Iran vs Tunisia

Iran vs Tunisia: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 19.7 nights, or 1.22 times that in Iran.

nights a year · CMIP6

Iran vs Tunisia: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 19.7 nights, or 1.22 times that in Iran.
IranTunisiaCMIP6 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 Iran at 124.4 nights and Tunisia at 143.8 nights in 2100.

Every year

nights a year · CMIP6

YearIranTunisia
201490.8110.5
201390.6110.7
201290.3110
201189.8108.9
201087109.6
200987.2106.1
200888108.6
200787.9106.6
200688.2107.6
200587.1105.6
200486.4105
200385.9105.5
200287.7103.8
200186.6101.8
200086.5104.5
199985.1100.1
199883.8100.1
199784.3100.1
199682.499.1
199581.695.9
199480.695
199377.791.3
19927789.9
199181.998.2
199083.198.6
198981.794.7
198880.494.2
198779.892.7
198680.193.7
198579.790.6
198478.891.8
198375.590
198277.993.9
198180.293.3
198079.492.5
197980.293.8
197878.190.2
197777.888.3
197677.290.5
197576.688.6
197476.488.3
197376.990.5
197277.491
19717588.8
197075.387.3
196975.690.1
196876.388.9
196776.187.6
196675.587.5
196575.384.5
196475.385.7
196376.488
196277.592.7
196177.788.3
196077.690.7
195976.892.2
195878.491.8
195778.292.3
195676.290
195576.592.7
195477.689.9
195377.389.4
195278.291.8
195176.691.6
195077.789.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranTunisia
201594.482.7–106110.796.9–126.1
201694.183.1–105.3111.596.6–130.1
201793.981.7–104116.5102.4–131.8
201894.183–106.3115.999.4–131.9
201995.183.4–105.8116.598.5–129.5
202095.985.5–107.5113.899.9–130.1
202197.286–107.7117.4104.1–129.3
202296.285.2–108.3119.7103–137.3
202398.485.7–110.6118.7102.2–131.9
20249885.1–110.5121107.5–132.6
202598.787.2–110.5120.2100–134
202699.186.7–111.7122.1110.1–134.5
2027100.288.7–112.1119103.6–134.1
202899.686.2–111.6121.1104.5–135.4
202999.386.7–109.9121.5110.2–135.8
2030100.889.8–111.6121.6104–133.4
2031102.990.1–114.8121.8105.7–134.9
2032101.289–113.9125.2111.6–138.9
2033102.889.9–115.1124.7107.6–137.5
2034104.690.7–117.3124.6107–141.7
203510592.1–116.2126.3115.5–142.6
2036103.591.4–115.2126112.5–141.9
203710693.1–119.4126.5110–140
2038105.993.2–116.5126.2111.1–139.1
2039104.392.9–116.6127112.5–142.3
2040105.592.3–118.4127.5112.8–144.3
2041104.892.5–116.4125.5109.1–140.4
2042107.793.4–120.7129.9114.8–145.8
204310692.9–118.8129.1111.6–142
2044106.893.6–121.2127.1112.8–141.8
2045108.795.1–121.8128.5113.8–140.8
2046109.296.1–121.9128.3109.9–144
2047110.596.9–123.3131.2113.6–147.5
2048111.498.6–124129.9114.9–142.3
204911095.7–123.4130115.4–143.5
2050112.199.6–125.1132.3117.6–147.6
2051111.797.6–124.1130.1112.6–148.6
205211298.3–126132.7116.8–146.7
2053111.597.5–124132.5119.5–149.8
2054111.899–126.3135.2118.4–148.8
2055114.6101.4–128135.1119.2–151.6
2056113.1100.2–126.2134.8119.6–149.5
2057113.899.9–128.9131.9118.5–148.6
2058114.2100–127.7137.8122.5–156.5
2059113.498.9–126.3134.9117.1–152.5
2060116.3100.3–129.5136.2120.5–150.1
2061115100.5–127.6139119.4–154
2062115.799.7–131.1134.9119.1–155.9
2063117103.7–130.3138.6119.2–152.5
2064115.1101.7–130.3134.9121.1–152.7
2065117.3102.8–132.3137.1123.3–150.5
2066117.7103.7–132.1136.6119.2–155.1
2067119103–133.5138.9124.4–154.3
2068118.1104.3–131.4141.7124.8–159.2
2069118.4103.8–133.2140.3123.5–154.1
2070118.2104.9–132.9137123.6–155.3
2071119.3105.1–135.3140.5123.1–156.1
2072119103.2–135.1142.6128–154.3
2073120.6104.9–137.7139.3124.7–154.6
2074119.1104.4–134.5140.1123–156.5
2075119.7105.9–135.5139.6124.5–157.1
2076118.9102.6–137143.4125.2–158.8
2077120.3104.3–135.3141.3119.1–158.3
2078119.2105.3–136143127.2–155.9
2079120.1103.2–135.6144.7123.9–158.5
2080120.4106.1–139.5143.6123.6–158.7
2081120.5104.3–137.1139.9126.3–158.8
2082122.5107.5–137.7145.5125.9–158.1
2083122.6105.8–140.4143.4124.3–158.7
2084123.7107.6–139.1144.8129.6–159.7
2085121.3106.6–140.6145.3124.7–159.5
2086122.1107.9–139.8144.7129.5–162.7
2087123.7108–140.7144125.7–159.2
2088124106.5–142.2147.3127.2–165.4
2089124.1109–139.7142.7125.3–164.8
2090122.5105.4–141.9145.2126.3–165.1
2091124.3108–140.5144.9127.4–164.4
2092125.5110.1–140148.2126.3–161.1
2093124.5109–139.3146.9127.2–165.6
2094125108.7–142.9145.7126.8–160.4
2095125.3108.5–141145.5125.4–161.5
2096125.8109–142.4146.3130–169.4
2097123.6106.9–141.8144.6125.7–160.6
2098125.8109.4–143.8147129.6–161.9
2099123.1107.8–140.1145.8130.3–163.7
2100124.4107.9–143.7143.8124.8–163.8

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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