Cambodia vs Thailand

Cambodia vs Thailand: Tropical nights

Tropical nights in 2014: 337.4 nights in Cambodia and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cambodia, by 51 nights, or 1.18 times that in Thailand.

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nights a year · CMIP6

Cambodia vs Thailand: Tropical nightsTropical nights in 2014: 337.4 nights in Cambodia and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cambodia, by 51 nights, or 1.18 times that in Thailand.
CambodiaThailandCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Cambodia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Cambodia at 357.6 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearCambodiaThailand
2014337.4286.4
2013342.5289.1
2012340.1286.6
2011338.3286.4
2010338.2286
2009339.2286.9
2008334.9284.8
2007336.1283.2
2006336284.3
2005334281.7
2004338.1287.5
2003332.9279.3
2002333.3280
2001337.1285.5
2000335.9283.4
1999335.1282.5
1998334.8282.7
1997336.8284.8
1996330.5279.8
1995328.7278.7
1994334.3280.8
1993329.9275.6
1992321.5268.8
1991328.1276.7
1990333.3279.2
1989330.3278.4
1988332279.6
1987329.7277.9
1986330.9277.5
1985330.8276
1984331.2277.9
1983328.7273.9
1982329.3275.7
1981331.2277.8
1980329.9277.9
1979330.4278
1978327.5276
1977331.6277.3
1976329.2275.6
1975328.1274.4
1974326.8276
1973331.2280.6
1972327.1273.9
1971327.4273.2
1970327.9276
1969327.4274.8
1968327.6277
1967323.9270.3
1966326.4274.4
1965329.8275.8
1964327.1271.9
1963328.6274.7
1962326.2275.4
1961332.3278.5
1960329276.2
1959328.5274.4
1958332.7278.7
1957331.1277.4
1956330277
1955326.8274.6
1954329275
1953329.6275.4
1952329.2275.1
1951330.9277.5
1950328.6276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearCambodiaThailand
2015340323.1–351.2290.6272.2–305
2016339.6325.3–352.5287.1269.8–306.2
2017341.9327.4–350.7290273.8–302.8
2018343.5320.1–353.1292.6275.1–308.7
2019340.8327.2–352.1291.2272.8–306.7
2020343325.7–352.6292.4272.2–307.8
2021345.2328.4–353294.2276.3–308.5
2022344.4332.5–353.4294.8277.2–311.9
2023344.7333.7–355.1296.1281.9–310.2
2024342.1327.5–352.9291.7275.5–307.8
2025343.4332.6–351294276.7–306.3
2026343.9324.7–353.4296278–309.3
2027345.3330.6–354.2295.8276.3–311.1
2028346.5331–356.9297279.3–315.1
2029346.5330.1–357.3300.3278.7–315
2030346.7332.4–355.4297.7280.2–312.5
2031347.7332.3–356.7300.8282.8–317.1
2032347.5332.3–354.7297.2280.9–311.4
2033346.5331.7–358.1300281.9–315.8
2034348.1335.3–357300.8279–318.4
2035347.7330.1–357.7298.6281.5–317.8
2036348.2329.7–355.8300.4279.9–316.9
2037347.4334.6–355.4299.8280–315.1
2038348.9335.4–357.3304.8286.6–319.3
2039349.3335.7–358.3300.9281.9–317
2040348.9339.2–356.6301.6284.5–315.7
2041349.9337.3–358.1303.1285.1–318.8
2042348.1336.5–357.9303.8290–318.3
2043348.4336.5–357.3302285.8–317.9
2044348.6337.6–357.8304.3286.3–318.8
2045349.4335.2–360.2307.1287.7–324.2
2046351.3337.9–359.4305.9285.2–321
2047352.1341.4–359.4306.6289.5–321.5
2048351.1338.7–360.6309.4288.9–325.7
2049352.5339.7–360308.1287.2–324.1
2050352.6340.1–359.7307.5291–321.5
2051354.4343.2–360.9312.8294.8–326
2052353.3343.5–359.5310.9291.2–323.4
2053351.8340.5–358.9308.3289.5–323.3
2054352343.5–359.3308.8292.8–322.3
2055352.8339.5–359.2308.6290.6–325.1
2056353.4339.8–360.9311.3294.9–326.3
2057352.1338.8–359.4308.5286.7–326.4
2058353.3343–360.6308291.1–325.1
2059355341.5–359.7312.7295.8–325.3
2060354344.1–362313.1294.6–328.6
2061355338.3–361314.4289.5–331.1
2062352.2341.4–361311.4293.4–330.3
2063356344–360.6314.8296.9–327.3
2064354.4341.4–361.7312.5295.4–330
2065352.7343.4–359.8309.6293.1–329.3
2066353.7341.8–360.2312.1292.6–328
2067352.9341.2–360.3311.2289.6–329.4
2068354.6343.6–361.1310.8292.4–330.6
2069355.6344.7–361.2315.5296.1–329.5
2070355343.5–361.4314.2292.9–330.7
2071356346.1–361.1313.8296.4–330.8
2072356.6345.8–361.5314.8296–329.6
2073357.1347.3–362316.5299.9–332.1
2074356.1341.9–362.3317.2295–333.8
2075354.9340.7–361.9317.2295.3–331.4
2076357.6347.1–362.9317.4299.8–335
2077356.7345.6–362.3317.5297.3–335.9
2078355345.5–361.7315.9297.1–331.6
2079356.5347.1–361.5318.5300.5–332.3
2080358347.4–363.9319.8297.4–337.5
2081355.8345.5–362.5317.7299.5–334.9
2082354.6345.1–360.9317.9294.8–333
2083355.2345.7–361.7315297.8–332.9
2084355.7343.4–361.6316295.5–330
2085358.4350–362.5322.6300.8–334.7
2086356.6345.5–361.8319.4295.2–335.2
2087357.5346.7–362.5320.2302.2–334.7
2088357347.6–362.4321.4299.8–334.8
2089357.2346.7–361.8318.9296.4–338.1
2090355.7347.6–362.1317.6304–337.4
2091357.8345.5–362.6320.1299.8–336.1
2092355.5343.9–362.3316.3298–336.4
2093355.6344.4–361.2316.1297.7–333.7
2094359.2347.3–362.9323.4301.8–337.3
2095358.6347.7–362.8322.9302.4–338.9
2096357.8348.4–363.2319.6302.8–336.7
2097356.8346.5–362.4319.8299.1–336
2098356.2346.9–362.6320.5303.9–336
2099356.8346.4–362.7319.9303.1–334.4
2100357.6347.9–363.1320.8301.1–336.7

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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