Brazil vs Paraguay

Brazil vs Paraguay: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 202.9 nights in Paraguay, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 79.1 nights, or 1.39 times that in Paraguay.

Watch it change on the map

nights a year · CMIP6

Brazil vs Paraguay: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 202.9 nights in Paraguay, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 79.1 nights, or 1.39 times that in Paraguay.
BrazilParaguayCMIP6 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 Paraguay at 250.2 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilParaguay
2014282202.9
2013282.5197.2
2012283.6200.5
2011281.8198.1
2010280.2201.6
2009279.2200.4
2008277.8196.1
2007275.9186.1
2006275.4188.5
2005275.8198.3
2004278.5194.8
2003276.7189.8
2002276.2194.4
2001277.7191.4
2000273.3195.8
1999271188.8
1998273.6195.1
1997270.9190.7
1996264.7183.9
1995263.8182.1
1994263.6177.4
1993258.3180.8
1992252.8172.7
1991269.7183.7
1990272.5189.6
1989267.1185.4
1988264.7181.8
1987265.9179.7
1986265.7184.5
1985260.6176.9
1984261.1177.7
1983255.9180.1
1982264.8179.6
1981265.3185
1980262184.1
1979261.2185.9
1978259.7178.1
1977261.8179
1976258.4178.3
1975252.4174
1974258.7176.5
1973261176.4
1972258.1179.4
1971256.5173.8
1970254.5173.6
1969255.1171.7
1968254.9174.8
1967250.3169.8
1966254.5173
1965250.8168.3
1964246.2164.7
1963241.9164.3
1962257.9175.9
1961258.2176.1
1960260.3175.1
1959255.7176.2
1958258.1170.6
1957256.6176.3
1956251.2170.4
1955257.2176.1
1954258175.2
1953255.2175.6
1952255.8180.5
1951256.3174.9
1950254.4174.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilParaguay
2015284257.6–299.5203.5180.7–228.9
2016281.5261.4–296.3202.2171.5–224.3
2017284.1263.2–297.8201.3180.6–222.8
2018283.4263.1–298.8196.9170.8–225.1
2019283.7262.9–302.4202.2175.2–227
2020286.3264.2–303.6204.2179.6–236.7
2021287.9266.9–302.3211186.7–234.8
2022289.6270.7–303.9211.3175.3–237.2
2023287.3270.5–303207.4184.7–225.6
2024291.5268.2–304.6213.3188.8–236.5
2025289.6269.1–304.8205.4186.1–232.5
2026289.7266.2–305.1209.4178.8–228.7
2027289.5269.1–303.7209185.2–237.4
2028291.2271.9–306210.8179.1–233.5
2029295.5276.3–309.6218.4188.8–243.2
2030292.2269.1–306.9214.3179.2–245.6
2031295.3274–308.9210184.3–238.2
2032296.8280.1–310.9218.4187.5–246
2033295.4273.3–308.5211.7186.3–234.1
2034294.3273.5–311.8216.7190.9–239.5
2035295.2274.4–310.9212.1185.1–244.7
2036295.1278.2–307.8216190.9–238.6
2037299.9283.7–311.3222.7201.4–242
2038299.6283.5–312.1212.9191.8–238.7
2039296.9279.9–311219.3196.4–243.2
2040298.5279.4–311.9221.8197.3–243.4
2041301.4282.2–314.1225.9200.7–245.5
2042300.6277.8–314.7218.4185.8–239.7
2043298.2279.8–312.7219.9194.4–247.3
2044300.3281.2–315.6222.9198.5–246.5
2045299.9279.7–313.1225.4201.2–249
2046302.8285.8–316.6222.3195–248.4
2047303.3285–316.4225.3203.5–250.5
2048304.4287.3–317.3233.4214.5–252.3
2049305.4288.4–318.5230.7205.1–253.8
2050303.9283.9–316.2224.3193.5–249
2051305.7287.5–317.5232.3210.5–252.7
2052305.9290.6–318.8232.8205.9–257.6
2053305.3285.9–317.5229.9205.2–255.9
2054306.1288.4–319.3227.4204.3–253.3
2055306.4290.8–319.8232.6202.1–255.1
2056306.7288.3–321.1232.5203.6–257.8
2057306.4287.6–321.1234.8211.3–255.1
2058309291–321.4232.9202–260.8
2059310.4290.7–322.8237.9217.3–255.2
2060311.6294.4–325.1234.2205.8–258.5
2061307.5290.3–321.2230.7207.6–258.3
2062309291.5–322.8234.6217.3–262.8
2063310.8290.6–322.8237.1211.2–255.7
2064309.6290.2–321.1234.6207–259.5
2065311.1291.6–323.1236.5216.7–260.5
2066312.2294.2–324.2237.2208.8–253.5
2067310.9291.5–323.3235.4214.5–254.3
2068311.5293–324.5235.6210.7–265.5
2069310.6292.2–323.6235.9207.8–265.8
2070312.7293–325.3242.2216.6–265.3
2071311.5292.1–323.9239.8204.9–260.7
2072313.3297.8–325.5239.9212.6–266.9
2073313.8298.6–327.2242.1214.2–262
2074311.4292.4–323.5242.1214.2–267.1
2075310.9291.5–324.5241.8219.2–259.7
2076314.2294.4–327.7243.8221.7–267.7
2077315.1295.6–326.8244.9208.1–264.7
2078314.9296.3–327.1245.9222–265.6
2079313292.8–326.8237.4218–266.2
2080311.9294.7–325.4243.2217.9–268.8
2081313.5295.5–325.6242.6221.4–259.8
2082315296.8–327.1244.9214.1–264.3
2083315.7295.3–328.7241.5212.1–266.3
2084316.6298.5–327.9244.6219.4–269.9
2085317.4299.3–329.8247.6216.5–271.8
2086315.8294–328249220.5–274.6
2087316.5297.9–328.5243.9217.8–265.9
2088315.6297.3–328.8249225.7–274.3
2089315296.6–327.9241.8216.4–271.4
2090316298.9–330.3249.4226.7–273.9
2091317298.1–330.6249.3225.7–271.9
2092317.6298.7–330.7248.4225.1–268.1
2093316.3297.5–328.6245.2217.9–268.1
2094316.4300.2–327.5243.2219–266.2
2095319299.8–330.7247.3217.5–268.2
2096317.7299.5–330.8245.1222.1–273.7
2097316.9297.8–329247.9221.8–271.9
2098318.6299.9–331.9251.3228.7–274.7
2099318.1300–330.2246.4221.2–271.2
2100317.3298.4–330.3250.2222.5–281.6

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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