Malawi vs Tanzania

Malawi vs Tanzania: Tropical nights

Tropical nights in 2014: 138.1 nights in Malawi and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Malawi, by 31.8 nights, or 1.3 times that in Tanzania.

nights a year · CMIP6

Malawi vs Tanzania: Tropical nightsTropical nights in 2014: 138.1 nights in Malawi and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Malawi, by 31.8 nights, or 1.3 times that in Tanzania.
MalawiTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Malawi has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Malawi at 213.3 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearMalawiTanzania
2014138.1106.3
2013138.9105.5
2012137.4108.4
2011136.6109
2010132.4103.9
2009131.4101.1
2008130.8100.3
2007132.899.5
2006129.8100.4
2005129.598.7
2004133.4100.4
2003132.599.6
2002130.398.4
2001134101.5
2000126.694.9
1999124.894.2
1998127.196.8
1997124.293.5
1996121.389.6
1995120.988.5
1994118.485.4
1993113.881.2
1992114.180.1
1991120.989.6
1990123.891.1
1989120.589.1
1988120.887.6
1987118.888.5
1986121.189.4
1985115.783
1984116.283.1
1983115.582.1
1982115.184.8
198111988
1980116.985
1979117.785.5
1978114.882.9
1977117.284.1
197611481
197511480.8
1974115.282.2
1973114.783.6
1972113.881.4
1971114.180.7
1970115.881.8
1969114.379.5
196811079.1
1967109.877.5
196611178.1
1965111.578
1964106.373.8
1963107.573.1
1962114.781.1
196111682.6
1960117.483.9
1959115.681.4
1958116.482.1
1957114.680.9
1956111.480
1955115.281.6
1954113.981.4
195311380.6
1952113.581.4
1951113.582.1
1950112.880.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMalawiTanzania
2015145.7126.7–164.3114.895.2–137.4
2016139.8122.6–157.4108.391.6–125.6
2017143.6127–161.8114.893.6–137.8
2018143.1124.6–162.6116.497.4–137.1
2019143.8128.3–161.4113.495.2–133.2
2020145127.3–165.8119.396.2–143.5
2021145.3128–163.6119.5100.9–147.1
2022151130.1–169.1124.4105.3–147.4
2023149.2129.5–171.2122.1102.1–147.8
2024152.4130–172.6126.2100–150.1
2025151.1129.7–170.4124.6100.9–154
2026151.1126.2–173.8126.999.1–155.6
2027154.4135.1–173.1128102.9–147.7
2028155.5134.6–174129.9106.4–152.1
2029159.8139.2–178.5134.1111–156.5
2030155.6138.7–174.5129.4106.4–151.1
2031161.1143.4–177.6136.4115.9–158.4
2032160.8141.3–181.3135.1114–166.8
2033161.3135.6–179.2135.2110.9–161.9
2034160.9138.9–185134.7112.5–166.3
2035164.3140.4–189.5140.2114.6–165
2036163.8137.6–182.5137.8113.3–165.5
2037166.9144.6–189.2142.9121.5–168.9
2038172.2148.4–191.2147.9124.3–169.3
2039164.8147.3–188.2144.3117.6–171.3
2040164.4146.4–189.7140.5117–178
2041169.3143.7–192.5149.1121.7–175.6
2042169.8146.3–197.8146.3120.5–185.3
2043167.5147.1–193.2144.6117–173
2044172.6148.3–197147.7121.2–175.8
2045170.4153.1–194.7150.1125.2–183.4
2046176.3151.2–203.1161.5128.6–192.2
2047178.7157.8–200.9160.2129.7–194.4
2048180.7158.9–204.1158.8132.7–193.1
2049176.7154–205.4157.6131.1–196
2050180.4155.2–204.9159.7127.8–192
2051182.9162.1–207.4163.2135.5–197.8
2052184.9163.2–209.6161.9136.2–199.1
2053177.2149.6–207.4160.6127.5–197.7
2054185.1157.1–208163.2131.5–200.2
2055186.1159.2–212.6167.4137–208.3
2056184.6158.5–214.3166.4130.8–209.7
2057184.7159.3–212.3168134.6–208.3
2058188.5163.8–214.7168.7134.9–210.3
2059189.8166.9–218.5174.7144.9–219.5
2060192.6163.4–218.1181.7138.1–219.8
2061186.4158.8–216.8171.8135.5–218.1
2062192.3163.9–218.6177.5139.9–224
2063189.2165.2–220.3181.4140.1–213.8
2064197161.3–218185.3140.1–215.2
2065193.1165.8–225.2183.5141.1–221.8
2066201170.1–224.7181.9146.3–219.3
2067193.1164.2–223.7178.8138.8–229.2
2068198.6163.7–227.1186144.2–228.4
2069199.4165.8–225183.7141.7–225.3
2070198.7168–226.7180.7140.4–228.2
2071199.3167.9–233.5184.9146.9–235.2
2072202.3173.2–226.2191.3155–226.1
2073205.4168.2–233.4191.6152.4–235.6
2074198.2175.4–227.7183.3149.7–231.7
2075199.6168.9–228.3183.8144.8–233
2076198.8169.8–225.2191.1150.9–233.2
2077202172.2–231.2191.3152.6–238.2
2078203.5175.8–232.1189156.6–233.8
2079203.6172.2–236.1190.5147–237.3
2080204.7172.2–234.3197.3150.7–241.2
2081202.2174.9–231.3195.6153.4–237.4
2082204.3178.3–228.6194.5157.3–237.3
2083205.8170.7–238.3193.2151–249.8
2084208.1175.9–235.6201.1152.2–246.7
2085211.1179.4–241204.2162.3–252.3
2086203.3175.4–237195156–248.7
2087205.3181.2–237.7196.7160.8–244.5
2088211.6174.7–240.6208.4154.7–246.9
2089208.9180.5–237.8201.3158.6–248.2
2090209.4173.4–243197.9160.7–253.6
2091214.3179.7–244.8210161.6–256
2092213.2176.8–242.3205.8158.3–253.6
2093212.5177.8–242.2207.2161.2–251.9
2094211.8179.7–241.5207.9161.3–250.6
2095216.9185–243.8214.2166.4–258.5
2096213.1182–247.6205.3159.8–257.4
2097210.8174.9–242.1206.6158.4–256.8
2098214.4181.5–242.2209.1161–258.3
2099213.5181.9–244.1208.5160.1–256
2100213.3181.5–246.3208158.6–258.6

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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