Brazil vs India

Brazil vs India: Tropical nights

Tropical nights in 2014: 282 nights in Brazil and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 66.5 nights, or 1.31 times that in India.

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nights a year · CMIP6

Brazil vs India: Tropical nightsTropical nights in 2014: 282 nights in Brazil and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in Brazil, by 66.5 nights, or 1.31 times that in India.
BrazilIndiaCMIP6 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 India at 250.4 nights in 2100.

Every year

nights a year · CMIP6

YearBrazilIndia
2014282215.5
2013282.5216
2012283.6217.4
2011281.8215.5
2010280.2215.2
2009279.2213.7
2008277.8213.7
2007275.9213.3
2006275.4212.5
2005275.8212.9
2004278.5214.9
2003276.7212.1
2002276.2213
2001277.7212.2
2000273.3210.8
1999271211.9
1998273.6210.3
1997270.9209.5
1996264.7207
1995263.8208.8
1994263.6207.1
1993258.3206
1992252.8203.5
1991269.7208
1990272.5209.9
1989267.1208
1988264.7207.3
1987265.9207.2
1986265.7207.2
1985260.6205.9
1984261.1206.7
1983255.9203.3
1982264.8205.7
1981265.3208.4
1980262205.3
1979261.2205.5
1978259.7204.1
1977261.8205.9
1976258.4204.6
1975252.4202.6
1974258.7205.3
1973261205.6
1972258.1203.8
1971256.5203.6
1970254.5202.6
1969255.1203.6
1968254.9201.7
1967250.3201.6
1966254.5203.9
1965250.8202.4
1964246.2201.2
1963241.9201.8
1962257.9203.8
1961258.2206.3
1960260.3206
1959255.7206.1
1958258.1204
1957256.6206.5
1956251.2204
1955257.2203.2
1954258206
1953255.2204
1952255.8204.4
1951256.3204.3
1950254.4206.3
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBrazilIndia
2015284257.6–299.5216.9202.1–228.4
2016281.5261.4–296.3215202.5–227.6
2017284.1263.2–297.8216.2202.1–228.5
2018283.4263.1–298.8218.3204.5–231.4
2019283.7262.9–302.4217.4202.3–230.4
2020286.3264.2–303.6217.6203.1–232
2021287.9266.9–302.3219.7204.5–233.2
2022289.6270.7–303.9220.5205.8–233
2023287.3270.5–303220.4206.4–233.7
2024291.5268.2–304.6222.6208.1–236.3
2025289.6269.1–304.8219.7202.7–236.2
2026289.7266.2–305.1220.2204.2–236.8
2027289.5269.1–303.7223.6207.1–239
2028291.2271.9–306222.1205.1–235.7
2029295.5276.3–309.6225.4210–240.3
2030292.2269.1–306.9222.7207.3–235.6
2031295.3274–308.9223.8207.1–237.8
2032296.8280.1–310.9225.9210–240.5
2033295.4273.3–308.5223.8209.3–235.4
2034294.3273.5–311.8225.8210–242.7
2035295.2274.4–310.9224.9210.6–240.9
2036295.1278.2–307.8224.2210.4–240.3
2037299.9283.7–311.3228.3213.6–242.6
2038299.6283.5–312.1228.1212.6–241.4
2039296.9279.9–311227.4211.9–242.8
2040298.5279.4–311.9227212.2–242
2041301.4282.2–314.1227.1210.7–240.5
2042300.6277.8–314.7229.1214.8–244.2
2043298.2279.8–312.7228.9214.5–244
2044300.3281.2–315.6229.7214.7–244.2
2045299.9279.7–313.1231.2216.6–246.1
2046302.8285.8–316.6232.6216.2–248.6
2047303.3285–316.4232.4215.5–250
2048304.4287.3–317.3235.6218.5–254.3
2049305.4288.4–318.5235.3218.3–249.9
2050303.9283.9–316.2233.5216.6–253.4
2051305.7287.5–317.5234.9218.6–249.9
2052305.9290.6–318.8234219.4–249.3
2053305.3285.9–317.5234.9219.5–252.5
2054306.1288.4–319.3237.2219.4–253.1
2055306.4290.8–319.8237.2220.7–256.6
2056306.7288.3–321.1238.8221.2–254.9
2057306.4287.6–321.1235.7218.5–253.8
2058309291–321.4238.8222.8–254.1
2059310.4290.7–322.8241.1224.9–256.2
2060311.6294.4–325.1240.9225.6–255.6
2061307.5290.3–321.2237.9220.6–253.7
2062309291.5–322.8239.9221.2–259.7
2063310.8290.6–322.8239.9222.3–256.1
2064309.6290.2–321.1240223.8–256.3
2065311.1291.6–323.1240.9222.9–257.3
2066312.2294.2–324.2241.5224.1–258.6
2067310.9291.5–323.3241.6224.8–257.9
2068311.5293–324.5242.3224.6–262.1
2069310.6292.2–323.6242.8225.4–259.1
2070312.7293–325.3240.1225.3–257.1
2071311.5292.1–323.9241.8223.7–260.2
2072313.3297.8–325.5242.6225.4–259.2
2073313.8298.6–327.2243.8228–259.3
2074311.4292.4–323.5241.6226.9–258.4
2075310.9291.5–324.5243.5226.4–258.2
2076314.2294.4–327.7243.2224.6–259.9
2077315.1295.6–326.8243.7226.6–264.6
2078314.9296.3–327.1246.7230.1–261.5
2079313292.8–326.8244.9226.4–261.3
2080311.9294.7–325.4246.7227–263.7
2081313.5295.5–325.6247.5230.4–264.8
2082315296.8–327.1244.6227.9–262.3
2083315.7295.3–328.7247.5227.8–265.1
2084316.6298.5–327.9247.3228.3–266.8
2085317.4299.3–329.8246.5227.5–267.1
2086315.8294–328245.6227.7–266.5
2087316.5297.9–328.5245.5226.7–266.2
2088315.6297.3–328.8247229.4–266.9
2089315296.6–327.9248.1230–266.3
2090316298.9–330.3249228.9–266.4
2091317298.1–330.6248.9230–266.5
2092317.6298.7–330.7249.8232.3–267.8
2093316.3297.5–328.6248.1229–266.5
2094316.4300.2–327.5249.1230.6–268.4
2095319299.8–330.7251233.2–270
2096317.7299.5–330.8247.8231.4–269.3
2097316.9297.8–329251.1231.4–268
2098318.6299.9–331.9252.3230.8–268.3
2099318.1300–330.2248.7230.1–268.3
2100317.3298.4–330.3250.4232.9–266.7

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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