Nigeria vs Thailand

Nigeria vs Thailand: Tropical nights

Tropical nights in 2014: 303.9 nights in Nigeria and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Nigeria, by 17.5 nights, or 1.06 times that in Thailand.

Watch it change on the map

nights a year · CMIP6

Nigeria vs Thailand: Tropical nightsTropical nights in 2014: 303.9 nights in Nigeria and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Nigeria, by 17.5 nights, or 1.06 times that in Thailand.
NigeriaThailandCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Nigeria has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Nigeria at 332.3 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearNigeriaThailand
2014303.9286.4
2013299.5289.1
2012304.4286.6
2011301.5286.4
2010301.4286
2009297.8286.9
2008297.4284.8
2007298283.2
2006297.2284.3
2005295.4281.7
2004294.1287.5
2003298.4279.3
2002295.2280
2001299.1285.5
2000293.9283.4
1999290.3282.5
1998289.9282.7
1997292.5284.8
1996290279.8
1995289.1278.7
1994287.4280.8
1993284275.6
1992281.6268.8
1991289.1276.7
1990290.6279.2
1989287.2278.4
1988288279.6
1987285.6277.9
1986289.1277.5
1985284.2276
1984284.4277.9
1983281.9273.9
1982283.5275.7
1981286.4277.8
1980282.8277.9
1979283278
1978282.8276
1977285.9277.3
1976281.7275.6
1975280.4274.4
1974280.7276
1973284.3280.6
1972284.1273.9
1971279.3273.2
1970282276
1969278.7274.8
1968279.6277
1967278.1270.3
1966279.4274.4
1965279275.8
1964276.8271.9
1963275.1274.7
1962284.1275.4
1961281.9278.5
1960285.9276.2
1959282.8274.4
1958281.4278.7
1957283.3277.4
1956280.8277
1955280.4274.6
1954284.1275
1953280.4275.4
1952280.8275.1
1951284.2277.5
1950279.3276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearNigeriaThailand
2015301.7282.9–317.3290.6272.2–305
2016301.4280.8–312.5287.1269.8–306.2
2017302.5284.3–316.3290273.8–302.8
2018302.2286.8–316.5292.6275.1–308.7
2019300.1281.2–318291.2272.8–306.7
2020303283.7–318.5292.4272.2–307.8
2021305.1287.1–318.4294.2276.3–308.5
2022305.1286–319.5294.8277.2–311.9
2023305286.4–318.9296.1281.9–310.2
2024310.6295.1–321.5291.7275.5–307.8
2025307.5292–319.4294276.7–306.3
2026306.9286.1–322.9296278–309.3
2027307.4288–321.7295.8276.3–311.1
2028310.7293.4–322.6297279.3–315.1
2029311.4293.3–324.4300.3278.7–315
2030310.6294.1–322.5297.7280.2–312.5
2031312.2295–324.8300.8282.8–317.1
2032310290–323.5297.2280.9–311.4
2033313292.9–327300281.9–315.8
2034311.7294.8–325.1300.8279–318.4
2035314.5296.7–327.7298.6281.5–317.8
2036313.5294.1–326.5300.4279.9–316.9
2037315.6297.9–327.1299.8280–315.1
2038316.9301.2–329.6304.8286.6–319.3
2039315.4299.4–328.2300.9281.9–317
2040315.6297.9–327.4301.6284.5–315.7
2041316.8300.6–330.2303.1285.1–318.8
2042316.3300.3–330.3303.8290–318.3
2043316298.4–326302285.8–317.9
2044317.9299.5–329.6304.3286.3–318.8
2045316.6300.5–330.4307.1287.7–324.2
2046317.8302.2–330.7305.9285.2–321
2047319.8301.5–333306.6289.5–321.5
2048320.1302.4–331.7309.4288.9–325.7
2049320.7305.3–331.7308.1287.2–324.1
2050320.9304–335307.5291–321.5
2051321304.1–334.2312.8294.8–326
2052320.9303.9–333.5310.9291.2–323.4
2053320.9303.3–334.1308.3289.5–323.3
2054324.5304.5–338.2308.8292.8–322.3
2055322.2308.4–333.7308.6290.6–325.1
2056324.8305.8–336.3311.3294.9–326.3
2057326310.8–337.3308.5286.7–326.4
2058322.9307.4–334.2308291.1–325.1
2059325.7308.9–339312.7295.8–325.3
2060323.8307.5–337313.1294.6–328.6
2061324.4307.1–338.2314.4289.5–331.1
2062325.7308–339.3311.4293.4–330.3
2063326.6308.7–337314.8296.9–327.3
2064326.2311–339.8312.5295.4–330
2065327.6313.5–339.4309.6293.1–329.3
2066328.4311.3–339.6312.1292.6–328
2067326308.4–340.5311.2289.6–329.4
2068329.3311.2–342.9310.8292.4–330.6
2069326.6309.9–338.1315.5296.1–329.5
2070327.4312.6–340.7314.2292.9–330.7
2071329.1313–341.1313.8296.4–330.8
2072330.3315.9–342.1314.8296–329.6
2073326.3309.5–341316.5299.9–332.1
2074326.7311.4–341.4317.2295–333.8
2075328.9314.5–341.8317.2295.3–331.4
2076329.6313.4–342317.4299.8–335
2077332.5314.4–343.3317.5297.3–335.9
2078329.8312.8–342.1315.9297.1–331.6
2079329.6313.8–340.6318.5300.5–332.3
2080331.7314.1–344.8319.8297.4–337.5
2081329.3311.6–343.7317.7299.5–334.9
2082329.3313.3–341.4317.9294.8–333
2083330.4315–342.2315297.8–332.9
2084330.5311.9–344.2316295.5–330
2085332.7316.6–343.6322.6300.8–334.7
2086331.9316.3–343.6319.4295.2–335.2
2087330.7314.9–342.4320.2302.2–334.7
2088331.7313.2–342.7321.4299.8–334.8
2089331.1318.3–341.9318.9296.4–338.1
2090332.4312.7–343.9317.6304–337.4
2091333.3311–345.8320.1299.8–336.1
2092332.7313.8–345.7316.3298–336.4
2093334.2318.6–344.9316.1297.7–333.7
2094334.2317.3–345.6323.4301.8–337.3
2095333.8319.3–346.3322.9302.4–338.9
2096332.5317.4–346.7319.6302.8–336.7
2097331.8312.6–344.6319.8299.1–336
2098332.3316–343.7320.5303.9–336
2099333316.9–344.2319.9303.1–334.4
2100332.3318.5–345320.8301.1–336.7

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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