Angola vs Chad

Angola vs Chad: Tropical nights

Tropical nights in 2014: 61.1 nights in Angola and 237.6 nights in Chad, in the CMIP6 climate models’ median run. In 2014 the value was higher in Chad, by 176.6 nights, or 3.89 times that in Angola.

nights a year · CMIP6

Angola vs Chad: Tropical nightsTropical nights in 2014: 61.1 nights in Angola and 237.6 nights in Chad, in the CMIP6 climate models’ median run. In 2014 the value was higher in Chad, by 176.6 nights, or 3.89 times that in Angola.
AngolaChadCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Chad has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Angola at 173.4 nights and Chad at 273.4 nights in 2100.

Every year

nights a year · CMIP6

YearAngolaChad
201461.1237.6
201362.3231.8
201263.6237.9
201159.9236.2
201058.9234.8
200956.9231.5
200854.5230.8
200754.6229.6
200654229.5
200553.8228.8
200455.8228
200355.3230.9
200253.2229.8
200155230.2
200051.4226.4
199948.1225.1
199850.5222.9
199747.9226.3
199643.2222.4
199543222.3
199441.6221.4
199335.9215.6
199235.3214.4
199145.5223
199046.7222.8
198943.8220
198842.7219.9
198742.7218.4
198642.7222.6
198539.3218
198438.2216.1
198337.8213.7
198240.8214.8
198142218.1
198039.9215
197939.1214.5
197838.6216
197738.6216.2
197636.8215.7
197538.1212.2
197437.4213.8
197338.7216.9
197236.6215.2
197136212.6
197036.6214.3
196936.5210.3
196834.5212.8
196732.4209.1
196634.3210.8
196534.2210.3
196431.5210.6
196330.5207.5
196237.6214.7
196137.3212.3
196038.7217.3
195938212.5
195837.3213.8
195738214
195635.1213.4
195537.5213.8
195436.5214.3
195336.2211.3
195237.3213.1
195137.4213.8
195036.5213.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearAngolaChad
201567.946.7–89.4235.8215.6–253.1
201663.143.9–82.7233.3212.8–247.7
201768.248.7–87.9237.6218.6–253.1
201869.250.6–90.9235.8217.8–254.4
201969.547.5–97.7235.2213.3–255.6
20207351.1–97.1237217.1–255
202175.654.9–97.2239.6220–258.2
202278.758–105.7240.4223.1–258.2
202378.357.5–103.3239.1216.7–256.4
202483.457.6–108.1246.7227.6–261.2
202579.154–111.7243.2223.9–259.4
202682.455.4–117.5242.9220.8–260.9
202784.157.6–115.3242.3221.2–258.6
202885.862.6–117.4242.7225.4–259.7
20299165.8–120246.3227.2–264.1
203087.661.6–119.2244.7225.8–261.1
203192.363.9–122.5246.8224.7–264.8
20329566.1–124.5244.3226.5–260.2
203392.766.8–125247.6228.7–266.1
203491.466.7–131.8247.8224.9–263.9
203596.364.7–131.8250.9230.3–268.9
203695.964.2–129246.7226.3–264.1
2037103.870.4–136.7249.9230.3–266.2
2038105.376.7–136.8252.4233.4–268.7
203999.367–137.4250230.8–267.5
2040100.569.2–143.1248.9227–266.8
2041109.975.5–145.2252230–270.9
204210775.4–153.1250.4232–271.8
2043102.572.6–148.6251.1232–265.5
2044106.872.1–147.2251.4230.2–271.3
2045107.276.5–148.5252.3230.8–270.2
2046119.383.6–159.4253.6231.9–272.3
2047123.483.9–157.3254.6236.7–274.4
2048121.483.1–161.4254.4236.6–273.6
2049122.883.6–165.9256235.4–272
2050124.786.1–168.1255.9234.4–276.1
2051122.389.3–169.4256.1237.8–275.9
2052127.289.2–173.9258.3237.1–273.9
2053124.885.7–169.4255.9234.9–275
2054129.386.8–169.7260.6233–279.6
2055127.194.6–174.1259.9239.1–276.6
2056130.688.2–184.1259.4233.3–279
2057137.790.4–179.2262.5240.8–278.4
2058134.592.1–179.4259.3239.2–275.5
2059136.698.3–189.8263.7240.5–282.9
2060145.896.6–186.9259.3239.3–280
2061136.989.6–192.5261.1240.7–281.2
2062140.689.9–190261.4238.1–281.4
2063142.592.2–189.4263.4239.6–278.6
2064142.295.4–186.9263.9244.3–283.2
2065144.2101–193.2263.7247.7–283.1
2066144.2100.5–193.3265.2245.7–285.6
2067142.496.2–194.4262.5242.8–283.8
2068150.1103.4–196.7266.8241.4–286.3
2069145.898.5–197.6262.7242.8–283.1
2070143.196.6–202.5264.9243.5–284.9
2071151.7103.6–205.4267.9248.5–286
2072158.8110.5–197.3269.2246.8–285.6
2073159.8114–208.3263.7241.6–284.2
2074151.1103.1–205.9264239.7–285.1
2075148.7100.3–201.6266.5246.7–287
2076157.3106.3–204.8267.8245.8–285.7
2077161.8115.3–206.2269.5247.1–290.8
2078158.1114–211.5268.6247.9–286.4
2079158.3109.9–212.9266.4247.9–286.3
2080162.8109.6–212.5269.4249.6–289.4
2081161.1112.7–207.9267.4247.1–291.8
2082161.2114.4–207.5266.7249.2–286.8
2083159.9106–216.6269.8248.9–287.6
2084169.2117.7–215.2268.4243.4–289.7
2085175118.5–226270.8251.2–287.4
2086160.3115.4–221.3270.6249.6–291.5
2087162.4118.5–223.3266.3246.2–289.2
2088169.9116–218.4269.2245.6–290.7
2089166.9119.1–220270.4251.1–289
2090165.8119.6–223.4270.9245.5–291.1
2091175.2120.2–229.1271.3246.1–293.5
2092172.5119.9–228.5270.6248.3–291.9
2093169.9116.3–228.6272.4254.3–289.2
2094172.3118.2–221274254.8–290.2
2095179122.5–229.5273.5251.8–291.6
2096170.5117.6–228.9273.9252.1–292.5
2097169.6116.1–222.1270.8246–292.1
2098174.6115.2–234.3271.1248.3–290.6
2099170.7118.3–232.7271.8250.5–291.1
2100173.4123.5–231273.4254–291.9

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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