Bangladesh vs India

Bangladesh vs India: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 24.4 nights, or 1.11 times that in India.

Watch it change on the map

nights a year · CMIP6

Bangladesh vs India: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 24.4 nights, or 1.11 times that in India.
BangladeshIndiaCMIP6 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 India at 250.4 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshIndia
2014239.9215.5
2013239216
2012240.4217.4
2011240.5215.5
2010241215.2
2009238.6213.7
2008236.7213.7
2007236.9213.3
2006238.9212.5
2005238.2212.9
2004238.7214.9
2003236.5212.1
2002237.6213
2001237.2212.2
2000239.3210.8
1999236.6211.9
1998235.5210.3
1997235.5209.5
1996235.5207
1995234.8208.8
1994233.6207.1
1993232.2206
1992228203.5
1991233.4208
1990234.6209.9
1989235.7208
1988235.1207.3
1987236.4207.2
1986233.8207.2
1985233.6205.9
1984236206.7
1983230203.3
1982232.3205.7
1981235.9208.4
1980233.4205.3
1979234.5205.5
1978231.8204.1
1977232.3205.9
1976232204.6
1975231.3202.6
1974232.9205.3
1973232.1205.6
1972234.3203.8
1971233.1203.6
1970232.5202.6
1969231.1203.6
1968229.7201.7
1967231.6201.6
1966232.6203.9
1965232.5202.4
1964229.3201.2
1963233.8201.8
1962231.9203.8
1961236.2206.3
1960232.5206
1959234.7206.1
1958233.5204
1957232.5206.5
1956234.3204
1955230.2203.2
1954232.9206
1953234204
1952230.3204.4
1951233.5204.3
1950233.9206.3
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshIndia
2015241.2227–252.4216.9202.1–228.4
2016237.9226.6–249.3215202.5–227.6
2017239.8227.5–249.4216.2202.1–228.5
2018242.6227–255218.3204.5–231.4
2019241.2228.5–251.9217.4202.3–230.4
2020242.6229.3–254.4217.6203.1–232
2021244.3230.4–254.4219.7204.5–233.2
2022243.8231.5–254.2220.5205.8–233
2023243.5229.2–254.5220.4206.4–233.7
2024245.7231.4–257.1222.6208.1–236.3
2025242.5229.4–253.9219.7202.7–236.2
2026243.9227.9–258.1220.2204.2–236.8
2027247.1232.8–259.3223.6207.1–239
2028244.2232.2–254.4222.1205.1–235.7
2029247.3232.7–261.5225.4210–240.3
2030243.9232.3–255.2222.7207.3–235.6
2031245.1232.9–262.3223.8207.1–237.8
2032247.6236.6–257.8225.9210–240.5
2033245.3231.7–256.6223.8209.3–235.4
2034246.3233.2–260.4225.8210–242.7
2035246.4234.1–260.9224.9210.6–240.9
2036246.2228.6–260.4224.2210.4–240.3
2037247.7235.4–260.2228.3213.6–242.6
2038249232.1–261228.1212.6–241.4
2039250234.4–262.7227.4211.9–242.8
2040248.9235.5–260.5227212.2–242
2041248.3235.6–261.9227.1210.7–240.5
2042252.5237.8–265.3229.1214.8–244.2
2043250.8234.7–263.4228.9214.5–244
2044251.8239.1–265.2229.7214.7–244.2
2045250.3239.1–265.6231.2216.6–246.1
2046252.7238.9–267.8232.6216.2–248.6
2047253.9239.4–267.1232.4215.5–250
2048254.4242.7–270.5235.6218.5–254.3
2049253.7241.5–266.4235.3218.3–249.9
2050254.6242.5–269.2233.5216.6–253.4
2051254.7242.7–270.1234.9218.6–249.9
2052252.3240.2–264.6234219.4–249.3
2053256.9244–272.4234.9219.5–252.5
2054255.9243.5–269.4237.2219.4–253.1
2055255.2243.8–273.6237.2220.7–256.6
2056259.1243.6–274.7238.8221.2–254.9
2057257.5243.8–273.7235.7218.5–253.8
2058257.4245.6–274.2238.8222.8–254.1
2059258.3246.4–271.8241.1224.9–256.2
2060259.2246.1–272.6240.9225.6–255.6
2061257.7244.8–270.1237.9220.6–253.7
2062260.4246.4–274.2239.9221.2–259.7
2063259.9241.3–272.7239.9222.3–256.1
2064260.2245.9–273.1240223.8–256.3
2065259.8244.1–274.7240.9222.9–257.3
2066260246.6–274.6241.5224.1–258.6
2067261.4246.4–272.3241.6224.8–257.9
2068260.1245.8–274.8242.3224.6–262.1
2069263.3249.8–276.6242.8225.4–259.1
2070259.6245.8–272.6240.1225.3–257.1
2071262.2248.7–283.4241.8223.7–260.2
2072259.8248.6–276242.6225.4–259.2
2073264.1246.6–277.2243.8228–259.3
2074262.6248.3–276.6241.6226.9–258.4
2075263.6248.5–277.7243.5226.4–258.2
2076261.6251–276.9243.2224.6–259.9
2077264251.1–279.8243.7226.6–264.6
2078265251.6–281.6246.7230.1–261.5
2079263.8248.5–277.2244.9226.4–261.3
2080266.8251.9–280.3246.7227–263.7
2081266.5250.7–279.9247.5230.4–264.8
2082264249.6–277.3244.6227.9–262.3
2083266.6251.8–282.8247.5227.8–265.1
2084264.8253.1–284.2247.3228.3–266.8
2085265.4251.2–283.4246.5227.5–267.1
2086268.2252.8–285.3245.6227.7–266.5
2087265.7251.3–280.8245.5226.7–266.2
2088267.2252.6–284.4247229.4–266.9
2089267.1252.5–286.7248.1230–266.3
2090267.9254.9–283.4249228.9–266.4
2091267.7254.5–282.2248.9230–266.5
2092268.8253.6–281.7249.8232.3–267.8
2093268.1251.7–287248.1229–266.5
2094267.4251.3–287.4249.1230.6–268.4
2095270.8253.7–284.9251233.2–270
2096267.9250.5–285.8247.8231.4–269.3
2097269.3254.9–287.3251.1231.4–268
2098268.8252.4–284.9252.3230.8–268.3
2099269253–282.3248.7230.1–268.3
2100269.8254.8–284.9250.4232.9–266.7

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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