Cuba vs Mexico

Cuba vs Mexico: Tropical nights

Tropical nights in 2014: 309.7 nights in Cuba and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cuba, by 206 nights, or 2.99 times that in Mexico.

nights a year · CMIP6

Cuba vs Mexico: Tropical nightsTropical nights in 2014: 309.7 nights in Cuba and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cuba, by 206 nights, or 2.99 times that in Mexico.
CubaMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Cuba has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Cuba at 346 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearCubaMexico
2014309.7103.7
2013315.2103.9
2012312102.8
2011312.1102.9
2010313101.5
2009308.8101.8
2008309.3100.1
2007308.599.1
2006309.999.8
2005309.199.5
2004309.399.4
2003304.698.3
2002310.499.1
2001304.898.7
2000308.197.9
1999304.496.6
1998304.995.8
1997299.895.9
199629893.8
1995295.192.7
1994297.390.7
1993294.589
1992295.788.5
1991299.193.4
199030294.9
1989298.193
1988298.392.1
198729492
1986293.690.2
1985297.490
1984289.488
1983292.286.7
198229488.7
1981293.691.5
1980295.890.1
1979295.190.8
1978290.989
1977289.389
1976293.489.1
197528986.8
1974291.687.9
1973291.288.6
1972289.487.7
1971286.586.8
1970283.386.1
1969287.287.5
1968290.687.1
1967289.986.7
1966290.786.4
1965284.884.9
1964287.784.7
1963288.987.1
1962292.988
1961292.289.5
1960293.389.7
1959292.789.6
1958291.689.1
195729289
1956294.688.5
1955293.488.2
1954289.588.4
1953289.288.6
1952290.987.8
1951292.189.4
1950292.388.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearCubaMexico
2015315.1292.1–332.6106.192.9–118.4
2016317.9302.7–334.8107.695–120
2017317304–329.5108.696.3–119.7
2018319.5301–334.210997.1–120.4
2019317.6297.3–336.1110.396.4–123
2020319.5296.6–334.3109.696.8–121.8
2021320.6301.8–335.1111.296.9–124.1
2022318.2303.4–331.8109.796–121.7
2023322.4302.9–336.9111.898.6–125.3
2024320.1297.1–341.5112.298.2–126.2
2025319.6297.1–334.811298.8–125.8
2026327.3300.6–343.1113.999.5–126.4
2027328.7307.3–344.9112.999.5–128.3
2028327.5306.8–343.5115.2101.9–127.9
2029326.5309–340.3115.6101.9–127.9
2030328.8305–342.3115.9101.7–128.4
2031328.6308.6–343.5116.1100.9–129.9
2032332.1308.4–344.7116.1102.5–129.1
2033328.3305.5–342.9117.5102.5–131.1
2034329.4308.9–346.2117.2104.1–130.3
2035325.7307.3–342.4116.4103.1–130.3
2036329307–341.7117.8105.1–131
2037332.6311.4–346.9118.6104.3–131.7
2038331.4313–345.1121107.5–133.4
2039328305.6–345.9121.3107–135.6
2040328.8309–347.6121.9108.1–135.1
2041331.4307.4–344.3121.3105.3–134.6
2042331.6309.6–345.1122.7107.7–137.1
2043332.1311–348.9122.4108.1–137.5
2044335.1315.6–348.6121.9108–135.6
2045336.3317.6–348.6123.1108.8–139.2
2046328.7309–349.2123.8109.9–139.4
2047334.4316.3–350.1125.6111.9–139.4
2048335.2316.3–349.1126.3113–140.3
2049339.5317–350.8127111.2–140.8
2050338.7316.7–350.6128.1112.6–142.5
2051337.4313.8–349.8127.2113.4–140.8
2052331311.8–349.4126.2112.5–141.1
2053339.5314.6–351.2128.4111.5–142.7
2054338.4322.5–348.7128.1113.1–142.3
2055336.9318.7–350.1129114.4–144.7
2056338.1320.4–351.5129.5114.3–143.8
2057340.6316.7–351.1130.3113.5–145.9
2058340.8322.3–351.7128.8114.1–144.5
2059334.6319.6–349.6129.5114.5–144.5
2060340.7320.6–352.9131.4115.5–146.5
2061337.9324.8–351.5131.3118.4–146.8
2062340.1323.4–351130.8115.1–146.3
2063340.9316.3–354.4131.2115.6–147.9
2064341315.6–353.1132.2116.5–147.8
2065340.3319.5–352133.1115.8–148.6
2066339.5319.3–352.1133.3117.2–149.4
2067342.1324.2–351.9133.3117–150.3
2068344.3320.4–354.8134.6117.4–150.5
2069342.8323.8–355.6134.4117.8–150.9
2070344.4322.1–356.2134.2116.7–151.8
2071345326.4–354.8136.3120.8–152.7
2072345318.5–356.3137.2119.9–153.1
2073343.1321.4–355.1136.1119.1–153.6
2074342.9325.4–354.5136119.7–152.2
2075341.8319.7–353.7135.2118.5–151.8
2076344.9323.6–356.2136.3117.4–154.7
2077342320.4–351.9136.8119.6–152.8
2078345324.3–355.7137.1118.3–154.2
2079343.3323.8–356138.1121.3–157.1
2080344.9328.1–358.4137.6120.5–157.9
2081342.7326–353.6137.8120.7–154.7
2082344.9329.8–355.4138.7121.6–155.2
2083343.8321.8–354.5139.2119.3–158.8
2084344328.8–356.5140.3123.4–157.5
2085346.4322.1–356.6139.2120.9–157.2
2086342.6316.5–352.9139.8121–157.8
2087345.5325.6–356.7139.5121.5–157.4
2088346.5325.1–358.5141121.8–159.9
2089347.8327.2–357.7140.4121.7–158.9
2090346.9334.4–356.8141.2123–160.7
2091346.9330.1–357.1141.8123–161.6
2092346.6327–356141.3122.5–159.3
2093345.4326.9–356.3141.4124.3–161
2094347326.3–357.7142123.3–159.6
2095343.9329.1–355.1143.5124–160.7
2096344326.6–356.1142.3125–161.3
2097346.7329.2–355.1141.2123.2–160
2098347.2326.3–356.6142.2122.5–162
2099345.5327.5–357.7141.8122.4–160.7
2100346329.4–356.1142.8124.3–160.8

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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