孟加拉国与缅甸对比

孟加拉国与缅甸:热带夜

2014 年热带夜:孟加拉国为 239.9 夜,缅甸为 201.9 夜(CMIP6 气候模型中位数模拟)。 2014 年孟加拉国的数值较高,高出 38 夜,是缅甸的 1.19 倍。

每年夜数 · CMIP6

孟加拉国与缅甸:热带夜2014 年热带夜:孟加拉国为 239.9 夜,缅甸为 201.9 夜(CMIP6 气候模型中位数模拟)。 2014 年孟加拉国的数值较高,高出 38 夜,是缅甸的 1.19 倍。
孟加拉国缅甸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,孟加拉国的数值都更高。
  • 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年孟加拉国为 269.8 夜,缅甸为 244.5 夜。

逐年数据

每年夜数 · CMIP6

年份孟加拉国缅甸
2014239.9201.9
2013239203.1
2012240.4201.1
2011240.5200.9
2010241202.1
2009238.6199
2008236.7198.1
2007236.9196.8
2006238.9198.2
2005238.2196.7
2004238.7200.3
2003236.5195.3
2002237.6196.6
2001237.2199
2000239.3197.2
1999236.6196.4
1998235.5194.7
1997235.5194.4
1996235.5191.4
1995234.8189.9
1994233.6188.8
1993232.2185
1992228180.5
1991233.4191.7
1990234.6191.5
1989235.7190.3
1988235.1190.7
1987236.4190.8
1986233.8189.7
1985233.6187.4
1984236189.1
1983230182.3
1982232.3186.7
1981235.9188.4
1980233.4189
1979234.5189.8
1978231.8186.8
1977232.3187.4
1976232185.8
1975231.3183.6
1974232.9185.5
1973232.1187.5
1972234.3184.8
1971233.1185.2
1970232.5184.9
1969231.1184.3
1968229.7183.7
1967231.6182.3
1966232.6186.2
1965232.5182.9
1964229.3180.6
1963233.8183.1
1962231.9187.3
1961236.2188.7
1960232.5187.1
1959234.7186.5
1958233.5187.1
1957232.5186.2
1956234.3187.9
1955230.2185.9
1954232.9185.7
1953234185
1952230.3186.1
1951233.5187.1
1950233.9186.9
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
年份孟加拉国缅甸
2015241.2227–252.4205.2186.4–218.9
2016237.9226.6–249.3202.8186.2–218.8
2017239.8227.5–249.4203.4187.3–218.3
2018242.6227–255205.5190.9–219.9
2019241.2228.5–251.9205.2186.7–222.2
2020242.6229.3–254.4208.2188.5–223.5
2021244.3230.4–254.4208.9191.2–224.1
2022243.8231.5–254.2209.9192.7–224.9
2023243.5229.2–254.5210.6195.4–226.3
2024245.7231.4–257.1210.4193.8–226.6
2025242.5229.4–253.9209.9190.3–225.2
2026243.9227.9–258.1212.2194.3–229.2
2027247.1232.8–259.3212195.6–228.6
2028244.2232.2–254.4213195.7–227.2
2029247.3232.7–261.5215.3193.9–231.9
2030243.9232.3–255.2212.2194.9–228
2031245.1232.9–262.3214.3197.2–230.8
2032247.6236.6–257.8215199.3–229.6
2033245.3231.7–256.6215.5198.5–230.1
2034246.3233.2–260.4214.9198.4–233.5
2035246.4234.1–260.9214.9199.2–236.8
2036246.2228.6–260.4216198.7–234.5
2037247.7235.4–260.2217.2199.6–233.5
2038249232.1–261220.7204.8–235.1
2039250234.4–262.7219.7202.4–234.3
2040248.9235.5–260.5219.2202.9–235
2041248.3235.6–261.9220.7203.9–237.7
2042252.5237.8–265.3221.8206.1–237.2
2043250.8234.7–263.4219.5201.2–237.1
2044251.8239.1–265.2221.4201.6–239.6
2045250.3239.1–265.6223.7204.8–241.5
2046252.7238.9–267.8223.2203.2–240.2
2047253.9239.4–267.1224.3204.8–241.1
2048254.4242.7–270.5226.4207.7–243.8
2049253.7241.5–266.4226.5205.6–242.8
2050254.6242.5–269.2227209.3–243.5
2051254.7242.7–270.1229.6212.4–246.4
2052252.3240.2–264.6227.2208.6–244.2
2053256.9244–272.4227.9208.7–247.7
2054255.9243.5–269.4227.9209.6–244.8
2055255.2243.8–273.6229.1209.8–247.5
2056259.1243.6–274.7231.8210.4–252.1
2057257.5243.8–273.7228.6208–249
2058257.4245.6–274.2228.9208.8–249
2059258.3246.4–271.8230.7212.1–247.5
2060259.2246.1–272.6234.7211.1–251.5
2061257.7244.8–270.1231.9213–247.7
2062260.4246.4–274.2233.6209.9–252.8
2063259.9241.3–272.7233215.4–250.5
2064260.2245.9–273.1233.2214.4–251.3
2065259.8244.1–274.7230.7210.4–250.7
2066260246.6–274.6233.5214.3–251.2
2067261.4246.4–272.3233211.5–253.3
2068260.1245.8–274.8233.1212.4–253.7
2069263.3249.8–276.6236.1214.6–253.4
2070259.6245.8–272.6235.9218.1–253.4
2071262.2248.7–283.4235.1213.5–259.6
2072259.8248.6–276234.6216.1–252.6
2073264.1246.6–277.2237.2219.3–257.2
2074262.6248.3–276.6236.4215.7–254.5
2075263.6248.5–277.7236.7214.4–255.9
2076261.6251–276.9237.7216–257
2077264251.1–279.8237.5219–258.7
2078265251.6–281.6238.5217.3–257.8
2079263.8248.5–277.2238.5219.2–257.2
2080266.8251.9–280.3240.5218.8–258.3
2081266.5250.7–279.9240219.7–260.9
2082264249.6–277.3239.4217.1–258.8
2083266.6251.8–282.8239.1220.5–259.2
2084264.8253.1–284.2241.3218.9–260.6
2085265.4251.2–283.4241.7218.8–260.7
2086268.2252.8–285.3241.7217.4–262.7
2087265.7251.3–280.8241.4220.5–260.9
2088267.2252.6–284.4241.8222.3–261.5
2089267.1252.5–286.7240.7221.2–262.6
2090267.9254.9–283.4241.3224.4–260.9
2091267.7254.5–282.2242.6220.3–262.5
2092268.8253.6–281.7241.9221.6–263.3
2093268.1251.7–287242.1220.2–260
2094267.4251.3–287.4242.5222.5–261.9
2095270.8253.7–284.9244.9224–264.4
2096267.9250.5–285.8243.9221.1–266.5
2097269.3254.9–287.3243.6219.6–264.2
2098268.8252.4–284.9243.6222.5–263.9
2099269253–282.3244.7221.8–263.5
2100269.8254.8–284.9244.5223.2–261.8

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

孟加拉国与缅甸对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境