India vs Thailand

India vs Thailand: Tropical nights

Tropical nights in 2014: 215.5 nights in India and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 70.9 nights, or 1.33 times that in India.

Watch it change on the map

nights a year · CMIP6

India vs Thailand: Tropical nightsTropical nights in 2014: 215.5 nights in India and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 70.9 nights, or 1.33 times that in India.
IndiaThailandCMIP6 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 India at 250.4 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearIndiaThailand
2014215.5286.4
2013216289.1
2012217.4286.6
2011215.5286.4
2010215.2286
2009213.7286.9
2008213.7284.8
2007213.3283.2
2006212.5284.3
2005212.9281.7
2004214.9287.5
2003212.1279.3
2002213280
2001212.2285.5
2000210.8283.4
1999211.9282.5
1998210.3282.7
1997209.5284.8
1996207279.8
1995208.8278.7
1994207.1280.8
1993206275.6
1992203.5268.8
1991208276.7
1990209.9279.2
1989208278.4
1988207.3279.6
1987207.2277.9
1986207.2277.5
1985205.9276
1984206.7277.9
1983203.3273.9
1982205.7275.7
1981208.4277.8
1980205.3277.9
1979205.5278
1978204.1276
1977205.9277.3
1976204.6275.6
1975202.6274.4
1974205.3276
1973205.6280.6
1972203.8273.9
1971203.6273.2
1970202.6276
1969203.6274.8
1968201.7277
1967201.6270.3
1966203.9274.4
1965202.4275.8
1964201.2271.9
1963201.8274.7
1962203.8275.4
1961206.3278.5
1960206276.2
1959206.1274.4
1958204278.7
1957206.5277.4
1956204277
1955203.2274.6
1954206275
1953204275.4
1952204.4275.1
1951204.3277.5
1950206.3276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIndiaThailand
2015216.9202.1–228.4290.6272.2–305
2016215202.5–227.6287.1269.8–306.2
2017216.2202.1–228.5290273.8–302.8
2018218.3204.5–231.4292.6275.1–308.7
2019217.4202.3–230.4291.2272.8–306.7
2020217.6203.1–232292.4272.2–307.8
2021219.7204.5–233.2294.2276.3–308.5
2022220.5205.8–233294.8277.2–311.9
2023220.4206.4–233.7296.1281.9–310.2
2024222.6208.1–236.3291.7275.5–307.8
2025219.7202.7–236.2294276.7–306.3
2026220.2204.2–236.8296278–309.3
2027223.6207.1–239295.8276.3–311.1
2028222.1205.1–235.7297279.3–315.1
2029225.4210–240.3300.3278.7–315
2030222.7207.3–235.6297.7280.2–312.5
2031223.8207.1–237.8300.8282.8–317.1
2032225.9210–240.5297.2280.9–311.4
2033223.8209.3–235.4300281.9–315.8
2034225.8210–242.7300.8279–318.4
2035224.9210.6–240.9298.6281.5–317.8
2036224.2210.4–240.3300.4279.9–316.9
2037228.3213.6–242.6299.8280–315.1
2038228.1212.6–241.4304.8286.6–319.3
2039227.4211.9–242.8300.9281.9–317
2040227212.2–242301.6284.5–315.7
2041227.1210.7–240.5303.1285.1–318.8
2042229.1214.8–244.2303.8290–318.3
2043228.9214.5–244302285.8–317.9
2044229.7214.7–244.2304.3286.3–318.8
2045231.2216.6–246.1307.1287.7–324.2
2046232.6216.2–248.6305.9285.2–321
2047232.4215.5–250306.6289.5–321.5
2048235.6218.5–254.3309.4288.9–325.7
2049235.3218.3–249.9308.1287.2–324.1
2050233.5216.6–253.4307.5291–321.5
2051234.9218.6–249.9312.8294.8–326
2052234219.4–249.3310.9291.2–323.4
2053234.9219.5–252.5308.3289.5–323.3
2054237.2219.4–253.1308.8292.8–322.3
2055237.2220.7–256.6308.6290.6–325.1
2056238.8221.2–254.9311.3294.9–326.3
2057235.7218.5–253.8308.5286.7–326.4
2058238.8222.8–254.1308291.1–325.1
2059241.1224.9–256.2312.7295.8–325.3
2060240.9225.6–255.6313.1294.6–328.6
2061237.9220.6–253.7314.4289.5–331.1
2062239.9221.2–259.7311.4293.4–330.3
2063239.9222.3–256.1314.8296.9–327.3
2064240223.8–256.3312.5295.4–330
2065240.9222.9–257.3309.6293.1–329.3
2066241.5224.1–258.6312.1292.6–328
2067241.6224.8–257.9311.2289.6–329.4
2068242.3224.6–262.1310.8292.4–330.6
2069242.8225.4–259.1315.5296.1–329.5
2070240.1225.3–257.1314.2292.9–330.7
2071241.8223.7–260.2313.8296.4–330.8
2072242.6225.4–259.2314.8296–329.6
2073243.8228–259.3316.5299.9–332.1
2074241.6226.9–258.4317.2295–333.8
2075243.5226.4–258.2317.2295.3–331.4
2076243.2224.6–259.9317.4299.8–335
2077243.7226.6–264.6317.5297.3–335.9
2078246.7230.1–261.5315.9297.1–331.6
2079244.9226.4–261.3318.5300.5–332.3
2080246.7227–263.7319.8297.4–337.5
2081247.5230.4–264.8317.7299.5–334.9
2082244.6227.9–262.3317.9294.8–333
2083247.5227.8–265.1315297.8–332.9
2084247.3228.3–266.8316295.5–330
2085246.5227.5–267.1322.6300.8–334.7
2086245.6227.7–266.5319.4295.2–335.2
2087245.5226.7–266.2320.2302.2–334.7
2088247229.4–266.9321.4299.8–334.8
2089248.1230–266.3318.9296.4–338.1
2090249228.9–266.4317.6304–337.4
2091248.9230–266.5320.1299.8–336.1
2092249.8232.3–267.8316.3298–336.4
2093248.1229–266.5316.1297.7–333.7
2094249.1230.6–268.4323.4301.8–337.3
2095251233.2–270322.9302.4–338.9
2096247.8231.4–269.3319.6302.8–336.7
2097251.1231.4–268319.8299.1–336
2098252.3230.8–268.3320.5303.9–336
2099248.7230.1–268.3319.9303.1–334.4
2100250.4232.9–266.7320.8301.1–336.7

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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