China vs Mexico

China vs Mexico: Tropical nights

Tropical nights in 2014: 41.5 nights in China and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 62.3 nights, or 2.5 times that in China.

nights a year · CMIP6

China vs Mexico: Tropical nightsTropical nights in 2014: 41.5 nights in China and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 62.3 nights, or 2.5 times that in China.
ChinaMexicoCMIP6 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 China at 63.3 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearChinaMexico
201441.5103.7
201341.7103.9
201240.8102.8
201140.2102.9
201040.5101.5
200939.5101.8
200839.2100.1
200738.799.1
200639.599.8
200539.599.5
200439.799.4
200338.598.3
200238.899.1
200139.598.7
200038.697.9
199938.596.6
199837.695.8
199737.195.9
199636.693.8
199535.192.7
199434.990.7
199333.289
199232.388.5
199135.993.4
199036.494.9
198936.193
198835.192.1
198734.592
19863490.2
198533.590
198433.488
198331.586.7
198234.188.7
198134.291.5
198034.390.1
197933.890.8
197834.889
197733.389
197632.789.1
197533.186.8
197433.387.9
197333.188.6
197232.687.7
19713386.8
197032.486.1
196933.487.5
196832.887.1
196733.486.7
196633.486.4
196532.584.9
196432.184.7
196334.587.1
19623488
196134.689.5
196034.189.7
19593489.6
19583589.1
195734.489
195634.688.5
195534.288.2
195434.288.4
195334.388.6
195234.387.8
195135.189.4
195034.988.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearChinaMexico
201542.334.8–49.8106.192.9–118.4
201642.134.4–50107.695–120
201743.135.3–51.6108.696.3–119.7
201842.335.5–49.510997.1–120.4
201943.836.5–51.1110.396.4–123
202043.736.8–51.1109.696.8–121.8
202144.136–52.1111.296.9–124.1
202244.737.5–52.7109.796–121.7
202345.737.8–53.4111.898.6–125.3
202445.738.1–54112.298.2–126.2
202546.337.5–54.811298.8–125.8
202646.237.6–55.5113.999.5–126.4
202746.138–54.9112.999.5–128.3
202846.438.4–54.3115.2101.9–127.9
202946.939.1–55.6115.6101.9–127.9
203047.138.8–55.3115.9101.7–128.4
20314738.8–56116.1100.9–129.9
203248.339.3–57.4116.1102.5–129.1
203347.939.7–56.6117.5102.5–131.1
203448.440.5–57.3117.2104.1–130.3
203549.740.8–58.6116.4103.1–130.3
20364940.1–58.2117.8105.1–131
20374941.2–57.6118.6104.3–131.7
203850.542.4–59.3121107.5–133.4
203949.641.2–59.2121.3107–135.6
204050.942.4–60.4121.9108.1–135.1
204151.342.5–61.1121.3105.3–134.6
204251.642–61.5122.7107.7–137.1
204350.742.7–61122.4108.1–137.5
204451.942.4–61.9121.9108–135.6
204551.542.8–61.1123.1108.8–139.2
20465343.7–62.7123.8109.9–139.4
204753.544.5–62.5125.6111.9–139.4
204853.144–62.6126.3113–140.3
204952.843.8–63.3127111.2–140.8
205053.644.4–63.8128.1112.6–142.5
205154.345.1–64.8127.2113.4–140.8
205253.444.6–63.2126.2112.5–141.1
205354.244.2–64.2128.4111.5–142.7
205454.545.3–64.8128.1113.1–142.3
20555545.1–65.8129114.4–144.7
205655.245.1–66.6129.5114.3–143.8
205754.844.9–65.7130.3113.5–145.9
205855.145.8–67.7128.8114.1–144.5
205955.345.1–67.2129.5114.5–144.5
206057.246.9–68.1131.4115.5–146.5
206156.546.6–66.3131.3118.4–146.8
206256.846.9–68.5130.8115.1–146.3
206357.247.2–68.6131.2115.6–147.9
20645747.1–67.7132.2116.5–147.8
206557.347.1–67.8133.1115.8–148.6
206657.347.9–68.7133.3117.2–149.4
206757.546.4–68.2133.3117–150.3
206858.748.5–70.5134.6117.4–150.5
206958.548.4–69134.4117.8–150.9
20705847.6–71.7134.2116.7–151.8
207159.347.4–71.6136.3120.8–152.7
207259.248.1–71.5137.2119.9–153.1
207359.849.1–70.9136.1119.1–153.6
207459.648.7–71.1136119.7–152.2
207558.748.3–71.4135.2118.5–151.8
207660.249–70.9136.3117.4–154.7
207760.851.1–72.4136.8119.6–152.8
207859.648.8–72.4137.1118.3–154.2
207960.750.1–72.6138.1121.3–157.1
208059.950–72.3137.6120.5–157.9
208160.950–73.2137.8120.7–154.7
20826149.8–73.3138.7121.6–155.2
208361.251.2–73.6139.2119.3–158.8
208461.749.7–74.6140.3123.4–157.5
208561.250.8–75.2139.2120.9–157.2
208661.648.9–74.5139.8121–157.8
208761.650.6–75139.5121.5–157.4
208862.750.5–77.1141121.8–159.9
208961.950–75.2140.4121.7–158.9
209062.551.4–73.7141.2123–160.7
209163.852–75.7141.8123–161.6
209263.251.2–75.1141.3122.5–159.3
209363.252–75.4141.4124.3–161
20946351.1–76.3142123.3–159.6
209563.952.8–76.4143.5124–160.7
209663.852.2–76.8142.3125–161.3
209762.750.7–75.1141.2123.2–160
209863.451.2–76.8142.2122.5–162
209963.851.9–76.1141.8122.4–160.7
210063.351.7–76.2142.8124.3–160.8

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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