Argentina vs Peru

Argentina vs Peru: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Peru, by 121.9 nights, or 3.86 times that in Argentina.

nights a year · CMIP6

Argentina vs Peru: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Peru, by 121.9 nights, or 3.86 times that in Argentina.
ArgentinaPeruCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Peru 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 Peru at 192.3 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaPeru
201442.6164.5
201341.8163.1
201241164.8
201141.5164.3
201040.8163.3
200941.6162.3
200841.4162
200739.6159.8
200639.3159.1
200540.1159.3
200440.6161.8
200338.7160.5
200240.2159.9
200139.5160.7
200039.5158
199938.4155.7
199838.8157.4
199738.5156.1
199637152.2
199535.7152.1
199434.7150.8
199334.3148.5
199233.4144
199136.8156
199036158.3
198937153.2
198836.9151.2
198736.1152
198636.4153.4
198536149
198434.7148.3
198335.2145.4
198235.7151.4
198137.3153.1
198036.3150.9
197937.5150.5
197835.7149.1
197735.1150.3
197635.7147.5
197534.8142.1
197435.4148.6
197334.1151.5
197235.5147.6
197134.7145.7
197034.9145.6
196933.4147
196834.6146
196733142.3
196634.3145.7
196532.2143.3
196430.3141.6
196332135.9
196235.2148.9
196135.6146.5
196035.6149.8
195934.5146.1
195833.3149.1
195735.7148.7
195635144
195534.4148.3
195433.6148.7
195335.8148.2
195234.4148.1
195135.4147.2
195033.9147.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaPeru
201544.433.5–53.4164.3148.5–174.9
201643.532.4–53.4163.4149.8–171.5
201742.834.2–52.6165.5155–175.2
201842.632.7–52.6165152.9–176.6
201943.633.4–53.1163.7151–176.8
202045.735.5–57.2165.3151.6–176.2
202145.634.3–56.4167.6154.7–177.3
202244.633.3–56.4169.5156.6–179.2
202344.934.9–53.9167.1156.3–178.4
202445.834.2–57.5170.6157.3–180.2
202546.536–58.1168.6155–179.9
202647.936.7–57167.8153.3–179.7
202746.434.5–56.3168.3155.2–178.8
202846.133.5–58.5169.8158.3–179.9
202948.336–58.8174162.8–181.7
203047.835.4–60.3168.1153.2–180.6
203146.935.5–58.7172.5156.2–183.7
20324837.9–59.7173.2162.7–184.7
203347.436.7–57.6172156.5–181
203447.837.8–58.9171.6158.7–185.6
203547.339–59172159.3–184.1
203648.939.2–58.4172.5160.7–183.2
20375141.2–60.9175.6166.3–185.3
203848.737.9–59.7175.8164.6–184.9
203948.839.1–58.4174.1162.7–185
204050.440.4–62.3175.4163.9–187
204150.740.4–61.7176.5165.3–186.1
20425037.3–61.1176.3161.9–189.7
204350.340.5–61174.8163.7–185.3
20445240–65175.3161.9–188.2
204552.441.3–65.6177.3165.5–186.9
204651.941.2–62.7180.3167.4–189.9
204751.542–64178.6167.5–189
204854.542.6–65181.2168.2–192.2
204953.942.8–64.9180.4168.1–189.8
205052.543.6–62.4178.6166.4–190.8
205155.743.3–67.4180.3168.5–190.6
205255.642.2–67181.5170.8–191.7
205355.342.6–67.6179.5168.3–190.8
205454.743–66.7180.1167.3–193.9
205555.942.3–67.2181.7171–194.8
205657.642.8–68.6182.2170–193
205756.842.3–68.7181.6168.7–193
205854.841.5–68.1183.1169.4–195.5
205957.844.9–70.3184.6169.7–195.3
206056.943.4–67.9185.6171.1–197.1
206156.542.3–70.6182.7169.9–195.8
206257.345.8–68.5184.3168.7–196.9
206358.244.6–70.2184.6170.8–196.9
206458.845.8–71.5184.4170.1–194.8
206558.746–71.1186.3173.3–196.9
206659.947–68.9185.6172.3–197.4
206758.944.8–71.5184.3169.4–198.2
206857.844.3–70.3186.1172.1–198.3
206959.445.4–70.5184.9169–198.3
207061.348.2–74.3185.4171.8–198.4
207160.148.7–73.2187.3173.3–198.7
207260.146.7–73.7188.1174.9–199.8
207360.847.6–73.5187.6175.9–202.1
207460.447.6–73.7186.4169.5–198.9
207561.347.9–73.9186.4170.6–198.3
207661.146.8–75.8188.8174.2–201
207760.647.1–73.1189.1174.7–201.8
207863.449.4–75.6188.4175.6–202.3
207959.948.7–73188172–199.7
20806348.1–75.5189.1172.8–201.7
208161.448.7–73.5188.4173.6–201.8
208261.747.7–75188.8174.8–199.7
208362.148.2–75.6189.9175.7–204.7
208462.950.3–76190.7176.3–204.4
20856246.9–76.4192176.2–204.6
208662.749.4–76.4189.1175.4–204
208761.847.9–74.9189.1175.9–203.6
208864.450.8–77.5191.1174.7–204.9
208962.749.3–76.3190.1174.3–203
209064.152.5–77.1190.4177–206.2
209164.451.7–78.3192.6174.4–205.9
209265.650.8–78.3192.6176.6–204.7
209362.749.7–76.8190.6176–206
209463.950.1–78.5192.3178.2–204.1
209562.948.8–77.9193.4176.5–207.3
209664.749.4–78.9191.4176.2–207.6
209764.552.4–80.1190.7174.9–202.2
209865.652.7–78.7192.9177.8–208.9
209965.249.3–80.2191.5176.8–205
210065.250–81.7192.3176.6–205.6

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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