Argentina vs Mexico

Argentina vs Mexico: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 61.1 nights, or 2.43 times that in Argentina.

nights a year · CMIP6

Argentina vs Mexico: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 61.1 nights, or 2.43 times that in Argentina.
ArgentinaMexicoCMIP6 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 Argentina at 65.2 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaMexico
201442.6103.7
201341.8103.9
201241102.8
201141.5102.9
201040.8101.5
200941.6101.8
200841.4100.1
200739.699.1
200639.399.8
200540.199.5
200440.699.4
200338.798.3
200240.299.1
200139.598.7
200039.597.9
199938.496.6
199838.895.8
199738.595.9
19963793.8
199535.792.7
199434.790.7
199334.389
199233.488.5
199136.893.4
19903694.9
19893793
198836.992.1
198736.192
198636.490.2
19853690
198434.788
198335.286.7
198235.788.7
198137.391.5
198036.390.1
197937.590.8
197835.789
197735.189
197635.789.1
197534.886.8
197435.487.9
197334.188.6
197235.587.7
197134.786.8
197034.986.1
196933.487.5
196834.687.1
19673386.7
196634.386.4
196532.284.9
196430.384.7
19633287.1
196235.288
196135.689.5
196035.689.7
195934.589.6
195833.389.1
195735.789
19563588.5
195534.488.2
195433.688.4
195335.888.6
195234.487.8
195135.489.4
195033.988.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaMexico
201544.433.5–53.4106.192.9–118.4
201643.532.4–53.4107.695–120
201742.834.2–52.6108.696.3–119.7
201842.632.7–52.610997.1–120.4
201943.633.4–53.1110.396.4–123
202045.735.5–57.2109.696.8–121.8
202145.634.3–56.4111.296.9–124.1
202244.633.3–56.4109.796–121.7
202344.934.9–53.9111.898.6–125.3
202445.834.2–57.5112.298.2–126.2
202546.536–58.111298.8–125.8
202647.936.7–57113.999.5–126.4
202746.434.5–56.3112.999.5–128.3
202846.133.5–58.5115.2101.9–127.9
202948.336–58.8115.6101.9–127.9
203047.835.4–60.3115.9101.7–128.4
203146.935.5–58.7116.1100.9–129.9
20324837.9–59.7116.1102.5–129.1
203347.436.7–57.6117.5102.5–131.1
203447.837.8–58.9117.2104.1–130.3
203547.339–59116.4103.1–130.3
203648.939.2–58.4117.8105.1–131
20375141.2–60.9118.6104.3–131.7
203848.737.9–59.7121107.5–133.4
203948.839.1–58.4121.3107–135.6
204050.440.4–62.3121.9108.1–135.1
204150.740.4–61.7121.3105.3–134.6
20425037.3–61.1122.7107.7–137.1
204350.340.5–61122.4108.1–137.5
20445240–65121.9108–135.6
204552.441.3–65.6123.1108.8–139.2
204651.941.2–62.7123.8109.9–139.4
204751.542–64125.6111.9–139.4
204854.542.6–65126.3113–140.3
204953.942.8–64.9127111.2–140.8
205052.543.6–62.4128.1112.6–142.5
205155.743.3–67.4127.2113.4–140.8
205255.642.2–67126.2112.5–141.1
205355.342.6–67.6128.4111.5–142.7
205454.743–66.7128.1113.1–142.3
205555.942.3–67.2129114.4–144.7
205657.642.8–68.6129.5114.3–143.8
205756.842.3–68.7130.3113.5–145.9
205854.841.5–68.1128.8114.1–144.5
205957.844.9–70.3129.5114.5–144.5
206056.943.4–67.9131.4115.5–146.5
206156.542.3–70.6131.3118.4–146.8
206257.345.8–68.5130.8115.1–146.3
206358.244.6–70.2131.2115.6–147.9
206458.845.8–71.5132.2116.5–147.8
206558.746–71.1133.1115.8–148.6
206659.947–68.9133.3117.2–149.4
206758.944.8–71.5133.3117–150.3
206857.844.3–70.3134.6117.4–150.5
206959.445.4–70.5134.4117.8–150.9
207061.348.2–74.3134.2116.7–151.8
207160.148.7–73.2136.3120.8–152.7
207260.146.7–73.7137.2119.9–153.1
207360.847.6–73.5136.1119.1–153.6
207460.447.6–73.7136119.7–152.2
207561.347.9–73.9135.2118.5–151.8
207661.146.8–75.8136.3117.4–154.7
207760.647.1–73.1136.8119.6–152.8
207863.449.4–75.6137.1118.3–154.2
207959.948.7–73138.1121.3–157.1
20806348.1–75.5137.6120.5–157.9
208161.448.7–73.5137.8120.7–154.7
208261.747.7–75138.7121.6–155.2
208362.148.2–75.6139.2119.3–158.8
208462.950.3–76140.3123.4–157.5
20856246.9–76.4139.2120.9–157.2
208662.749.4–76.4139.8121–157.8
208761.847.9–74.9139.5121.5–157.4
208864.450.8–77.5141121.8–159.9
208962.749.3–76.3140.4121.7–158.9
209064.152.5–77.1141.2123–160.7
209164.451.7–78.3141.8123–161.6
209265.650.8–78.3141.3122.5–159.3
209362.749.7–76.8141.4124.3–161
209463.950.1–78.5142123.3–159.6
209562.948.8–77.9143.5124–160.7
209664.749.4–78.9142.3125–161.3
209764.552.4–80.1141.2123.2–160
209865.652.7–78.7142.2122.5–162
209965.249.3–80.2141.8122.4–160.7
210065.250–81.7142.8124.3–160.8

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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