Argentina vs Haiti

Argentina vs Haiti: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 298.9 nights in Haiti, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 256.3 nights, or 7.01 times that in Argentina.

nights a year · CMIP6

Argentina vs Haiti: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 298.9 nights in Haiti, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 256.3 nights, or 7.01 times that in Argentina.
ArgentinaHaitiCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Haiti 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 Haiti at 346.8 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaHaiti
201442.6298.9
201341.8301.1
201241301.5
201141.5301
201040.8298.6
200941.6298.7
200841.4296.4
200739.6293.6
200639.3294.2
200540.1295.3
200440.6298
200338.7295.4
200240.2295.6
200139.5296
200039.5291
199938.4290.8
199838.8291.4
199738.5288
199637287
199535.7283.1
199434.7282.6
199334.3278.8
199233.4277.7
199136.8286.2
199036291.1
198937286.3
198836.9282.7
198736.1282.9
198636.4281
198536277.9
198434.7277.7
198335.2276.1
198235.7280.4
198137.3281.3
198036.3280.2
197937.5280.2
197835.7277.8
197735.1280.4
197635.7276
197534.8275.1
197435.4278.1
197334.1278.3
197235.5276.6
197134.7275.5
197034.9272.2
196933.4275.5
196834.6274.5
196733275
196634.3277.8
196532.2274.1
196430.3274.8
196332274.2
196235.2278.6
196135.6278.2
196035.6278.2
195934.5278.6
195833.3281.6
195735.7278
195635277.9
195534.4280.7
195433.6277.6
195335.8276.8
195234.4279.7
195135.4277.9
195033.9276.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaHaiti
201544.433.5–53.4305.5285.9–322.7
201643.532.4–53.4306288.9–319.7
201742.834.2–52.6307.5292–322.8
201842.632.7–52.6308.8294.3–322.5
201943.633.4–53.1307.1290.7–322.4
202045.735.5–57.2307.4293.2–321.3
202145.634.3–56.4311.8296.6–324.5
202244.633.3–56.4312.1298–329.1
202344.934.9–53.9311.6297.9–324.7
202445.834.2–57.5312.3294.2–326.9
202546.536–58.1314.6291.3–328.7
202647.936.7–57316.3297.5–332.3
202746.434.5–56.3316.4293.9–332.7
202846.133.5–58.5316.4299.6–334.9
202948.336–58.8316.5298.3–333.6
203047.835.4–60.3314.8301.6–331.6
203146.935.5–58.7317.8303.5–333.7
20324837.9–59.7321.4303.7–333.1
203347.436.7–57.6319.5302–332.4
203447.837.8–58.9319.5298.9–337.1
203547.339–59322.6304.3–335.1
203648.939.2–58.4321.3304.1–335.4
20375141.2–60.9325310.6–336
203848.737.9–59.7322305.4–338.2
203948.839.1–58.4322.3305.5–339.8
204050.440.4–62.3324.1309.7–338.7
204150.740.4–61.7323.8310.9–339.7
20425037.3–61.1325307.1–339.2
204350.340.5–61325.4306.3–339.9
20445240–65326.8308.2–345.7
204552.441.3–65.6327312.5–341.6
204651.941.2–62.7330.7312.9–342.1
204751.542–64327.3313.3–343.2
204854.542.6–65331.4313.9–344.2
204953.942.8–64.9333.3314.4–344.6
205052.543.6–62.4331.2312.1–348
205155.743.3–67.4331.4314–342.3
205255.642.2–67331.5314.8–346
205355.342.6–67.6332.8314.2–342.8
205454.743–66.7331.7315.8–348.4
205555.942.3–67.2331.2317.8–348.8
205657.642.8–68.6330317.4–348.3
205756.842.3–68.7335.7314–347.6
205854.841.5–68.1335.3316.4–350.6
205957.844.9–70.3336.7319.6–349
206056.943.4–67.9337.6318.4–350
206156.542.3–70.6336.4318.8–349.6
206257.345.8–68.5336.1317.5–349.7
206358.244.6–70.2338320.8–354
206458.845.8–71.5336.6319.4–350.9
206558.746–71.1335.5318.9–349
206659.947–68.9338.8321.1–351.7
206758.944.8–71.5337.2317.8–350.8
206857.844.3–70.3340.4321.9–353.8
206959.445.4–70.5337.2320.2–351.6
207061.348.2–74.3339.5319.8–351.4
207160.148.7–73.2339.8320.1–353.6
207260.146.7–73.7342.6319.9–353.2
207360.847.6–73.5340.9320.2–353.6
207460.447.6–73.7340.9324.7–353.4
207561.347.9–73.9338.8321.7–353.5
207661.146.8–75.8344.1322–355.4
207760.647.1–73.1340.8321.6–354
207863.449.4–75.6340.6325.1–354.5
207959.948.7–73341.6323.7–354.4
20806348.1–75.5340.3322.6–354.3
208161.448.7–73.5340322.6–353.4
208261.747.7–75342.4326.5–353.5
208362.148.2–75.6342.2326.4–352.5
208462.950.3–76345.5326.2–354.6
20856246.9–76.4344325–355.4
208662.749.4–76.4344.9326.6–355.1
208761.847.9–74.9342.6322.5–354.4
208864.450.8–77.5342.5328.2–356.1
208962.749.3–76.3345.8326.6–358
209064.152.5–77.1343.2328.2–355.8
209164.451.7–78.3344.7323.1–357.7
209265.650.8–78.3346.5326.6–356.5
209362.749.7–76.8341.4324.8–356.7
209463.950.1–78.5341.4327.9–355.8
209562.948.8–77.9345.6326.2–356.1
209664.749.4–78.9344327.2–358.3
209764.552.4–80.1344.2330–356.7
209865.652.7–78.7343.8324.3–358.4
209965.249.3–80.2346.6323.1–358.1
210065.250–81.7346.8326.2–356.3

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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