Bangladesh vs Egypt

Bangladesh vs Egypt: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 145 nights in Egypt, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 94.9 nights, or 1.65 times that in Egypt.

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nights a year · CMIP6

Bangladesh vs Egypt: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 145 nights in Egypt, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 94.9 nights, or 1.65 times that in Egypt.
BangladeshEgyptCMIP6 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 Egypt at 183.4 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshEgypt
2014239.9145
2013239145
2012240.4145.1
2011240.5144.7
2010241143.5
2009238.6140.2
2008236.7142.6
2007236.9140.5
2006238.9139.6
2005238.2140
2004238.7141.3
2003236.5141
2002237.6137.7
2001237.2139
2000239.3134.8
1999236.6135.5
1998235.5133
1997235.5134
1996235.5132.1
1995234.8130.2
1994233.6129.8
1993232.2123.6
1992228126.1
1991233.4129.7
1990234.6129.7
1989235.7126
1988235.1124.3
1987236.4125.8
1986233.8128.9
1985233.6125.7
1984236119.4
1983230119.4
1982232.3120.7
1981235.9122.6
1980233.4124.9
1979234.5119.2
1978231.8122.6
1977232.3121.3
1976232123.2
1975231.3121.9
1974232.9123.1
1973232.1123.5
1972234.3120.1
1971233.1120.7
1970232.5119.7
1969231.1118.3
1968229.7119.4
1967231.6116.2
1966232.6116.1
1965232.5112.9
1964229.3116.4
1963233.8120.2
1962231.9118.9
1961236.2118.7
1960232.5123.6
1959234.7123.2
1958233.5120.7
1957232.5122.4
1956234.3122.7
1955230.2119.4
1954232.9120.8
1953234121.3
1952230.3120.7
1951233.5121.2
1950233.9118.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshEgypt
2015241.2227–252.4149.6131.4–164.2
2016237.9226.6–249.3147.7133.5–160.2
2017239.8227.5–249.4150.8134.8–163.2
2018242.6227–255147.4133.4–165.6
2019241.2228.5–251.9149.6132.7–164
2020242.6229.3–254.4150.8136.4–164.7
2021244.3230.4–254.4152.1137.8–168.1
2022243.8231.5–254.2154138.1–170.6
2023243.5229.2–254.5154.4139–168.4
2024245.7231.4–257.1155.8141.7–168.5
2025242.5229.4–253.9154.5139.6–168.1
2026243.9227.9–258.1155.1144.5–165.9
2027247.1232.8–259.3154.2139.5–166.3
2028244.2232.2–254.4154.5141.8–168.6
2029247.3232.7–261.5156.3139.9–169.5
2030243.9232.3–255.2156.3143.1–169.1
2031245.1232.9–262.3155.5141.5–171.2
2032247.6236.6–257.8158.3144.6–170.4
2033245.3231.7–256.6159.9143.8–172.9
2034246.3233.2–260.4159.8144.9–173.2
2035246.4234.1–260.9163.5146.6–175.8
2036246.2228.6–260.4156.2143.7–170.6
2037247.7235.4–260.2158.8142.9–173.8
2038249232.1–261164.9146.1–177.8
2039250234.4–262.7161.8146.1–180.1
2040248.9235.5–260.5161.6147.9–176.5
2041248.3235.6–261.9163.7149.4–177.3
2042252.5237.8–265.3166.5149.7–180.6
2043250.8234.7–263.4163.6150.3–176.8
2044251.8239.1–265.2162.2147–178
2045250.3239.1–265.6167.2152.5–181
2046252.7238.9–267.8166149–181.1
2047253.9239.4–267.1165.9151.8–181.5
2048254.4242.7–270.5167.2154.5–180.1
2049253.7241.5–266.4165.3148.7–177.9
2050254.6242.5–269.2170152.8–183
2051254.7242.7–270.1165.6152.7–179.5
2052252.3240.2–264.6167.3156–180.2
2053256.9244–272.4170.1153.6–183.8
2054255.9243.5–269.4169153.3–183
2055255.2243.8–273.6170.5153.5–183.3
2056259.1243.6–274.7168.3151.2–181.4
2057257.5243.8–273.7166.8150.7–185.3
2058257.4245.6–274.2171.8154.2–188.2
2059258.3246.4–271.8173.3157.8–188.6
2060259.2246.1–272.6170.5154.8–189.3
2061257.7244.8–270.1170.3155.1–184.6
2062260.4246.4–274.2172.1155.2–185.7
2063259.9241.3–272.7169.7152.8–182.6
2064260.2245.9–273.1172.3155.9–187.2
2065259.8244.1–274.7173.3159.7–189.9
2066260246.6–274.6170155–187.7
2067261.4246.4–272.3176.2161.5–190
2068260.1245.8–274.8174.6157.3–193.1
2069263.3249.8–276.6175.8158.8–191.7
2070259.6245.8–272.6173.3158.3–191.7
2071262.2248.7–283.4176.8158.1–194.7
2072259.8248.6–276177.6160.8–192.1
2073264.1246.6–277.2176159.2–189.3
2074262.6248.3–276.6171.9156.5–194.1
2075263.6248.5–277.7171.8157–191.9
2076261.6251–276.9177161–194.6
2077264251.1–279.8179.7157–194.1
2078265251.6–281.6178.4161–195
2079263.8248.5–277.2178.2160.2–193.7
2080266.8251.9–280.3178.5163–193.3
2081266.5250.7–279.9177.2160–192.8
2082264249.6–277.3178.8164.5–193.3
2083266.6251.8–282.8180.6164.4–195.7
2084264.8253.1–284.2181.4162.4–197.8
2085265.4251.2–283.4178.8163–196.7
2086268.2252.8–285.3181.9166.6–198.8
2087265.7251.3–280.8178156.4–194.3
2088267.2252.6–284.4177.8163.5–196
2089267.1252.5–286.7180.9163.5–198.9
2090267.9254.9–283.4179.9162.4–197.8
2091267.7254.5–282.2184.2165.1–198.9
2092268.8253.6–281.7180.3162.9–196.3
2093268.1251.7–287181.1166.1–198.2
2094267.4251.3–287.4185.4168–198.9
2095270.8253.7–284.9181.9165.5–197.3
2096267.9250.5–285.8183.1163.5–200.3
2097269.3254.9–287.3181.5165.4–198.9
2098268.8252.4–284.9181.7162.1–198.8
2099269253–282.3179.9164.2–197.8
2100269.8254.8–284.9183.4162.9–198.1

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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