Iran vs Turkmenistan

Iran vs Turkmenistan: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 93.3 nights in Turkmenistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Turkmenistan, by 2.5 nights, or 1.03 times that in Iran.

nights a year · CMIP6

Iran vs Turkmenistan: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 93.3 nights in Turkmenistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Turkmenistan, by 2.5 nights, or 1.03 times that in Iran.
IranTurkmenistanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Turkmenistan has been higher since 2012, when it overtook Iran.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Iran at 124.4 nights and Turkmenistan at 123.4 nights in 2100.

Every year

nights a year · CMIP6

YearIranTurkmenistan
201490.893.3
201390.692.7
201290.391.5
201189.889.1
20108787.4
200987.290.4
20088888.7
200787.989.8
200688.291.4
200587.187.2
200486.488.6
200385.987.4
200287.790.3
200186.688.4
200086.585.4
199985.185.3
199883.886
199784.386.4
199682.482.9
199581.681.6
199480.679.9
199377.774.7
19927775.9
199181.981.8
199083.181.2
198981.780.9
198880.480.8
198779.879.7
198680.176.9
198579.781.1
198478.877.2
198375.570.8
198277.979
198180.277.5
198079.476.7
197980.280.1
197878.177.1
197777.875.9
197677.274.7
197576.674.8
197476.473.6
197376.975.3
197277.475.6
19717572.7
197075.374.2
196975.675.3
196876.373.2
196776.174.4
196675.574.6
196575.373.1
196475.375.4
196376.474.7
196277.576.9
196177.776.1
196077.673.2
195976.875.2
195878.481.9
195778.276.6
195676.277
195576.575.2
195477.679.1
195377.374
195278.277.1
195176.675.7
195077.777.9
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranTurkmenistan
201594.482.7–10693.981.5–108.7
201694.183.1–105.393.481.1–108.3
201793.981.7–10495.280.7–105.1
201894.183–106.394.681.1–108.5
201995.183.4–105.896.183.3–108.3
202095.985.5–107.597.584.6–110.3
202197.286–107.798.487.5–108
202296.285.2–108.397.284.1–108.3
202398.485.7–110.610085.3–110.1
20249885.1–110.5100.185.6–111.4
202598.787.2–110.5100.788.4–112.2
202699.186.7–111.798.887.1–111.2
2027100.288.7–112.1101.188.6–116
202899.686.2–111.6100.189.1–111.8
202999.386.7–109.9100.785.9–112.9
2030100.889.8–111.6101.390–111.1
2031102.990.1–114.8103.491.2–113.9
2032101.289–113.9104.991.4–116.6
2033102.889.9–115.1103.188.1–115.3
2034104.690.7–117.3101.286.4–115.9
203510592.1–116.2105.891.6–116.5
2036103.591.4–115.2104.292.7–118.2
203710693.1–119.4105.993.3–118.2
2038105.993.2–116.5106.495.2–117
2039104.392.9–116.610289.8–112.2
2040105.592.3–118.4107.790–117.9
2041104.892.5–116.4106.893.1–117.7
2042107.793.4–120.7105.293–118.1
204310692.9–118.8105.890.5–116.6
2044106.893.6–121.2107.795–120.8
2045108.795.1–121.8108.191.8–119.5
2046109.296.1–121.9109.493.3–122.1
2047110.596.9–123.3108.994.6–122
2048111.498.6–124110.799.4–120.9
204911095.7–123.4108.897.1–120.8
2050112.199.6–125.1110.898.7–122.9
2051111.797.6–124.1109.997.7–119.6
205211298.3–126111.297.7–122.2
2053111.597.5–124110.598.2–121.7
2054111.899–126.3112.5100.2–123.3
2055114.6101.4–128111.8100.8–123.7
2056113.1100.2–126.2114101.6–125.2
2057113.899.9–128.9113.598.9–125.3
2058114.2100–127.7111.999.1–124.1
2059113.498.9–126.3112.9100.1–123.1
2060116.3100.3–129.5116.1102.3–128.1
2061115100.5–127.6112.898.8–123.9
2062115.799.7–131.1115.4100.9–128.7
2063117103.7–130.3115102.5–128.4
2064115.1101.7–130.3111.299.7–125.6
2065117.3102.8–132.3117102.7–130.4
2066117.7103.7–132.1116.1103.6–127.8
2067119103–133.5117.9101.2–132.6
2068118.1104.3–131.4115.7104.8–126.9
2069118.4103.8–133.2117.4103.3–132.4
2070118.2104.9–132.9114102.7–127.9
2071119.3105.1–135.3114.7102.5–127.8
2072119103.2–135.1116.5100–131.3
2073120.6104.9–137.7116.8102.9–132.7
2074119.1104.4–134.5117.9105.4–130.7
2075119.7105.9–135.5116.5103.6–130.2
2076118.9102.6–137117.5100–132.4
2077120.3104.3–135.3118.3101–132.2
2078119.2105.3–136118.3102.7–132.7
2079120.1103.2–135.6115.8103.3–131.5
2080120.4106.1–139.5117.4103.8–133.7
2081120.5104.3–137.1117.3103.4–130.7
2082122.5107.5–137.7120.1106.1–131.6
2083122.6105.8–140.4121.9106.8–134.7
2084123.7107.6–139.1118.8102–134.2
2085121.3106.6–140.6116.3104.3–136.1
2086122.1107.9–139.8117.8104.4–134.2
2087123.7108–140.7121.6107.7–135
2088124106.5–142.2119.5103.8–136.4
2089124.1109–139.7120.3105.1–135.4
2090122.5105.4–141.9119.4104.3–138.7
2091124.3108–140.5121.9104.2–138.7
2092125.5110.1–140122.4106.6–135.9
2093124.5109–139.3121.9104.5–134.7
2094125108.7–142.9123.5107.7–140.4
2095125.3108.5–141123.7106.6–135.4
2096125.8109–142.4123110.5–139
2097123.6106.9–141.8121.5105.9–137.1
2098125.8109.4–143.8124.1108.5–138.7
2099123.1107.8–140.1123.5110.4–137.4
2100124.4107.9–143.7123.4108.1–141.6

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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