Argentina vs Congo - Kinshasa

Argentina vs Congo - Kinshasa: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 248.5 nights in Congo - Kinshasa, in the CMIP6 climate models’ median run. In 2014 the value was higher in Congo - Kinshasa, by 205.9 nights, or 5.83 times that in Argentina.

nights a year · CMIP6

Argentina vs Congo - Kinshasa: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 248.5 nights in Congo - Kinshasa, in the CMIP6 climate models’ median run. In 2014 the value was higher in Congo - Kinshasa, by 205.9 nights, or 5.83 times that in Argentina.
ArgentinaCongo - KinshasaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Congo - Kinshasa 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 Congo - Kinshasa at 324.1 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaCongo - Kinshasa
201442.6248.5
201341.8249.2
201241250.9
201141.5248.7
201040.8243.5
200941.6243
200841.4239.7
200739.6237.7
200639.3239
200540.1237.3
200440.6238.5
200338.7239.3
200240.2236.5
200139.5242.5
200039.5233.5
199938.4226.2
199838.8230.6
199738.5226.6
199637218.6
199535.7217.2
199434.7211.9
199334.3201.5
199233.4197.6
199136.8220.1
199036225.4
198937218.4
198836.9216.7
198736.1216.6
198636.4216.8
198536206.1
198434.7205.9
198335.2204.3
198235.7204.5
198137.3215.2
198036.3211.4
197937.5208.5
197835.7202.6
197735.1206.5
197635.7201.9
197534.8199
197435.4204
197334.1208.4
197235.5202.5
197134.7196.3
197034.9201.7
196933.4197.3
196834.6199
196733188.8
196634.3194.7
196532.2189
196430.3177.3
196332178.5
196235.2203.2
196135.6203.9
196035.6209.8
195934.5203.3
195833.3204.3
195735.7204
195635197.6
195534.4200.5
195433.6201
195335.8204.6
195234.4201.9
195135.4204.8
195033.9200.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaCongo - Kinshasa
201544.433.5–53.4256.6217.3–277.7
201643.532.4–53.4247.7213.3–269.3
201742.834.2–52.6257.4226.6–278.3
201842.632.7–52.6258.8228.1–276.8
201943.633.4–53.1255.8222.6–278.7
202045.735.5–57.2259.4227.4–282.3
202145.634.3–56.4262.6234.7–283.8
202244.633.3–56.4264.8235.1–288.5
202344.934.9–53.9263.9236.8–287.2
202445.834.2–57.5270.9237.9–290
202546.536–58.1266.1230.6–292.2
202647.936.7–57267.4226.8–294.5
202746.434.5–56.3268.6230.6–293.6
202846.133.5–58.5271.7239.7–295.9
202948.336–58.8275.9249.3–296.6
203047.835.4–60.3270.4241.7–296.1
203146.935.5–58.7279.4246.6–297.5
20324837.9–59.7277.9249.4–302.3
203347.436.7–57.6276.9245.9–301.6
203447.837.8–58.9276.7247.4–305.6
203547.339–59281243.7–305.1
203648.939.2–58.4278.3244.7–304.9
20375141.2–60.9286.9256.1–308.6
203848.737.9–59.7289261.5–307.1
203948.839.1–58.4284.7253.4–307.3
204050.440.4–62.3284.5254.7–311.5
204150.740.4–61.7289.9258.4–310.8
20425037.3–61.1286.9254.1–314.3
204350.340.5–61285.9253–313
20445240–65288.3253.6–312.5
204552.441.3–65.6289.4260.1–314.1
204651.941.2–62.7298.3261.3–317.3
204751.542–64298.5268.2–317.8
204854.542.6–65299.1268–320.8
204953.942.8–64.9300.3269.6–320.4
205052.543.6–62.4297.8267.2–320.6
205155.743.3–67.4298.4272.3–323.1
205255.642.2–67300.2271.5–324
205355.342.6–67.6298.7265.5–322.6
205454.743–66.7300.6269.6–322.8
205555.942.3–67.2301.9274.9–325.6
205657.642.8–68.6302.1266.2–328.3
205756.842.3–68.7305.1274.4–326.5
205854.841.5–68.1305.3274.1–327.1
205957.844.9–70.3305.4279–329.6
206056.943.4–67.9310.7273.5–330.2
206156.542.3–70.6307266.1–329.8
206257.345.8–68.5308.8269.1–332
206358.244.6–70.2308.4277.6–328.4
206458.845.8–71.5310.6278.4–329.6
206558.746–71.1311.9282.4–331.2
206659.947–68.9310.4284.2–330.3
206758.944.8–71.5308.8275.9–334
206857.844.3–70.3313.9280.8–334.6
206959.445.4–70.5312.1270.6–332.7
207061.348.2–74.3309.6278–334
207160.148.7–73.2312.6285–336.5
207260.146.7–73.7317287.7–334.6
207360.847.6–73.5316.2291.2–337.1
207460.447.6–73.7311.6284.5–334.9
207561.347.9–73.9312.3279.3–335.2
207661.146.8–75.8315.9288.7–337.1
207760.647.1–73.1318.5292.6–338.2
207863.449.4–75.6315287.3–337.1
207959.948.7–73314.8286.3–336
20806348.1–75.5318.5286.8–337.8
208161.448.7–73.5318.4287.8–336.7
208261.747.7–75318.7289.8–336.5
208362.148.2–75.6317.4290.6–340.9
208462.950.3–76321.6293.8–339.8
20856246.9–76.4324.4294.3–341.4
208662.749.4–76.4319290.7–340.7
208761.847.9–74.9318.3291.9–339.6
208864.450.8–77.5320.9292.9–340
208962.749.3–76.3322.1293.9–339.8
209064.152.5–77.1320.4295.5–341.7
209164.451.7–78.3325.4294.3–343.3
209265.650.8–78.3321.5294.4–342.4
209362.749.7–76.8323.1297.8–341.2
209463.950.1–78.5323.1296.5–341.1
209562.948.8–77.9325.6299.1–343.7
209664.749.4–78.9321.8296.2–344.1
209764.552.4–80.1321.5292.6–342
209865.652.7–78.7324.2295.1–342.8
209965.249.3–80.2322.8293.7–344.6
210065.250–81.7324.1292.1–344.1

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

Argentina vs Congo - Kinshasa

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