Syria vs Tunisia

Syria vs Tunisia: Tropical nights

Tropical nights in 2014: 89.6 nights in Syria and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 20.9 nights, or 1.23 times that in Syria.

nights a year · CMIP6

Syria vs Tunisia: Tropical nightsTropical nights in 2014: 89.6 nights in Syria and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 20.9 nights, or 1.23 times that in Syria.
SyriaTunisiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Tunisia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Syria at 133.8 nights and Tunisia at 143.8 nights in 2100.

Every year

nights a year · CMIP6

YearSyriaTunisia
201489.6110.5
201390.8110.7
201291.2110
201189.6108.9
201088.1109.6
200986.2106.1
200887.9108.6
200785106.6
200687.3107.6
200585.3105.6
200486.7105
200386.7105.5
200284.3103.8
200185.9101.8
200083.2104.5
199982.1100.1
199880.5100.1
199780.5100.1
199678.199.1
199575.895.9
199476.795
199371.591.3
199271.389.9
199175.598.2
199079.398.6
198975.794.7
198876.294.2
19877392.7
19867693.7
198572.690.6
198469.691.8
198367.990
19827293.9
19817293.3
19807592.5
197967.793.8
197870.290.2
197770.188.3
197673.490.5
19756988.6
19747088.3
197370.790.5
197270.191
197170.788.8
197070.987.3
196971.390.1
196868.788.9
196768.887.6
196668.887.5
196564.384.5
196466.485.7
196369.188
196271.592.7
196170.888.3
196071.790.7
195972.792.2
195872.891.8
195772.692.3
195672.290
195570.392.7
195468.989.9
195372.289.4
195270.891.8
195172.491.6
195068.989.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearSyriaTunisia
201596.981.9–110.9110.796.9–126.1
201693.581.2–108.2111.596.6–130.1
20179782.1–109.5116.5102.4–131.8
201897.785.9–111115.999.4–131.9
201998.983.7–111.2116.598.5–129.5
202098.683.7–112.6113.899.9–130.1
202110087.1–110.7117.4104.1–129.3
2022101.684.9–113.2119.7103–137.3
2023101.988.3–115.3118.7102.2–131.9
2024102.790.7–113.8121107.5–132.6
2025102.988.6–114.2120.2100–134
2026103.389.5–116.1122.1110.1–134.5
2027103.886.7–116.5119103.6–134.1
2028103.589.2–116.4121.1104.5–135.4
2029105.694–116.3121.5110.2–135.8
2030105.991.3–119.2121.6104–133.4
2031105.190.7–116121.8105.7–134.9
2032107.893.2–119.4125.2111.6–138.9
2033108.796.6–119.1124.7107.6–137.5
2034107.593.9–119124.6107–141.7
2035108.596.3–118.3126.3115.5–142.6
2036105.793.2–118.7126112.5–141.9
2037109.294.8–121.9126.5110–140
2038111.897.8–125.5126.2111.1–139.1
2039112.398.9–128127112.5–142.3
2040111.898.5–127.5127.5112.8–144.3
2041110.799.1–124.5125.5109.1–140.4
2042112.996.4–126.5129.9114.8–145.8
2043113.199.7–127.3129.1111.6–142
2044112.599.8–128.8127.1112.8–141.8
2045118.4105.5–131.3128.5113.8–140.8
2046117.2104.7–129128.3109.9–144
2047114.9100.6–129.1131.2113.6–147.5
2048114.3101.2–130.8129.9114.9–142.3
204911499.3–128.9130115.4–143.5
2050116.8104.6–132.7132.3117.6–147.6
2051117.7105.5–129130.1112.6–148.6
2052116.2103.9–128.2132.7116.8–146.7
2053119.1105.2–131.3132.5119.5–149.8
2054119.7102.7–135.5135.2118.4–148.8
2055120.8104.3–134.2135.1119.2–151.6
2056119.799.9–132.9134.8119.6–149.5
2057120.6102.3–137.1131.9118.5–148.6
2058120.1103.1–136.5137.8122.5–156.5
2059123.5107.4–137.2134.9117.1–152.5
2060119.6106.4–140.3136.2120.5–150.1
2061122.8103.9–136.1139119.4–154
2062121.8104.3–136.5134.9119.1–155.9
2063122.1106.2–136.7138.6119.2–152.5
2064124.3108.4–136.6134.9121.1–152.7
2065123.7108.9–138.7137.1123.3–150.5
2066122.1104.4–136.2136.6119.2–155.1
2067126111.1–142.7138.9124.4–154.3
2068126.8112.1–140.3141.7124.8–159.2
2069123107.9–137.3140.3123.5–154.1
2070126.5110.3–139.4137123.6–155.3
2071126109.5–142.8140.5123.1–156.1
2072128111.8–141.9142.6128–154.3
2073127.6108–143.7139.3124.7–154.6
2074124.2107–139.7140.1123–156.5
2075124.7109.2–140.6139.6124.5–157.1
2076126.6109.8–140.8143.4125.2–158.8
2077127.5109–143.3141.3119.1–158.3
2078127.2113.3–141.8143127.2–155.9
2079132.9116–146.9144.7123.9–158.5
2080129111.8–144.3143.6123.6–158.7
2081127.6112.5–145.6139.9126.3–158.8
2082129.1111.3–143.8145.5125.9–158.1
2083133.2110.3–144.1143.4124.3–158.7
2084132.2111–145.1144.8129.6–159.7
2085130.9112.7–143.3145.3124.7–159.5
2086130.9112.6–146.5144.7129.5–162.7
2087129.6109.8–148.7144125.7–159.2
2088132.5116.9–146.5147.3127.2–165.4
2089130.4115.3–148.4142.7125.3–164.8
2090128.9115–145.8145.2126.3–165.1
2091133.4116–150.3144.9127.4–164.4
2092131.6115.3–149148.2126.3–161.1
2093135119.8–151146.9127.2–165.6
2094134118–148.5145.7126.8–160.4
2095134.3117.3–148.9145.5125.4–161.5
2096131.5113.7–148.7146.3130–169.4
2097136.2112.7–154.1144.6125.7–160.6
2098131.5115.2–152.2147129.6–161.9
2099132.8116–145.1145.8130.3–163.7
2100133.8113.2–152.2143.8124.8–163.8

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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