Mexico vs Venezuela

Mexico vs Venezuela: Tropical nights

Tropical nights in 2014: 103.7 nights in Mexico and 301.6 nights in Venezuela, in the CMIP6 climate models’ median run. In 2014 the value was higher in Venezuela, by 197.9 nights, or 2.91 times that in Mexico.

nights a year · CMIP6

Mexico vs Venezuela: Tropical nightsTropical nights in 2014: 103.7 nights in Mexico and 301.6 nights in Venezuela, in the CMIP6 climate models’ median run. In 2014 the value was higher in Venezuela, by 197.9 nights, or 2.91 times that in Mexico.
MexicoVenezuelaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Venezuela has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Mexico at 142.8 nights and Venezuela at 345 nights in 2100.

Every year

nights a year · CMIP6

YearMexicoVenezuela
2014103.7301.6
2013103.9302
2012102.8303.7
2011102.9301.3
2010101.5300.3
2009101.8300
2008100.1298.4
200799.1296.4
200699.8296.8
200599.5296.8
200499.4299.4
200398.3295.2
200299.1296.3
200198.7298.7
200097.9292.3
199996.6291.6
199895.8291.4
199795.9290.5
199693.8286.8
199592.7285.4
199490.7282.3
199389279.5
199288.5274.7
199193.4289.7
199094.9291.4
198993283.8
198892.1284.2
198792284.2
198690.2284.4
198590278.3
198488279.8
198386.7274.3
198288.7280.8
198191.5283.4
198090.1280.5
197990.8281.1
197889278.7
197789281.2
197689.1276.6
197586.8272.3
197487.9277.7
197388.6278.9
197287.7275.9
197186.8276.5
197086.1275.6
196987.5275.6
196887.1273.2
196786.7271.5
196686.4273.1
196584.9272.1
196484.7270.3
196387.1268.9
196288276.8
196189.5278.6
196089.7279.9
195989.6276.1
195889.1280.9
195789277.6
195688.5275.1
195588.2277.7
195488.4277.5
195388.6277.3
195287.8278.4
195189.4277.5
195088.1275.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMexicoVenezuela
2015106.192.9–118.4306.4280.3–320.1
2016107.695–120303.9282.3–316.9
2017108.696.3–119.7308.5288.7–319.9
201810997.1–120.4307.6289.9–320.7
2019110.396.4–123306.7288.7–321.7
2020109.696.8–121.8310.2287.9–323.6
2021111.296.9–124.1311.3295.3–324.1
2022109.796–121.7314.4295–326.3
2023111.898.6–125.3311.5294.4–326.5
2024112.298.2–126.2316298.2–327.4
202511298.8–125.8313.8294.2–329.5
2026113.999.5–126.4314290.3–329.4
2027112.999.5–128.3315.6292.6–328.8
2028115.2101.9–127.9317.7296.4–332.1
2029115.6101.9–127.9319.3296.9–332
2030115.9101.7–128.4317.7295–328.5
2031116.1100.9–129.9320.1295.9–331.8
2032116.1102.5–129.1321.4304.7–335
2033117.5102.5–131.1320.6301.8–331.2
2034117.2104.1–130.3318.1298.1–335
2035116.4103.1–130.3319.3302.3–335.9
2036117.8105.1–131320.5305.3–332.3
2037118.6104.3–131.7324.1307.2–334.1
2038121107.5–133.4325.8309.6–336.2
2039121.3107–135.6324.3307.9–335.8
2040121.9108.1–135.1323.5307.5–338.7
2041121.3105.3–134.6325.3309.6–336.6
2042122.7107.7–137.1324.8305.5–341.2
2043122.4108.1–137.5324.2307.1–337.7
2044121.9108–135.6324.1306.3–339.8
2045123.1108.8–139.2327.5309.7–338.6
2046123.8109.9–139.4329.6310.8–340.5
2047125.6111.9–139.4329.5313.9–341.5
2048126.3113–140.3331.2313.7–342.8
2049127111.2–140.8332.3314.9–340.5
2050128.1112.6–142.5330.9311.8–343.6
2051127.2113.4–140.8330.7310.1–344
2052126.2112.5–141.1332.4316.6–343.5
2053128.4111.5–142.7330.6312.7–343.6
2054128.1113.1–142.3331.9313.8–344.6
2055129114.4–144.7333317–345.8
2056129.5114.3–143.8332.7313.1–347.7
2057130.3113.5–145.9334.2315.2–345.3
2058128.8114.1–144.5333.5314.3–346.2
2059129.5114.5–144.5335.6317.1–348.3
2060131.4115.5–146.5337.4319.4–349
2061131.3118.4–146.8335.3317.3–347.2
2062130.8115.1–146.3335.9315–348.4
2063131.2115.6–147.9338317.5–347.9
2064132.2116.5–147.8336.3319.9–347.5
2065133.1115.8–148.6336.8319.9–349
2066133.3117.2–149.4337.9320.9–349.1
2067133.3117–150.3337.5317.9–348.2
2068134.6117.4–150.5339.3317.4–349.4
2069134.4117.8–150.9336.5318.1–349
2070134.2116.7–151.8336.4319.5–349.1
2071136.3120.8–152.7338.9319.1–349.1
2072137.2119.9–153.1340321.8–350.6
2073136.1119.1–153.6340.3322.9–351.4
2074136119.7–152.2338.9319.1–349.5
2075135.2118.5–151.8339.5318.1–349.2
2076136.3117.4–154.7339.8322.6–350.2
2077136.8119.6–152.8340.3322.1–351
2078137.1118.3–154.2340.2323–351
2079138.1121.3–157.1340.1320.9–351.4
2080137.6120.5–157.9341.4320.2–351.6
2081137.8120.7–154.7340.7322.5–351.3
2082138.7121.6–155.2341.6323.9–350.1
2083139.2119.3–158.8341.7323.3–353
2084140.3123.4–157.5343.3321.3–352.4
2085139.2120.9–157.2344.7322.8–353.5
2086139.8121–157.8341.4322.6–352.2
2087139.5121.5–157.4342.5322.4–352.2
2088141121.8–159.9342.9322.8–353.6
2089140.4121.7–158.9342.3324.8–353.1
2090141.2123–160.7341.9325.2–352.9
2091141.8123–161.6344.3323.4–353.3
2092141.3122.5–159.3344.3324.9–354.2
2093141.4124.3–161343324.8–353.6
2094142123.3–159.6343.9326.6–352.8
2095143.5124–160.7345.4325.4–354.5
2096142.3125–161.3343.7326–355.2
2097141.2123.2–160343.5324.6–351.9
2098142.2122.5–162344.5326.1–354.4
2099141.8122.4–160.7344.6324.8–353.8
2100142.8124.3–160.8345328.4–353.9

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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