Bangladesh vs Sri Lanka

Bangladesh vs Sri Lanka: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 337.9 nights in Sri Lanka, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sri Lanka, by 98 nights, or 1.41 times that in Bangladesh.

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nights a year · CMIP6

Bangladesh vs Sri Lanka: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 337.9 nights in Sri Lanka, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sri Lanka, by 98 nights, or 1.41 times that in Bangladesh.
BangladeshSri LankaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Sri Lanka 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 Sri Lanka at 356.1 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshSri Lanka
2014239.9337.9
2013239338.4
2012240.4336.9
2011240.5336.8
2010241336.2
2009238.6337.2
2008236.7335.4
2007236.9333.4
2006238.9335.8
2005238.2335.4
2004238.7336
2003236.5334.5
2002237.6335.5
2001237.2335
2000239.3332.9
1999236.6332.1
1998235.5334.3
1997235.5330.9
1996235.5331.1
1995234.8331.2
1994233.6328.8
1993232.2326.3
1992228324.5
1991233.4331.7
1990234.6332.5
1989235.7330.1
1988235.1330.7
1987236.4329.7
1986233.8329.1
1985233.6328
1984236328.3
1983230324
1982232.3328
1981235.9330.5
1980233.4328.6
1979234.5328.3
1978231.8326.9
1977232.3328.8
1976232325.9
1975231.3325.6
1974232.9326.3
1973232.1326.9
1972234.3325.1
1971233.1326.9
1970232.5324.4
1969231.1324.5
1968229.7323.2
1967231.6322.4
1966232.6324.6
1965232.5324.1
1964229.3324.6
1963233.8322.6
1962231.9327.7
1961236.2326.8
1960232.5326.4
1959234.7326.1
1958233.5327.2
1957232.5325.5
1956234.3324.6
1955230.2326.1
1954232.9324.6
1953234324.4
1952230.3325.9
1951233.5326.3
1950233.9328.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshSri Lanka
2015241.2227–252.4339.4328.1–347.4
2016237.9226.6–249.3339326.4–346.7
2017239.8227.5–249.4339.5327.6–346.8
2018242.6227–255340.4328.3–347
2019241.2228.5–251.9340.4328.1–346.4
2020242.6229.3–254.4341.6331.3–348.4
2021244.3230.4–254.4341.5327.8–347.3
2022243.8231.5–254.2340.6329.7–347.9
2023243.5229.2–254.5342.4331–349.4
2024245.7231.4–257.1343.6332.7–349.8
2025242.5229.4–253.9342.3331–348.4
2026243.9227.9–258.1341.7328.8–350.2
2027247.1232.8–259.3344334.3–351.2
2028244.2232.2–254.4344.3334.6–350.5
2029247.3232.7–261.5344333.2–350
2030243.9232.3–255.2345.4334.7–351.4
2031245.1232.9–262.3344.1331.4–351.1
2032247.6236.6–257.8344.5332.2–352.3
2033245.3231.7–256.6346.1333.6–351.7
2034246.3233.2–260.4346.2334.9–352.2
2035246.4234.1–260.9345.6337.6–353
2036246.2228.6–260.4347.3335.8–353.1
2037247.7235.4–260.2347332.5–352.5
2038249232.1–261348338.7–353.5
2039250234.4–262.7347.7338.1–352.8
2040248.9235.5–260.5347.7337.4–353.8
2041248.3235.6–261.9347.8336.6–353.4
2042252.5237.8–265.3347.4336.7–353.8
2043250.8234.7–263.4348.1337.1–353.8
2044251.8239.1–265.2347.5338.5–354.6
2045250.3239.1–265.6348.5339.9–354.9
2046252.7238.9–267.8350339–355.4
2047253.9239.4–267.1350.1339.2–355.3
2048254.4242.7–270.5350.9339.3–356.1
2049253.7241.5–266.4351.7340.7–355.9
2050254.6242.5–269.2350.2339.4–356.3
2051254.7242.7–270.1350.4340.3–356.3
2052252.3240.2–264.6351.5341.3–356.8
2053256.9244–272.4350.6341.6–356.1
2054255.9243.5–269.4351.2339.9–357.3
2055255.2243.8–273.6351.2342.2–356.7
2056259.1243.6–274.7352.4341–358.2
2057257.5243.8–273.7352.2341–357
2058257.4245.6–274.2351.2340.8–358.1
2059258.3246.4–271.8352.4343–357.5
2060259.2246.1–272.6354342.7–358.8
2061257.7244.8–270.1351.9340.9–357.2
2062260.4246.4–274.2352.6341.4–358.1
2063259.9241.3–272.7353341.7–358.6
2064260.2245.9–273.1353.4342.5–358.9
2065259.8244.1–274.7353.2343.7–357.9
2066260246.6–274.6353.9342.3–358.5
2067261.4246.4–272.3352.9342.4–358.9
2068260.1245.8–274.8353.4343–359.6
2069263.3249.8–276.6354344.3–359.1
2070259.6245.8–272.6354.3342.8–358.6
2071262.2248.7–283.4353.5343.4–359.4
2072259.8248.6–276354.7345.5–359.2
2073264.1246.6–277.2353.6343.3–359
2074262.6248.3–276.6354.1345–359.7
2075263.6248.5–277.7354.7344.7–359.5
2076261.6251–276.9354.7341.4–360.4
2077264251.1–279.8354.9343.5–359.9
2078265251.6–281.6353.6342.5–359.6
2079263.8248.5–277.2354.2343.4–360
2080266.8251.9–280.3354.8343–361.4
2081266.5250.7–279.9355.4345.4–360.3
2082264249.6–277.3355.3345–359.4
2083266.6251.8–282.8355.7344.3–360.1
2084264.8253.1–284.2355.9346.4–361.2
2085265.4251.2–283.4354.7345.1–360.5
2086268.2252.8–285.3356344.9–360.4
2087265.7251.3–280.8355.2344.8–360.4
2088267.2252.6–284.4355.7345–361.9
2089267.1252.5–286.7356346.1–360.1
2090267.9254.9–283.4355.6345.5–360.8
2091267.7254.5–282.2356.2343.4–360.7
2092268.8253.6–281.7356.2345.3–361.5
2093268.1251.7–287355.8343.7–360.9
2094267.4251.3–287.4356344.9–360.6
2095270.8253.7–284.9357.1345.9–361
2096267.9250.5–285.8356.2346.8–362.3
2097269.3254.9–287.3356.6344.6–360.4
2098268.8252.4–284.9356.8344.4–361.1
2099269253–282.3355.9344.9–361.1
2100269.8254.8–284.9356.1346.8–360.4

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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