巴西与洪都拉斯对比

巴西与洪都拉斯：热带夜

2014 年热带夜：巴西为 282 夜，洪都拉斯为 176.7 夜（CMIP6 气候模型中位数模拟）。 2014 年巴西的数值较高，高出 105.3 夜，是洪都拉斯的 1.6 倍。

在地图上查看其变化

每年夜数 · CMIP6

巴西与洪都拉斯：热带夜2014 年热带夜：巴西为 282 夜，洪都拉斯为 176.7 夜（CMIP6 气候模型中位数模拟）。 2014 年巴西的数值较高，高出 105.3 夜，是洪都拉斯的 1.6 倍。
巴西洪都拉斯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，洪都拉斯为 279.1 夜。

逐年数据

每年夜数 · CMIP6

年份巴西洪都拉斯
2014282176.7
2013282.5181.1
2012283.6181.4
2011281.8180.5
2010280.2176.9
2009279.2174.4
2008277.8170.5
2007275.9171.8
2006275.4171
2005275.8171.6
2004278.5174.2
2003276.7170.2
2002276.2169.1
2001277.7168.2
2000273.3164.8
1999271162.2
1998273.6163
1997270.9160.4
1996264.7154.7
1995263.8152.5
1994263.6151.9
1993258.3149
1992252.8145
1991269.7156.7
1990272.5162.1
1989267.1153.8
1988264.7151.1
1987265.9151.9
1986265.7151.3
1985260.6146.1
1984261.1147.5
1983255.9143.7
1982264.8148.4
1981265.3150.9
1980262147.8
1979261.2148.9
1978259.7146
1977261.8148.6
1976258.4145.5
1975252.4141.8
1974258.7146.8
1973261145.1
1972258.1140.4
1971256.5141.1
1970254.5140.6
1969255.1142.2
1968254.9141.9
1967250.3138.4
1966254.5139.9
1965250.8138.1
1964246.2138.4
1963241.9136.8
1962257.9144.2
1961258.2145.5
1960260.3146.1
1959255.7143.3
1958258.1147.6
1957256.6144.5
1956251.2143.8
1955257.2146.3
1954258144
1953255.2143.2
1952255.8143.6
1951256.3145.5
1950254.4143.7
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份巴西洪都拉斯
2015284257.6–299.5186.4151.3–215.3
2016281.5261.4–296.3185.7154.8–211.9
2017284.1263.2–297.8194.4164.9–215.2
2018283.4263.1–298.8190.6168.8–218.5
2019283.7262.9–302.4189161–221
2020286.3264.2–303.6196.8164.4–223
2021287.9266.9–302.3199.3176.3–226.8
2022289.6270.7–303.9202.9173–227.6
2023287.3270.5–303198.1175.2–230.1
2024291.5268.2–304.6204.7177.9–233.2
2025289.6269.1–304.8202.7173.9–230.8
2026289.7266.2–305.1206.8174–235.2
2027289.5269.1–303.7206.5177.9–235.7
2028291.2271.9–306211.3184–238.7
2029295.5276.3–309.6210.3185.4–244.5
2030292.2269.1–306.9208.9176.9–241.7
2031295.3274–308.9217.3187.1–246.4
2032296.8280.1–310.9218.9194.5–247.9
2033295.4273.3–308.5213.3188.2–239.7
2034294.3273.5–311.8211.3186.1–248.7
2035295.2274.4–310.9215.3184.2–248.2
2036295.1278.2–307.8215.5194.1–242.5
2037299.9283.7–311.3226.4202.4–251.6
2038299.6283.5–312.1228.9198.7–256.2
2039296.9279.9–311224.4196.6–256.2
2040298.5279.4–311.9225.1201–258
2041301.4282.2–314.1225.9203–251.8
2042300.6277.8–314.7229.3200.2–262.8
2043298.2279.8–312.7224.4199–262.5
2044300.3281.2–315.6224.8201.2–262.7
2045299.9279.7–313.1231206.1–262.3
2046302.8285.8–316.6236.9204.5–267.7
2047303.3285–316.4236.3213.3–269.3
2048304.4287.3–317.3241.2216.7–268.9
2049305.4288.4–318.5244.8213.5–270.7
2050303.9283.9–316.2241.1207.2–277.8
2051305.7287.5–317.5239.9210.5–270.2
2052305.9290.6–318.8245.1215.7–271.2
2053305.3285.9–317.5240.8211.7–277.5
2054306.1288.4–319.3243.9220.4–286.6
2055306.4290.8–319.8248.1220.1–282.1
2056306.7288.3–321.1245.6213.1–279
2057306.4287.6–321.1249.4214.2–279.1
2058309291–321.4248.4217.2–289.1
2059310.4290.7–322.8252.6220.5–283.1
2060311.6294.4–325.1256.8225.2–289.4
2061307.5290.3–321.2254.5220.4–285.9
2062309291.5–322.8252.8217.4–291.1
2063310.8290.6–322.8258.7226.2–288
2064309.6290.2–321.1252.1224.1–285.7
2065311.1291.6–323.1258.1226.9–288.9
2066312.2294.2–324.2256.4227.7–287.4
2067310.9291.5–323.3258.3228.2–294.9
2068311.5293–324.5264.6231.2–295
2069310.6292.2–323.6258.1229.3–292
2070312.7293–325.3256.9225.3–297.9
2071311.5292.1–323.9261.9231–292.9
2072313.3297.8–325.5267.3235.2–300.4
2073313.8298.6–327.2268.1233.7–304.7
2074311.4292.4–323.5263.7234.2–295.9
2075310.9291.5–324.5262.1229.5–295.4
2076314.2294.4–327.7266.8231.8–298.5
2077315.1295.6–326.8268.6232.1–298.8
2078314.9296.3–327.1270.1236.8–299.6
2079313292.8–326.8265.3229.5–304.2
2080311.9294.7–325.4268.4230.2–304.2
2081313.5295.5–325.6268231.9–300.8
2082315296.8–327.1267.4230.2–301.8
2083315.7295.3–328.7268.3236.2–307.4
2084316.6298.5–327.9273.9235.2–307.1
2085317.4299.3–329.8276.4234.2–305.9
2086315.8294–328267.9238.8–305.2
2087316.5297.9–328.5270.4233.7–301.8
2088315.6297.3–328.8277239.9–310.2
2089315296.6–327.9275.4246–309.8
2090316298.9–330.3275.3244.1–307
2091317298.1–330.6281.9240.6–310.6
2092317.6298.7–330.7277.1245.6–312.3
2093316.3297.5–328.6272.8244.2–311.6
2094316.4300.2–327.5274.9245.2–308.4
2095319299.8–330.7280.8244.6–313.5
2096317.7299.5–330.8275.2245.8–313.5
2097316.9297.8–329276247.2–305.4
2098318.6299.9–331.9278.9238.9–313.4
2099318.1300–330.2280.8240.6–312.8
2100317.3298.4–330.3279.1248.3–309.6

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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。

各图层如何运作、数据从何而来，以及它们无法告诉你什么： 历年各国数据

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