Brazil vs Pakistan

Brazil vs Pakistan: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 132.1 nights, or 1.88 times that in Pakistan.

Watch it change on the map

nights a year · CMIP6

Brazil vs Pakistan: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 132.1 nights, or 1.88 times that in Pakistan.
BrazilPakistanCMIP6 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 Pakistan at 177.6 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilPakistan
2014282149.9
2013282.5149.1
2012283.6149.9
2011281.8149
2010280.2148.4
2009279.2147.1
2008277.8147.4
2007275.9147.3
2006275.4146.7
2005275.8146.5
2004278.5147.5
2003276.7146
2002276.2148.3
2001277.7145.4
2000273.3144.7
1999271146.9
1998273.6144.8
1997270.9143.2
1996264.7141.2
1995263.8141.8
1994263.6142.1
1993258.3140.4
1992252.8139.9
1991269.7142.5
1990272.5142.6
1989267.1142.5
1988264.7140.3
1987265.9140
1986265.7140
1985260.6140
1984261.1138.9
1983255.9136.3
1982264.8138.5
1981265.3141.5
1980262139.5
1979261.2139.1
1978259.7139
1977261.8138.6
1976258.4139.2
1975252.4136.5
1974258.7138.7
1973261137.8
1972258.1137.4
1971256.5136
1970254.5137.7
1969255.1135.9
1968254.9136.6
1967250.3135.2
1966254.5136.9
1965250.8138.3
1964246.2135.1
1963241.9135.7
1962257.9137
1961258.2138.6
1960260.3139
1959255.7138.6
1958258.1137.7
1957256.6140
1956251.2137.8
1955257.2137.5
1954258137.8
1953255.2136.9
1952255.8138.1
1951256.3136.7
1950254.4139.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilPakistan
2015284257.6–299.5152.4138.7–163.3
2016281.5261.4–296.3150.6139.4–161.7
2017284.1263.2–297.8151.3138.8–162
2018283.4263.1–298.8152.6139.8–161.8
2019283.7262.9–302.4151.8138.1–163.3
2020286.3264.2–303.6153.1140.3–164.5
2021287.9266.9–302.3154.1140.6–165.7
2022289.6270.7–303.9153.1140.2–165.7
2023287.3270.5–303155.5141.6–165.9
2024291.5268.2–304.6156.8143.3–168.7
2025289.6269.1–304.8155.7141.5–168.6
2026289.7266.2–305.1155.3142.2–167.9
2027289.5269.1–303.7156.8140.9–168.9
2028291.2271.9–306156.5143.9–167.6
2029295.5276.3–309.6155.9141.5–167.7
2030292.2269.1–306.9156.3143.3–167.6
2031295.3274–308.9157.3144.4–168.1
2032296.8280.1–310.9157.4142.5–169.6
2033295.4273.3–308.5157.7143.6–169.4
2034294.3273.5–311.8159.5145.6–173.4
2035295.2274.4–310.9159.3146.7–170.3
2036295.1278.2–307.8159.1147.5–171.4
2037299.9283.7–311.3162.2147.5–175.3
2038299.6283.5–312.1161.4148.6–171.7
2039296.9279.9–311160148.2–170.4
2040298.5279.4–311.9160.9147.9–171.3
2041301.4282.2–314.1160.8146.7–171.7
2042300.6277.8–314.7162.3149.9–175.6
2043298.2279.8–312.7161.1150.3–173.8
2044300.3281.2–315.6163150.9–173.9
2045299.9279.7–313.1163149.5–174.8
2046302.8285.8–316.6163.5149.8–177.2
2047303.3285–316.4165.2151.8–178.5
2048304.4287.3–317.3166.4154.1–179.4
2049305.4288.4–318.5165150.8–178.2
2050303.9283.9–316.2166.9153.5–179.3
2051305.7287.5–317.5165.6150.8–180
2052305.9290.6–318.8166.7155.4–179.5
2053305.3285.9–317.5166.3154.2–178.8
2054306.1288.4–319.3167.5153.9–181
2055306.4290.8–319.8167.8155.8–182.5
2056306.7288.3–321.1166.3153.6–179.7
2057306.4287.6–321.1168.3153.9–182.3
2058309291–321.4167.5157–179.9
2059310.4290.7–322.8170.9155.9–183.8
2060311.6294.4–325.1170.3156.5–181.8
2061307.5290.3–321.2168.8156.8–179.6
2062309291.5–322.8171.6153.5–186.5
2063310.8290.6–322.8171.3159.5–183.8
2064309.6290.2–321.1170.2155.3–184.5
2065311.1291.6–323.1169.7156.4–185
2066312.2294.2–324.2172.2157–186.7
2067310.9291.5–323.3173.2160.2–186.3
2068311.5293–324.5172.6157.7–186.3
2069310.6292.2–323.6171.8157.3–185.6
2070312.7293–325.3171.7158.9–186.7
2071311.5292.1–323.9173.4158.7–186.8
2072313.3297.8–325.5174161.5–186.9
2073313.8298.6–327.2175.6157.2–187.9
2074311.4292.4–323.5173.5160–186.3
2075310.9291.5–324.5173161.5–187.8
2076314.2294.4–327.7172.9158.8–186.7
2077315.1295.6–326.8175161.3–187.8
2078314.9296.3–327.1174.4160.9–189.3
2079313292.8–326.8172.5158.3–187.7
2080311.9294.7–325.4175.1160.7–189.2
2081313.5295.5–325.6174.9159.2–190.2
2082315296.8–327.1175.4161.8–190.6
2083315.7295.3–328.7176.5161.8–190.8
2084316.6298.5–327.9176.1160.9–190.5
2085317.4299.3–329.8176.3161.9–193.6
2086315.8294–328173.9160–189.1
2087316.5297.9–328.5176161–193.1
2088315.6297.3–328.8175.4160.5–195.2
2089315296.6–327.9177.2164.2–191.7
2090316298.9–330.3177.7163.9–192.2
2091317298.1–330.6177.8162.8–192.2
2092317.6298.7–330.7178.7162.9–192.9
2093316.3297.5–328.6177164–191
2094316.4300.2–327.5176.8164.1–190.7
2095319299.8–330.7178.6163.8–193.1
2096317.7299.5–330.8177.8163.7–192.5
2097316.9297.8–329177.3160.4–192.5
2098318.6299.9–331.9178.7162.6–195.7
2099318.1300–330.2176159.9–193.2
2100317.3298.4–330.3177.6162.2–193

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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