Israel vs Syria

Israel vs Syria: Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 89.6 nights in Syria, in the CMIP6 climate models’ median run. In 2014 the value was higher in Israel, by 8.3 nights, or 1.09 times that in Syria.

nights a year · CMIP6

Israel vs Syria: Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 89.6 nights in Syria, in the CMIP6 climate models’ median run. In 2014 the value was higher in Israel, by 8.3 nights, or 1.09 times that in Syria.
IsraelSyriaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Israel has been higher since 1985, when it overtook Syria.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Israel at 149.4 nights and Syria at 133.8 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelSyria
201497.989.6
20139890.8
201296.391.2
201196.189.6
201095.588.1
200992.586.2
200894.187.9
200792.785
20069287.3
200592.385.3
200490.786.7
200393.986.7
200289.584.3
20019185.9
200089.583.2
199986.282.1
199884.880.5
199784.280.5
199683.778.1
199579.375.8
199480.176.7
199371.671.5
199274.971.3
199178.475.5
199080.279.3
198976.975.7
198876.576.2
198775.173
198678.376
19857472.6
198469.469.6
198368.967.9
198273.572
198173.572
198075.375
197968.767.7
197871.670.2
197772.370.1
197673.273.4
197570.969
197472.570
197371.970.7
197269.970.1
197173.170.7
197071.670.9
196970.671.3
196869.668.7
196766.968.8
196668.868.8
196563.564.3
196466.166.4
196370.969.1
19627371.5
196171.570.8
196074.971.7
19597572.7
19587372.8
195774.872.6
195674.372.2
195572.870.3
195471.468.9
195373.772.2
19527270.8
195175.172.4
195069.568.9
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelSyria
2015105.988.4–122.796.981.9–110.9
2016104.186.9–120.193.581.2–108.2
2017107.892.2–121.49782.1–109.5
201810993.8–124.297.785.9–111
201910989.1–124.598.983.7–111.2
2020111.594.8–123.598.683.7–112.6
202111097.7–128.410087.1–110.7
2022111.493.6–130.2101.684.9–113.2
2023117.297.9–130.5101.988.3–115.3
2024114.5100.4–127.3102.790.7–113.8
2025116.698.3–129.2102.988.6–114.2
2026115.9104.9–126.2103.389.5–116.1
2027115.699–127.1103.886.7–116.5
2028116.3100.2–127.9103.589.2–116.4
2029117103.1–129.2105.694–116.3
2030118.6102.1–131.2105.991.3–119.2
2031116.8104.4–132.8105.190.7–116
2032121.4106.5–134.7107.893.2–119.4
2033122.1108.9–134.7108.796.6–119.1
2034119.7103.1–133.4107.593.9–119
2035122.8105.8–138.8108.596.3–118.3
2036120.2105.5–136.2105.793.2–118.7
2037121.6106.3–139.4109.294.8–121.9
2038126.5105.7–142.1111.897.8–125.5
2039127.7110.5–147.1112.398.9–128
2040124.2109.7–144.9111.898.5–127.5
2041126108.4–141.5110.799.1–124.5
2042128.5105.8–144.3112.996.4–126.5
2043126.5111.8–144.3113.199.7–127.3
2044125.9108.5–142.9112.599.8–128.8
2045130.9117.5–148.6118.4105.5–131.3
2046131114.4–147.2117.2104.7–129
2047132.3116.1–145.4114.9100.6–129.1
2048129.9118.5–146.9114.3101.2–130.8
2049127.9108.7–143.911499.3–128.9
2050133.3114.3–147116.8104.6–132.7
2051130.3116.7–143.9117.7105.5–129
2052130.3119.9–143.5116.2103.9–128.2
2053135120.4–149.7119.1105.2–131.3
2054134.1118.8–149.3119.7102.7–135.5
2055134.1115.2–150.3120.8104.3–134.2
2056136110.1–151.1119.799.9–132.9
2057132.7110.9–155120.6102.3–137.1
2058135.7119.1–155.4120.1103.1–136.5
2059138.8118.5–156.7123.5107.4–137.2
2060136.1116.3–159.2119.6106.4–140.3
2061136119–150.7122.8103.9–136.1
2062139118.7–156121.8104.3–136.5
2063137.4120.1–151.2122.1106.2–136.7
2064139.3121–154.3124.3108.4–136.6
2065139.6122.3–154.3123.7108.9–138.7
2066137.3119.6–153.7122.1104.4–136.2
2067142.8126–157.8126111.1–142.7
2068141.2122.8–156.4126.8112.1–140.3
2069141.5123.7–157.6123107.9–137.3
2070141.8120.5–157.5126.5110.3–139.4
2071142.9124.3–161.8126109.5–142.8
2072144.3127–158.5128111.8–141.9
2073143.6127.3–159.2127.6108–143.7
2074138.8123–162.2124.2107–139.7
2075138.1120.8–154.6124.7109.2–140.6
2076143.2126.8–161.5126.6109.8–140.8
2077142.8120.5–161.6127.5109–143.3
2078143.6128.2–160.6127.2113.3–141.8
2079148.6123.7–160.2132.9116–146.9
2080145.5123.5–163.7129111.8–144.3
2081143.7128.1–161.2127.6112.5–145.6
2082145.8129.5–160.6129.1111.3–143.8
2083149.4126–163.1133.2110.3–144.1
2084148128.2–164132.2111–145.1
2085149127.9–162.4130.9112.7–143.3
2086148127.4–167.1130.9112.6–146.5
2087146.4123.7–165.7129.6109.8–148.7
2088147.6133.5–165.3132.5116.9–146.5
2089148.4131.4–169.1130.4115.3–148.4
2090147.6132.4–168.8128.9115–145.8
2091151.9131.7–170.6133.4116–150.3
2092148.2132–167.4131.6115.3–149
2093154.1135.3–172.2135119.8–151
2094153.2133.6–170.3134118–148.5
2095148.2131.4–164.1134.3117.3–148.9
2096150.5130.5–172.6131.5113.7–148.7
2097149.8134.4–172.7136.2112.7–154.1
2098150.9131.3–170.1131.5115.2–152.2
2099149.5129–166.6132.8116–145.1
2100149.4130.1–168.5133.8113.2–152.2

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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