Bangladesh vs South Korea

Bangladesh vs South Korea: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 68.9 nights in South Korea, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 171 nights, or 3.48 times that in South Korea.

nights a year · CMIP6

Bangladesh vs South Korea: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 68.9 nights in South Korea, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 171 nights, or 3.48 times that in South Korea.
BangladeshSouth KoreaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Bangladesh has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Bangladesh at 269.8 nights and South Korea at 96.3 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshSouth Korea
2014239.968.9
201323969.7
2012240.467.7
2011240.565.3
201024168.3
2009238.665.8
2008236.763.7
2007236.964.2
2006238.964.8
2005238.265.1
2004238.766.8
2003236.563.2
2002237.663.3
2001237.263.4
2000239.361.7
1999236.664.2
1998235.560.7
1997235.560.4
1996235.561.2
1995234.855.2
1994233.654.8
1993232.249.2
199222850.7
1991233.456.9
1990234.658.8
1989235.758.7
1988235.155.6
1987236.452.6
1986233.851.4
1985233.653.1
198423650.4
198323046.8
1982232.354
1981235.953.9
1980233.451.6
1979234.552.6
1978231.856.4
1977232.351.8
197623252.8
1975231.354.6
1974232.952.7
1973232.150.4
1972234.351.8
1971233.149.7
1970232.550.4
1969231.155.2
1968229.751.7
1967231.657.3
1966232.652.9
1965232.552.8
1964229.352.2
1963233.857.9
1962231.953.3
1961236.258.2
1960232.555.2
1959234.754.8
1958233.556
1957232.555.8
1956234.359.1
1955230.255.7
1954232.954
195323455.4
1952230.357
1951233.554.7
1950233.959.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshSouth Korea
2015241.2227–252.468.656.8–82
2016237.9226.6–249.370.353.5–81.8
2017239.8227.5–249.470.559.5–82.9
2018242.6227–25569.156.9–81.2
2019241.2228.5–251.974.663.1–84.4
2020242.6229.3–254.47157.6–83
2021244.3230.4–254.470.252.7–84.1
2022243.8231.5–254.272.563–81.2
2023243.5229.2–254.574.563.2–84.2
2024245.7231.4–257.173.558.6–87.1
2025242.5229.4–253.975.762.3–87.1
2026243.9227.9–258.17564–88.4
2027247.1232.8–259.374.163.4–88.9
2028244.2232.2–254.477.361.5–87.9
2029247.3232.7–261.575.463.1–86.7
2030243.9232.3–255.275.364.5–87.6
2031245.1232.9–262.376.763.6–87.3
2032247.6236.6–257.876.761–89.2
2033245.3231.7–256.678.860–92.7
2034246.3233.2–260.477.264.7–87.2
2035246.4234.1–260.98168.9–92.1
2036246.2228.6–260.481.964.1–95
2037247.7235.4–260.278.465.8–89.3
2038249232.1–26178.866.9–89.4
2039250234.4–262.777.564.7–89.2
2040248.9235.5–260.580.567.4–92.7
2041248.3235.6–261.980.966.4–97.7
2042252.5237.8–265.382.469.1–95
2043250.8234.7–263.483.268.5–97.9
2044251.8239.1–265.283.169.3–91.6
2045250.3239.1–265.68170.4–92.2
2046252.7238.9–267.88668.3–95.2
2047253.9239.4–267.183.469.7–96.7
2048254.4242.7–270.582.769.2–95.2
2049253.7241.5–266.481.669–96.8
2050254.6242.5–269.281.569.8–93.8
2051254.7242.7–270.184.572.7–98.8
2052252.3240.2–264.683.167.8–98.5
2053256.9244–272.486.969.8–98.1
2054255.9243.5–269.484.773.3–97.5
2055255.2243.8–273.686.570.8–101.3
2056259.1243.6–274.785.874.5–99.8
2057257.5243.8–273.787.976.1–100.7
2058257.4245.6–274.286.275.2–99.4
2059258.3246.4–271.886.766.9–100.4
2060259.2246.1–272.686.371.9–101.9
2061257.7244.8–270.18974.8–99.5
2062260.4246.4–274.287.772.3–102.2
2063259.9241.3–272.786.774.6–101.2
2064260.2245.9–273.186.673.6–100.3
2065259.8244.1–274.791.575.3–102.2
2066260246.6–274.689.272.6–100.5
2067261.4246.4–272.390.372.7–102.6
2068260.1245.8–274.890.473.8–106.4
2069263.3249.8–276.69174.5–102.5
2070259.6245.8–272.689.774.6–107
2071262.2248.7–283.492.674.9–107.9
2072259.8248.6–27690.976.6–103.9
2073264.1246.6–277.291.376.2–104
2074262.6248.3–276.691.974.6–107
2075263.6248.5–277.794.576.4–103.7
2076261.6251–276.993.477.5–105.6
2077264251.1–279.895.776.3–107.2
2078265251.6–281.693.576.9–110.5
2079263.8248.5–277.291.179.2–105.7
2080266.8251.9–280.392.481.7–107.1
2081266.5250.7–279.993.878–108.8
2082264249.6–277.396.279.9–110.1
2083266.6251.8–282.894.481.1–108
2084264.8253.1–284.291.574.4–107.3
2085265.4251.2–283.49481.4–107.4
2086268.2252.8–285.393.678.5–111.5
2087265.7251.3–280.894.480.9–113.5
2088267.2252.6–284.493.779.8–108.5
2089267.1252.5–286.794.478.9–107
2090267.9254.9–283.497.979.5–109
2091267.7254.5–282.295.280.6–107.7
2092268.8253.6–281.79580–106.3
2093268.1251.7–28795.379.5–109.9
2094267.4251.3–287.492.279.8–111
2095270.8253.7–284.994.884–112.2
2096267.9250.5–285.8100.481–113.2
2097269.3254.9–287.397.278.6–108.8
2098268.8252.4–284.997.479.9–110.4
2099269253–282.395.879.9–109.3
2100269.8254.8–284.996.381.6–113.8

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

Bangladesh vs South Korea

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment