缅甸与越南对比

缅甸与越南：热带夜

2014 年热带夜：缅甸为 201.9 夜，越南为 242.6 夜（CMIP6 气候模型中位数模拟）。 2014 年越南的数值较高，高出 40.7 夜，是缅甸的 1.2 倍。

在地图上查看其变化

每年夜数 · CMIP6

缅甸与越南：热带夜2014 年热带夜：缅甸为 201.9 夜，越南为 242.6 夜（CMIP6 气候模型中位数模拟）。 2014 年越南的数值较高，高出 40.7 夜，是缅甸的 1.2 倍。
缅甸越南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，越南的数值都更高。
  • 根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年缅甸为 244.5 夜，越南为 282.7 夜。

逐年数据

每年夜数 · CMIP6

年份缅甸越南
2014201.9242.6
2013203.1243.6
2012201.1242.4
2011200.9241.9
2010202.1240.9
2009199240
2008198.1238.7
2007196.8238
2006198.2239.1
2005196.7238.3
2004200.3241.8
2003195.3235.9
2002196.6236.3
2001199241.3
2000197.2237
1999196.4236
1998194.7236.8
1997194.4237.1
1996191.4231.4
1995189.9229.9
1994188.8231.2
1993185225.3
1992180.5221.9
1991191.7229.8
1990191.5233.1
1989190.3229.2
1988190.7231.7
1987190.8230.3
1986189.7230.9
1985187.4228
1984189.1230.2
1983182.3224.9
1982186.7227.5
1981188.4229.7
1980189228.1
1979189.8228.9
1978186.8227.5
1977187.4229
1976185.8225.8
1975183.6225.8
1974185.5225.7
1973187.5230.3
1972184.8225.6
1971185.2225.5
1970184.9226.1
1969184.3227
1968183.7227.1
1967182.3222.9
1966186.2226.8
1965182.9225.4
1964180.6222.6
1963183.1224.3
1962187.3227.8
1961188.7229.4
1960187.1228.5
1959186.5226.2
1958187.1230.9
1957186.2228.4
1956187.9228.7
1955185.9227.5
1954185.7226.3
1953185228.2
1952186.1228.5
1951187.1229.2
1950186.9228.9
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份缅甸越南
2015205.2186.4–218.9245.8228.2–261.9
2016202.8186.2–218.8243.7226.1–259.4
2017203.4187.3–218.3247229.6–260.7
2018205.5190.9–219.9248.3228.8–263.3
2019205.2186.7–222.2248.1229.2–262.8
2020208.2188.5–223.5248.8229.6–262.9
2021208.9191.2–224.1251.1233.1–266.7
2022209.9192.7–224.9252.4234.3–266.8
2023210.6195.4–226.3253.4235.4–266.6
2024210.4193.8–226.6251.3236.7–264.6
2025209.9190.3–225.2252.4234.1–266.2
2026212.2194.3–229.2252.8232.9–268.5
2027212195.6–228.6253.2237–268.8
2028213195.7–227.2254.3237.7–272
2029215.3193.9–231.9258.1238.5–273.7
2030212.2194.9–228256.4240.9–270.1
2031214.3197.2–230.8255.9241.2–270.9
2032215199.3–229.6257.4239.1–269.9
2033215.5198.5–230.1258.3241.7–273.2
2034214.9198.4–233.5258.8240.7–275.8
2035214.9199.2–236.8258.6242.5–275.4
2036216198.7–234.5258.3239.1–273.8
2037217.2199.6–233.5258.7242.4–272.4
2038220.7204.8–235.1263.4247.6–277.3
2039219.7202.4–234.3260.2243.7–275.9
2040219.2202.9–235260.1242.8–274.8
2041220.7203.9–237.7263.1245.9–279
2042221.8206.1–237.2263.6246.5–279
2043219.5201.2–237.1261.4245.5–279.6
2044221.4201.6–239.6263.2245.2–277.6
2045223.7204.8–241.5265.5249.6–281.4
2046223.2203.2–240.2264.9246.8–278.1
2047224.3204.8–241.1266.9250.4–282.9
2048226.4207.7–243.8268250.5–283.8
2049226.5205.6–242.8267.8251.2–284.8
2050227209.3–243.5268251.2–283.5
2051229.6212.4–246.4270.9254.3–285.4
2052227.2208.6–244.2268.3253.3–282.8
2053227.9208.7–247.7268.5250.1–283.2
2054227.9209.6–244.8269.1250.8–283.6
2055229.1209.8–247.5270249.8–284.2
2056231.8210.4–252.1271.7254.8–290.1
2057228.6208–249270253–285.7
2058228.9208.8–249270.7252.9–286.5
2059230.7212.1–247.5273257.6–286.6
2060234.7211.1–251.5275.7255.6–290.6
2061231.9213–247.7273.5254.6–289.5
2062233.6209.9–252.8271.4253.1–290.2
2063233215.4–250.5272.9252.7–288.1
2064233.2214.4–251.3273.8254.4–288.1
2065230.7210.4–250.7272255.8–286.3
2066233.5214.3–251.2271.8254.4–287.3
2067233211.5–253.3270.8252.1–287.6
2068233.1212.4–253.7275.6256.9–292.4
2069236.1214.6–253.4276.4258.5–292
2070235.9218.1–253.4274.6257.8–292.8
2071235.1213.5–259.6276.2255.2–294.1
2072234.6216.1–252.6277256.8–291.4
2073237.2219.3–257.2278.5262.7–293.4
2074236.4215.7–254.5277.6259.2–295.8
2075236.7214.4–255.9276.4258.7–294.4
2076237.7216–257279.2258.5–296.6
2077237.5219–258.7280264.9–294.7
2078238.5217.3–257.8278.4258.6–295.5
2079238.5219.2–257.2279.3263.4–293.6
2080240.5218.8–258.3280261.4–296.5
2081240219.7–260.9280.4261.2–297.9
2082239.4217.1–258.8280.9258.9–296
2083239.1220.5–259.2278.4261.6–295
2084241.3218.9–260.6279257.4–293.8
2085241.7218.8–260.7281.3265–297.8
2086241.7217.4–262.7282.3260.2–297.5
2087241.4220.5–260.9281.9261.3–300.7
2088241.8222.3–261.5283.1265.7–301.5
2089240.7221.2–262.6280.8261.2–301.6
2090241.3224.4–260.9280.5264.5–297.6
2091242.6220.3–262.5283.3264.3–298.9
2092241.9221.6–263.3281.1261.5–299.4
2093242.1220.2–260280.5263.4–296.1
2094242.5222.5–261.9283264.5–300
2095244.9224–264.4285.5264.5–302.9
2096243.9221.1–266.5281.8264.8–299.8
2097243.6219.6–264.2281.5263.3–299
2098243.6222.5–263.9282.5263.9–301.5
2099244.7221.8–263.5282.7265.1–298
2100244.5223.2–261.8282.7261–298.2

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

缅甸与越南对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境