Haiti vs Mexico

Haiti vs Mexico: Tropical nights

Tropical nights in 2014: 298.9 nights in Haiti and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 195.2 nights, or 2.88 times that in Mexico.

nights a year · CMIP6

Haiti vs Mexico: Tropical nightsTropical nights in 2014: 298.9 nights in Haiti and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 195.2 nights, or 2.88 times that in Mexico.
HaitiMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Haiti has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Haiti at 346.8 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearHaitiMexico
2014298.9103.7
2013301.1103.9
2012301.5102.8
2011301102.9
2010298.6101.5
2009298.7101.8
2008296.4100.1
2007293.699.1
2006294.299.8
2005295.399.5
200429899.4
2003295.498.3
2002295.699.1
200129698.7
200029197.9
1999290.896.6
1998291.495.8
199728895.9
199628793.8
1995283.192.7
1994282.690.7
1993278.889
1992277.788.5
1991286.293.4
1990291.194.9
1989286.393
1988282.792.1
1987282.992
198628190.2
1985277.990
1984277.788
1983276.186.7
1982280.488.7
1981281.391.5
1980280.290.1
1979280.290.8
1978277.889
1977280.489
197627689.1
1975275.186.8
1974278.187.9
1973278.388.6
1972276.687.7
1971275.586.8
1970272.286.1
1969275.587.5
1968274.587.1
196727586.7
1966277.886.4
1965274.184.9
1964274.884.7
1963274.287.1
1962278.688
1961278.289.5
1960278.289.7
1959278.689.6
1958281.689.1
195727889
1956277.988.5
1955280.788.2
1954277.688.4
1953276.888.6
1952279.787.8
1951277.989.4
1950276.888.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearHaitiMexico
2015305.5285.9–322.7106.192.9–118.4
2016306288.9–319.7107.695–120
2017307.5292–322.8108.696.3–119.7
2018308.8294.3–322.510997.1–120.4
2019307.1290.7–322.4110.396.4–123
2020307.4293.2–321.3109.696.8–121.8
2021311.8296.6–324.5111.296.9–124.1
2022312.1298–329.1109.796–121.7
2023311.6297.9–324.7111.898.6–125.3
2024312.3294.2–326.9112.298.2–126.2
2025314.6291.3–328.711298.8–125.8
2026316.3297.5–332.3113.999.5–126.4
2027316.4293.9–332.7112.999.5–128.3
2028316.4299.6–334.9115.2101.9–127.9
2029316.5298.3–333.6115.6101.9–127.9
2030314.8301.6–331.6115.9101.7–128.4
2031317.8303.5–333.7116.1100.9–129.9
2032321.4303.7–333.1116.1102.5–129.1
2033319.5302–332.4117.5102.5–131.1
2034319.5298.9–337.1117.2104.1–130.3
2035322.6304.3–335.1116.4103.1–130.3
2036321.3304.1–335.4117.8105.1–131
2037325310.6–336118.6104.3–131.7
2038322305.4–338.2121107.5–133.4
2039322.3305.5–339.8121.3107–135.6
2040324.1309.7–338.7121.9108.1–135.1
2041323.8310.9–339.7121.3105.3–134.6
2042325307.1–339.2122.7107.7–137.1
2043325.4306.3–339.9122.4108.1–137.5
2044326.8308.2–345.7121.9108–135.6
2045327312.5–341.6123.1108.8–139.2
2046330.7312.9–342.1123.8109.9–139.4
2047327.3313.3–343.2125.6111.9–139.4
2048331.4313.9–344.2126.3113–140.3
2049333.3314.4–344.6127111.2–140.8
2050331.2312.1–348128.1112.6–142.5
2051331.4314–342.3127.2113.4–140.8
2052331.5314.8–346126.2112.5–141.1
2053332.8314.2–342.8128.4111.5–142.7
2054331.7315.8–348.4128.1113.1–142.3
2055331.2317.8–348.8129114.4–144.7
2056330317.4–348.3129.5114.3–143.8
2057335.7314–347.6130.3113.5–145.9
2058335.3316.4–350.6128.8114.1–144.5
2059336.7319.6–349129.5114.5–144.5
2060337.6318.4–350131.4115.5–146.5
2061336.4318.8–349.6131.3118.4–146.8
2062336.1317.5–349.7130.8115.1–146.3
2063338320.8–354131.2115.6–147.9
2064336.6319.4–350.9132.2116.5–147.8
2065335.5318.9–349133.1115.8–148.6
2066338.8321.1–351.7133.3117.2–149.4
2067337.2317.8–350.8133.3117–150.3
2068340.4321.9–353.8134.6117.4–150.5
2069337.2320.2–351.6134.4117.8–150.9
2070339.5319.8–351.4134.2116.7–151.8
2071339.8320.1–353.6136.3120.8–152.7
2072342.6319.9–353.2137.2119.9–153.1
2073340.9320.2–353.6136.1119.1–153.6
2074340.9324.7–353.4136119.7–152.2
2075338.8321.7–353.5135.2118.5–151.8
2076344.1322–355.4136.3117.4–154.7
2077340.8321.6–354136.8119.6–152.8
2078340.6325.1–354.5137.1118.3–154.2
2079341.6323.7–354.4138.1121.3–157.1
2080340.3322.6–354.3137.6120.5–157.9
2081340322.6–353.4137.8120.7–154.7
2082342.4326.5–353.5138.7121.6–155.2
2083342.2326.4–352.5139.2119.3–158.8
2084345.5326.2–354.6140.3123.4–157.5
2085344325–355.4139.2120.9–157.2
2086344.9326.6–355.1139.8121–157.8
2087342.6322.5–354.4139.5121.5–157.4
2088342.5328.2–356.1141121.8–159.9
2089345.8326.6–358140.4121.7–158.9
2090343.2328.2–355.8141.2123–160.7
2091344.7323.1–357.7141.8123–161.6
2092346.5326.6–356.5141.3122.5–159.3
2093341.4324.8–356.7141.4124.3–161
2094341.4327.9–355.8142123.3–159.6
2095345.6326.2–356.1143.5124–160.7
2096344327.2–358.3142.3125–161.3
2097344.2330–356.7141.2123.2–160
2098343.8324.3–358.4142.2122.5–162
2099346.6323.1–358.1141.8122.4–160.7
2100346.8326.2–356.3142.8124.3–160.8

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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