Bangladesh vs Germany

Bangladesh vs Germany: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 0.8 nights in Germany, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 239.1 nights, or 290 times that in Germany.

Watch it change on the map

nights a year · CMIP6

Bangladesh vs Germany: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 0.8 nights in Germany, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 239.1 nights, or 290 times that in Germany.
BangladeshGermanyCMIP6 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 Germany at 8.8 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshGermany
2014239.90.8
20132390.7
2012240.40.9
2011240.50.5
20102410.9
2009238.60.5
2008236.70.2
2007236.90.3
2006238.90.3
2005238.20.6
2004238.70.7
2003236.50.6
2002237.60.2
2001237.20.5
2000239.30.2
1999236.60.2
1998235.50.1
1997235.50.1
1996235.50.2
1995234.80.1
1994233.60
1993232.20
19922280
1991233.40.1
1990234.60.1
1989235.70.1
1988235.10
1987236.40
1986233.80
1985233.60.1
19842360.1
19832300
1982232.30
1981235.90
1980233.40
1979234.50
1978231.80.1
1977232.30
19762320
1975231.30
1974232.90.1
1973232.10
1972234.30
1971233.10
1970232.50.1
1969231.10
1968229.70
1967231.60
1966232.60
1965232.50
1964229.30
1963233.80
1962231.90
1961236.20
1960232.50
1959234.70.1
1958233.50
1957232.50
1956234.30
1955230.20
1954232.90.1
19532340
1952230.30
1951233.50
1950233.90
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshGermany
2015241.2227–252.40.50–4
2016237.9226.6–249.30.80–4.3
2017239.8227.5–249.40.70–5.1
2018242.6227–2550.70–3.5
2019241.2228.5–251.91.20–5
2020242.6229.3–254.41.20–5.7
2021244.3230.4–254.410–6
2022243.8231.5–254.21.40–5.7
2023243.5229.2–254.51.10–5.7
2024245.7231.4–257.11.20–5.2
2025242.5229.4–253.91.90–8.2
2026243.9227.9–258.11.90.1–6.5
2027247.1232.8–259.31.40–4.7
2028244.2232.2–254.41.50.1–5.5
2029247.3232.7–261.520.1–6.4
2030243.9232.3–255.21.60–6.1
2031245.1232.9–262.31.40–5.4
2032247.6236.6–257.81.50.1–7.6
2033245.3231.7–256.61.70–6.8
2034246.3233.2–260.42.10.2–8.3
2035246.4234.1–260.91.70.1–6.9
2036246.2228.6–260.42.80.1–7.8
2037247.7235.4–260.22.50–9.2
2038249232.1–2612.20.1–9.7
2039250234.4–262.730–8.9
2040248.9235.5–260.52.30.1–7.1
2041248.3235.6–261.92.40.1–7.9
2042252.5237.8–265.32.90.4–8.9
2043250.8234.7–263.43.10.1–8.7
2044251.8239.1–265.23.10.2–10.1
2045250.3239.1–265.630.1–8.7
2046252.7238.9–267.83.10.5–10.9
2047253.9239.4–267.14.30.3–10.6
2048254.4242.7–270.53.70.2–12.9
2049253.7241.5–266.44.40.2–11.8
2050254.6242.5–269.23.10.6–9.3
2051254.7242.7–270.12.70.1–9.5
2052252.3240.2–264.63.60.2–11.5
2053256.9244–272.42.30.4–8.7
2054255.9243.5–269.43.50.4–10.3
2055255.2243.8–273.63.30.4–11.3
2056259.1243.6–274.74.50.7–14.3
2057257.5243.8–273.740.4–11.3
2058257.4245.6–274.25.80.7–15.5
2059258.3246.4–271.85.10.1–15.6
2060259.2246.1–272.64.40.6–12.3
2061257.7244.8–270.15.31–12.3
2062260.4246.4–274.25.51.6–14.2
2063259.9241.3–272.75.20.8–13.8
2064260.2245.9–273.14.10.5–12.2
2065259.8244.1–274.74.90.3–15.8
2066260246.6–274.65.30.7–11.8
2067261.4246.4–272.37.21.4–17.5
2068260.1245.8–274.83.90.9–11.3
2069263.3249.8–276.66.11.6–15
2070259.6245.8–272.65.80.6–14.9
2071262.2248.7–283.46.30.6–16.4
2072259.8248.6–2766.21.9–13
2073264.1246.6–277.25.51.3–16.2
2074262.6248.3–276.65.50.5–16.7
2075263.6248.5–277.76.21.4–18.3
2076261.6251–276.97.41.1–20.1
2077264251.1–279.86.31.1–17.4
2078265251.6–281.66.50.7–21.4
2079263.8248.5–277.26.70.6–22.7
2080266.8251.9–280.36.51.2–14.9
2081266.5250.7–279.96.60.9–18.5
2082264249.6–277.37.91.4–22.5
2083266.6251.8–282.87.61.3–16.8
2084264.8253.1–284.25.91.1–15.9
2085265.4251.2–283.46.50.9–17.6
2086268.2252.8–285.37.90.8–23
2087265.7251.3–280.89.91.1–24.1
2088267.2252.6–284.48.92–18.4
2089267.1252.5–286.78.31.9–19.2
2090267.9254.9–283.46.20.8–24.1
2091267.7254.5–282.29.31.3–23.5
2092268.8253.6–281.78.61.7–19.2
2093268.1251.7–2876.20.8–18.2
2094267.4251.3–287.49.32.4–20.4
2095270.8253.7–284.99.51.1–24
2096267.9250.5–285.88.10.2–21.4
2097269.3254.9–287.36.40.5–20.1
2098268.8252.4–284.99.31.4–22.1
2099269253–282.38.11.4–20.8
2100269.8254.8–284.98.81.9–21.1

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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