Mexico vs Sudan

Mexico vs Sudan: Tropical nights

Tropical nights in 2014: 103.7 nights in Mexico and 242.4 nights in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 138.7 nights, or 2.34 times that in Mexico.

nights a year · CMIP6

Mexico vs Sudan: Tropical nightsTropical nights in 2014: 103.7 nights in Mexico and 242.4 nights in Sudan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Sudan, by 138.7 nights, or 2.34 times that in Mexico.
MexicoSudanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Sudan 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 Sudan at 278.6 nights in 2100.

Every year

nights a year · CMIP6

YearMexicoSudan
2014103.7242.4
2013103.9240
2012102.8242
2011102.9242.2
2010101.5240.6
2009101.8236.5
2008100.1237.1
200799.1236
200699.8235.3
200599.5233.1
200499.4233.5
200398.3235.6
200299.1234.7
200198.7235.4
200097.9230.5
199996.6232.1
199895.8230.2
199795.9231.1
199693.8227.3
199592.7227.8
199490.7225.3
199389219.1
199288.5217.8
199193.4227.3
199094.9227.5
198993223
198892.1223.1
198792224.4
198690.2226.4
198590222.1
198488220.7
198386.7217
198288.7216.3
198191.5223.2
198090.1220
197990.8218.4
197889218.5
197789219.3
197689.1220.1
197586.8215.7
197487.9217.5
197388.6220
197287.7217.9
197186.8215.5
197086.1217
196987.5213.1
196887.1214
196786.7210.3
196686.4213.3
196584.9213.4
196484.7213.2
196387.1210.1
196288217
196189.5216.9
196089.7221.3
195989.6217.8
195889.1216.2
195789218.9
195688.5217.2
195588.2216.6
195488.4218.9
195388.6215.1
195287.8216.4
195189.4218.5
195088.1214.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMexicoSudan
2015106.192.9–118.4242.3225.3–258.3
2016107.695–120241.4223.3–254.1
2017108.696.3–119.7243.2223–259.1
201810997.1–120.4242.3226.4–258.5
2019110.396.4–123243.1221.7–260.4
2020109.696.8–121.8244.9225.9–261.7
2021111.296.9–124.1245.6229.1–261.5
2022109.796–121.7249230.9–262.3
2023111.898.6–125.3247.1226.8–263.1
2024112.298.2–126.2251.5232.8–266.1
202511298.8–125.8250.7232.4–265.6
2026113.999.5–126.4250230.8–266.6
2027112.999.5–128.3248.8228.4–265.6
2028115.2101.9–127.9249232.2–263.1
2029115.6101.9–127.9251.4232.1–266
2030115.9101.7–128.4252235.4–266.7
2031116.1100.9–129.9253.3234.4–268.9
2032116.1102.5–129.1250.4232.3–266.6
2033117.5102.5–131.1254.4235.3–269.4
2034117.2104.1–130.3254.2234.5–269.9
2035116.4103.1–130.3258.3240.2–273.6
2036117.8105.1–131252.8235.6–268.6
2037118.6104.3–131.7256.7238.6–271.8
2038121107.5–133.4258.7244.8–272.1
2039121.3107–135.6259.5241.2–272.5
2040121.9108.1–135.1256.4236.7–272.3
2041121.3105.3–134.6259.1241.2–274.5
2042122.7107.7–137.1258.7242–274.7
2043122.4108.1–137.5258.1240.3–272.6
2044121.9108–135.6257.3238.6–274.7
2045123.1108.8–139.2258.8243.1–276.2
2046123.8109.9–139.4261.1241.7–277.6
2047125.6111.9–139.4261.4244.6–278.4
2048126.3113–140.3260.4243.4–279.5
2049127111.2–140.8261.9242.6–275.9
2050128.1112.6–142.5263.5245.4–279
2051127.2113.4–140.8263.6246.6–278.8
2052126.2112.5–141.1263.8248.7–278.3
2053128.4111.5–142.7262.8242.4–279.2
2054128.1113.1–142.3266.3246.6–282.9
2055129114.4–144.7265.6245.9–281.4
2056129.5114.3–143.8264.1242.6–281.5
2057130.3113.5–145.9266.4247.6–283.4
2058128.8114.1–144.5265.2247.4–280.3
2059129.5114.5–144.5268.4249.6–285.4
2060131.4115.5–146.5263.6246.7–284.4
2061131.3118.4–146.8266.9250.1–281.9
2062130.8115.1–146.3266.4248.5–285
2063131.2115.6–147.9267.1246.9–283.4
2064132.2116.5–147.8269250.7–284.7
2065133.1115.8–148.6269.8253.9–285.6
2066133.3117.2–149.4271.4251.9–287.3
2067133.3117–150.3270.9250–288.4
2068134.6117.4–150.5271.9251.7–289.8
2069134.4117.8–150.9268251.1–286.2
2070134.2116.7–151.8269252.3–285.8
2071136.3120.8–152.7275.5254.1–290.4
2072137.2119.9–153.1273.3254.2–289.4
2073136.1119.1–153.6271.9250.7–287.6
2074136119.7–152.2270.9249–290.1
2075135.2118.5–151.8273.1254–291.9
2076136.3117.4–154.7272.7255.2–290.9
2077136.8119.6–152.8274.6255.2–292.7
2078137.1118.3–154.2274.3255.6–291.2
2079138.1121.3–157.1272255.2–288.5
2080137.6120.5–157.9276.6256–292.2
2081137.8120.7–154.7275.1254.1–294.8
2082138.7121.6–155.2272.9258.7–288.6
2083139.2119.3–158.8276.5258–291.7
2084140.3123.4–157.5275.4253–294.9
2085139.2120.9–157.2275.3258.6–291.6
2086139.8121–157.8276.4256.9–296.6
2087139.5121.5–157.4273.5253.1–293.3
2088141121.8–159.9273.6253.7–293.6
2089140.4121.7–158.9276.5256.6–293.4
2090141.2123–160.7276.6256.4–294.6
2091141.8123–161.6277.4256.4–296.6
2092141.3122.5–159.3274.6254.3–294.9
2093141.4124.3–161278261.9–292.1
2094142123.3–159.6280.3262.2–294
2095143.5124–160.7277.5262.6–294
2096142.3125–161.3279.7258.7–297
2097141.2123.2–160276.3254.1–297.6
2098142.2122.5–162277.7258.2–295.5
2099141.8122.4–160.7276.8257.2–296.2
2100142.8124.3–160.8278.6259–294.3

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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