Egypt vs Thailand

Egypt vs Thailand: Tropical nights

Tropical nights in 2014: 145 nights in Egypt and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 141.4 nights, or 1.98 times that in Egypt.

Watch it change on the map

nights a year · CMIP6

Egypt vs Thailand: Tropical nightsTropical nights in 2014: 145 nights in Egypt and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 141.4 nights, or 1.98 times that in Egypt.
EgyptThailandCMIP6 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 Egypt at 183.4 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearEgyptThailand
2014145286.4
2013145289.1
2012145.1286.6
2011144.7286.4
2010143.5286
2009140.2286.9
2008142.6284.8
2007140.5283.2
2006139.6284.3
2005140281.7
2004141.3287.5
2003141279.3
2002137.7280
2001139285.5
2000134.8283.4
1999135.5282.5
1998133282.7
1997134284.8
1996132.1279.8
1995130.2278.7
1994129.8280.8
1993123.6275.6
1992126.1268.8
1991129.7276.7
1990129.7279.2
1989126278.4
1988124.3279.6
1987125.8277.9
1986128.9277.5
1985125.7276
1984119.4277.9
1983119.4273.9
1982120.7275.7
1981122.6277.8
1980124.9277.9
1979119.2278
1978122.6276
1977121.3277.3
1976123.2275.6
1975121.9274.4
1974123.1276
1973123.5280.6
1972120.1273.9
1971120.7273.2
1970119.7276
1969118.3274.8
1968119.4277
1967116.2270.3
1966116.1274.4
1965112.9275.8
1964116.4271.9
1963120.2274.7
1962118.9275.4
1961118.7278.5
1960123.6276.2
1959123.2274.4
1958120.7278.7
1957122.4277.4
1956122.7277
1955119.4274.6
1954120.8275
1953121.3275.4
1952120.7275.1
1951121.2277.5
1950118.8276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearEgyptThailand
2015149.6131.4–164.2290.6272.2–305
2016147.7133.5–160.2287.1269.8–306.2
2017150.8134.8–163.2290273.8–302.8
2018147.4133.4–165.6292.6275.1–308.7
2019149.6132.7–164291.2272.8–306.7
2020150.8136.4–164.7292.4272.2–307.8
2021152.1137.8–168.1294.2276.3–308.5
2022154138.1–170.6294.8277.2–311.9
2023154.4139–168.4296.1281.9–310.2
2024155.8141.7–168.5291.7275.5–307.8
2025154.5139.6–168.1294276.7–306.3
2026155.1144.5–165.9296278–309.3
2027154.2139.5–166.3295.8276.3–311.1
2028154.5141.8–168.6297279.3–315.1
2029156.3139.9–169.5300.3278.7–315
2030156.3143.1–169.1297.7280.2–312.5
2031155.5141.5–171.2300.8282.8–317.1
2032158.3144.6–170.4297.2280.9–311.4
2033159.9143.8–172.9300281.9–315.8
2034159.8144.9–173.2300.8279–318.4
2035163.5146.6–175.8298.6281.5–317.8
2036156.2143.7–170.6300.4279.9–316.9
2037158.8142.9–173.8299.8280–315.1
2038164.9146.1–177.8304.8286.6–319.3
2039161.8146.1–180.1300.9281.9–317
2040161.6147.9–176.5301.6284.5–315.7
2041163.7149.4–177.3303.1285.1–318.8
2042166.5149.7–180.6303.8290–318.3
2043163.6150.3–176.8302285.8–317.9
2044162.2147–178304.3286.3–318.8
2045167.2152.5–181307.1287.7–324.2
2046166149–181.1305.9285.2–321
2047165.9151.8–181.5306.6289.5–321.5
2048167.2154.5–180.1309.4288.9–325.7
2049165.3148.7–177.9308.1287.2–324.1
2050170152.8–183307.5291–321.5
2051165.6152.7–179.5312.8294.8–326
2052167.3156–180.2310.9291.2–323.4
2053170.1153.6–183.8308.3289.5–323.3
2054169153.3–183308.8292.8–322.3
2055170.5153.5–183.3308.6290.6–325.1
2056168.3151.2–181.4311.3294.9–326.3
2057166.8150.7–185.3308.5286.7–326.4
2058171.8154.2–188.2308291.1–325.1
2059173.3157.8–188.6312.7295.8–325.3
2060170.5154.8–189.3313.1294.6–328.6
2061170.3155.1–184.6314.4289.5–331.1
2062172.1155.2–185.7311.4293.4–330.3
2063169.7152.8–182.6314.8296.9–327.3
2064172.3155.9–187.2312.5295.4–330
2065173.3159.7–189.9309.6293.1–329.3
2066170155–187.7312.1292.6–328
2067176.2161.5–190311.2289.6–329.4
2068174.6157.3–193.1310.8292.4–330.6
2069175.8158.8–191.7315.5296.1–329.5
2070173.3158.3–191.7314.2292.9–330.7
2071176.8158.1–194.7313.8296.4–330.8
2072177.6160.8–192.1314.8296–329.6
2073176159.2–189.3316.5299.9–332.1
2074171.9156.5–194.1317.2295–333.8
2075171.8157–191.9317.2295.3–331.4
2076177161–194.6317.4299.8–335
2077179.7157–194.1317.5297.3–335.9
2078178.4161–195315.9297.1–331.6
2079178.2160.2–193.7318.5300.5–332.3
2080178.5163–193.3319.8297.4–337.5
2081177.2160–192.8317.7299.5–334.9
2082178.8164.5–193.3317.9294.8–333
2083180.6164.4–195.7315297.8–332.9
2084181.4162.4–197.8316295.5–330
2085178.8163–196.7322.6300.8–334.7
2086181.9166.6–198.8319.4295.2–335.2
2087178156.4–194.3320.2302.2–334.7
2088177.8163.5–196321.4299.8–334.8
2089180.9163.5–198.9318.9296.4–338.1
2090179.9162.4–197.8317.6304–337.4
2091184.2165.1–198.9320.1299.8–336.1
2092180.3162.9–196.3316.3298–336.4
2093181.1166.1–198.2316.1297.7–333.7
2094185.4168–198.9323.4301.8–337.3
2095181.9165.5–197.3322.9302.4–338.9
2096183.1163.5–200.3319.6302.8–336.7
2097181.5165.4–198.9319.8299.1–336
2098181.7162.1–198.8320.5303.9–336
2099179.9164.2–197.8319.9303.1–334.4
2100183.4162.9–198.1320.8301.1–336.7

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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