印度尼西亚与马来西亚对比

印度尼西亚与马来西亚：热带夜

2014 年热带夜：印度尼西亚为 306.5 夜，马来西亚为 323 夜（CMIP6 气候模型中位数模拟）。 2014 年马来西亚的数值较高，高出 16.5 夜，是印度尼西亚的 1.05 倍。

在地图上查看其变化

每年夜数 · CMIP6

印度尼西亚与马来西亚：热带夜2014 年热带夜：印度尼西亚为 306.5 夜，马来西亚为 323 夜（CMIP6 气候模型中位数模拟）。 2014 年马来西亚的数值较高，高出 16.5 夜，是印度尼西亚的 1.05 倍。
印度尼西亚马来西亚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，马来西亚的数值都更高。
  • 根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年印度尼西亚为 334.7 夜，马来西亚为 354.8 夜。

逐年数据

每年夜数 · CMIP6

年份印度尼西亚马来西亚
2014306.5323
2013306.4323.9
2012306.3323.3
2011304.6320.9
2010305.6320.9
2009303.9320.3
2008303.4317.9
2007302.8317.8
2006302.8317.3
2005303.1318.4
2004303.8319.4
2003301.9316
2002301.5316
2001302.5316.5
2000300.9314.5
1999300.4312.9
1998299.1312.5
1997297.9310.6
1996296.9307.1
1995296.7307.3
1994294.6304.1
1993291.6298.2
1992288.5293.6
1991297.5308.9
1990298.6310.4
1989296306.9
1988296.5306.8
1987295.6306
1986295.8305.5
1985292.8301.7
1984293.4302.1
1983290.1297.2
1982294.4302.6
1981294.8303.7
1980294.5303.3
1979294.1302.4
1978292.4301
1977293.4301.3
1976290.8298.9
1975290.7297.7
1974291.5298.1
1973293299.1
1972290.7297
1971291.2298.3
1970288.9296
1969290.4297.4
1968289.1295.2
1967288.4293.1
1966290.5296.2
1965288.1293.1
1964286.2291.3
1963286.4291.6
1962291.2299.1
1961292.9299.5
1960292.8300.1
1959291.9299.9
1958293.3301.7
1957290.8299
1956291.5298.1
1955292.4299.3
1954290296.8
1953291.4298.8
1952291.7299.4
1951291.7299.1
1950291.8300
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份印度尼西亚马来西亚
2015308295.7–315.1324.4308.5–333.7
2016307.5296.9–315.6323.8310.5–334.9
2017308.4295.5–315.6325.6309.9–334.4
2018308.9296.4–316.6325.7310.7–335.4
2019309.9297.8–316.7326.4311.9–335.3
2020310.9299–318.6328313.4–337.7
2021310.4298.7–316.4328.8314–336.3
2022311.4300–319.6329315.3–339
2023311.4300.1–320.6330.1316–340.5
2024313.2302–321.2332319.6–340.7
2025312300.2–321.9330.3317.7–342
2026312.6299.9–322.8330.2315.1–342.9
2027312.7301–321.6331315.2–342.4
2028313.8302.4–321.9332.4319–341.9
2029315.5303.9–324.1334.4322.5–344.9
2030314.2303.1–322.6333.4319.2–342.6
2031314.4301.6–321.9333.8317.1–342.5
2032316.9304.8–325.8336.5323.3–345.9
2033316.6305.4–323.3336.4322.5–343.3
2034315.4303.9–323.9334.8322.7–344.3
2035316.3305.6–327.9334.7323.3–347.9
2036317.7305.2–326.2336.9320.7–346.2
2037318.1306.6–325.2338.3325.4–345.3
2038319.3307.6–326.7339.7326.9–347.4
2039319.4307.7–326.7340326–347.4
2040318.5306.5–329338.6325.1–349
2041320.2308.3–328340.3326.3–348.1
2042320308.7–329.2339.9326.9–349.6
2043318.6306.6–327.8338.3324.3–348.3
2044321309–329.6340.6326.3–350.4
2045320.8308.6–329.8340.9327.4–349.8
2046322.8308.8–331343.3327.6–351.4
2047323.2308.8–333343325.3–352.9
2048322.3310.5–332.3342.6329–352.5
2049323.8311.6–334.1343.8331.1–354.1
2050323.3310.3–333.5342.7328.1–353.5
2051323.6311.2–334.4344.5330.7–354.3
2052325.1311.7–334.7345.1330.3–355
2053323.9310.9–333.8344.2331–353.5
2054324.4311.9–335.4345330.1–354.6
2055325.3312.6–335346.1332–354.3
2056325.9312.4–337.2346.5332.2–356.6
2057326.9311.9–335.2347.9332.3–355.4
2058326.4313–336.3347333.5–355.6
2059326.4313.9–337.8346.9333.4–356.2
2060329.5314.9–338.2349.7334.9–357.3
2061327.9313.6–336.9348.4334.1–356.1
2062327.6312.4–339.1348.4331.8–357.7
2063327.6313.9–339.4348.7333.2–357.7
2064328.8314.4–338.6349.1333.8–357.5
2065327.6314.3–337.9348.6334.6–356.8
2066328.6314.7–338.5349.3335–357.5
2067328.8314.3–338349.1334–356.6
2068329.8314.4–339.9350334.6–358.7
2069329.5315.5–339.3349.5334.2–357.9
2070328.6315.1–338.8349.2336.2–357.7
2071331.4315.5–340.4350.9336.1–358.6
2072330.3315.9–339.4351337.2–357.9
2073331.4317.7–341351.1338.7–359.9
2074329.9316.8–341.1350337.8–359.4
2075330.5315.2–340.2350.5335.4–358.1
2076331.5316.2–341.2351.6337.5–359.7
2077332315.9–341.8352.4336.4–359.9
2078331.4318.2–340.9351.3338.9–358.8
2079331.5316.6–341.5351.8337.9–359.7
2080332.4317.4–343.2352.4338.8–360.7
2081332.3318.4–341.8352.2337.3–359.7
2082332.8317.8–340.4352.7336.9–358.9
2083333.1318.7–342.6352.5339.6–360.4
2084333317.8–342.7353.5337.9–360.4
2085332.6318.1–342.7352.9340.2–360.2
2086333.1318.9–342.3352.8339.9–360
2087332.6318–343.2352.8338.4–361
2088334.5319.5–343.1354340–360.9
2089333.6319–342.6353.7339.7–359.9
2090333.3319.6–343.3353.3340.3–360.6
2091334.5318.2–343.9354.7338.9–361
2092335.1319.7–343.6355.3340.4–361.7
2093333.9320–344.9353.5339.3–362
2094335.6320.4–342.8355.4341.2–360.4
2095335.4319.7–343355339.4–360.6
2096334.3319.4–346.1353.6339.6–363.1
2097334.2319.5–343.3354.3339.5–360.6
2098334.9319.4–343.4354.8340.2–360.7
2099334.4319.4–344.6353.7340–361.8
2100334.7318.7–343.3354.8340.4–360.8

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

印度尼西亚与马来西亚对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境