Ghana vs Zimbabwe

Ghana vs Zimbabwe: Tropical nights

Tropical nights in 2014: 356.8 nights in Ghana and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ghana, by 280.4 nights, or 4.67 times that in Zimbabwe.

nights a year · CMIP6

Ghana vs Zimbabwe: Tropical nightsTropical nights in 2014: 356.8 nights in Ghana and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ghana, by 280.4 nights, or 4.67 times that in Zimbabwe.
GhanaZimbabweCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Ghana has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Ghana at 364.2 nights and Zimbabwe at 148.3 nights in 2100.

Every year

nights a year · CMIP6

YearGhanaZimbabwe
2014356.876.4
2013355.878.4
2012356.875.9
2011355.773.3
2010355.971.5
2009353.269.6
2008353.169.8
2007353.869.3
2006353.970.3
2005352.769.5
2004352.471.8
2003353.872.9
2002353.271.3
2001354.971.3
2000352.267.4
1999350.262.3
1998350.666.3
1997350.562
1996349.157.7
1995348.958.9
1994347.956.8
1993347.150.1
1992344.552.1
1991348.458.7
1990352.161.5
1989347.960.4
1988347.261.6
1987346.657.3
1986348.458.6
1985347.254.1
1984346.254.6
1983344.853.3
1982344.853.7
1981346.857
1980344.557.3
1979346.456.2
1978343.953.1
1977345.955.2
1976344.551.2
1975345.353.6
197434354.2
197334453.9
1972344.453.2
1971342.751.1
197034453.1
1969342.553.3
196834248.7
1967342.748.7
1966342.148.8
196534248.6
196434044.6
1963342.847.4
1962345.955.8
1961344.151.6
1960345.755.6
1959344.653.6
1958344.655.3
1957344.153.2
1956343.548.6
1955342.554.4
1954346.853
1953344.551.8
1952341.952.7
1951343.852.3
1950340.351.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearGhanaZimbabwe
2015356341.5–361.779.463.5–98.5
2016356.5341.4–361.578.657.9–101.7
2017355.2341.3–361.681.263.3–98.5
2018355.8345.7–362.182.160.5–104.1
2019353.9343.6–362.382.863.9–102.3
2020356341.7–362.984.362.9–106.9
2021356.9345.4–362.782.564.7–102.7
2022358.2342–362.689.870.1–108.8
2023356.7344–361.790.672.5–110.7
2024358.6347.7–363.493.769.8–113.4
2025357.1347.2–361.98865.1–114.6
2026357.2343.5–362.789.767.8–113.9
2027357.5344.3–362.495.668.4–119.6
2028359.5348.6–363.693.371.4–115.7
2029358.8349–363.1100.277.2–120
2030359.6350.6–363.29671.6–115.3
2031360.8351–3649874.9–119.8
2032359.7346.4–363.998.574.7–118.5
2033360.2349–364.198.974–120.6
2034359.4350.8–363.1100.277.3–128.1
2035360.5350.8–364103.975.7–130.6
2036360.9350.6–364.9100.878–123
2037361350.5–36410882.1–131.1
2038361.4354.4–363.9110.986.5–135
2039361.3352.3–364.5102.480.4–122.3
2040361.5352.2–365.2101.379.5–133.5
2041361.3351.7–364.3108.483.7–134.2
2042360.6352.3–364.3108.883.1–139.9
2043360.6351.8–364107.985.7–137.3
2044361.6353.6–364.8111.287–134.8
2045361.1353.2–364.4106.186.2–130.7
2046361.9353.1–364.1112.386.4–139.1
2047362.3350.3–364.5119.692.1–145.9
2048362.1354.7–365.3116.888.4–143.9
2049362.6354–364.4119.290.4–146.2
2050362.2355.3–364.4122.794.1–148.6
2051362.3355.7–364.6122.4100.9–147.7
2052362.1354.2–365124.2101.3–152.8
2053362.4354.1–364.5121.689–146.9
2054362.9354.8–364.6123.993.9–150.8
2055362.5355.1–364.5126.597.9–153.7
2056363.3355.6–365.7126.198–154.7
2057363.2355.9–364.8122.797.6–150.7
2058363356.3–364.9125.3103–154.1
2059362.9356.2–364.8132.2107.4–157.4
2060362.9354.1–365.7132.599.9–159
2061363.2354–364.9126.694.2–161.1
2062363.1355–364.9126.399.6–157.3
2063363.2355.5–364.9127.7101–159.7
2064363.3356.6–365.6130.498–151.3
2065363.7357.8–364.9132.4107.6–165.6
2066362.7356.9–364.8134.5106.8–159.8
2067363.6354.1–364.9125.598.9–160.5
2068364.1356.3–365.8134102.3–166.1
2069362.8356.3–364.9136.9106.4–164.2
2070363.3356.2–364.9133.199.8–166.3
2071363.5355.3–364.9135.2108.4–173.7
2072364.1355.6–365.8140.4110.6–166.8
2073363.6355.1–364.8140.9109.7–173.6
2074363.4355.4–364.8135.5112–170.6
2075363.4357–364.9136108.5–166.6
2076363.8358.4–365.8133.7105.9–163.7
2077363.8357.8–365140.2114.3–170.6
2078363.9356.6–364.9137.5111.3–172.3
2079364.2358–365136.9110.2–172.6
2080364.3357.8–366145115.8–173.2
2081363.8357.1–365147.2106.5–174.1
2082363.5357.1–364.9141.4111.4–169.9
2083364.1358.3–365143.6106.5–179.2
2084364358.5–365.9149.4117.3–176.9
2085364.1358.3–365154.3114.9–182.7
2086364.1357.8–365141.7115.3–176.1
2087364.1357.9–365142.7116.8–177.3
2088364.2356.4–365.9150.2118.3–178.9
2089363.9357.6–365148.9121.3–176.4
2090364.2357.6–365145.7113.7–179.4
2091363.9357.6–364.9149.7116.5–181.8
2092364.4356.6–366149.4119.7–181.7
2093364.4358.2–365152.5117.1–184.1
2094364.1357.9–365150.9117.3–182.2
2095364358.2–365155118.3–181.5
2096363.9358–366152.4113.1–189.2
2097363.9356.3–364.9144.1113.8–183.3
2098363.7357.8–364.9152.4119.2–187
2099363.9358.6–365152.9117.3–185
2100364.2357.6–365148.3120.1–184.6

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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