Indonesia vs Iran

Indonesia vs Iran: Tropical nights

Tropical nights in 2014: 306.5 nights in Indonesia and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Indonesia, by 215.7 nights, or 3.37 times that in Iran.

nights a year · CMIP6

Indonesia vs Iran: Tropical nightsTropical nights in 2014: 306.5 nights in Indonesia and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Indonesia, by 215.7 nights, or 3.37 times that in Iran.
IndonesiaIranCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Indonesia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Indonesia at 334.7 nights and Iran at 124.4 nights in 2100.

Every year

nights a year · CMIP6

YearIndonesiaIran
2014306.590.8
2013306.490.6
2012306.390.3
2011304.689.8
2010305.687
2009303.987.2
2008303.488
2007302.887.9
2006302.888.2
2005303.187.1
2004303.886.4
2003301.985.9
2002301.587.7
2001302.586.6
2000300.986.5
1999300.485.1
1998299.183.8
1997297.984.3
1996296.982.4
1995296.781.6
1994294.680.6
1993291.677.7
1992288.577
1991297.581.9
1990298.683.1
198929681.7
1988296.580.4
1987295.679.8
1986295.880.1
1985292.879.7
1984293.478.8
1983290.175.5
1982294.477.9
1981294.880.2
1980294.579.4
1979294.180.2
1978292.478.1
1977293.477.8
1976290.877.2
1975290.776.6
1974291.576.4
197329376.9
1972290.777.4
1971291.275
1970288.975.3
1969290.475.6
1968289.176.3
1967288.476.1
1966290.575.5
1965288.175.3
1964286.275.3
1963286.476.4
1962291.277.5
1961292.977.7
1960292.877.6
1959291.976.8
1958293.378.4
1957290.878.2
1956291.576.2
1955292.476.5
195429077.6
1953291.477.3
1952291.778.2
1951291.776.6
1950291.877.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIndonesiaIran
2015308295.7–315.194.482.7–106
2016307.5296.9–315.694.183.1–105.3
2017308.4295.5–315.693.981.7–104
2018308.9296.4–316.694.183–106.3
2019309.9297.8–316.795.183.4–105.8
2020310.9299–318.695.985.5–107.5
2021310.4298.7–316.497.286–107.7
2022311.4300–319.696.285.2–108.3
2023311.4300.1–320.698.485.7–110.6
2024313.2302–321.29885.1–110.5
2025312300.2–321.998.787.2–110.5
2026312.6299.9–322.899.186.7–111.7
2027312.7301–321.6100.288.7–112.1
2028313.8302.4–321.999.686.2–111.6
2029315.5303.9–324.199.386.7–109.9
2030314.2303.1–322.6100.889.8–111.6
2031314.4301.6–321.9102.990.1–114.8
2032316.9304.8–325.8101.289–113.9
2033316.6305.4–323.3102.889.9–115.1
2034315.4303.9–323.9104.690.7–117.3
2035316.3305.6–327.910592.1–116.2
2036317.7305.2–326.2103.591.4–115.2
2037318.1306.6–325.210693.1–119.4
2038319.3307.6–326.7105.993.2–116.5
2039319.4307.7–326.7104.392.9–116.6
2040318.5306.5–329105.592.3–118.4
2041320.2308.3–328104.892.5–116.4
2042320308.7–329.2107.793.4–120.7
2043318.6306.6–327.810692.9–118.8
2044321309–329.6106.893.6–121.2
2045320.8308.6–329.8108.795.1–121.8
2046322.8308.8–331109.296.1–121.9
2047323.2308.8–333110.596.9–123.3
2048322.3310.5–332.3111.498.6–124
2049323.8311.6–334.111095.7–123.4
2050323.3310.3–333.5112.199.6–125.1
2051323.6311.2–334.4111.797.6–124.1
2052325.1311.7–334.711298.3–126
2053323.9310.9–333.8111.597.5–124
2054324.4311.9–335.4111.899–126.3
2055325.3312.6–335114.6101.4–128
2056325.9312.4–337.2113.1100.2–126.2
2057326.9311.9–335.2113.899.9–128.9
2058326.4313–336.3114.2100–127.7
2059326.4313.9–337.8113.498.9–126.3
2060329.5314.9–338.2116.3100.3–129.5
2061327.9313.6–336.9115100.5–127.6
2062327.6312.4–339.1115.799.7–131.1
2063327.6313.9–339.4117103.7–130.3
2064328.8314.4–338.6115.1101.7–130.3
2065327.6314.3–337.9117.3102.8–132.3
2066328.6314.7–338.5117.7103.7–132.1
2067328.8314.3–338119103–133.5
2068329.8314.4–339.9118.1104.3–131.4
2069329.5315.5–339.3118.4103.8–133.2
2070328.6315.1–338.8118.2104.9–132.9
2071331.4315.5–340.4119.3105.1–135.3
2072330.3315.9–339.4119103.2–135.1
2073331.4317.7–341120.6104.9–137.7
2074329.9316.8–341.1119.1104.4–134.5
2075330.5315.2–340.2119.7105.9–135.5
2076331.5316.2–341.2118.9102.6–137
2077332315.9–341.8120.3104.3–135.3
2078331.4318.2–340.9119.2105.3–136
2079331.5316.6–341.5120.1103.2–135.6
2080332.4317.4–343.2120.4106.1–139.5
2081332.3318.4–341.8120.5104.3–137.1
2082332.8317.8–340.4122.5107.5–137.7
2083333.1318.7–342.6122.6105.8–140.4
2084333317.8–342.7123.7107.6–139.1
2085332.6318.1–342.7121.3106.6–140.6
2086333.1318.9–342.3122.1107.9–139.8
2087332.6318–343.2123.7108–140.7
2088334.5319.5–343.1124106.5–142.2
2089333.6319–342.6124.1109–139.7
2090333.3319.6–343.3122.5105.4–141.9
2091334.5318.2–343.9124.3108–140.5
2092335.1319.7–343.6125.5110.1–140
2093333.9320–344.9124.5109–139.3
2094335.6320.4–342.8125108.7–142.9
2095335.4319.7–343125.3108.5–141
2096334.3319.4–346.1125.8109–142.4
2097334.2319.5–343.3123.6106.9–141.8
2098334.9319.4–343.4125.8109.4–143.8
2099334.4319.4–344.6123.1107.8–140.1
2100334.7318.7–343.3124.4107.9–143.7

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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