Bangladesh vs Brazil

Bangladesh vs Brazil: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 282 nights in Brazil, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 42.1 nights, or 1.18 times that in Bangladesh.

Watch it change on the map

nights a year · CMIP6

Bangladesh vs Brazil: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 282 nights in Brazil, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 42.1 nights, or 1.18 times that in Bangladesh.
BangladeshBrazilCMIP6 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 Bangladesh at 269.8 nights and Brazil at 317.3 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshBrazil
2014239.9282
2013239282.5
2012240.4283.6
2011240.5281.8
2010241280.2
2009238.6279.2
2008236.7277.8
2007236.9275.9
2006238.9275.4
2005238.2275.8
2004238.7278.5
2003236.5276.7
2002237.6276.2
2001237.2277.7
2000239.3273.3
1999236.6271
1998235.5273.6
1997235.5270.9
1996235.5264.7
1995234.8263.8
1994233.6263.6
1993232.2258.3
1992228252.8
1991233.4269.7
1990234.6272.5
1989235.7267.1
1988235.1264.7
1987236.4265.9
1986233.8265.7
1985233.6260.6
1984236261.1
1983230255.9
1982232.3264.8
1981235.9265.3
1980233.4262
1979234.5261.2
1978231.8259.7
1977232.3261.8
1976232258.4
1975231.3252.4
1974232.9258.7
1973232.1261
1972234.3258.1
1971233.1256.5
1970232.5254.5
1969231.1255.1
1968229.7254.9
1967231.6250.3
1966232.6254.5
1965232.5250.8
1964229.3246.2
1963233.8241.9
1962231.9257.9
1961236.2258.2
1960232.5260.3
1959234.7255.7
1958233.5258.1
1957232.5256.6
1956234.3251.2
1955230.2257.2
1954232.9258
1953234255.2
1952230.3255.8
1951233.5256.3
1950233.9254.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshBrazil
2015241.2227–252.4284257.6–299.5
2016237.9226.6–249.3281.5261.4–296.3
2017239.8227.5–249.4284.1263.2–297.8
2018242.6227–255283.4263.1–298.8
2019241.2228.5–251.9283.7262.9–302.4
2020242.6229.3–254.4286.3264.2–303.6
2021244.3230.4–254.4287.9266.9–302.3
2022243.8231.5–254.2289.6270.7–303.9
2023243.5229.2–254.5287.3270.5–303
2024245.7231.4–257.1291.5268.2–304.6
2025242.5229.4–253.9289.6269.1–304.8
2026243.9227.9–258.1289.7266.2–305.1
2027247.1232.8–259.3289.5269.1–303.7
2028244.2232.2–254.4291.2271.9–306
2029247.3232.7–261.5295.5276.3–309.6
2030243.9232.3–255.2292.2269.1–306.9
2031245.1232.9–262.3295.3274–308.9
2032247.6236.6–257.8296.8280.1–310.9
2033245.3231.7–256.6295.4273.3–308.5
2034246.3233.2–260.4294.3273.5–311.8
2035246.4234.1–260.9295.2274.4–310.9
2036246.2228.6–260.4295.1278.2–307.8
2037247.7235.4–260.2299.9283.7–311.3
2038249232.1–261299.6283.5–312.1
2039250234.4–262.7296.9279.9–311
2040248.9235.5–260.5298.5279.4–311.9
2041248.3235.6–261.9301.4282.2–314.1
2042252.5237.8–265.3300.6277.8–314.7
2043250.8234.7–263.4298.2279.8–312.7
2044251.8239.1–265.2300.3281.2–315.6
2045250.3239.1–265.6299.9279.7–313.1
2046252.7238.9–267.8302.8285.8–316.6
2047253.9239.4–267.1303.3285–316.4
2048254.4242.7–270.5304.4287.3–317.3
2049253.7241.5–266.4305.4288.4–318.5
2050254.6242.5–269.2303.9283.9–316.2
2051254.7242.7–270.1305.7287.5–317.5
2052252.3240.2–264.6305.9290.6–318.8
2053256.9244–272.4305.3285.9–317.5
2054255.9243.5–269.4306.1288.4–319.3
2055255.2243.8–273.6306.4290.8–319.8
2056259.1243.6–274.7306.7288.3–321.1
2057257.5243.8–273.7306.4287.6–321.1
2058257.4245.6–274.2309291–321.4
2059258.3246.4–271.8310.4290.7–322.8
2060259.2246.1–272.6311.6294.4–325.1
2061257.7244.8–270.1307.5290.3–321.2
2062260.4246.4–274.2309291.5–322.8
2063259.9241.3–272.7310.8290.6–322.8
2064260.2245.9–273.1309.6290.2–321.1
2065259.8244.1–274.7311.1291.6–323.1
2066260246.6–274.6312.2294.2–324.2
2067261.4246.4–272.3310.9291.5–323.3
2068260.1245.8–274.8311.5293–324.5
2069263.3249.8–276.6310.6292.2–323.6
2070259.6245.8–272.6312.7293–325.3
2071262.2248.7–283.4311.5292.1–323.9
2072259.8248.6–276313.3297.8–325.5
2073264.1246.6–277.2313.8298.6–327.2
2074262.6248.3–276.6311.4292.4–323.5
2075263.6248.5–277.7310.9291.5–324.5
2076261.6251–276.9314.2294.4–327.7
2077264251.1–279.8315.1295.6–326.8
2078265251.6–281.6314.9296.3–327.1
2079263.8248.5–277.2313292.8–326.8
2080266.8251.9–280.3311.9294.7–325.4
2081266.5250.7–279.9313.5295.5–325.6
2082264249.6–277.3315296.8–327.1
2083266.6251.8–282.8315.7295.3–328.7
2084264.8253.1–284.2316.6298.5–327.9
2085265.4251.2–283.4317.4299.3–329.8
2086268.2252.8–285.3315.8294–328
2087265.7251.3–280.8316.5297.9–328.5
2088267.2252.6–284.4315.6297.3–328.8
2089267.1252.5–286.7315296.6–327.9
2090267.9254.9–283.4316298.9–330.3
2091267.7254.5–282.2317298.1–330.6
2092268.8253.6–281.7317.6298.7–330.7
2093268.1251.7–287316.3297.5–328.6
2094267.4251.3–287.4316.4300.2–327.5
2095270.8253.7–284.9319299.8–330.7
2096267.9250.5–285.8317.7299.5–330.8
2097269.3254.9–287.3316.9297.8–329
2098268.8252.4–284.9318.6299.9–331.9
2099269253–282.3318.1300–330.2
2100269.8254.8–284.9317.3298.4–330.3

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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