Mexico vs Saudi Arabia

Mexico vs Saudi Arabia: Tropical nights

Tropical nights in 2014: 103.7 nights in Mexico and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 77.8 nights, or 1.75 times that in Mexico.

nights a year · CMIP6

Mexico vs Saudi Arabia: Tropical nightsTropical nights in 2014: 103.7 nights in Mexico and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 77.8 nights, or 1.75 times that in Mexico.
MexicoSaudi ArabiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Saudi Arabia 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 Saudi Arabia at 218.7 nights in 2100.

Every year

nights a year · CMIP6

YearMexicoSaudi Arabia
2014103.7181.5
2013103.9180.4
2012102.8182.8
2011102.9182.7
2010101.5179.2
2009101.8177.1
2008100.1180.3
200799.1178.9
200699.8177.5
200599.5177.9
200499.4177.6
200398.3177.4
200299.1175.6
200198.7178.1
200097.9176.4
199996.6173.2
199895.8173.4
199795.9173.8
199693.8172
199592.7169.2
199490.7170.4
199389164.6
199288.5165.9
199193.4169.2
199094.9172.7
198993168.9
198892.1166.8
198792167.3
198690.2169.4
198590166
198488165
198386.7163.5
198288.7164.7
198191.5168.9
198090.1166.8
197990.8165.3
197889164.8
197789165.6
197689.1165.9
197586.8161.2
197487.9162.9
197388.6163.7
197287.7163.7
197186.8160.4
197086.1162.5
196987.5161.3
196887.1162.7
196786.7159.5
196686.4159.5
196584.9159.5
196484.7159.9
196387.1160.2
196288163.2
196189.5163.7
196089.7165.7
195989.6164.4
195889.1164.1
195789165.5
195688.5163.6
195588.2162
195488.4161.2
195388.6162.5
195287.8163.4
195189.4161.2
195088.1161.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMexicoSaudi Arabia
2015106.192.9–118.4184.9169.4–198.7
2016107.695–120183167.7–195.7
2017108.696.3–119.7182.6168.1–196.7
201810997.1–120.4186.8173.1–199.4
2019110.396.4–123184.1168.8–199.1
2020109.696.8–121.8185.3171.8–198.9
2021111.296.9–124.1188.6173.6–202.8
2022109.796–121.7187.6170.7–202
2023111.898.6–125.3188.6173–203.8
2024112.298.2–126.2187.1172.9–203.9
202511298.8–125.8191.5176–206.1
2026113.999.5–126.4191.8177.1–205.5
2027112.999.5–128.3191.2176.6–206.8
2028115.2101.9–127.9191.9175.5–205.1
2029115.6101.9–127.9192.2176.6–205.7
2030115.9101.7–128.4193.3178.4–206.3
2031116.1100.9–129.9194.7179.1–207.6
2032116.1102.5–129.1192.2175.2–206
2033117.5102.5–131.1192.6177.5–206.9
2034117.2104.1–130.3196.7181.6–213
2035116.4103.1–130.3196.5179.9–211.6
2036117.8105.1–131194.1180–209.7
2037118.6104.3–131.7197183.7–209.9
2038121107.5–133.4198.4182.3–213.3
2039121.3107–135.6198184.4–213.6
2040121.9108.1–135.1199.2182.1–212.7
2041121.3105.3–134.6197.7181.4–211.7
2042122.7107.7–137.1198.3181.2–217
2043122.4108.1–137.5198.2182.3–215.3
2044121.9108–135.6199.2185.5–213.5
2045123.1108.8–139.2202187.1–216.8
2046123.8109.9–139.4204.1185.3–219.4
2047125.6111.9–139.4204.1187.4–220
2048126.3113–140.3206.1190.7–220
2049127111.2–140.8201.6187.7–216.2
2050128.1112.6–142.5205.7190.2–219.3
2051127.2113.4–140.8204.3188.8–222.1
2052126.2112.5–141.1203.8189.6–218
2053128.4111.5–142.7203.8186.3–218.8
2054128.1113.1–142.3207.6188.3–222.3
2055129114.4–144.7207.8190.8–221
2056129.5114.3–143.8203.7186.6–220.1
2057130.3113.5–145.9207.5188.8–224.2
2058128.8114.1–144.5205.9189.2–221.4
2059129.5114.5–144.5207.3191.6–226.9
2060131.4115.5–146.5206.9192.7–222.8
2061131.3118.4–146.8206.5190.4–220.9
2062130.8115.1–146.3208.1189.4–228.3
2063131.2115.6–147.9210.4193–227.1
2064132.2116.5–147.8207.5191.9–223.3
2065133.1115.8–148.6208.9193.9–226.1
2066133.3117.2–149.4210.3194.9–228
2067133.3117–150.3210.9193.1–228.6
2068134.6117.4–150.5209.8194.6–228.6
2069134.4117.8–150.9208.9194.5–226.3
2070134.2116.7–151.8211.2191.2–229
2071136.3120.8–152.7215.1196.3–233.3
2072137.2119.9–153.1213.6195.3–229.3
2073136.1119.1–153.6213.7194.1–231.6
2074136119.7–152.2210.5191.9–229.3
2075135.2118.5–151.8212.1196.6–231.8
2076136.3117.4–154.7212.8194.8–230.3
2077136.8119.6–152.8215.1196.6–233.9
2078137.1118.3–154.2215.5197.6–230.7
2079138.1121.3–157.1213.6197–229
2080137.6120.5–157.9213.6197.1–233.9
2081137.8120.7–154.7214.7194.4–231.6
2082138.7121.6–155.2214198.9–230.9
2083139.2119.3–158.8214.2198.5–238
2084140.3123.4–157.5217.4197.4–233.1
2085139.2120.9–157.2217.4199.6–237.9
2086139.8121–157.8217197.4–237.4
2087139.5121.5–157.4217.3199.7–238.7
2088141121.8–159.9216.1198.2–243.1
2089140.4121.7–158.9217.6199.5–239
2090141.2123–160.7217.3198.5–239.2
2091141.8123–161.6218.5202.8–238.4
2092141.3122.5–159.3218.5198.5–241.6
2093141.4124.3–161216.6197.8–236.3
2094142123.3–159.6218.8202–236.9
2095143.5124–160.7219.4204.2–237.4
2096142.3125–161.3219.9197.7–239.6
2097141.2123.2–160216.7196.8–239.7
2098142.2122.5–162219.7199.6–241.3
2099141.8122.4–160.7216.8200.8–236.8
2100142.8124.3–160.8218.7202.3–241

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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