Cameroon vs Zimbabwe

Cameroon vs Zimbabwe: Tropical nights

Tropical nights in 2014: 238.7 nights in Cameroon and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cameroon, by 162.3 nights, or 3.13 times that in Zimbabwe.

nights a year · CMIP6

Cameroon vs Zimbabwe: Tropical nightsTropical nights in 2014: 238.7 nights in Cameroon and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Cameroon, by 162.3 nights, or 3.13 times that in Zimbabwe.
CameroonZimbabweCMIP6 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 Zimbabwe at 148.3 nights in 2100.

Every year

nights a year · CMIP6

YearCameroonZimbabwe
2014238.776.4
2013236.778.4
2012242.275.9
2011237.673.3
2010230.471.5
2009226.669.6
2008223.169.8
2007222.169.3
2006220.170.3
2005216.169.5
2004217.671.8
200322172.9
2002215.571.3
200122371.3
200021067.4
1999200.562.3
1998203.566.3
199720262
199619057.7
1995187.358.9
1994183.156.8
1993165.250.1
1992156.752.1
1991192.658.7
1990200.761.5
1989187.560.4
1988185.861.6
1987182.757.3
1986188.958.6
1985173.254.1
1984172.954.6
1983165.553.3
1982176.353.7
1981182.657
1980173.657.3
1979175.856.2
1978172.853.1
1977175.755.2
1976164.551.2
1975159.553.6
1974166.854.2
1973170.453.9
1972165.253.2
1971161.351.1
1970164.453.1
196916053.3
1968157.848.7
1967147.948.7
1966156.548.8
1965151.648.6
1964143.144.6
1963145.947.4
1962171.855.8
1961167.251.6
1960176.255.6
1959166.553.6
1958169.255.3
1957168.253.2
195616048.6
1955163.754.4
1954167.653
1953168.251.8
1952165.752.7
1951172.852.3
1950162.851.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearCameroonZimbabwe
2015242.2196.9–270.879.463.5–98.5
2016237.7192.1–259.978.657.9–101.7
2017245.8205.7–271.381.263.3–98.5
2018245.7208–270.582.160.5–104.1
2019243.7200.2–275.682.863.9–102.3
2020246.4210.4–27884.362.9–106.9
2021255.2220.2–279.682.564.7–102.7
2022255.8221–285.789.870.1–108.8
2023254.5221.7–284.190.672.5–110.7
2024263225.8–286.893.769.8–113.4
2025257.3222.7–293.98865.1–114.6
2026260.4211.9–29289.767.8–113.9
2027258.5223.8–291.595.668.4–119.6
2028266.9235.5–294.793.371.4–115.7
2029269.9242.3–293.5100.277.2–120
2030266.6229–293.59671.6–115.3
2031273.2229.9–298.59874.9–119.8
2032269.8240.6–296.298.574.7–118.5
2033271.8235.6–303.498.974–120.6
2034268.1239.2–299.1100.277.3–128.1
2035277.5241.5–302.7103.975.7–130.6
2036275.7235.1–301.3100.878–123
2037283.5252.3–305.910882.1–131.1
2038285.8258–307.9110.986.5–135
2039280.9250.4–305.8102.480.4–122.3
2040279.5252.1–310.6101.379.5–133.5
2041284.5254.6–309.9108.483.7–134.2
2042284.8253.6–313.2108.883.1–139.9
2043281.2251.4–309.8107.985.7–137.3
2044283.8244.4–312.3111.287–134.8
2045286.8253.7–311.4106.186.2–130.7
2046296.1260.6–318.1112.386.4–139.1
2047294.3260.7–316.6119.692.1–145.9
2048297.3265.6–318.1116.888.4–143.9
2049298.3267.8–318.1119.290.4–146.2
2050296.9267.9–322.7122.794.1–148.6
2051297.8266.7–319.9122.4100.9–147.7
2052298.7270.1–322.3124.2101.3–152.8
2053297.7261.3–321.7121.689–146.9
2054301.2268.2–324.6123.993.9–150.8
2055301.3276.5–324.3126.597.9–153.7
2056302.1270.4–329.2126.198–154.7
2057305.4277.7–327.4122.797.6–150.7
2058302.6272.1–325.2125.3103–154.1
2059306.2279.6–330.1132.2107.4–157.4
2060306.1276.1–331.1132.599.9–159
2061304.4267.2–329.7126.694.2–161.1
2062307.6266.2–332.2126.399.6–157.3
2063309.1272.5–328.8127.7101–159.7
2064308.5278.7–331130.498–151.3
2065311.3284.1–329.6132.4107.6–165.6
2066311.9284–332.7134.5106.8–159.8
2067310.1271.7–335.6125.598.9–160.5
2068312.9278.7–335134102.3–166.1
2069310.4278.4–333.4136.9106.4–164.2
2070309.8281.2–334.9133.199.8–166.3
2071316.4282.3–336135.2108.4–173.7
2072315.4289.2–335.3140.4110.6–166.8
2073314282.6–339.5140.9109.7–173.6
2074311.7281.9–336.8135.5112–170.6
2075314.8285.3–335.3136108.5–166.6
2076315.2284.7–338.4133.7105.9–163.7
2077318.2289.7–341.4140.2114.3–170.6
2078315.8286.4–338.5137.5111.3–172.3
2079317.7287.8–337.5136.9110.2–172.6
2080321.5285.9–341.7145115.8–173.2
2081318.7290–339147.2106.5–174.1
2082316.2289–337.7141.4111.4–169.9
2083317.7288.2–341.6143.6106.5–179.2
2084318.5284.5–342.1149.4117.3–176.9
2085323.4294–342.7154.3114.9–182.7
2086319.5292.3–343141.7115.3–176.1
2087318292.7–342.5142.7116.8–177.3
2088320.4288.1–342150.2118.3–178.9
2089320.1289.6–340.7148.9121.3–176.4
2090322.4292.8–342.6145.7113.7–179.4
2091322.6289.9–345149.7116.5–181.8
2092324.9291.6–343.6149.4119.7–181.7
2093322.3299.7–342.6152.5117.1–184.1
2094324299.3–343.4150.9117.3–182.2
2095326.4300.2–346.4155118.3–181.5
2096322.1294.4–346.4152.4113.1–189.2
2097320.9287.4–342.5144.1113.8–183.3
2098323.1293.8–344.4152.4119.2–187
2099322.6295.7–344.2152.9117.3–185
2100324.2293.6–346.6148.3120.1–184.6

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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