Argentina vs Paraguay

Argentina vs Paraguay: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 202.9 nights in Paraguay, in the CMIP6 climate models’ median run. In 2014 the value was higher in Paraguay, by 160.3 nights, or 4.76 times that in Argentina.

nights a year · CMIP6

Argentina vs Paraguay: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 202.9 nights in Paraguay, in the CMIP6 climate models’ median run. In 2014 the value was higher in Paraguay, by 160.3 nights, or 4.76 times that in Argentina.
ArgentinaParaguayCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Paraguay 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 Paraguay at 250.2 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaParaguay
201442.6202.9
201341.8197.2
201241200.5
201141.5198.1
201040.8201.6
200941.6200.4
200841.4196.1
200739.6186.1
200639.3188.5
200540.1198.3
200440.6194.8
200338.7189.8
200240.2194.4
200139.5191.4
200039.5195.8
199938.4188.8
199838.8195.1
199738.5190.7
199637183.9
199535.7182.1
199434.7177.4
199334.3180.8
199233.4172.7
199136.8183.7
199036189.6
198937185.4
198836.9181.8
198736.1179.7
198636.4184.5
198536176.9
198434.7177.7
198335.2180.1
198235.7179.6
198137.3185
198036.3184.1
197937.5185.9
197835.7178.1
197735.1179
197635.7178.3
197534.8174
197435.4176.5
197334.1176.4
197235.5179.4
197134.7173.8
197034.9173.6
196933.4171.7
196834.6174.8
196733169.8
196634.3173
196532.2168.3
196430.3164.7
196332164.3
196235.2175.9
196135.6176.1
196035.6175.1
195934.5176.2
195833.3170.6
195735.7176.3
195635170.4
195534.4176.1
195433.6175.2
195335.8175.6
195234.4180.5
195135.4174.9
195033.9174.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaParaguay
201544.433.5–53.4203.5180.7–228.9
201643.532.4–53.4202.2171.5–224.3
201742.834.2–52.6201.3180.6–222.8
201842.632.7–52.6196.9170.8–225.1
201943.633.4–53.1202.2175.2–227
202045.735.5–57.2204.2179.6–236.7
202145.634.3–56.4211186.7–234.8
202244.633.3–56.4211.3175.3–237.2
202344.934.9–53.9207.4184.7–225.6
202445.834.2–57.5213.3188.8–236.5
202546.536–58.1205.4186.1–232.5
202647.936.7–57209.4178.8–228.7
202746.434.5–56.3209185.2–237.4
202846.133.5–58.5210.8179.1–233.5
202948.336–58.8218.4188.8–243.2
203047.835.4–60.3214.3179.2–245.6
203146.935.5–58.7210184.3–238.2
20324837.9–59.7218.4187.5–246
203347.436.7–57.6211.7186.3–234.1
203447.837.8–58.9216.7190.9–239.5
203547.339–59212.1185.1–244.7
203648.939.2–58.4216190.9–238.6
20375141.2–60.9222.7201.4–242
203848.737.9–59.7212.9191.8–238.7
203948.839.1–58.4219.3196.4–243.2
204050.440.4–62.3221.8197.3–243.4
204150.740.4–61.7225.9200.7–245.5
20425037.3–61.1218.4185.8–239.7
204350.340.5–61219.9194.4–247.3
20445240–65222.9198.5–246.5
204552.441.3–65.6225.4201.2–249
204651.941.2–62.7222.3195–248.4
204751.542–64225.3203.5–250.5
204854.542.6–65233.4214.5–252.3
204953.942.8–64.9230.7205.1–253.8
205052.543.6–62.4224.3193.5–249
205155.743.3–67.4232.3210.5–252.7
205255.642.2–67232.8205.9–257.6
205355.342.6–67.6229.9205.2–255.9
205454.743–66.7227.4204.3–253.3
205555.942.3–67.2232.6202.1–255.1
205657.642.8–68.6232.5203.6–257.8
205756.842.3–68.7234.8211.3–255.1
205854.841.5–68.1232.9202–260.8
205957.844.9–70.3237.9217.3–255.2
206056.943.4–67.9234.2205.8–258.5
206156.542.3–70.6230.7207.6–258.3
206257.345.8–68.5234.6217.3–262.8
206358.244.6–70.2237.1211.2–255.7
206458.845.8–71.5234.6207–259.5
206558.746–71.1236.5216.7–260.5
206659.947–68.9237.2208.8–253.5
206758.944.8–71.5235.4214.5–254.3
206857.844.3–70.3235.6210.7–265.5
206959.445.4–70.5235.9207.8–265.8
207061.348.2–74.3242.2216.6–265.3
207160.148.7–73.2239.8204.9–260.7
207260.146.7–73.7239.9212.6–266.9
207360.847.6–73.5242.1214.2–262
207460.447.6–73.7242.1214.2–267.1
207561.347.9–73.9241.8219.2–259.7
207661.146.8–75.8243.8221.7–267.7
207760.647.1–73.1244.9208.1–264.7
207863.449.4–75.6245.9222–265.6
207959.948.7–73237.4218–266.2
20806348.1–75.5243.2217.9–268.8
208161.448.7–73.5242.6221.4–259.8
208261.747.7–75244.9214.1–264.3
208362.148.2–75.6241.5212.1–266.3
208462.950.3–76244.6219.4–269.9
20856246.9–76.4247.6216.5–271.8
208662.749.4–76.4249220.5–274.6
208761.847.9–74.9243.9217.8–265.9
208864.450.8–77.5249225.7–274.3
208962.749.3–76.3241.8216.4–271.4
209064.152.5–77.1249.4226.7–273.9
209164.451.7–78.3249.3225.7–271.9
209265.650.8–78.3248.4225.1–268.1
209362.749.7–76.8245.2217.9–268.1
209463.950.1–78.5243.2219–266.2
209562.948.8–77.9247.3217.5–268.2
209664.749.4–78.9245.1222.1–273.7
209764.552.4–80.1247.9221.8–271.9
209865.652.7–78.7251.3228.7–274.7
209965.249.3–80.2246.4221.2–271.2
210065.250–81.7250.2222.5–281.6

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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