Bangladesh vs Pakistan

Bangladesh vs Pakistan: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 90 nights, or 1.6 times that in Pakistan.

Watch it change on the map

nights a year · CMIP6

Bangladesh vs Pakistan: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 90 nights, or 1.6 times that in Pakistan.
BangladeshPakistanCMIP6 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 Pakistan at 177.6 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshPakistan
2014239.9149.9
2013239149.1
2012240.4149.9
2011240.5149
2010241148.4
2009238.6147.1
2008236.7147.4
2007236.9147.3
2006238.9146.7
2005238.2146.5
2004238.7147.5
2003236.5146
2002237.6148.3
2001237.2145.4
2000239.3144.7
1999236.6146.9
1998235.5144.8
1997235.5143.2
1996235.5141.2
1995234.8141.8
1994233.6142.1
1993232.2140.4
1992228139.9
1991233.4142.5
1990234.6142.6
1989235.7142.5
1988235.1140.3
1987236.4140
1986233.8140
1985233.6140
1984236138.9
1983230136.3
1982232.3138.5
1981235.9141.5
1980233.4139.5
1979234.5139.1
1978231.8139
1977232.3138.6
1976232139.2
1975231.3136.5
1974232.9138.7
1973232.1137.8
1972234.3137.4
1971233.1136
1970232.5137.7
1969231.1135.9
1968229.7136.6
1967231.6135.2
1966232.6136.9
1965232.5138.3
1964229.3135.1
1963233.8135.7
1962231.9137
1961236.2138.6
1960232.5139
1959234.7138.6
1958233.5137.7
1957232.5140
1956234.3137.8
1955230.2137.5
1954232.9137.8
1953234136.9
1952230.3138.1
1951233.5136.7
1950233.9139.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshPakistan
2015241.2227–252.4152.4138.7–163.3
2016237.9226.6–249.3150.6139.4–161.7
2017239.8227.5–249.4151.3138.8–162
2018242.6227–255152.6139.8–161.8
2019241.2228.5–251.9151.8138.1–163.3
2020242.6229.3–254.4153.1140.3–164.5
2021244.3230.4–254.4154.1140.6–165.7
2022243.8231.5–254.2153.1140.2–165.7
2023243.5229.2–254.5155.5141.6–165.9
2024245.7231.4–257.1156.8143.3–168.7
2025242.5229.4–253.9155.7141.5–168.6
2026243.9227.9–258.1155.3142.2–167.9
2027247.1232.8–259.3156.8140.9–168.9
2028244.2232.2–254.4156.5143.9–167.6
2029247.3232.7–261.5155.9141.5–167.7
2030243.9232.3–255.2156.3143.3–167.6
2031245.1232.9–262.3157.3144.4–168.1
2032247.6236.6–257.8157.4142.5–169.6
2033245.3231.7–256.6157.7143.6–169.4
2034246.3233.2–260.4159.5145.6–173.4
2035246.4234.1–260.9159.3146.7–170.3
2036246.2228.6–260.4159.1147.5–171.4
2037247.7235.4–260.2162.2147.5–175.3
2038249232.1–261161.4148.6–171.7
2039250234.4–262.7160148.2–170.4
2040248.9235.5–260.5160.9147.9–171.3
2041248.3235.6–261.9160.8146.7–171.7
2042252.5237.8–265.3162.3149.9–175.6
2043250.8234.7–263.4161.1150.3–173.8
2044251.8239.1–265.2163150.9–173.9
2045250.3239.1–265.6163149.5–174.8
2046252.7238.9–267.8163.5149.8–177.2
2047253.9239.4–267.1165.2151.8–178.5
2048254.4242.7–270.5166.4154.1–179.4
2049253.7241.5–266.4165150.8–178.2
2050254.6242.5–269.2166.9153.5–179.3
2051254.7242.7–270.1165.6150.8–180
2052252.3240.2–264.6166.7155.4–179.5
2053256.9244–272.4166.3154.2–178.8
2054255.9243.5–269.4167.5153.9–181
2055255.2243.8–273.6167.8155.8–182.5
2056259.1243.6–274.7166.3153.6–179.7
2057257.5243.8–273.7168.3153.9–182.3
2058257.4245.6–274.2167.5157–179.9
2059258.3246.4–271.8170.9155.9–183.8
2060259.2246.1–272.6170.3156.5–181.8
2061257.7244.8–270.1168.8156.8–179.6
2062260.4246.4–274.2171.6153.5–186.5
2063259.9241.3–272.7171.3159.5–183.8
2064260.2245.9–273.1170.2155.3–184.5
2065259.8244.1–274.7169.7156.4–185
2066260246.6–274.6172.2157–186.7
2067261.4246.4–272.3173.2160.2–186.3
2068260.1245.8–274.8172.6157.7–186.3
2069263.3249.8–276.6171.8157.3–185.6
2070259.6245.8–272.6171.7158.9–186.7
2071262.2248.7–283.4173.4158.7–186.8
2072259.8248.6–276174161.5–186.9
2073264.1246.6–277.2175.6157.2–187.9
2074262.6248.3–276.6173.5160–186.3
2075263.6248.5–277.7173161.5–187.8
2076261.6251–276.9172.9158.8–186.7
2077264251.1–279.8175161.3–187.8
2078265251.6–281.6174.4160.9–189.3
2079263.8248.5–277.2172.5158.3–187.7
2080266.8251.9–280.3175.1160.7–189.2
2081266.5250.7–279.9174.9159.2–190.2
2082264249.6–277.3175.4161.8–190.6
2083266.6251.8–282.8176.5161.8–190.8
2084264.8253.1–284.2176.1160.9–190.5
2085265.4251.2–283.4176.3161.9–193.6
2086268.2252.8–285.3173.9160–189.1
2087265.7251.3–280.8176161–193.1
2088267.2252.6–284.4175.4160.5–195.2
2089267.1252.5–286.7177.2164.2–191.7
2090267.9254.9–283.4177.7163.9–192.2
2091267.7254.5–282.2177.8162.8–192.2
2092268.8253.6–281.7178.7162.9–192.9
2093268.1251.7–287177164–191
2094267.4251.3–287.4176.8164.1–190.7
2095270.8253.7–284.9178.6163.8–193.1
2096267.9250.5–285.8177.8163.7–192.5
2097269.3254.9–287.3177.3160.4–192.5
2098268.8252.4–284.9178.7162.6–195.7
2099269253–282.3176159.9–193.2
2100269.8254.8–284.9177.6162.2–193

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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