Brazil vs Iran

Brazil vs Iran: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 191.2 nights, or 3.1 times that in Iran.

nights a year · CMIP6

Brazil vs Iran: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 191.2 nights, or 3.1 times that in Iran.
BrazilIranCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Brazil has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Brazil at 317.3 nights and Iran at 124.4 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilIran
201428290.8
2013282.590.6
2012283.690.3
2011281.889.8
2010280.287
2009279.287.2
2008277.888
2007275.987.9
2006275.488.2
2005275.887.1
2004278.586.4
2003276.785.9
2002276.287.7
2001277.786.6
2000273.386.5
199927185.1
1998273.683.8
1997270.984.3
1996264.782.4
1995263.881.6
1994263.680.6
1993258.377.7
1992252.877
1991269.781.9
1990272.583.1
1989267.181.7
1988264.780.4
1987265.979.8
1986265.780.1
1985260.679.7
1984261.178.8
1983255.975.5
1982264.877.9
1981265.380.2
198026279.4
1979261.280.2
1978259.778.1
1977261.877.8
1976258.477.2
1975252.476.6
1974258.776.4
197326176.9
1972258.177.4
1971256.575
1970254.575.3
1969255.175.6
1968254.976.3
1967250.376.1
1966254.575.5
1965250.875.3
1964246.275.3
1963241.976.4
1962257.977.5
1961258.277.7
1960260.377.6
1959255.776.8
1958258.178.4
1957256.678.2
1956251.276.2
1955257.276.5
195425877.6
1953255.277.3
1952255.878.2
1951256.376.6
1950254.477.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilIran
2015284257.6–299.594.482.7–106
2016281.5261.4–296.394.183.1–105.3
2017284.1263.2–297.893.981.7–104
2018283.4263.1–298.894.183–106.3
2019283.7262.9–302.495.183.4–105.8
2020286.3264.2–303.695.985.5–107.5
2021287.9266.9–302.397.286–107.7
2022289.6270.7–303.996.285.2–108.3
2023287.3270.5–30398.485.7–110.6
2024291.5268.2–304.69885.1–110.5
2025289.6269.1–304.898.787.2–110.5
2026289.7266.2–305.199.186.7–111.7
2027289.5269.1–303.7100.288.7–112.1
2028291.2271.9–30699.686.2–111.6
2029295.5276.3–309.699.386.7–109.9
2030292.2269.1–306.9100.889.8–111.6
2031295.3274–308.9102.990.1–114.8
2032296.8280.1–310.9101.289–113.9
2033295.4273.3–308.5102.889.9–115.1
2034294.3273.5–311.8104.690.7–117.3
2035295.2274.4–310.910592.1–116.2
2036295.1278.2–307.8103.591.4–115.2
2037299.9283.7–311.310693.1–119.4
2038299.6283.5–312.1105.993.2–116.5
2039296.9279.9–311104.392.9–116.6
2040298.5279.4–311.9105.592.3–118.4
2041301.4282.2–314.1104.892.5–116.4
2042300.6277.8–314.7107.793.4–120.7
2043298.2279.8–312.710692.9–118.8
2044300.3281.2–315.6106.893.6–121.2
2045299.9279.7–313.1108.795.1–121.8
2046302.8285.8–316.6109.296.1–121.9
2047303.3285–316.4110.596.9–123.3
2048304.4287.3–317.3111.498.6–124
2049305.4288.4–318.511095.7–123.4
2050303.9283.9–316.2112.199.6–125.1
2051305.7287.5–317.5111.797.6–124.1
2052305.9290.6–318.811298.3–126
2053305.3285.9–317.5111.597.5–124
2054306.1288.4–319.3111.899–126.3
2055306.4290.8–319.8114.6101.4–128
2056306.7288.3–321.1113.1100.2–126.2
2057306.4287.6–321.1113.899.9–128.9
2058309291–321.4114.2100–127.7
2059310.4290.7–322.8113.498.9–126.3
2060311.6294.4–325.1116.3100.3–129.5
2061307.5290.3–321.2115100.5–127.6
2062309291.5–322.8115.799.7–131.1
2063310.8290.6–322.8117103.7–130.3
2064309.6290.2–321.1115.1101.7–130.3
2065311.1291.6–323.1117.3102.8–132.3
2066312.2294.2–324.2117.7103.7–132.1
2067310.9291.5–323.3119103–133.5
2068311.5293–324.5118.1104.3–131.4
2069310.6292.2–323.6118.4103.8–133.2
2070312.7293–325.3118.2104.9–132.9
2071311.5292.1–323.9119.3105.1–135.3
2072313.3297.8–325.5119103.2–135.1
2073313.8298.6–327.2120.6104.9–137.7
2074311.4292.4–323.5119.1104.4–134.5
2075310.9291.5–324.5119.7105.9–135.5
2076314.2294.4–327.7118.9102.6–137
2077315.1295.6–326.8120.3104.3–135.3
2078314.9296.3–327.1119.2105.3–136
2079313292.8–326.8120.1103.2–135.6
2080311.9294.7–325.4120.4106.1–139.5
2081313.5295.5–325.6120.5104.3–137.1
2082315296.8–327.1122.5107.5–137.7
2083315.7295.3–328.7122.6105.8–140.4
2084316.6298.5–327.9123.7107.6–139.1
2085317.4299.3–329.8121.3106.6–140.6
2086315.8294–328122.1107.9–139.8
2087316.5297.9–328.5123.7108–140.7
2088315.6297.3–328.8124106.5–142.2
2089315296.6–327.9124.1109–139.7
2090316298.9–330.3122.5105.4–141.9
2091317298.1–330.6124.3108–140.5
2092317.6298.7–330.7125.5110.1–140
2093316.3297.5–328.6124.5109–139.3
2094316.4300.2–327.5125108.7–142.9
2095319299.8–330.7125.3108.5–141
2096317.7299.5–330.8125.8109–142.4
2097316.9297.8–329123.6106.9–141.8
2098318.6299.9–331.9125.8109.4–143.8
2099318.1300–330.2123.1107.8–140.1
2100317.3298.4–330.3124.4107.9–143.7

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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