Bangladesh vs Tanzania

Bangladesh vs Tanzania: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 133.6 nights, or 2.26 times that in Tanzania.

Watch it change on the map

nights a year · CMIP6

Bangladesh vs Tanzania: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 133.6 nights, or 2.26 times that in Tanzania.
BangladeshTanzaniaCMIP6 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 Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshTanzania
2014239.9106.3
2013239105.5
2012240.4108.4
2011240.5109
2010241103.9
2009238.6101.1
2008236.7100.3
2007236.999.5
2006238.9100.4
2005238.298.7
2004238.7100.4
2003236.599.6
2002237.698.4
2001237.2101.5
2000239.394.9
1999236.694.2
1998235.596.8
1997235.593.5
1996235.589.6
1995234.888.5
1994233.685.4
1993232.281.2
199222880.1
1991233.489.6
1990234.691.1
1989235.789.1
1988235.187.6
1987236.488.5
1986233.889.4
1985233.683
198423683.1
198323082.1
1982232.384.8
1981235.988
1980233.485
1979234.585.5
1978231.882.9
1977232.384.1
197623281
1975231.380.8
1974232.982.2
1973232.183.6
1972234.381.4
1971233.180.7
1970232.581.8
1969231.179.5
1968229.779.1
1967231.677.5
1966232.678.1
1965232.578
1964229.373.8
1963233.873.1
1962231.981.1
1961236.282.6
1960232.583.9
1959234.781.4
1958233.582.1
1957232.580.9
1956234.380
1955230.281.6
1954232.981.4
195323480.6
1952230.381.4
1951233.582.1
1950233.980.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshTanzania
2015241.2227–252.4114.895.2–137.4
2016237.9226.6–249.3108.391.6–125.6
2017239.8227.5–249.4114.893.6–137.8
2018242.6227–255116.497.4–137.1
2019241.2228.5–251.9113.495.2–133.2
2020242.6229.3–254.4119.396.2–143.5
2021244.3230.4–254.4119.5100.9–147.1
2022243.8231.5–254.2124.4105.3–147.4
2023243.5229.2–254.5122.1102.1–147.8
2024245.7231.4–257.1126.2100–150.1
2025242.5229.4–253.9124.6100.9–154
2026243.9227.9–258.1126.999.1–155.6
2027247.1232.8–259.3128102.9–147.7
2028244.2232.2–254.4129.9106.4–152.1
2029247.3232.7–261.5134.1111–156.5
2030243.9232.3–255.2129.4106.4–151.1
2031245.1232.9–262.3136.4115.9–158.4
2032247.6236.6–257.8135.1114–166.8
2033245.3231.7–256.6135.2110.9–161.9
2034246.3233.2–260.4134.7112.5–166.3
2035246.4234.1–260.9140.2114.6–165
2036246.2228.6–260.4137.8113.3–165.5
2037247.7235.4–260.2142.9121.5–168.9
2038249232.1–261147.9124.3–169.3
2039250234.4–262.7144.3117.6–171.3
2040248.9235.5–260.5140.5117–178
2041248.3235.6–261.9149.1121.7–175.6
2042252.5237.8–265.3146.3120.5–185.3
2043250.8234.7–263.4144.6117–173
2044251.8239.1–265.2147.7121.2–175.8
2045250.3239.1–265.6150.1125.2–183.4
2046252.7238.9–267.8161.5128.6–192.2
2047253.9239.4–267.1160.2129.7–194.4
2048254.4242.7–270.5158.8132.7–193.1
2049253.7241.5–266.4157.6131.1–196
2050254.6242.5–269.2159.7127.8–192
2051254.7242.7–270.1163.2135.5–197.8
2052252.3240.2–264.6161.9136.2–199.1
2053256.9244–272.4160.6127.5–197.7
2054255.9243.5–269.4163.2131.5–200.2
2055255.2243.8–273.6167.4137–208.3
2056259.1243.6–274.7166.4130.8–209.7
2057257.5243.8–273.7168134.6–208.3
2058257.4245.6–274.2168.7134.9–210.3
2059258.3246.4–271.8174.7144.9–219.5
2060259.2246.1–272.6181.7138.1–219.8
2061257.7244.8–270.1171.8135.5–218.1
2062260.4246.4–274.2177.5139.9–224
2063259.9241.3–272.7181.4140.1–213.8
2064260.2245.9–273.1185.3140.1–215.2
2065259.8244.1–274.7183.5141.1–221.8
2066260246.6–274.6181.9146.3–219.3
2067261.4246.4–272.3178.8138.8–229.2
2068260.1245.8–274.8186144.2–228.4
2069263.3249.8–276.6183.7141.7–225.3
2070259.6245.8–272.6180.7140.4–228.2
2071262.2248.7–283.4184.9146.9–235.2
2072259.8248.6–276191.3155–226.1
2073264.1246.6–277.2191.6152.4–235.6
2074262.6248.3–276.6183.3149.7–231.7
2075263.6248.5–277.7183.8144.8–233
2076261.6251–276.9191.1150.9–233.2
2077264251.1–279.8191.3152.6–238.2
2078265251.6–281.6189156.6–233.8
2079263.8248.5–277.2190.5147–237.3
2080266.8251.9–280.3197.3150.7–241.2
2081266.5250.7–279.9195.6153.4–237.4
2082264249.6–277.3194.5157.3–237.3
2083266.6251.8–282.8193.2151–249.8
2084264.8253.1–284.2201.1152.2–246.7
2085265.4251.2–283.4204.2162.3–252.3
2086268.2252.8–285.3195156–248.7
2087265.7251.3–280.8196.7160.8–244.5
2088267.2252.6–284.4208.4154.7–246.9
2089267.1252.5–286.7201.3158.6–248.2
2090267.9254.9–283.4197.9160.7–253.6
2091267.7254.5–282.2210161.6–256
2092268.8253.6–281.7205.8158.3–253.6
2093268.1251.7–287207.2161.2–251.9
2094267.4251.3–287.4207.9161.3–250.6
2095270.8253.7–284.9214.2166.4–258.5
2096267.9250.5–285.8205.3159.8–257.4
2097269.3254.9–287.3206.6158.4–256.8
2098268.8252.4–284.9209.1161–258.3
2099269253–282.3208.5160.1–256
2100269.8254.8–284.9208158.6–258.6

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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