巴西与海地对比

巴西与海地：热带夜

2014 年热带夜：巴西为 282 夜，海地为 298.9 夜（CMIP6 气候模型中位数模拟）。 2014 年海地的数值较高，高出 16.9 夜，是巴西的 1.06 倍。

在地图上查看其变化

每年夜数 · CMIP6

巴西与海地：热带夜2014 年热带夜：巴西为 282 夜，海地为 298.9 夜（CMIP6 气候模型中位数模拟）。 2014 年海地的数值较高，高出 16.9 夜，是巴西的 1.06 倍。
巴西海地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，海地的数值都更高。
  • 根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年巴西为 317.3 夜，海地为 346.8 夜。

逐年数据

每年夜数 · CMIP6

年份巴西海地
2014282298.9
2013282.5301.1
2012283.6301.5
2011281.8301
2010280.2298.6
2009279.2298.7
2008277.8296.4
2007275.9293.6
2006275.4294.2
2005275.8295.3
2004278.5298
2003276.7295.4
2002276.2295.6
2001277.7296
2000273.3291
1999271290.8
1998273.6291.4
1997270.9288
1996264.7287
1995263.8283.1
1994263.6282.6
1993258.3278.8
1992252.8277.7
1991269.7286.2
1990272.5291.1
1989267.1286.3
1988264.7282.7
1987265.9282.9
1986265.7281
1985260.6277.9
1984261.1277.7
1983255.9276.1
1982264.8280.4
1981265.3281.3
1980262280.2
1979261.2280.2
1978259.7277.8
1977261.8280.4
1976258.4276
1975252.4275.1
1974258.7278.1
1973261278.3
1972258.1276.6
1971256.5275.5
1970254.5272.2
1969255.1275.5
1968254.9274.5
1967250.3275
1966254.5277.8
1965250.8274.1
1964246.2274.8
1963241.9274.2
1962257.9278.6
1961258.2278.2
1960260.3278.2
1959255.7278.6
1958258.1281.6
1957256.6278
1956251.2277.9
1955257.2280.7
1954258277.6
1953255.2276.8
1952255.8279.7
1951256.3277.9
1950254.4276.8
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份巴西海地
2015284257.6–299.5305.5285.9–322.7
2016281.5261.4–296.3306288.9–319.7
2017284.1263.2–297.8307.5292–322.8
2018283.4263.1–298.8308.8294.3–322.5
2019283.7262.9–302.4307.1290.7–322.4
2020286.3264.2–303.6307.4293.2–321.3
2021287.9266.9–302.3311.8296.6–324.5
2022289.6270.7–303.9312.1298–329.1
2023287.3270.5–303311.6297.9–324.7
2024291.5268.2–304.6312.3294.2–326.9
2025289.6269.1–304.8314.6291.3–328.7
2026289.7266.2–305.1316.3297.5–332.3
2027289.5269.1–303.7316.4293.9–332.7
2028291.2271.9–306316.4299.6–334.9
2029295.5276.3–309.6316.5298.3–333.6
2030292.2269.1–306.9314.8301.6–331.6
2031295.3274–308.9317.8303.5–333.7
2032296.8280.1–310.9321.4303.7–333.1
2033295.4273.3–308.5319.5302–332.4
2034294.3273.5–311.8319.5298.9–337.1
2035295.2274.4–310.9322.6304.3–335.1
2036295.1278.2–307.8321.3304.1–335.4
2037299.9283.7–311.3325310.6–336
2038299.6283.5–312.1322305.4–338.2
2039296.9279.9–311322.3305.5–339.8
2040298.5279.4–311.9324.1309.7–338.7
2041301.4282.2–314.1323.8310.9–339.7
2042300.6277.8–314.7325307.1–339.2
2043298.2279.8–312.7325.4306.3–339.9
2044300.3281.2–315.6326.8308.2–345.7
2045299.9279.7–313.1327312.5–341.6
2046302.8285.8–316.6330.7312.9–342.1
2047303.3285–316.4327.3313.3–343.2
2048304.4287.3–317.3331.4313.9–344.2
2049305.4288.4–318.5333.3314.4–344.6
2050303.9283.9–316.2331.2312.1–348
2051305.7287.5–317.5331.4314–342.3
2052305.9290.6–318.8331.5314.8–346
2053305.3285.9–317.5332.8314.2–342.8
2054306.1288.4–319.3331.7315.8–348.4
2055306.4290.8–319.8331.2317.8–348.8
2056306.7288.3–321.1330317.4–348.3
2057306.4287.6–321.1335.7314–347.6
2058309291–321.4335.3316.4–350.6
2059310.4290.7–322.8336.7319.6–349
2060311.6294.4–325.1337.6318.4–350
2061307.5290.3–321.2336.4318.8–349.6
2062309291.5–322.8336.1317.5–349.7
2063310.8290.6–322.8338320.8–354
2064309.6290.2–321.1336.6319.4–350.9
2065311.1291.6–323.1335.5318.9–349
2066312.2294.2–324.2338.8321.1–351.7
2067310.9291.5–323.3337.2317.8–350.8
2068311.5293–324.5340.4321.9–353.8
2069310.6292.2–323.6337.2320.2–351.6
2070312.7293–325.3339.5319.8–351.4
2071311.5292.1–323.9339.8320.1–353.6
2072313.3297.8–325.5342.6319.9–353.2
2073313.8298.6–327.2340.9320.2–353.6
2074311.4292.4–323.5340.9324.7–353.4
2075310.9291.5–324.5338.8321.7–353.5
2076314.2294.4–327.7344.1322–355.4
2077315.1295.6–326.8340.8321.6–354
2078314.9296.3–327.1340.6325.1–354.5
2079313292.8–326.8341.6323.7–354.4
2080311.9294.7–325.4340.3322.6–354.3
2081313.5295.5–325.6340322.6–353.4
2082315296.8–327.1342.4326.5–353.5
2083315.7295.3–328.7342.2326.4–352.5
2084316.6298.5–327.9345.5326.2–354.6
2085317.4299.3–329.8344325–355.4
2086315.8294–328344.9326.6–355.1
2087316.5297.9–328.5342.6322.5–354.4
2088315.6297.3–328.8342.5328.2–356.1
2089315296.6–327.9345.8326.6–358
2090316298.9–330.3343.2328.2–355.8
2091317298.1–330.6344.7323.1–357.7
2092317.6298.7–330.7346.5326.6–356.5
2093316.3297.5–328.6341.4324.8–356.7
2094316.4300.2–327.5341.4327.9–355.8
2095319299.8–330.7345.6326.2–356.1
2096317.7299.5–330.8344327.2–358.3
2097316.9297.8–329344.2330–356.7
2098318.6299.9–331.9343.8324.3–358.4
2099318.1300–330.2346.6323.1–358.1
2100317.3298.4–330.3346.8326.2–356.3

分别查看各国

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

巴西与海地对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境