Pakistan vs Thailand

Pakistan vs Thailand: Tropical nights

Tropical nights in 2014: 149.9 nights in Pakistan and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 136.5 nights, or 1.91 times that in Pakistan.

Watch it change on the map

nights a year · CMIP6

Pakistan vs Thailand: Tropical nightsTropical nights in 2014: 149.9 nights in Pakistan and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 136.5 nights, or 1.91 times that in Pakistan.
PakistanThailandCMIP6 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 Pakistan at 177.6 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearPakistanThailand
2014149.9286.4
2013149.1289.1
2012149.9286.6
2011149286.4
2010148.4286
2009147.1286.9
2008147.4284.8
2007147.3283.2
2006146.7284.3
2005146.5281.7
2004147.5287.5
2003146279.3
2002148.3280
2001145.4285.5
2000144.7283.4
1999146.9282.5
1998144.8282.7
1997143.2284.8
1996141.2279.8
1995141.8278.7
1994142.1280.8
1993140.4275.6
1992139.9268.8
1991142.5276.7
1990142.6279.2
1989142.5278.4
1988140.3279.6
1987140277.9
1986140277.5
1985140276
1984138.9277.9
1983136.3273.9
1982138.5275.7
1981141.5277.8
1980139.5277.9
1979139.1278
1978139276
1977138.6277.3
1976139.2275.6
1975136.5274.4
1974138.7276
1973137.8280.6
1972137.4273.9
1971136273.2
1970137.7276
1969135.9274.8
1968136.6277
1967135.2270.3
1966136.9274.4
1965138.3275.8
1964135.1271.9
1963135.7274.7
1962137275.4
1961138.6278.5
1960139276.2
1959138.6274.4
1958137.7278.7
1957140277.4
1956137.8277
1955137.5274.6
1954137.8275
1953136.9275.4
1952138.1275.1
1951136.7277.5
1950139.1276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearPakistanThailand
2015152.4138.7–163.3290.6272.2–305
2016150.6139.4–161.7287.1269.8–306.2
2017151.3138.8–162290273.8–302.8
2018152.6139.8–161.8292.6275.1–308.7
2019151.8138.1–163.3291.2272.8–306.7
2020153.1140.3–164.5292.4272.2–307.8
2021154.1140.6–165.7294.2276.3–308.5
2022153.1140.2–165.7294.8277.2–311.9
2023155.5141.6–165.9296.1281.9–310.2
2024156.8143.3–168.7291.7275.5–307.8
2025155.7141.5–168.6294276.7–306.3
2026155.3142.2–167.9296278–309.3
2027156.8140.9–168.9295.8276.3–311.1
2028156.5143.9–167.6297279.3–315.1
2029155.9141.5–167.7300.3278.7–315
2030156.3143.3–167.6297.7280.2–312.5
2031157.3144.4–168.1300.8282.8–317.1
2032157.4142.5–169.6297.2280.9–311.4
2033157.7143.6–169.4300281.9–315.8
2034159.5145.6–173.4300.8279–318.4
2035159.3146.7–170.3298.6281.5–317.8
2036159.1147.5–171.4300.4279.9–316.9
2037162.2147.5–175.3299.8280–315.1
2038161.4148.6–171.7304.8286.6–319.3
2039160148.2–170.4300.9281.9–317
2040160.9147.9–171.3301.6284.5–315.7
2041160.8146.7–171.7303.1285.1–318.8
2042162.3149.9–175.6303.8290–318.3
2043161.1150.3–173.8302285.8–317.9
2044163150.9–173.9304.3286.3–318.8
2045163149.5–174.8307.1287.7–324.2
2046163.5149.8–177.2305.9285.2–321
2047165.2151.8–178.5306.6289.5–321.5
2048166.4154.1–179.4309.4288.9–325.7
2049165150.8–178.2308.1287.2–324.1
2050166.9153.5–179.3307.5291–321.5
2051165.6150.8–180312.8294.8–326
2052166.7155.4–179.5310.9291.2–323.4
2053166.3154.2–178.8308.3289.5–323.3
2054167.5153.9–181308.8292.8–322.3
2055167.8155.8–182.5308.6290.6–325.1
2056166.3153.6–179.7311.3294.9–326.3
2057168.3153.9–182.3308.5286.7–326.4
2058167.5157–179.9308291.1–325.1
2059170.9155.9–183.8312.7295.8–325.3
2060170.3156.5–181.8313.1294.6–328.6
2061168.8156.8–179.6314.4289.5–331.1
2062171.6153.5–186.5311.4293.4–330.3
2063171.3159.5–183.8314.8296.9–327.3
2064170.2155.3–184.5312.5295.4–330
2065169.7156.4–185309.6293.1–329.3
2066172.2157–186.7312.1292.6–328
2067173.2160.2–186.3311.2289.6–329.4
2068172.6157.7–186.3310.8292.4–330.6
2069171.8157.3–185.6315.5296.1–329.5
2070171.7158.9–186.7314.2292.9–330.7
2071173.4158.7–186.8313.8296.4–330.8
2072174161.5–186.9314.8296–329.6
2073175.6157.2–187.9316.5299.9–332.1
2074173.5160–186.3317.2295–333.8
2075173161.5–187.8317.2295.3–331.4
2076172.9158.8–186.7317.4299.8–335
2077175161.3–187.8317.5297.3–335.9
2078174.4160.9–189.3315.9297.1–331.6
2079172.5158.3–187.7318.5300.5–332.3
2080175.1160.7–189.2319.8297.4–337.5
2081174.9159.2–190.2317.7299.5–334.9
2082175.4161.8–190.6317.9294.8–333
2083176.5161.8–190.8315297.8–332.9
2084176.1160.9–190.5316295.5–330
2085176.3161.9–193.6322.6300.8–334.7
2086173.9160–189.1319.4295.2–335.2
2087176161–193.1320.2302.2–334.7
2088175.4160.5–195.2321.4299.8–334.8
2089177.2164.2–191.7318.9296.4–338.1
2090177.7163.9–192.2317.6304–337.4
2091177.8162.8–192.2320.1299.8–336.1
2092178.7162.9–192.9316.3298–336.4
2093177164–191316.1297.7–333.7
2094176.8164.1–190.7323.4301.8–337.3
2095178.6163.8–193.1322.9302.4–338.9
2096177.8163.7–192.5319.6302.8–336.7
2097177.3160.4–192.5319.8299.1–336
2098178.7162.6–195.7320.5303.9–336
2099176159.9–193.2319.9303.1–334.4
2100177.6162.2–193320.8301.1–336.7

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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