Mexico vs Nigeria

Mexico vs Nigeria: Tropical nights

Tropical nights in 2014: 103.7 nights in Mexico and 303.9 nights in Nigeria, in the CMIP6 climate models’ median run. In 2014 the value was higher in Nigeria, by 200.2 nights, or 2.93 times that in Mexico.

nights a year · CMIP6

Mexico vs Nigeria: Tropical nightsTropical nights in 2014: 103.7 nights in Mexico and 303.9 nights in Nigeria, in the CMIP6 climate models’ median run. In 2014 the value was higher in Nigeria, by 200.2 nights, or 2.93 times that in Mexico.
MexicoNigeriaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Nigeria 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 Nigeria at 332.3 nights in 2100.

Every year

nights a year · CMIP6

YearMexicoNigeria
2014103.7303.9
2013103.9299.5
2012102.8304.4
2011102.9301.5
2010101.5301.4
2009101.8297.8
2008100.1297.4
200799.1298
200699.8297.2
200599.5295.4
200499.4294.1
200398.3298.4
200299.1295.2
200198.7299.1
200097.9293.9
199996.6290.3
199895.8289.9
199795.9292.5
199693.8290
199592.7289.1
199490.7287.4
199389284
199288.5281.6
199193.4289.1
199094.9290.6
198993287.2
198892.1288
198792285.6
198690.2289.1
198590284.2
198488284.4
198386.7281.9
198288.7283.5
198191.5286.4
198090.1282.8
197990.8283
197889282.8
197789285.9
197689.1281.7
197586.8280.4
197487.9280.7
197388.6284.3
197287.7284.1
197186.8279.3
197086.1282
196987.5278.7
196887.1279.6
196786.7278.1
196686.4279.4
196584.9279
196484.7276.8
196387.1275.1
196288284.1
196189.5281.9
196089.7285.9
195989.6282.8
195889.1281.4
195789283.3
195688.5280.8
195588.2280.4
195488.4284.1
195388.6280.4
195287.8280.8
195189.4284.2
195088.1279.3
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMexicoNigeria
2015106.192.9–118.4301.7282.9–317.3
2016107.695–120301.4280.8–312.5
2017108.696.3–119.7302.5284.3–316.3
201810997.1–120.4302.2286.8–316.5
2019110.396.4–123300.1281.2–318
2020109.696.8–121.8303283.7–318.5
2021111.296.9–124.1305.1287.1–318.4
2022109.796–121.7305.1286–319.5
2023111.898.6–125.3305286.4–318.9
2024112.298.2–126.2310.6295.1–321.5
202511298.8–125.8307.5292–319.4
2026113.999.5–126.4306.9286.1–322.9
2027112.999.5–128.3307.4288–321.7
2028115.2101.9–127.9310.7293.4–322.6
2029115.6101.9–127.9311.4293.3–324.4
2030115.9101.7–128.4310.6294.1–322.5
2031116.1100.9–129.9312.2295–324.8
2032116.1102.5–129.1310290–323.5
2033117.5102.5–131.1313292.9–327
2034117.2104.1–130.3311.7294.8–325.1
2035116.4103.1–130.3314.5296.7–327.7
2036117.8105.1–131313.5294.1–326.5
2037118.6104.3–131.7315.6297.9–327.1
2038121107.5–133.4316.9301.2–329.6
2039121.3107–135.6315.4299.4–328.2
2040121.9108.1–135.1315.6297.9–327.4
2041121.3105.3–134.6316.8300.6–330.2
2042122.7107.7–137.1316.3300.3–330.3
2043122.4108.1–137.5316298.4–326
2044121.9108–135.6317.9299.5–329.6
2045123.1108.8–139.2316.6300.5–330.4
2046123.8109.9–139.4317.8302.2–330.7
2047125.6111.9–139.4319.8301.5–333
2048126.3113–140.3320.1302.4–331.7
2049127111.2–140.8320.7305.3–331.7
2050128.1112.6–142.5320.9304–335
2051127.2113.4–140.8321304.1–334.2
2052126.2112.5–141.1320.9303.9–333.5
2053128.4111.5–142.7320.9303.3–334.1
2054128.1113.1–142.3324.5304.5–338.2
2055129114.4–144.7322.2308.4–333.7
2056129.5114.3–143.8324.8305.8–336.3
2057130.3113.5–145.9326310.8–337.3
2058128.8114.1–144.5322.9307.4–334.2
2059129.5114.5–144.5325.7308.9–339
2060131.4115.5–146.5323.8307.5–337
2061131.3118.4–146.8324.4307.1–338.2
2062130.8115.1–146.3325.7308–339.3
2063131.2115.6–147.9326.6308.7–337
2064132.2116.5–147.8326.2311–339.8
2065133.1115.8–148.6327.6313.5–339.4
2066133.3117.2–149.4328.4311.3–339.6
2067133.3117–150.3326308.4–340.5
2068134.6117.4–150.5329.3311.2–342.9
2069134.4117.8–150.9326.6309.9–338.1
2070134.2116.7–151.8327.4312.6–340.7
2071136.3120.8–152.7329.1313–341.1
2072137.2119.9–153.1330.3315.9–342.1
2073136.1119.1–153.6326.3309.5–341
2074136119.7–152.2326.7311.4–341.4
2075135.2118.5–151.8328.9314.5–341.8
2076136.3117.4–154.7329.6313.4–342
2077136.8119.6–152.8332.5314.4–343.3
2078137.1118.3–154.2329.8312.8–342.1
2079138.1121.3–157.1329.6313.8–340.6
2080137.6120.5–157.9331.7314.1–344.8
2081137.8120.7–154.7329.3311.6–343.7
2082138.7121.6–155.2329.3313.3–341.4
2083139.2119.3–158.8330.4315–342.2
2084140.3123.4–157.5330.5311.9–344.2
2085139.2120.9–157.2332.7316.6–343.6
2086139.8121–157.8331.9316.3–343.6
2087139.5121.5–157.4330.7314.9–342.4
2088141121.8–159.9331.7313.2–342.7
2089140.4121.7–158.9331.1318.3–341.9
2090141.2123–160.7332.4312.7–343.9
2091141.8123–161.6333.3311–345.8
2092141.3122.5–159.3332.7313.8–345.7
2093141.4124.3–161334.2318.6–344.9
2094142123.3–159.6334.2317.3–345.6
2095143.5124–160.7333.8319.3–346.3
2096142.3125–161.3332.5317.4–346.7
2097141.2123.2–160331.8312.6–344.6
2098142.2122.5–162332.3316–343.7
2099141.8122.4–160.7333316.9–344.2
2100142.8124.3–160.8332.3318.5–345

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

Mexico vs Nigeria

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment