Brazil vs Tanzania

Brazil vs Tanzania: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 175.7 nights, or 2.65 times that in Tanzania.

nights a year · CMIP6

Brazil vs Tanzania: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 175.7 nights, or 2.65 times that in Tanzania.
BrazilTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Brazil has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Brazil at 317.3 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilTanzania
2014282106.3
2013282.5105.5
2012283.6108.4
2011281.8109
2010280.2103.9
2009279.2101.1
2008277.8100.3
2007275.999.5
2006275.4100.4
2005275.898.7
2004278.5100.4
2003276.799.6
2002276.298.4
2001277.7101.5
2000273.394.9
199927194.2
1998273.696.8
1997270.993.5
1996264.789.6
1995263.888.5
1994263.685.4
1993258.381.2
1992252.880.1
1991269.789.6
1990272.591.1
1989267.189.1
1988264.787.6
1987265.988.5
1986265.789.4
1985260.683
1984261.183.1
1983255.982.1
1982264.884.8
1981265.388
198026285
1979261.285.5
1978259.782.9
1977261.884.1
1976258.481
1975252.480.8
1974258.782.2
197326183.6
1972258.181.4
1971256.580.7
1970254.581.8
1969255.179.5
1968254.979.1
1967250.377.5
1966254.578.1
1965250.878
1964246.273.8
1963241.973.1
1962257.981.1
1961258.282.6
1960260.383.9
1959255.781.4
1958258.182.1
1957256.680.9
1956251.280
1955257.281.6
195425881.4
1953255.280.6
1952255.881.4
1951256.382.1
1950254.480.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilTanzania
2015284257.6–299.5114.895.2–137.4
2016281.5261.4–296.3108.391.6–125.6
2017284.1263.2–297.8114.893.6–137.8
2018283.4263.1–298.8116.497.4–137.1
2019283.7262.9–302.4113.495.2–133.2
2020286.3264.2–303.6119.396.2–143.5
2021287.9266.9–302.3119.5100.9–147.1
2022289.6270.7–303.9124.4105.3–147.4
2023287.3270.5–303122.1102.1–147.8
2024291.5268.2–304.6126.2100–150.1
2025289.6269.1–304.8124.6100.9–154
2026289.7266.2–305.1126.999.1–155.6
2027289.5269.1–303.7128102.9–147.7
2028291.2271.9–306129.9106.4–152.1
2029295.5276.3–309.6134.1111–156.5
2030292.2269.1–306.9129.4106.4–151.1
2031295.3274–308.9136.4115.9–158.4
2032296.8280.1–310.9135.1114–166.8
2033295.4273.3–308.5135.2110.9–161.9
2034294.3273.5–311.8134.7112.5–166.3
2035295.2274.4–310.9140.2114.6–165
2036295.1278.2–307.8137.8113.3–165.5
2037299.9283.7–311.3142.9121.5–168.9
2038299.6283.5–312.1147.9124.3–169.3
2039296.9279.9–311144.3117.6–171.3
2040298.5279.4–311.9140.5117–178
2041301.4282.2–314.1149.1121.7–175.6
2042300.6277.8–314.7146.3120.5–185.3
2043298.2279.8–312.7144.6117–173
2044300.3281.2–315.6147.7121.2–175.8
2045299.9279.7–313.1150.1125.2–183.4
2046302.8285.8–316.6161.5128.6–192.2
2047303.3285–316.4160.2129.7–194.4
2048304.4287.3–317.3158.8132.7–193.1
2049305.4288.4–318.5157.6131.1–196
2050303.9283.9–316.2159.7127.8–192
2051305.7287.5–317.5163.2135.5–197.8
2052305.9290.6–318.8161.9136.2–199.1
2053305.3285.9–317.5160.6127.5–197.7
2054306.1288.4–319.3163.2131.5–200.2
2055306.4290.8–319.8167.4137–208.3
2056306.7288.3–321.1166.4130.8–209.7
2057306.4287.6–321.1168134.6–208.3
2058309291–321.4168.7134.9–210.3
2059310.4290.7–322.8174.7144.9–219.5
2060311.6294.4–325.1181.7138.1–219.8
2061307.5290.3–321.2171.8135.5–218.1
2062309291.5–322.8177.5139.9–224
2063310.8290.6–322.8181.4140.1–213.8
2064309.6290.2–321.1185.3140.1–215.2
2065311.1291.6–323.1183.5141.1–221.8
2066312.2294.2–324.2181.9146.3–219.3
2067310.9291.5–323.3178.8138.8–229.2
2068311.5293–324.5186144.2–228.4
2069310.6292.2–323.6183.7141.7–225.3
2070312.7293–325.3180.7140.4–228.2
2071311.5292.1–323.9184.9146.9–235.2
2072313.3297.8–325.5191.3155–226.1
2073313.8298.6–327.2191.6152.4–235.6
2074311.4292.4–323.5183.3149.7–231.7
2075310.9291.5–324.5183.8144.8–233
2076314.2294.4–327.7191.1150.9–233.2
2077315.1295.6–326.8191.3152.6–238.2
2078314.9296.3–327.1189156.6–233.8
2079313292.8–326.8190.5147–237.3
2080311.9294.7–325.4197.3150.7–241.2
2081313.5295.5–325.6195.6153.4–237.4
2082315296.8–327.1194.5157.3–237.3
2083315.7295.3–328.7193.2151–249.8
2084316.6298.5–327.9201.1152.2–246.7
2085317.4299.3–329.8204.2162.3–252.3
2086315.8294–328195156–248.7
2087316.5297.9–328.5196.7160.8–244.5
2088315.6297.3–328.8208.4154.7–246.9
2089315296.6–327.9201.3158.6–248.2
2090316298.9–330.3197.9160.7–253.6
2091317298.1–330.6210161.6–256
2092317.6298.7–330.7205.8158.3–253.6
2093316.3297.5–328.6207.2161.2–251.9
2094316.4300.2–327.5207.9161.3–250.6
2095319299.8–330.7214.2166.4–258.5
2096317.7299.5–330.8205.3159.8–257.4
2097316.9297.8–329206.6158.4–256.8
2098318.6299.9–331.9209.1161–258.3
2099318.1300–330.2208.5160.1–256
2100317.3298.4–330.3208158.6–258.6

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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