Argentina vs Bolivia

Argentina vs Bolivia: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 179.5 nights in Bolivia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bolivia, by 136.9 nights, or 4.21 times that in Argentina.

nights a year · CMIP6

Argentina vs Bolivia: Tropical nightsTropical nights in 2014: 42.6 nights in Argentina and 179.5 nights in Bolivia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bolivia, by 136.9 nights, or 4.21 times that in Argentina.
ArgentinaBoliviaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Bolivia 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 Bolivia at 210.8 nights in 2100.

Every year

nights a year · CMIP6

YearArgentinaBolivia
201442.6179.5
201341.8176.3
201241177
201141.5177.2
201040.8176.7
200941.6175.9
200841.4174.1
200739.6169
200639.3169.8
200540.1170.5
200440.6175.5
200338.7170.6
200240.2173.3
200139.5172.9
200039.5169
199938.4167.3
199838.8170.7
199738.5167.7
199637163.3
199535.7164.4
199434.7162.7
199334.3160.4
199233.4155.4
199136.8169.7
199036172
198937164.4
198836.9161.5
198736.1162.5
198636.4163.8
198536157.8
198434.7159.8
198335.2156.8
198235.7164.2
198137.3166.5
198036.3162.2
197937.5162.7
197835.7161.1
197735.1161
197635.7160.1
197534.8155.5
197435.4160.5
197334.1160.5
197235.5158.8
197134.7156.7
197034.9155.1
196933.4155.7
196834.6155.9
196733153.3
196634.3156.7
196532.2154.2
196430.3150.7
196332148.4
196235.2157.9
196135.6158.7
196035.6160.3
195934.5159
195833.3157.5
195735.7159.3
195635154.5
195534.4160.3
195433.6159.7
195335.8157.8
195234.4159.1
195135.4157.6
195033.9158.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearArgentinaBolivia
201544.433.5–53.4177.7162.4–194.8
201643.532.4–53.4177.1155.9–190.7
201742.834.2–52.6179.6164.6–190.9
201842.632.7–52.6177.8162.1–196.3
201943.633.4–53.1180.1164.5–199.9
202045.735.5–57.2180.5162–200.6
202145.634.3–56.4185.6169.2–197.3
202244.633.3–56.4184.7165.7–200.5
202344.934.9–53.9181.3166.6–196.7
202445.834.2–57.5187.1168.2–202.1
202546.536–58.1183.5168.8–195.7
202647.936.7–57182.5164.8–198.1
202746.434.5–56.3182.7165–201.6
202846.133.5–58.5186.3169.6–200.3
202948.336–58.8192.5175.6–205.4
203047.835.4–60.3185.5161.7–204.2
203146.935.5–58.7189.2166.2–205.3
20324837.9–59.7189.7173.8–209.6
203347.436.7–57.6188.2167.7–204.1
203447.837.8–58.9188172.2–207.8
203547.339–59186.7169.1–206.1
203648.939.2–58.4190.5173.5–205.2
20375141.2–60.9195.3181.4–208.5
203848.737.9–59.7189.2174.7–207.8
203948.839.1–58.4192.7175.7–205.5
204050.440.4–62.3192.3176.8–204.2
204150.740.4–61.7193.9179–209
20425037.3–61.1191.3171.9–207.6
204350.340.5–61191.2174.4–209.9
20445240–65194.5179.1–209.4
204552.441.3–65.6194.4180.2–209
204651.941.2–62.7194.8181.4–213
204751.542–64196.5181.4–213.3
204854.542.6–65200.2184.6–212.8
204953.942.8–64.9199.8181.3–214.4
205052.543.6–62.4196.3173.9–210.9
205155.743.3–67.4198.5184.2–213.3
205255.642.2–67200.6185.7–214.8
205355.342.6–67.6198182.1–211
205454.743–66.7195.9179.8–211
205555.942.3–67.2201.2187.1–215
205657.642.8–68.6201.3181.5–216.1
205756.842.3–68.7200.6184.3–214.4
205854.841.5–68.1200.8182.8–216.5
205957.844.9–70.3203.2186.1–215.8
206056.943.4–67.9203.4186.2–219.7
206156.542.3–70.6197.9184–216.3
206257.345.8–68.5201.4186.2–219.1
206358.244.6–70.2201.5184.9–217
206458.845.8–71.5200.5184.6–216.1
206558.746–71.1204.9187.3–218.4
206659.947–68.9203.3186.8–218.1
206758.944.8–71.5203.6187.7–215.6
206857.844.3–70.3204.4188–218
206959.445.4–70.5203.8184.5–219
207061.348.2–74.3205.1188.3–221.4
207160.148.7–73.2203186.9–214.6
207260.146.7–73.7206186.6–221.5
207360.847.6–73.5206.5193.2–220.7
207460.447.6–73.7204.5184.1–219.5
207561.347.9–73.9203.8185.8–217.9
207661.146.8–75.8206.5190.1–220.4
207760.647.1–73.1209.1185.4–221.4
207863.449.4–75.6208.1192.7–222.9
207959.948.7–73204.7186.2–218.6
20806348.1–75.5208.7192.4–221.1
208161.448.7–73.5208.1190.7–221.1
208261.747.7–75208.2189.7–220.1
208362.148.2–75.6209.3192.8–222.6
208462.950.3–76208.2193.3–223.1
20856246.9–76.4210.4194–225
208662.749.4–76.4210.4189.7–225.4
208761.847.9–74.9207.9193.8–222
208864.450.8–77.5210.3193.4–225.2
208962.749.3–76.3208.2191.3–222.9
209064.152.5–77.1209.7195.5–225.2
209164.451.7–78.3209.7192.5–227.1
209265.650.8–78.3209.8192.1–223.9
209362.749.7–76.8209.4195.7–222.1
209463.950.1–78.5208.9194.6–222.7
209562.948.8–77.9210.3191.2–225.3
209664.749.4–78.9211.6193.9–225
209764.552.4–80.1208.6189.8–220.3
209865.652.7–78.7211.7196.2–226.5
209965.249.3–80.2211.2195.3–224
210065.250–81.7210.8195.8–226.8

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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