Chad vs Tanzania

Chad vs Tanzania: Tropical nights

Tropical nights in 2014: 237.6 nights in Chad and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Chad, by 131.3 nights, or 2.24 times that in Tanzania.

Watch it change on the map

nights a year · CMIP6

Chad vs Tanzania: Tropical nightsTropical nights in 2014: 237.6 nights in Chad and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Chad, by 131.3 nights, or 2.24 times that in Tanzania.
ChadTanzaniaCMIP6 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 Chad at 273.4 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearChadTanzania
2014237.6106.3
2013231.8105.5
2012237.9108.4
2011236.2109
2010234.8103.9
2009231.5101.1
2008230.8100.3
2007229.699.5
2006229.5100.4
2005228.898.7
2004228100.4
2003230.999.6
2002229.898.4
2001230.2101.5
2000226.494.9
1999225.194.2
1998222.996.8
1997226.393.5
1996222.489.6
1995222.388.5
1994221.485.4
1993215.681.2
1992214.480.1
199122389.6
1990222.891.1
198922089.1
1988219.987.6
1987218.488.5
1986222.689.4
198521883
1984216.183.1
1983213.782.1
1982214.884.8
1981218.188
198021585
1979214.585.5
197821682.9
1977216.284.1
1976215.781
1975212.280.8
1974213.882.2
1973216.983.6
1972215.281.4
1971212.680.7
1970214.381.8
1969210.379.5
1968212.879.1
1967209.177.5
1966210.878.1
1965210.378
1964210.673.8
1963207.573.1
1962214.781.1
1961212.382.6
1960217.383.9
1959212.581.4
1958213.882.1
195721480.9
1956213.480
1955213.881.6
1954214.381.4
1953211.380.6
1952213.181.4
1951213.882.1
1950213.180.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearChadTanzania
2015235.8215.6–253.1114.895.2–137.4
2016233.3212.8–247.7108.391.6–125.6
2017237.6218.6–253.1114.893.6–137.8
2018235.8217.8–254.4116.497.4–137.1
2019235.2213.3–255.6113.495.2–133.2
2020237217.1–255119.396.2–143.5
2021239.6220–258.2119.5100.9–147.1
2022240.4223.1–258.2124.4105.3–147.4
2023239.1216.7–256.4122.1102.1–147.8
2024246.7227.6–261.2126.2100–150.1
2025243.2223.9–259.4124.6100.9–154
2026242.9220.8–260.9126.999.1–155.6
2027242.3221.2–258.6128102.9–147.7
2028242.7225.4–259.7129.9106.4–152.1
2029246.3227.2–264.1134.1111–156.5
2030244.7225.8–261.1129.4106.4–151.1
2031246.8224.7–264.8136.4115.9–158.4
2032244.3226.5–260.2135.1114–166.8
2033247.6228.7–266.1135.2110.9–161.9
2034247.8224.9–263.9134.7112.5–166.3
2035250.9230.3–268.9140.2114.6–165
2036246.7226.3–264.1137.8113.3–165.5
2037249.9230.3–266.2142.9121.5–168.9
2038252.4233.4–268.7147.9124.3–169.3
2039250230.8–267.5144.3117.6–171.3
2040248.9227–266.8140.5117–178
2041252230–270.9149.1121.7–175.6
2042250.4232–271.8146.3120.5–185.3
2043251.1232–265.5144.6117–173
2044251.4230.2–271.3147.7121.2–175.8
2045252.3230.8–270.2150.1125.2–183.4
2046253.6231.9–272.3161.5128.6–192.2
2047254.6236.7–274.4160.2129.7–194.4
2048254.4236.6–273.6158.8132.7–193.1
2049256235.4–272157.6131.1–196
2050255.9234.4–276.1159.7127.8–192
2051256.1237.8–275.9163.2135.5–197.8
2052258.3237.1–273.9161.9136.2–199.1
2053255.9234.9–275160.6127.5–197.7
2054260.6233–279.6163.2131.5–200.2
2055259.9239.1–276.6167.4137–208.3
2056259.4233.3–279166.4130.8–209.7
2057262.5240.8–278.4168134.6–208.3
2058259.3239.2–275.5168.7134.9–210.3
2059263.7240.5–282.9174.7144.9–219.5
2060259.3239.3–280181.7138.1–219.8
2061261.1240.7–281.2171.8135.5–218.1
2062261.4238.1–281.4177.5139.9–224
2063263.4239.6–278.6181.4140.1–213.8
2064263.9244.3–283.2185.3140.1–215.2
2065263.7247.7–283.1183.5141.1–221.8
2066265.2245.7–285.6181.9146.3–219.3
2067262.5242.8–283.8178.8138.8–229.2
2068266.8241.4–286.3186144.2–228.4
2069262.7242.8–283.1183.7141.7–225.3
2070264.9243.5–284.9180.7140.4–228.2
2071267.9248.5–286184.9146.9–235.2
2072269.2246.8–285.6191.3155–226.1
2073263.7241.6–284.2191.6152.4–235.6
2074264239.7–285.1183.3149.7–231.7
2075266.5246.7–287183.8144.8–233
2076267.8245.8–285.7191.1150.9–233.2
2077269.5247.1–290.8191.3152.6–238.2
2078268.6247.9–286.4189156.6–233.8
2079266.4247.9–286.3190.5147–237.3
2080269.4249.6–289.4197.3150.7–241.2
2081267.4247.1–291.8195.6153.4–237.4
2082266.7249.2–286.8194.5157.3–237.3
2083269.8248.9–287.6193.2151–249.8
2084268.4243.4–289.7201.1152.2–246.7
2085270.8251.2–287.4204.2162.3–252.3
2086270.6249.6–291.5195156–248.7
2087266.3246.2–289.2196.7160.8–244.5
2088269.2245.6–290.7208.4154.7–246.9
2089270.4251.1–289201.3158.6–248.2
2090270.9245.5–291.1197.9160.7–253.6
2091271.3246.1–293.5210161.6–256
2092270.6248.3–291.9205.8158.3–253.6
2093272.4254.3–289.2207.2161.2–251.9
2094274254.8–290.2207.9161.3–250.6
2095273.5251.8–291.6214.2166.4–258.5
2096273.9252.1–292.5205.3159.8–257.4
2097270.8246–292.1206.6158.4–256.8
2098271.1248.3–290.6209.1161–258.3
2099271.8250.5–291.1208.5160.1–256
2100273.4254–291.9208158.6–258.6

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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