Brazil vs South Korea

Brazil vs South Korea: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 68.9 nights in South Korea, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 213.1 nights, or 4.09 times that in South Korea.

nights a year · CMIP6

Brazil vs South Korea: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 68.9 nights in South Korea, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 213.1 nights, or 4.09 times that in South Korea.
BrazilSouth KoreaCMIP6 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 South Korea at 96.3 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilSouth Korea
201428268.9
2013282.569.7
2012283.667.7
2011281.865.3
2010280.268.3
2009279.265.8
2008277.863.7
2007275.964.2
2006275.464.8
2005275.865.1
2004278.566.8
2003276.763.2
2002276.263.3
2001277.763.4
2000273.361.7
199927164.2
1998273.660.7
1997270.960.4
1996264.761.2
1995263.855.2
1994263.654.8
1993258.349.2
1992252.850.7
1991269.756.9
1990272.558.8
1989267.158.7
1988264.755.6
1987265.952.6
1986265.751.4
1985260.653.1
1984261.150.4
1983255.946.8
1982264.854
1981265.353.9
198026251.6
1979261.252.6
1978259.756.4
1977261.851.8
1976258.452.8
1975252.454.6
1974258.752.7
197326150.4
1972258.151.8
1971256.549.7
1970254.550.4
1969255.155.2
1968254.951.7
1967250.357.3
1966254.552.9
1965250.852.8
1964246.252.2
1963241.957.9
1962257.953.3
1961258.258.2
1960260.355.2
1959255.754.8
1958258.156
1957256.655.8
1956251.259.1
1955257.255.7
195425854
1953255.255.4
1952255.857
1951256.354.7
1950254.459.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilSouth Korea
2015284257.6–299.568.656.8–82
2016281.5261.4–296.370.353.5–81.8
2017284.1263.2–297.870.559.5–82.9
2018283.4263.1–298.869.156.9–81.2
2019283.7262.9–302.474.663.1–84.4
2020286.3264.2–303.67157.6–83
2021287.9266.9–302.370.252.7–84.1
2022289.6270.7–303.972.563–81.2
2023287.3270.5–30374.563.2–84.2
2024291.5268.2–304.673.558.6–87.1
2025289.6269.1–304.875.762.3–87.1
2026289.7266.2–305.17564–88.4
2027289.5269.1–303.774.163.4–88.9
2028291.2271.9–30677.361.5–87.9
2029295.5276.3–309.675.463.1–86.7
2030292.2269.1–306.975.364.5–87.6
2031295.3274–308.976.763.6–87.3
2032296.8280.1–310.976.761–89.2
2033295.4273.3–308.578.860–92.7
2034294.3273.5–311.877.264.7–87.2
2035295.2274.4–310.98168.9–92.1
2036295.1278.2–307.881.964.1–95
2037299.9283.7–311.378.465.8–89.3
2038299.6283.5–312.178.866.9–89.4
2039296.9279.9–31177.564.7–89.2
2040298.5279.4–311.980.567.4–92.7
2041301.4282.2–314.180.966.4–97.7
2042300.6277.8–314.782.469.1–95
2043298.2279.8–312.783.268.5–97.9
2044300.3281.2–315.683.169.3–91.6
2045299.9279.7–313.18170.4–92.2
2046302.8285.8–316.68668.3–95.2
2047303.3285–316.483.469.7–96.7
2048304.4287.3–317.382.769.2–95.2
2049305.4288.4–318.581.669–96.8
2050303.9283.9–316.281.569.8–93.8
2051305.7287.5–317.584.572.7–98.8
2052305.9290.6–318.883.167.8–98.5
2053305.3285.9–317.586.969.8–98.1
2054306.1288.4–319.384.773.3–97.5
2055306.4290.8–319.886.570.8–101.3
2056306.7288.3–321.185.874.5–99.8
2057306.4287.6–321.187.976.1–100.7
2058309291–321.486.275.2–99.4
2059310.4290.7–322.886.766.9–100.4
2060311.6294.4–325.186.371.9–101.9
2061307.5290.3–321.28974.8–99.5
2062309291.5–322.887.772.3–102.2
2063310.8290.6–322.886.774.6–101.2
2064309.6290.2–321.186.673.6–100.3
2065311.1291.6–323.191.575.3–102.2
2066312.2294.2–324.289.272.6–100.5
2067310.9291.5–323.390.372.7–102.6
2068311.5293–324.590.473.8–106.4
2069310.6292.2–323.69174.5–102.5
2070312.7293–325.389.774.6–107
2071311.5292.1–323.992.674.9–107.9
2072313.3297.8–325.590.976.6–103.9
2073313.8298.6–327.291.376.2–104
2074311.4292.4–323.591.974.6–107
2075310.9291.5–324.594.576.4–103.7
2076314.2294.4–327.793.477.5–105.6
2077315.1295.6–326.895.776.3–107.2
2078314.9296.3–327.193.576.9–110.5
2079313292.8–326.891.179.2–105.7
2080311.9294.7–325.492.481.7–107.1
2081313.5295.5–325.693.878–108.8
2082315296.8–327.196.279.9–110.1
2083315.7295.3–328.794.481.1–108
2084316.6298.5–327.991.574.4–107.3
2085317.4299.3–329.89481.4–107.4
2086315.8294–32893.678.5–111.5
2087316.5297.9–328.594.480.9–113.5
2088315.6297.3–328.893.779.8–108.5
2089315296.6–327.994.478.9–107
2090316298.9–330.397.979.5–109
2091317298.1–330.695.280.6–107.7
2092317.6298.7–330.79580–106.3
2093316.3297.5–328.695.379.5–109.9
2094316.4300.2–327.592.279.8–111
2095319299.8–330.794.884–112.2
2096317.7299.5–330.8100.481–113.2
2097316.9297.8–32997.278.6–108.8
2098318.6299.9–331.997.479.9–110.4
2099318.1300–330.295.879.9–109.3
2100317.3298.4–330.396.381.6–113.8

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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