Angola vs Tanzania

Angola vs Tanzania: Tropical nights

Tropical nights in 2014: 61.1 nights in Angola and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 45.3 nights, or 1.74 times that in Angola.

nights a year · CMIP6

Angola vs Tanzania: Tropical nightsTropical nights in 2014: 61.1 nights in Angola and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 45.3 nights, or 1.74 times that in Angola.
AngolaTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Tanzania 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 Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearAngolaTanzania
201461.1106.3
201362.3105.5
201263.6108.4
201159.9109
201058.9103.9
200956.9101.1
200854.5100.3
200754.699.5
200654100.4
200553.898.7
200455.8100.4
200355.399.6
200253.298.4
200155101.5
200051.494.9
199948.194.2
199850.596.8
199747.993.5
199643.289.6
19954388.5
199441.685.4
199335.981.2
199235.380.1
199145.589.6
199046.791.1
198943.889.1
198842.787.6
198742.788.5
198642.789.4
198539.383
198438.283.1
198337.882.1
198240.884.8
19814288
198039.985
197939.185.5
197838.682.9
197738.684.1
197636.881
197538.180.8
197437.482.2
197338.783.6
197236.681.4
19713680.7
197036.681.8
196936.579.5
196834.579.1
196732.477.5
196634.378.1
196534.278
196431.573.8
196330.573.1
196237.681.1
196137.382.6
196038.783.9
19593881.4
195837.382.1
19573880.9
195635.180
195537.581.6
195436.581.4
195336.280.6
195237.381.4
195137.482.1
195036.580.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearAngolaTanzania
201567.946.7–89.4114.895.2–137.4
201663.143.9–82.7108.391.6–125.6
201768.248.7–87.9114.893.6–137.8
201869.250.6–90.9116.497.4–137.1
201969.547.5–97.7113.495.2–133.2
20207351.1–97.1119.396.2–143.5
202175.654.9–97.2119.5100.9–147.1
202278.758–105.7124.4105.3–147.4
202378.357.5–103.3122.1102.1–147.8
202483.457.6–108.1126.2100–150.1
202579.154–111.7124.6100.9–154
202682.455.4–117.5126.999.1–155.6
202784.157.6–115.3128102.9–147.7
202885.862.6–117.4129.9106.4–152.1
20299165.8–120134.1111–156.5
203087.661.6–119.2129.4106.4–151.1
203192.363.9–122.5136.4115.9–158.4
20329566.1–124.5135.1114–166.8
203392.766.8–125135.2110.9–161.9
203491.466.7–131.8134.7112.5–166.3
203596.364.7–131.8140.2114.6–165
203695.964.2–129137.8113.3–165.5
2037103.870.4–136.7142.9121.5–168.9
2038105.376.7–136.8147.9124.3–169.3
203999.367–137.4144.3117.6–171.3
2040100.569.2–143.1140.5117–178
2041109.975.5–145.2149.1121.7–175.6
204210775.4–153.1146.3120.5–185.3
2043102.572.6–148.6144.6117–173
2044106.872.1–147.2147.7121.2–175.8
2045107.276.5–148.5150.1125.2–183.4
2046119.383.6–159.4161.5128.6–192.2
2047123.483.9–157.3160.2129.7–194.4
2048121.483.1–161.4158.8132.7–193.1
2049122.883.6–165.9157.6131.1–196
2050124.786.1–168.1159.7127.8–192
2051122.389.3–169.4163.2135.5–197.8
2052127.289.2–173.9161.9136.2–199.1
2053124.885.7–169.4160.6127.5–197.7
2054129.386.8–169.7163.2131.5–200.2
2055127.194.6–174.1167.4137–208.3
2056130.688.2–184.1166.4130.8–209.7
2057137.790.4–179.2168134.6–208.3
2058134.592.1–179.4168.7134.9–210.3
2059136.698.3–189.8174.7144.9–219.5
2060145.896.6–186.9181.7138.1–219.8
2061136.989.6–192.5171.8135.5–218.1
2062140.689.9–190177.5139.9–224
2063142.592.2–189.4181.4140.1–213.8
2064142.295.4–186.9185.3140.1–215.2
2065144.2101–193.2183.5141.1–221.8
2066144.2100.5–193.3181.9146.3–219.3
2067142.496.2–194.4178.8138.8–229.2
2068150.1103.4–196.7186144.2–228.4
2069145.898.5–197.6183.7141.7–225.3
2070143.196.6–202.5180.7140.4–228.2
2071151.7103.6–205.4184.9146.9–235.2
2072158.8110.5–197.3191.3155–226.1
2073159.8114–208.3191.6152.4–235.6
2074151.1103.1–205.9183.3149.7–231.7
2075148.7100.3–201.6183.8144.8–233
2076157.3106.3–204.8191.1150.9–233.2
2077161.8115.3–206.2191.3152.6–238.2
2078158.1114–211.5189156.6–233.8
2079158.3109.9–212.9190.5147–237.3
2080162.8109.6–212.5197.3150.7–241.2
2081161.1112.7–207.9195.6153.4–237.4
2082161.2114.4–207.5194.5157.3–237.3
2083159.9106–216.6193.2151–249.8
2084169.2117.7–215.2201.1152.2–246.7
2085175118.5–226204.2162.3–252.3
2086160.3115.4–221.3195156–248.7
2087162.4118.5–223.3196.7160.8–244.5
2088169.9116–218.4208.4154.7–246.9
2089166.9119.1–220201.3158.6–248.2
2090165.8119.6–223.4197.9160.7–253.6
2091175.2120.2–229.1210161.6–256
2092172.5119.9–228.5205.8158.3–253.6
2093169.9116.3–228.6207.2161.2–251.9
2094172.3118.2–221207.9161.3–250.6
2095179122.5–229.5214.2166.4–258.5
2096170.5117.6–228.9205.3159.8–257.4
2097169.6116.1–222.1206.6158.4–256.8
2098174.6115.2–234.3209.1161–258.3
2099170.7118.3–232.7208.5160.1–256
2100173.4123.5–231208158.6–258.6

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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