Japan vs Mexico

Japan vs Mexico: Tropical nights

Tropical nights in 2014: 58.6 nights in Japan and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 45.1 nights, or 1.77 times that in Japan.

nights a year · CMIP6

Japan vs Mexico: Tropical nightsTropical nights in 2014: 58.6 nights in Japan and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 45.1 nights, or 1.77 times that in Japan.
JapanMexicoCMIP6 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 Japan at 87.7 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearJapanMexico
201458.6103.7
201359.9103.9
201259.3102.8
201157.9102.9
201059.6101.5
200957.6101.8
200857.3100.1
200756.699.1
200657.599.8
200557.299.5
200456.799.4
200356.198.3
20025699.1
200154.298.7
200053.897.9
199955.396.6
199852.495.8
199752.495.9
199652.993.8
199549.792.7
199449.590.7
199345.489
199245.188.5
199149.493.4
199050.794.9
198951.493
198848.192.1
198747.792
198646.190.2
198546.790
198444.888
198341.986.7
198246.488.7
198145.991.5
198046.590.1
197946.790.8
197847.689
197745.889
19764689.1
197546.986.8
197445.687.9
197344.388.6
197245.887.7
197144.886.8
19704486.1
196946.987.5
196845.787.1
196748.386.7
196645.986.4
196545.884.9
196444.984.7
196348.387.1
196245.688
196148.989.5
196046.489.7
195946.989.6
195848.889.1
195749.289
195650.688.5
195547.988.2
195446.988.4
195349.288.6
195249.587.8
195146.289.4
195049.988.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearJapanMexico
201560.649.3–74.4106.192.9–118.4
201661.547.9–73.9107.695–120
201762.352.1–75.8108.696.3–119.7
201860.548.5–73.810997.1–120.4
201964.152.1–80.1110.396.4–123
202063.151–74.5109.696.8–121.8
202162.348.5–78.8111.296.9–124.1
202264.653.8–76.5109.796–121.7
202365.951.7–78111.898.6–125.3
202465.352.9–80.7112.298.2–126.2
202565.652.8–80.411298.8–125.8
202665.554.2–81.2113.999.5–126.4
202766.452.9–79.5112.999.5–128.3
202865.352.4–80.1115.2101.9–127.9
202968.555–80.4115.6101.9–127.9
203066.552.3–80.6115.9101.7–128.4
203166.554.7–80116.1100.9–129.9
20326650.8–82.1116.1102.5–129.1
203370.354.7–84.8117.5102.5–131.1
203468.553.9–81.7117.2104.1–130.3
203572.960.4–84.6116.4103.1–130.3
203672.556.1–89.7117.8105.1–131
203767.656.7–82.5118.6104.3–131.7
203870.558.6–83.8121107.5–133.4
203970.455.6–85.7121.3107–135.6
204073.657.4–89.3121.9108.1–135.1
204172.955.6–88.5121.3105.3–134.6
204271.258.1–86.4122.7107.7–137.1
204373.357.9–88.1122.4108.1–137.5
204472.657.8–85.5121.9108–135.6
204572.959.5–86.7123.1108.8–139.2
204676.261–90.3123.8109.9–139.4
204775.656.6–89.3125.6111.9–139.4
204874.858.5–89.4126.3113–140.3
204974.359.7–90.8127111.2–140.8
205075.160.8–89.3128.1112.6–142.5
205175.861.1–92.4127.2113.4–140.8
205274.557.9–90.4126.2112.5–141.1
205378.559.6–91.6128.4111.5–142.7
205475.959.6–89.3128.1113.1–142.3
205576.862.2–95.1129114.4–144.7
205677.861.9–93.7129.5114.3–143.8
205779.962.8–94.4130.3113.5–145.9
205879.263.7–94.9128.8114.1–144.5
205979.858–95.6129.5114.5–144.5
206078.261.1–95.1131.4115.5–146.5
206180.865.7–96.7131.3118.4–146.8
20628063.6–96.3130.8115.1–146.3
20638064.1–96.5131.2115.6–147.9
206477.661.4–95.2132.2116.5–147.8
206581.763–97.4133.1115.8–148.6
206680.363.8–94.2133.3117.2–149.4
206781.363.2–97.1133.3117–150.3
206879.861.4–99.3134.6117.4–150.5
206982.365–96.1134.4117.8–150.9
207083.360.2–102.3134.2116.7–151.8
207183.663.6–99.2136.3120.8–152.7
207284.363.3–99.1137.2119.9–153.1
207383.564.9–97.4136.1119.1–153.6
207484.366.8–100.9136119.7–152.2
207585.664.1–99.8135.2118.5–151.8
207683.968.8–99.3136.3117.4–154.7
207786.467.6–102.4136.8119.6–152.8
207884.167.7–103.2137.1118.3–154.2
207986.168.3–99.4138.1121.3–157.1
208084.767.6–103.7137.6120.5–157.9
208183.668.5–104.3137.8120.7–154.7
208286.469.4–107.7138.7121.6–155.2
208385.966.5–105.7139.2119.3–158.8
208485.867.4–102.3140.3123.4–157.5
208587.568.9–102.8139.2120.9–157.2
208684.668.6–105.3139.8121–157.8
208787.270.3–107139.5121.5–157.4
208886.866.3–102.5141121.8–159.9
208985.765.9–103.8140.4121.7–158.9
209089.469.5–104.4141.2123–160.7
209188.367.4–103.1141.8123–161.6
20928667.7–102.3141.3122.5–159.3
209388.969.8–107.4141.4124.3–161
209487.569.3–103.7142123.3–159.6
20958872.4–104.9143.5124–160.7
209690.771–107.3142.3125–161.3
209789.471–103.1141.2123.2–160
209888.571–106.5142.2122.5–162
209988.370.8–102.4141.8122.4–160.7
210087.769.2–106.2142.8124.3–160.8

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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