Madagascar vs Zimbabwe

Madagascar vs Zimbabwe: Tropical nights

Tropical nights in 2014: 138.3 nights in Madagascar and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Madagascar, by 61.9 nights, or 1.81 times that in Zimbabwe.

nights a year · CMIP6

Madagascar vs Zimbabwe: Tropical nightsTropical nights in 2014: 138.3 nights in Madagascar and 76.4 nights in Zimbabwe, in the CMIP6 climate models’ median run. In 2014 the value was higher in Madagascar, by 61.9 nights, or 1.81 times that in Zimbabwe.
MadagascarZimbabweCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Madagascar has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Madagascar at 198.5 nights and Zimbabwe at 148.3 nights in 2100.

Every year

nights a year · CMIP6

YearMadagascarZimbabwe
2014138.376.4
201313878.4
2012138.375.9
2011136.873.3
2010134.271.5
2009133.569.6
2008132.369.8
2007133.169.3
2006131.670.3
2005130.369.5
2004133.571.8
200313172.9
2002131.871.3
2001131.771.3
2000127.467.4
1999128.462.3
1998128.666.3
1997125.362
1996121.857.7
1995123.358.9
1994121.856.8
199311650.1
1992116.652.1
1991124.958.7
1990126.261.5
198912460.4
1988123.861.6
1987122.857.3
1986123.858.6
198512054.1
1984118.654.6
1983116.553.3
1982121.853.7
1981122.157
1980120.357.3
1979120.756.2
1978119.353.1
197711955.2
1976117.451.2
1975116.553.6
1974119.554.2
197311953.9
197211753.2
1971116.351.1
197011753.1
1969116.353.3
1968113.148.7
196711348.7
1966114.148.8
1965112.248.6
1964109.644.6
1963109.747.4
1962115.355.8
1961118.551.6
1960118.255.6
195911953.6
1958118.755.3
1957117.653.2
1956115.548.6
1955116.654.4
1954115.953
1953116.451.8
1952117.452.7
195111652.3
1950116.351.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMadagascarZimbabwe
2015142.8126.7–159.379.463.5–98.5
2016137.8122.2–15678.657.9–101.7
2017143.1125.6–159.481.263.3–98.5
2018143.7125.9–160.382.160.5–104.1
2019143.4124.4–162.382.863.9–102.3
2020143.4125.2–15984.362.9–106.9
2021145.4128.8–160.482.564.7–102.7
2022150.4133.4–165.289.870.1–108.8
2023149.7132.1–16690.672.5–110.7
2024150.7131.4–167.993.769.8–113.4
2025149128.8–169.18865.1–114.6
2026150.1127.4–169.989.767.8–113.9
2027151.8131.9–170.895.668.4–119.6
2028154.9137.7–173.193.371.4–115.7
2029155.7135.2–173.8100.277.2–120
2030154.8136.4–171.39671.6–115.3
2031158.1141.3–174.89874.9–119.8
2032157.9136.2–178.498.574.7–118.5
2033158.9136.7–177.898.974–120.6
2034158.6140.6–179.6100.277.3–128.1
2035161.1140.2–181.6103.975.7–130.6
2036159.5139.4–177.1100.878–123
2037165.8144.7–182.810882.1–131.1
2038166.5149.3–183.9110.986.5–135
2039164.1145.1–183.9102.480.4–122.3
2040162.8144.5–184.8101.379.5–133.5
2041165.8143.5–183.9108.483.7–134.2
2042165.1144.3–188.4108.883.1–139.9
2043165.6148.5–184.7107.985.7–137.3
2044167.3145.8–187111.287–134.8
2045166.9147.1–187.1106.186.2–130.7
2046171.4149.6–193112.386.4–139.1
2047171.7148.8–193.4119.692.1–145.9
2048173.7151.7–193.6116.888.4–143.9
2049172.2151.4–192.9119.290.4–146.2
2050174.4150.5–193.6122.794.1–148.6
2051175154.3–195.1122.4100.9–147.7
2052176153.8–196.7124.2101.3–152.8
2053176.6151.1–197.8121.689–146.9
2054175.5152.8–199.2123.993.9–150.8
2055179.2157.3–196.8126.597.9–153.7
2056178.8156.5–199.7126.198–154.7
2057177.7155.5–201122.797.6–150.7
2058180.5158.9–202.4125.3103–154.1
2059181.8158.3–202.5132.2107.4–157.4
2060185.1159.5–207.8132.599.9–159
2061180.6157.6–203.8126.694.2–161.1
2062180.6157.1–205.6126.399.6–157.3
2063185156.8–210.7127.7101–159.7
2064184.7159.1–205.7130.498–151.3
2065183.8157.1–208.5132.4107.6–165.6
2066187.3159.6–211134.5106.8–159.8
2067184.9155.9–208.9125.598.9–160.5
2068187.5161.7–211.1134102.3–166.1
2069187.5162–211.3136.9106.4–164.2
2070187.8160.4–213.6133.199.8–166.3
2071190.7162.7–216.6135.2108.4–173.7
2072191.8168.2–215.8140.4110.6–166.8
2073191.4168.7–214.5140.9109.7–173.6
2074189.4162.6–217.7135.5112–170.6
2075189.3163.8–214.2136108.5–166.6
2076191.1164.3–214133.7105.9–163.7
2077191.9168.8–217.1140.2114.3–170.6
2078190.1166.5–219.3137.5111.3–172.3
2079190.1163.7–216.2136.9110.2–172.6
2080194.8167.7–219.4145115.8–173.2
2081191.7166.7–218.1147.2106.5–174.1
2082193.8169.2–216.7141.4111.4–169.9
2083194.6166.1–218.1143.6106.5–179.2
2084197.9170–219.7149.4117.3–176.9
2085197.8172.3–223.7154.3114.9–182.7
2086192.9169.6–220141.7115.3–176.1
2087195.2170.4–220.1142.7116.8–177.3
2088198.1165.1–225.5150.2118.3–178.9
2089196.3167.9–227.6148.9121.3–176.4
2090197.5172.4–228.1145.7113.7–179.4
2091199.2172.7–226.7149.7116.5–181.8
2092202.4170.7–226.6149.4119.7–181.7
2093202.1172.3–230.5152.5117.1–184.1
2094198.3168.6–224150.9117.3–182.2
2095200.7171.7–225.1155118.3–181.5
2096199.8173.6–226.3152.4113.1–189.2
2097201.2170–227.6144.1113.8–183.3
2098201.1170.7–227.2152.4119.2–187
2099198.3173.8–225.8152.9117.3–185
2100198.5173.3–227.7148.3120.1–184.6

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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