.3
2072144.3127–158.5124.5106.3–140.9
2073143.6127.3–159.2126.6104.8–144.4
2074138.8123–162.2120.9103–139.6
2075138.1120.8–154.6121.7103.1–138.1
2076143.2126.8–161.5124.1105.4–144.2
2077142.8120.5–161.6124.2105.3–143.9
2078143.6128.2–160.6124.7105.6–142.8
2079148.6123.7–160.2132107–143.6
2080145.5123.5–163.7128.9106.2–144.4
2081143.7128.1–161.2125.3108.7–144.8
2082145.8129.5–160.6128107.9–145.2
2083149.4126–163.1130.9108–144.7
2084148128.2–164130.5110.6–145
2085149127.9–162.4129.1108.8–141.7
2086148127.4–167.1127.5108.9–147.6
2087146.4123.7–165.7129.8106.1–148.4
2088147.6133.5–165.3132.2114.9–149.4
2089148.4131.4–169.1128.7113.4–148.5
2090147.6132.4–168.8128.2111.9–151.3
2091151.9131.7–170.6132.8112.5–152.1
2092148.2132–167.4130.6108.3–152.6
2093154.1135.3–172.2135.8116.2–154.4
2094153.2133.6–170.3135.9116.3–150.6
2095148.2131.4–164.1133112.7–149.6
2096150.5130.5–172.6130.4108.1–151.3
2097149.8134.4–172.7134.5113.5–155.4
2098150.9131.3–170.1132.5114.9–152.3
2099149.5129–166.6132.1115.3–145.3
2100149.4130.1–168.5131.7111.2–153.1

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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