Argentina vs Colombia

Argentina vs Colombia: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 279.9 nights in Colombia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Colombia, by 237.3 nights, or 6.56 times that in Argentina.

nights a year · CMIP6

Argentina vs Colombia: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 279.9 nights in Colombia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Colombia, by 237.3 nights, or 6.56 times that in Argentina.
ArgentinaColombiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Colombia 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 Colombia at 297.4 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaColombia
201442.6279.9
201341.8279.8
201241280.7
201141.5280
201040.8279.1
200941.6279.3
200841.4278.4
200739.6277.3
200639.3277.5
200540.1277.7
200440.6278.2
200338.7277.5
200240.2277.3
200139.5278
200039.5276.2
199938.4274.6
199838.8275.2
199738.5274.4
199637271.2
199535.7271.3
199434.7270.4
199334.3268
199233.4264.7
199136.8273.9
199036275.6
198937271.9
198836.9270.3
198736.1271.8
198636.4271.4
198536268.4
198434.7268.2
198335.2265.1
198235.7269.2
198137.3272.1
198036.3270.2
197937.5269.3
197835.7268.3
197735.1269.6
197635.7266.1
197534.8261.6
197435.4266.6
197334.1269.9
197235.5266.6
197134.7265.7
197034.9265.4
196933.4266
196834.6264.6
196733261.7
196634.3263.7
196532.2263.2
196430.3260.3
196332254.8
196235.2266.7
196135.6267
196035.6268.6
195934.5265.5
195833.3268
195735.7267.4
195635263.3
195534.4267.7
195433.6267.2
195335.8267.9
195234.4268.1
195135.4267.2
195033.9266.5
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaColombia
201544.433.5–53.4280.4265.9–286.4
201643.532.4–53.4279.9267.9–285.6
201742.834.2–52.6281.7270.6–286.3
201842.632.7–52.6281.5271.8–286.3
201943.633.4–53.1281.1269.5–286.9
202045.735.5–57.2282.1270.6–287.9
202145.634.3–56.4283.2273.9–287.8
202244.633.3–56.4283.7273.6–288.5
202344.934.9–53.9282.6274.2–288.8
202445.834.2–57.5284.7274.7–289.8
202546.536–58.1283.5273.3–289.7
202647.936.7–57283.4272.7–289.7
202746.434.5–56.3283.9273.4–289.2
202846.133.5–58.5285275.1–290.7
202948.336–58.8285.8276–290.3
203047.835.4–60.3284.2273.4–289.8
203146.935.5–58.7285.8274.8–291.2
20324837.9–59.7286.7278.3–292.6
203347.436.7–57.6285.7274.7–290.3
203447.837.8–58.9285275.8–292.8
203547.339–59285.9277.3–292
203648.939.2–58.4286276.9–291.6
20375141.2–60.9287.5279.3–291.9
203848.737.9–59.7288279.7–292.4
203948.839.1–58.4287.6278.8–292.7
204050.440.4–62.3287.6279.3–294.5
204150.740.4–61.7288.2279.9–292.7
20425037.3–61.1288.2278.3–295
204350.340.5–61287.7277.7–293.4
20445240–65287.8278.5–295.1
204552.441.3–65.6288.8280.5–293.9
204651.941.2–62.7290.4281–295.5
204751.542–64289.9280.6–294.6
204854.542.6–65290.7281.4–296.8
204953.942.8–64.9290.9282–295.3
205052.543.6–62.4290.1280.8–296
205155.743.3–67.4290.6280.9–295.7
205255.642.2–67290.9281.9–296.7
205355.342.6–67.6290.5280.8–296.3
205454.743–66.7290.8281.3–297.2
205555.942.3–67.2291.1282.6–298
205657.642.8–68.6291.5281.5–298.6
205756.842.3–68.7291.5281.2–297.3
205854.841.5–68.1291.8281.7–298.9
205957.844.9–70.3292.8282–299.2
206056.943.4–67.9293.2283–300.1
206156.542.3–70.6292.2281.9–298.7
206257.345.8–68.5292.6282.4–299.7
206358.244.6–70.2293.6282.3–298.6
206458.845.8–71.5292.7282.9–299.1
206558.746–71.1293.8283.6–299.4
206659.947–68.9293.1283.4–299.8
206758.944.8–71.5292.9281.8–299.6
206857.844.3–70.3294.2282.5–300.6
206959.445.4–70.5292.9282.4–300
207061.348.2–74.3292.9282.8–300.8
207160.148.7–73.2294.2282.8–301.5
207260.146.7–73.7294.9285.1–301.9
207360.847.6–73.5294.9285.5–302.2
207460.447.6–73.7293.9283.3–300.3
207561.347.9–73.9294.1283.2–300.6
207661.146.8–75.8294.9284.6–302
207760.647.1–73.1295.3284.3–301.9
207863.449.4–75.6294.4285–302
207959.948.7–73294.8283.7–301.8
20806348.1–75.5295.1283.4–302.8
208161.448.7–73.5295.1284.8–302.6
208261.747.7–75295.1284.9–301.3
208362.148.2–75.6295.4284.5–304.6
208462.950.3–76296285.1–304.4
20856246.9–76.4296.6285–305
208662.749.4–76.4295.6284.8–303.6
208761.847.9–74.9295.3284.1–303.4
208864.450.8–77.5295.9284.5–305.5
208962.749.3–76.3295.6285–304.5
209064.152.5–77.1295.7285.8–304.6
209164.451.7–78.3297285–304.9
209265.650.8–78.3296.8286–305.7
209362.749.7–76.8296.3285.6–305.3
209463.950.1–78.5296.4285.8–305
209562.948.8–77.9297.9285.6–304.9
209664.749.4–78.9296285.9–307.5
209764.552.4–80.1296.5284.8–303.4
209865.652.7–78.7296.6286–307.3
209965.249.3–80.2297284.6–305.4
210065.250–81.7297.4286.5–305.2

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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