Bangladesh vs Thailand

Bangladesh vs Thailand: Tropical nights

Tropical nights in 2014: 239.9 nights in Bangladesh and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 46.5 nights, or 1.19 times that in Bangladesh.

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nights a year · CMIP6

Bangladesh vs Thailand: Tropical nightsTropical nights in 2014: 239.9 nights in Bangladesh and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 46.5 nights, or 1.19 times that in Bangladesh.
BangladeshThailandCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Thailand 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 Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearBangladeshThailand
2014239.9286.4
2013239289.1
2012240.4286.6
2011240.5286.4
2010241286
2009238.6286.9
2008236.7284.8
2007236.9283.2
2006238.9284.3
2005238.2281.7
2004238.7287.5
2003236.5279.3
2002237.6280
2001237.2285.5
2000239.3283.4
1999236.6282.5
1998235.5282.7
1997235.5284.8
1996235.5279.8
1995234.8278.7
1994233.6280.8
1993232.2275.6
1992228268.8
1991233.4276.7
1990234.6279.2
1989235.7278.4
1988235.1279.6
1987236.4277.9
1986233.8277.5
1985233.6276
1984236277.9
1983230273.9
1982232.3275.7
1981235.9277.8
1980233.4277.9
1979234.5278
1978231.8276
1977232.3277.3
1976232275.6
1975231.3274.4
1974232.9276
1973232.1280.6
1972234.3273.9
1971233.1273.2
1970232.5276
1969231.1274.8
1968229.7277
1967231.6270.3
1966232.6274.4
1965232.5275.8
1964229.3271.9
1963233.8274.7
1962231.9275.4
1961236.2278.5
1960232.5276.2
1959234.7274.4
1958233.5278.7
1957232.5277.4
1956234.3277
1955230.2274.6
1954232.9275
1953234275.4
1952230.3275.1
1951233.5277.5
1950233.9276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshThailand
2015241.2227–252.4290.6272.2–305
2016237.9226.6–249.3287.1269.8–306.2
2017239.8227.5–249.4290273.8–302.8
2018242.6227–255292.6275.1–308.7
2019241.2228.5–251.9291.2272.8–306.7
2020242.6229.3–254.4292.4272.2–307.8
2021244.3230.4–254.4294.2276.3–308.5
2022243.8231.5–254.2294.8277.2–311.9
2023243.5229.2–254.5296.1281.9–310.2
2024245.7231.4–257.1291.7275.5–307.8
2025242.5229.4–253.9294276.7–306.3
2026243.9227.9–258.1296278–309.3
2027247.1232.8–259.3295.8276.3–311.1
2028244.2232.2–254.4297279.3–315.1
2029247.3232.7–261.5300.3278.7–315
2030243.9232.3–255.2297.7280.2–312.5
2031245.1232.9–262.3300.8282.8–317.1
2032247.6236.6–257.8297.2280.9–311.4
2033245.3231.7–256.6300281.9–315.8
2034246.3233.2–260.4300.8279–318.4
2035246.4234.1–260.9298.6281.5–317.8
2036246.2228.6–260.4300.4279.9–316.9
2037247.7235.4–260.2299.8280–315.1
2038249232.1–261304.8286.6–319.3
2039250234.4–262.7300.9281.9–317
2040248.9235.5–260.5301.6284.5–315.7
2041248.3235.6–261.9303.1285.1–318.8
2042252.5237.8–265.3303.8290–318.3
2043250.8234.7–263.4302285.8–317.9
2044251.8239.1–265.2304.3286.3–318.8
2045250.3239.1–265.6307.1287.7–324.2
2046252.7238.9–267.8305.9285.2–321
2047253.9239.4–267.1306.6289.5–321.5
2048254.4242.7–270.5309.4288.9–325.7
2049253.7241.5–266.4308.1287.2–324.1
2050254.6242.5–269.2307.5291–321.5
2051254.7242.7–270.1312.8294.8–326
2052252.3240.2–264.6310.9291.2–323.4
2053256.9244–272.4308.3289.5–323.3
2054255.9243.5–269.4308.8292.8–322.3
2055255.2243.8–273.6308.6290.6–325.1
2056259.1243.6–274.7311.3294.9–326.3
2057257.5243.8–273.7308.5286.7–326.4
2058257.4245.6–274.2308291.1–325.1
2059258.3246.4–271.8312.7295.8–325.3
2060259.2246.1–272.6313.1294.6–328.6
2061257.7244.8–270.1314.4289.5–331.1
2062260.4246.4–274.2311.4293.4–330.3
2063259.9241.3–272.7314.8296.9–327.3
2064260.2245.9–273.1312.5295.4–330
2065259.8244.1–274.7309.6293.1–329.3
2066260246.6–274.6312.1292.6–328
2067261.4246.4–272.3311.2289.6–329.4
2068260.1245.8–274.8310.8292.4–330.6
2069263.3249.8–276.6315.5296.1–329.5
2070259.6245.8–272.6314.2292.9–330.7
2071262.2248.7–283.4313.8296.4–330.8
2072259.8248.6–276314.8296–329.6
2073264.1246.6–277.2316.5299.9–332.1
2074262.6248.3–276.6317.2295–333.8
2075263.6248.5–277.7317.2295.3–331.4
2076261.6251–276.9317.4299.8–335
2077264251.1–279.8317.5297.3–335.9
2078265251.6–281.6315.9297.1–331.6
2079263.8248.5–277.2318.5300.5–332.3
2080266.8251.9–280.3319.8297.4–337.5
2081266.5250.7–279.9317.7299.5–334.9
2082264249.6–277.3317.9294.8–333
2083266.6251.8–282.8315297.8–332.9
2084264.8253.1–284.2316295.5–330
2085265.4251.2–283.4322.6300.8–334.7
2086268.2252.8–285.3319.4295.2–335.2
2087265.7251.3–280.8320.2302.2–334.7
2088267.2252.6–284.4321.4299.8–334.8
2089267.1252.5–286.7318.9296.4–338.1
2090267.9254.9–283.4317.6304–337.4
2091267.7254.5–282.2320.1299.8–336.1
2092268.8253.6–281.7316.3298–336.4
2093268.1251.7–287316.1297.7–333.7
2094267.4251.3–287.4323.4301.8–337.3
2095270.8253.7–284.9322.9302.4–338.9
2096267.9250.5–285.8319.6302.8–336.7
2097269.3254.9–287.3319.8299.1–336
2098268.8252.4–284.9320.5303.9–336
2099269253–282.3319.9303.1–334.4
2100269.8254.8–284.9320.8301.1–336.7

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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