巴西与印度对比

巴西与印度：热带夜

2014 年热带夜：巴西为 282 夜，印度为 215.5 夜（CMIP6 气候模型中位数模拟）。 2014 年巴西的数值较高，高出 66.5 夜，是印度的 1.31 倍。

在地图上查看其变化

每年夜数 · CMIP6

巴西与印度：热带夜2014 年热带夜：巴西为 282 夜，印度为 215.5 夜（CMIP6 气候模型中位数模拟）。 2014 年巴西的数值较高，高出 66.5 夜，是印度的 1.31 倍。
巴西印度CMIP6 模型中位数（SSP2-4.5，中间路径）模型第 10–90 百分位

数据解读

  • 自 1950 年以来，在两国都有数据的每一年，巴西的数值都更高。
  • 根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年巴西为 317.3 夜，印度为 250.4 夜。

逐年数据

每年夜数 · CMIP6

年份巴西印度
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 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份巴西印度
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

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须知

  • 一年中气温始终高于 20 °C 的夜晚数，取全国平均。
  • 来源：World Bank Climate Change Knowledge Portal, CMIP6 multi-model median。
  • 虚线为CMIP6 模型中位数（SSP2-4.5，中间路径），是一种情景而非预报；阴影带为其模型第 10–90 百分位。
  • 气候模型值为 CMIP6 各模型的中位数：2014 年及以前按历史排放模拟，此后按中间路径 SSP2-4.5 模拟；它们并非实测数据。

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