Congo - Kinshasa vs Thailand

Congo - Kinshasa vs Thailand: Tropical nights

Tropical nights in 2014: 248.5 nights in Congo - Kinshasa and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 37.9 nights, or 1.15 times that in Congo - Kinshasa.

nights a year · CMIP6

Congo - Kinshasa vs Thailand: Tropical nightsTropical nights in 2014: 248.5 nights in Congo - Kinshasa and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 37.9 nights, or 1.15 times that in Congo - Kinshasa.
Congo - KinshasaThailandCMIP6 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 Congo - Kinshasa at 324.1 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearCongo - KinshasaThailand
2014248.5286.4
2013249.2289.1
2012250.9286.6
2011248.7286.4
2010243.5286
2009243286.9
2008239.7284.8
2007237.7283.2
2006239284.3
2005237.3281.7
2004238.5287.5
2003239.3279.3
2002236.5280
2001242.5285.5
2000233.5283.4
1999226.2282.5
1998230.6282.7
1997226.6284.8
1996218.6279.8
1995217.2278.7
1994211.9280.8
1993201.5275.6
1992197.6268.8
1991220.1276.7
1990225.4279.2
1989218.4278.4
1988216.7279.6
1987216.6277.9
1986216.8277.5
1985206.1276
1984205.9277.9
1983204.3273.9
1982204.5275.7
1981215.2277.8
1980211.4277.9
1979208.5278
1978202.6276
1977206.5277.3
1976201.9275.6
1975199274.4
1974204276
1973208.4280.6
1972202.5273.9
1971196.3273.2
1970201.7276
1969197.3274.8
1968199277
1967188.8270.3
1966194.7274.4
1965189275.8
1964177.3271.9
1963178.5274.7
1962203.2275.4
1961203.9278.5
1960209.8276.2
1959203.3274.4
1958204.3278.7
1957204277.4
1956197.6277
1955200.5274.6
1954201275
1953204.6275.4
1952201.9275.1
1951204.8277.5
1950200.8276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearCongo - KinshasaThailand
2015256.6217.3–277.7290.6272.2–305
2016247.7213.3–269.3287.1269.8–306.2
2017257.4226.6–278.3290273.8–302.8
2018258.8228.1–276.8292.6275.1–308.7
2019255.8222.6–278.7291.2272.8–306.7
2020259.4227.4–282.3292.4272.2–307.8
2021262.6234.7–283.8294.2276.3–308.5
2022264.8235.1–288.5294.8277.2–311.9
2023263.9236.8–287.2296.1281.9–310.2
2024270.9237.9–290291.7275.5–307.8
2025266.1230.6–292.2294276.7–306.3
2026267.4226.8–294.5296278–309.3
2027268.6230.6–293.6295.8276.3–311.1
2028271.7239.7–295.9297279.3–315.1
2029275.9249.3–296.6300.3278.7–315
2030270.4241.7–296.1297.7280.2–312.5
2031279.4246.6–297.5300.8282.8–317.1
2032277.9249.4–302.3297.2280.9–311.4
2033276.9245.9–301.6300281.9–315.8
2034276.7247.4–305.6300.8279–318.4
2035281243.7–305.1298.6281.5–317.8
2036278.3244.7–304.9300.4279.9–316.9
2037286.9256.1–308.6299.8280–315.1
2038289261.5–307.1304.8286.6–319.3
2039284.7253.4–307.3300.9281.9–317
2040284.5254.7–311.5301.6284.5–315.7
2041289.9258.4–310.8303.1285.1–318.8
2042286.9254.1–314.3303.8290–318.3
2043285.9253–313302285.8–317.9
2044288.3253.6–312.5304.3286.3–318.8
2045289.4260.1–314.1307.1287.7–324.2
2046298.3261.3–317.3305.9285.2–321
2047298.5268.2–317.8306.6289.5–321.5
2048299.1268–320.8309.4288.9–325.7
2049300.3269.6–320.4308.1287.2–324.1
2050297.8267.2–320.6307.5291–321.5
2051298.4272.3–323.1312.8294.8–326
2052300.2271.5–324310.9291.2–323.4
2053298.7265.5–322.6308.3289.5–323.3
2054300.6269.6–322.8308.8292.8–322.3
2055301.9274.9–325.6308.6290.6–325.1
2056302.1266.2–328.3311.3294.9–326.3
2057305.1274.4–326.5308.5286.7–326.4
2058305.3274.1–327.1308291.1–325.1
2059305.4279–329.6312.7295.8–325.3
2060310.7273.5–330.2313.1294.6–328.6
2061307266.1–329.8314.4289.5–331.1
2062308.8269.1–332311.4293.4–330.3
2063308.4277.6–328.4314.8296.9–327.3
2064310.6278.4–329.6312.5295.4–330
2065311.9282.4–331.2309.6293.1–329.3
2066310.4284.2–330.3312.1292.6–328
2067308.8275.9–334311.2289.6–329.4
2068313.9280.8–334.6310.8292.4–330.6
2069312.1270.6–332.7315.5296.1–329.5
2070309.6278–334314.2292.9–330.7
2071312.6285–336.5313.8296.4–330.8
2072317287.7–334.6314.8296–329.6
2073316.2291.2–337.1316.5299.9–332.1
2074311.6284.5–334.9317.2295–333.8
2075312.3279.3–335.2317.2295.3–331.4
2076315.9288.7–337.1317.4299.8–335
2077318.5292.6–338.2317.5297.3–335.9
2078315287.3–337.1315.9297.1–331.6
2079314.8286.3–336318.5300.5–332.3
2080318.5286.8–337.8319.8297.4–337.5
2081318.4287.8–336.7317.7299.5–334.9
2082318.7289.8–336.5317.9294.8–333
2083317.4290.6–340.9315297.8–332.9
2084321.6293.8–339.8316295.5–330
2085324.4294.3–341.4322.6300.8–334.7
2086319290.7–340.7319.4295.2–335.2
2087318.3291.9–339.6320.2302.2–334.7
2088320.9292.9–340321.4299.8–334.8
2089322.1293.9–339.8318.9296.4–338.1
2090320.4295.5–341.7317.6304–337.4
2091325.4294.3–343.3320.1299.8–336.1
2092321.5294.4–342.4316.3298–336.4
2093323.1297.8–341.2316.1297.7–333.7
2094323.1296.5–341.1323.4301.8–337.3
2095325.6299.1–343.7322.9302.4–338.9
2096321.8296.2–344.1319.6302.8–336.7
2097321.5292.6–342319.8299.1–336
2098324.2295.1–342.8320.5303.9–336
2099322.8293.7–344.6319.9303.1–334.4
2100324.1292.1–344.1320.8301.1–336.7

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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