Bangladesh vs Sudan

Bangladesh vs Sudan: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 242.4 nights in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 2.5 nights, or 1.01 times that in Bangladesh.

nights a year · CMIP6

Bangladesh vs Sudan: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 242.4 nights in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 2.5 nights, or 1.01 times that in Bangladesh.
BangladeshSudanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Sudan has been higher since 2011, when it overtook Bangladesh.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Bangladesh at 269.8 nights and Sudan at 278.6 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshSudan
2014239.9242.4
2013239240
2012240.4242
2011240.5242.2
2010241240.6
2009238.6236.5
2008236.7237.1
2007236.9236
2006238.9235.3
2005238.2233.1
2004238.7233.5
2003236.5235.6
2002237.6234.7
2001237.2235.4
2000239.3230.5
1999236.6232.1
1998235.5230.2
1997235.5231.1
1996235.5227.3
1995234.8227.8
1994233.6225.3
1993232.2219.1
1992228217.8
1991233.4227.3
1990234.6227.5
1989235.7223
1988235.1223.1
1987236.4224.4
1986233.8226.4
1985233.6222.1
1984236220.7
1983230217
1982232.3216.3
1981235.9223.2
1980233.4220
1979234.5218.4
1978231.8218.5
1977232.3219.3
1976232220.1
1975231.3215.7
1974232.9217.5
1973232.1220
1972234.3217.9
1971233.1215.5
1970232.5217
1969231.1213.1
1968229.7214
1967231.6210.3
1966232.6213.3
1965232.5213.4
1964229.3213.2
1963233.8210.1
1962231.9217
1961236.2216.9
1960232.5221.3
1959234.7217.8
1958233.5216.2
1957232.5218.9
1956234.3217.2
1955230.2216.6
1954232.9218.9
1953234215.1
1952230.3216.4
1951233.5218.5
1950233.9214.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshSudan
2015241.2227–252.4242.3225.3–258.3
2016237.9226.6–249.3241.4223.3–254.1
2017239.8227.5–249.4243.2223–259.1
2018242.6227–255242.3226.4–258.5
2019241.2228.5–251.9243.1221.7–260.4
2020242.6229.3–254.4244.9225.9–261.7
2021244.3230.4–254.4245.6229.1–261.5
2022243.8231.5–254.2249230.9–262.3
2023243.5229.2–254.5247.1226.8–263.1
2024245.7231.4–257.1251.5232.8–266.1
2025242.5229.4–253.9250.7232.4–265.6
2026243.9227.9–258.1250230.8–266.6
2027247.1232.8–259.3248.8228.4–265.6
2028244.2232.2–254.4249232.2–263.1
2029247.3232.7–261.5251.4232.1–266
2030243.9232.3–255.2252235.4–266.7
2031245.1232.9–262.3253.3234.4–268.9
2032247.6236.6–257.8250.4232.3–266.6
2033245.3231.7–256.6254.4235.3–269.4
2034246.3233.2–260.4254.2234.5–269.9
2035246.4234.1–260.9258.3240.2–273.6
2036246.2228.6–260.4252.8235.6–268.6
2037247.7235.4–260.2256.7238.6–271.8
2038249232.1–261258.7244.8–272.1
2039250234.4–262.7259.5241.2–272.5
2040248.9235.5–260.5256.4236.7–272.3
2041248.3235.6–261.9259.1241.2–274.5
2042252.5237.8–265.3258.7242–274.7
2043250.8234.7–263.4258.1240.3–272.6
2044251.8239.1–265.2257.3238.6–274.7
2045250.3239.1–265.6258.8243.1–276.2
2046252.7238.9–267.8261.1241.7–277.6
2047253.9239.4–267.1261.4244.6–278.4
2048254.4242.7–270.5260.4243.4–279.5
2049253.7241.5–266.4261.9242.6–275.9
2050254.6242.5–269.2263.5245.4–279
2051254.7242.7–270.1263.6246.6–278.8
2052252.3240.2–264.6263.8248.7–278.3
2053256.9244–272.4262.8242.4–279.2
2054255.9243.5–269.4266.3246.6–282.9
2055255.2243.8–273.6265.6245.9–281.4
2056259.1243.6–274.7264.1242.6–281.5
2057257.5243.8–273.7266.4247.6–283.4
2058257.4245.6–274.2265.2247.4–280.3
2059258.3246.4–271.8268.4249.6–285.4
2060259.2246.1–272.6263.6246.7–284.4
2061257.7244.8–270.1266.9250.1–281.9
2062260.4246.4–274.2266.4248.5–285
2063259.9241.3–272.7267.1246.9–283.4
2064260.2245.9–273.1269250.7–284.7
2065259.8244.1–274.7269.8253.9–285.6
2066260246.6–274.6271.4251.9–287.3
2067261.4246.4–272.3270.9250–288.4
2068260.1245.8–274.8271.9251.7–289.8
2069263.3249.8–276.6268251.1–286.2
2070259.6245.8–272.6269252.3–285.8
2071262.2248.7–283.4275.5254.1–290.4
2072259.8248.6–276273.3254.2–289.4
2073264.1246.6–277.2271.9250.7–287.6
2074262.6248.3–276.6270.9249–290.1
2075263.6248.5–277.7273.1254–291.9
2076261.6251–276.9272.7255.2–290.9
2077264251.1–279.8274.6255.2–292.7
2078265251.6–281.6274.3255.6–291.2
2079263.8248.5–277.2272255.2–288.5
2080266.8251.9–280.3276.6256–292.2
2081266.5250.7–279.9275.1254.1–294.8
2082264249.6–277.3272.9258.7–288.6
2083266.6251.8–282.8276.5258–291.7
2084264.8253.1–284.2275.4253–294.9
2085265.4251.2–283.4275.3258.6–291.6
2086268.2252.8–285.3276.4256.9–296.6
2087265.7251.3–280.8273.5253.1–293.3
2088267.2252.6–284.4273.6253.7–293.6
2089267.1252.5–286.7276.5256.6–293.4
2090267.9254.9–283.4276.6256.4–294.6
2091267.7254.5–282.2277.4256.4–296.6
2092268.8253.6–281.7274.6254.3–294.9
2093268.1251.7–287278261.9–292.1
2094267.4251.3–287.4280.3262.2–294
2095270.8253.7–284.9277.5262.6–294
2096267.9250.5–285.8279.7258.7–297
2097269.3254.9–287.3276.3254.1–297.6
2098268.8252.4–284.9277.7258.2–295.5
2099269253–282.3276.8257.2–296.2
2100269.8254.8–284.9278.6259–294.3

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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