France vs Mexico

France vs Mexico: Tropical nights

Tropical nights in 2014: 3.1 nights in France and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 100.6 nights, or 34 times that in France.

nights a year · CMIP6

France vs Mexico: Tropical nightsTropical nights in 2014: 3.1 nights in France and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 100.6 nights, or 34 times that in France.
FranceMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Mexico has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts France at 19.2 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearFranceMexico
20143.1103.7
20133.1103.9
20122.9102.8
20112.7102.9
20103.9101.5
20092.5101.8
20082.4100.1
20072.199.1
20062.699.8
20052.999.5
20042.799.4
20032.698.3
20021.899.1
20012.398.7
20001.897.9
19992.196.6
19981.595.8
19971.695.9
19961.593.8
19951.392.7
19941.590.7
19931.189
1992188.5
19911.893.4
19901.994.9
19891.293
19881.292.1
19871.392
19860.990.2
19850.990
19841.188
19831.186.7
1982188.7
19811.191.5
19801.290.1
19790.990.8
19781.389
19770.989
19760.889.1
19750.986.8
19741.287.9
19730.988.6
19720.987.7
1971186.8
19700.986.1
1969187.5
19680.987.1
19670.886.7
19660.886.4
19650.784.9
1964184.7
19630.987.1
19621.188
19610.989.5
19601.189.7
19591.289.6
1958189.1
1957189
19561.288.5
19551.188.2
19541.388.4
1953188.6
19521.387.8
19511.189.4
19501.288.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearFranceMexico
20153.61.5–8.6106.192.9–118.4
20164.11.5–9.9107.695–120
20173.51.3–10.2108.696.3–119.7
20183.91.7–10.810997.1–120.4
20194.51.6–9110.396.4–123
20204.11.6–10.5109.696.8–121.8
20214.51.3–13.2111.296.9–124.1
202251.5–12.5109.796–121.7
20234.81.6–12.5111.898.6–125.3
20245.51.8–11.2112.298.2–126.2
20255.81.5–12.111298.8–125.8
20266.22.1–12.7113.999.5–126.4
20275.41.7–11.2112.999.5–128.3
20285.91.7–13.3115.2101.9–127.9
20296.31.9–12.6115.6101.9–127.9
20305.82.1–11.9115.9101.7–128.4
20315.92–11.8116.1100.9–129.9
20325.92.7–12.9116.1102.5–129.1
203372.5–13.6117.5102.5–131.1
20347.92.4–17.3117.2104.1–130.3
20356.92.4–14.4116.4103.1–130.3
20367.32.6–14.6117.8105.1–131
20377.32.6–13.3118.6104.3–131.7
20386.53–15.1121107.5–133.4
20396.92.6–14.3121.3107–135.6
20407.72.3–16121.9108.1–135.1
20418.12.6–15.2121.3105.3–134.6
20426.93–16122.7107.7–137.1
20437.92.8–15.6122.4108.1–137.5
20447.93.1–16.6121.9108–135.6
20459.23.2–19.6123.1108.8–139.2
20468.93.2–17.6123.8109.9–139.4
20479.74–19.2125.6111.9–139.4
20489.13.4–17126.3113–140.3
204910.13.7–20.8127111.2–140.8
205010.94.8–18.9128.1112.6–142.5
20519.23.5–18.4127.2113.4–140.8
2052103.4–21.2126.2112.5–141.1
20538.73.8–18128.4111.5–142.7
20549.74.4–19.2128.1113.1–142.3
20559.93.9–17.2129114.4–144.7
2056114.3–21.8129.5114.3–143.8
205710.94.2–19.8130.3113.5–145.9
205813.85.1–25.7128.8114.1–144.5
205911.23.3–25129.5114.5–144.5
206012.86.1–22131.4115.5–146.5
206112.64.7–23.2131.3118.4–146.8
206212.36.2–22.4130.8115.1–146.3
2063125.2–24.9131.2115.6–147.9
2064125.3–21.6132.2116.5–147.8
206512.53.9–30.8133.1115.8–148.6
206611.55.3–22.1133.3117.2–149.4
206718.38.1–33.3133.3117–150.3
2068135.4–23.4134.6117.4–150.5
206915.65.7–25.5134.4117.8–150.9
207013.55.2–29.1134.2116.7–151.8
2071154.4–30.2136.3120.8–152.7
207215.57.4–26137.2119.9–153.1
207313.96–29.1136.1119.1–153.6
207412.84.3–27.3136119.7–152.2
207513.96.3–25.6135.2118.5–151.8
2076166.1–33.8136.3117.4–154.7
207713.25–29.8136.8119.6–152.8
207813.75.1–33.6137.1118.3–154.2
207912.95.3–28.4138.1121.3–157.1
208014.45.4–27.9137.6120.5–157.9
208115.15.8–29.8137.8120.7–154.7
208216.46.1–33.9138.7121.6–155.2
208315.97.9–32139.2119.3–158.8
208414.16.6–27.7140.3123.4–157.5
208516.57.3–30.2139.2120.9–157.2
208619.55.5–32.4139.8121–157.8
2087196.9–38139.5121.5–157.4
208818.47.7–35.2141121.8–159.9
20891910.6–29.3140.4121.7–158.9
209016.36.8–33.5141.2123–160.7
209119.77.6–32.3141.8123–161.6
209217.36.1–32.7141.3122.5–159.3
2093156.5–29.8141.4124.3–161
209418.68.5–32.8142123.3–159.6
209519.25.9–38.9143.5124–160.7
209619.37.6–35.5142.3125–161.3
209717.36.2–36.1141.2123.2–160
209818.16.9–36.3142.2122.5–162
209920.37.4–34.6141.8122.4–160.7
210019.27–36.7142.8124.3–160.8

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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