Cameroon vs Tanzania

Cameroon vs Tanzania: Tropical nights

Tropical nights in 2014: 238.7 nights in Cameroon and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cameroon, by 132.4 nights, or 2.25 times that in Tanzania.

Watch it change on the map

nights a year · CMIP6

Cameroon vs Tanzania: Tropical nightsTropical nights in 2014: 238.7 nights in Cameroon and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cameroon, by 132.4 nights, or 2.25 times that in Tanzania.
CameroonTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Cameroon has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Cameroon at 324.2 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearCameroonTanzania
2014238.7106.3
2013236.7105.5
2012242.2108.4
2011237.6109
2010230.4103.9
2009226.6101.1
2008223.1100.3
2007222.199.5
2006220.1100.4
2005216.198.7
2004217.6100.4
200322199.6
2002215.598.4
2001223101.5
200021094.9
1999200.594.2
1998203.596.8
199720293.5
199619089.6
1995187.388.5
1994183.185.4
1993165.281.2
1992156.780.1
1991192.689.6
1990200.791.1
1989187.589.1
1988185.887.6
1987182.788.5
1986188.989.4
1985173.283
1984172.983.1
1983165.582.1
1982176.384.8
1981182.688
1980173.685
1979175.885.5
1978172.882.9
1977175.784.1
1976164.581
1975159.580.8
1974166.882.2
1973170.483.6
1972165.281.4
1971161.380.7
1970164.481.8
196916079.5
1968157.879.1
1967147.977.5
1966156.578.1
1965151.678
1964143.173.8
1963145.973.1
1962171.881.1
1961167.282.6
1960176.283.9
1959166.581.4
1958169.282.1
1957168.280.9
195616080
1955163.781.6
1954167.681.4
1953168.280.6
1952165.781.4
1951172.882.1
1950162.880.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearCameroonTanzania
2015242.2196.9–270.8114.895.2–137.4
2016237.7192.1–259.9108.391.6–125.6
2017245.8205.7–271.3114.893.6–137.8
2018245.7208–270.5116.497.4–137.1
2019243.7200.2–275.6113.495.2–133.2
2020246.4210.4–278119.396.2–143.5
2021255.2220.2–279.6119.5100.9–147.1
2022255.8221–285.7124.4105.3–147.4
2023254.5221.7–284.1122.1102.1–147.8
2024263225.8–286.8126.2100–150.1
2025257.3222.7–293.9124.6100.9–154
2026260.4211.9–292126.999.1–155.6
2027258.5223.8–291.5128102.9–147.7
2028266.9235.5–294.7129.9106.4–152.1
2029269.9242.3–293.5134.1111–156.5
2030266.6229–293.5129.4106.4–151.1
2031273.2229.9–298.5136.4115.9–158.4
2032269.8240.6–296.2135.1114–166.8
2033271.8235.6–303.4135.2110.9–161.9
2034268.1239.2–299.1134.7112.5–166.3
2035277.5241.5–302.7140.2114.6–165
2036275.7235.1–301.3137.8113.3–165.5
2037283.5252.3–305.9142.9121.5–168.9
2038285.8258–307.9147.9124.3–169.3
2039280.9250.4–305.8144.3117.6–171.3
2040279.5252.1–310.6140.5117–178
2041284.5254.6–309.9149.1121.7–175.6
2042284.8253.6–313.2146.3120.5–185.3
2043281.2251.4–309.8144.6117–173
2044283.8244.4–312.3147.7121.2–175.8
2045286.8253.7–311.4150.1125.2–183.4
2046296.1260.6–318.1161.5128.6–192.2
2047294.3260.7–316.6160.2129.7–194.4
2048297.3265.6–318.1158.8132.7–193.1
2049298.3267.8–318.1157.6131.1–196
2050296.9267.9–322.7159.7127.8–192
2051297.8266.7–319.9163.2135.5–197.8
2052298.7270.1–322.3161.9136.2–199.1
2053297.7261.3–321.7160.6127.5–197.7
2054301.2268.2–324.6163.2131.5–200.2
2055301.3276.5–324.3167.4137–208.3
2056302.1270.4–329.2166.4130.8–209.7
2057305.4277.7–327.4168134.6–208.3
2058302.6272.1–325.2168.7134.9–210.3
2059306.2279.6–330.1174.7144.9–219.5
2060306.1276.1–331.1181.7138.1–219.8
2061304.4267.2–329.7171.8135.5–218.1
2062307.6266.2–332.2177.5139.9–224
2063309.1272.5–328.8181.4140.1–213.8
2064308.5278.7–331185.3140.1–215.2
2065311.3284.1–329.6183.5141.1–221.8
2066311.9284–332.7181.9146.3–219.3
2067310.1271.7–335.6178.8138.8–229.2
2068312.9278.7–335186144.2–228.4
2069310.4278.4–333.4183.7141.7–225.3
2070309.8281.2–334.9180.7140.4–228.2
2071316.4282.3–336184.9146.9–235.2
2072315.4289.2–335.3191.3155–226.1
2073314282.6–339.5191.6152.4–235.6
2074311.7281.9–336.8183.3149.7–231.7
2075314.8285.3–335.3183.8144.8–233
2076315.2284.7–338.4191.1150.9–233.2
2077318.2289.7–341.4191.3152.6–238.2
2078315.8286.4–338.5189156.6–233.8
2079317.7287.8–337.5190.5147–237.3
2080321.5285.9–341.7197.3150.7–241.2
2081318.7290–339195.6153.4–237.4
2082316.2289–337.7194.5157.3–237.3
2083317.7288.2–341.6193.2151–249.8
2084318.5284.5–342.1201.1152.2–246.7
2085323.4294–342.7204.2162.3–252.3
2086319.5292.3–343195156–248.7
2087318292.7–342.5196.7160.8–244.5
2088320.4288.1–342208.4154.7–246.9
2089320.1289.6–340.7201.3158.6–248.2
2090322.4292.8–342.6197.9160.7–253.6
2091322.6289.9–345210161.6–256
2092324.9291.6–343.6205.8158.3–253.6
2093322.3299.7–342.6207.2161.2–251.9
2094324299.3–343.4207.9161.3–250.6
2095326.4300.2–346.4214.2166.4–258.5
2096322.1294.4–346.4205.3159.8–257.4
2097320.9287.4–342.5206.6158.4–256.8
2098323.1293.8–344.4209.1161–258.3
2099322.6295.7–344.2208.5160.1–256
2100324.2293.6–346.6208158.6–258.6

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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