Bangladesh vs Israel

Bangladesh vs Israel: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 97.9 nights in Israel, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 142 nights, or 2.45 times that in Israel.

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nights a year · CMIP6

Bangladesh vs Israel: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 97.9 nights in Israel, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 142 nights, or 2.45 times that in Israel.
BangladeshIsraelCMIP6 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 Israel at 149.4 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshIsrael
2014239.997.9
201323998
2012240.496.3
2011240.596.1
201024195.5
2009238.692.5
2008236.794.1
2007236.992.7
2006238.992
2005238.292.3
2004238.790.7
2003236.593.9
2002237.689.5
2001237.291
2000239.389.5
1999236.686.2
1998235.584.8
1997235.584.2
1996235.583.7
1995234.879.3
1994233.680.1
1993232.271.6
199222874.9
1991233.478.4
1990234.680.2
1989235.776.9
1988235.176.5
1987236.475.1
1986233.878.3
1985233.674
198423669.4
198323068.9
1982232.373.5
1981235.973.5
1980233.475.3
1979234.568.7
1978231.871.6
1977232.372.3
197623273.2
1975231.370.9
1974232.972.5
1973232.171.9
1972234.369.9
1971233.173.1
1970232.571.6
1969231.170.6
1968229.769.6
1967231.666.9
1966232.668.8
1965232.563.5
1964229.366.1
1963233.870.9
1962231.973
1961236.271.5
1960232.574.9
1959234.775
1958233.573
1957232.574.8
1956234.374.3
1955230.272.8
1954232.971.4
195323473.7
1952230.372
1951233.575.1
1950233.969.5
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshIsrael
2015241.2227–252.4105.988.4–122.7
2016237.9226.6–249.3104.186.9–120.1
2017239.8227.5–249.4107.892.2–121.4
2018242.6227–25510993.8–124.2
2019241.2228.5–251.910989.1–124.5
2020242.6229.3–254.4111.594.8–123.5
2021244.3230.4–254.411097.7–128.4
2022243.8231.5–254.2111.493.6–130.2
2023243.5229.2–254.5117.297.9–130.5
2024245.7231.4–257.1114.5100.4–127.3
2025242.5229.4–253.9116.698.3–129.2
2026243.9227.9–258.1115.9104.9–126.2
2027247.1232.8–259.3115.699–127.1
2028244.2232.2–254.4116.3100.2–127.9
2029247.3232.7–261.5117103.1–129.2
2030243.9232.3–255.2118.6102.1–131.2
2031245.1232.9–262.3116.8104.4–132.8
2032247.6236.6–257.8121.4106.5–134.7
2033245.3231.7–256.6122.1108.9–134.7
2034246.3233.2–260.4119.7103.1–133.4
2035246.4234.1–260.9122.8105.8–138.8
2036246.2228.6–260.4120.2105.5–136.2
2037247.7235.4–260.2121.6106.3–139.4
2038249232.1–261126.5105.7–142.1
2039250234.4–262.7127.7110.5–147.1
2040248.9235.5–260.5124.2109.7–144.9
2041248.3235.6–261.9126108.4–141.5
2042252.5237.8–265.3128.5105.8–144.3
2043250.8234.7–263.4126.5111.8–144.3
2044251.8239.1–265.2125.9108.5–142.9
2045250.3239.1–265.6130.9117.5–148.6
2046252.7238.9–267.8131114.4–147.2
2047253.9239.4–267.1132.3116.1–145.4
2048254.4242.7–270.5129.9118.5–146.9
2049253.7241.5–266.4127.9108.7–143.9
2050254.6242.5–269.2133.3114.3–147
2051254.7242.7–270.1130.3116.7–143.9
2052252.3240.2–264.6130.3119.9–143.5
2053256.9244–272.4135120.4–149.7
2054255.9243.5–269.4134.1118.8–149.3
2055255.2243.8–273.6134.1115.2–150.3
2056259.1243.6–274.7136110.1–151.1
2057257.5243.8–273.7132.7110.9–155
2058257.4245.6–274.2135.7119.1–155.4
2059258.3246.4–271.8138.8118.5–156.7
2060259.2246.1–272.6136.1116.3–159.2
2061257.7244.8–270.1136119–150.7
2062260.4246.4–274.2139118.7–156
2063259.9241.3–272.7137.4120.1–151.2
2064260.2245.9–273.1139.3121–154.3
2065259.8244.1–274.7139.6122.3–154.3
2066260246.6–274.6137.3119.6–153.7
2067261.4246.4–272.3142.8126–157.8
2068260.1245.8–274.8141.2122.8–156.4
2069263.3249.8–276.6141.5123.7–157.6
2070259.6245.8–272.6141.8120.5–157.5
2071262.2248.7–283.4142.9124.3–161.8
2072259.8248.6–276144.3127–158.5
2073264.1246.6–277.2143.6127.3–159.2
2074262.6248.3–276.6138.8123–162.2
2075263.6248.5–277.7138.1120.8–154.6
2076261.6251–276.9143.2126.8–161.5
2077264251.1–279.8142.8120.5–161.6
2078265251.6–281.6143.6128.2–160.6
2079263.8248.5–277.2148.6123.7–160.2
2080266.8251.9–280.3145.5123.5–163.7
2081266.5250.7–279.9143.7128.1–161.2
2082264249.6–277.3145.8129.5–160.6
2083266.6251.8–282.8149.4126–163.1
2084264.8253.1–284.2148128.2–164
2085265.4251.2–283.4149127.9–162.4
2086268.2252.8–285.3148127.4–167.1
2087265.7251.3–280.8146.4123.7–165.7
2088267.2252.6–284.4147.6133.5–165.3
2089267.1252.5–286.7148.4131.4–169.1
2090267.9254.9–283.4147.6132.4–168.8
2091267.7254.5–282.2151.9131.7–170.6
2092268.8253.6–281.7148.2132–167.4
2093268.1251.7–287154.1135.3–172.2
2094267.4251.3–287.4153.2133.6–170.3
2095270.8253.7–284.9148.2131.4–164.1
2096267.9250.5–285.8150.5130.5–172.6
2097269.3254.9–287.3149.8134.4–172.7
2098268.8252.4–284.9150.9131.3–170.1
2099269253–282.3149.5129–166.6
2100269.8254.8–284.9149.4130.1–168.5

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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