孟加拉国与巴基斯坦对比

孟加拉国与巴基斯坦：热带夜

2014 年热带夜：孟加拉国为 239.9 夜，巴基斯坦为 149.9 夜（CMIP6 气候模型中位数模拟）。 2014 年孟加拉国的数值较高，高出 90 夜，是巴基斯坦的 1.6 倍。

在地图上查看其变化

每年夜数 · CMIP6

孟加拉国与巴基斯坦：热带夜2014 年热带夜：孟加拉国为 239.9 夜，巴基斯坦为 149.9 夜（CMIP6 气候模型中位数模拟）。 2014 年孟加拉国的数值较高，高出 90 夜，是巴基斯坦的 1.6 倍。
孟加拉国巴基斯坦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，巴基斯坦为 177.6 夜。

逐年数据

每年夜数 · CMIP6

年份孟加拉国巴基斯坦
2014239.9149.9
2013239149.1
2012240.4149.9
2011240.5149
2010241148.4
2009238.6147.1
2008236.7147.4
2007236.9147.3
2006238.9146.7
2005238.2146.5
2004238.7147.5
2003236.5146
2002237.6148.3
2001237.2145.4
2000239.3144.7
1999236.6146.9
1998235.5144.8
1997235.5143.2
1996235.5141.2
1995234.8141.8
1994233.6142.1
1993232.2140.4
1992228139.9
1991233.4142.5
1990234.6142.6
1989235.7142.5
1988235.1140.3
1987236.4140
1986233.8140
1985233.6140
1984236138.9
1983230136.3
1982232.3138.5
1981235.9141.5
1980233.4139.5
1979234.5139.1
1978231.8139
1977232.3138.6
1976232139.2
1975231.3136.5
1974232.9138.7
1973232.1137.8
1972234.3137.4
1971233.1136
1970232.5137.7
1969231.1135.9
1968229.7136.6
1967231.6135.2
1966232.6136.9
1965232.5138.3
1964229.3135.1
1963233.8135.7
1962231.9137
1961236.2138.6
1960232.5139
1959234.7138.6
1958233.5137.7
1957232.5140
1956234.3137.8
1955230.2137.5
1954232.9137.8
1953234136.9
1952230.3138.1
1951233.5136.7
1950233.9139.1
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份孟加拉国巴基斯坦
2015241.2227–252.4152.4138.7–163.3
2016237.9226.6–249.3150.6139.4–161.7
2017239.8227.5–249.4151.3138.8–162
2018242.6227–255152.6139.8–161.8
2019241.2228.5–251.9151.8138.1–163.3
2020242.6229.3–254.4153.1140.3–164.5
2021244.3230.4–254.4154.1140.6–165.7
2022243.8231.5–254.2153.1140.2–165.7
2023243.5229.2–254.5155.5141.6–165.9
2024245.7231.4–257.1156.8143.3–168.7
2025242.5229.4–253.9155.7141.5–168.6
2026243.9227.9–258.1155.3142.2–167.9
2027247.1232.8–259.3156.8140.9–168.9
2028244.2232.2–254.4156.5143.9–167.6
2029247.3232.7–261.5155.9141.5–167.7
2030243.9232.3–255.2156.3143.3–167.6
2031245.1232.9–262.3157.3144.4–168.1
2032247.6236.6–257.8157.4142.5–169.6
2033245.3231.7–256.6157.7143.6–169.4
2034246.3233.2–260.4159.5145.6–173.4
2035246.4234.1–260.9159.3146.7–170.3
2036246.2228.6–260.4159.1147.5–171.4
2037247.7235.4–260.2162.2147.5–175.3
2038249232.1–261161.4148.6–171.7
2039250234.4–262.7160148.2–170.4
2040248.9235.5–260.5160.9147.9–171.3
2041248.3235.6–261.9160.8146.7–171.7
2042252.5237.8–265.3162.3149.9–175.6
2043250.8234.7–263.4161.1150.3–173.8
2044251.8239.1–265.2163150.9–173.9
2045250.3239.1–265.6163149.5–174.8
2046252.7238.9–267.8163.5149.8–177.2
2047253.9239.4–267.1165.2151.8–178.5
2048254.4242.7–270.5166.4154.1–179.4
2049253.7241.5–266.4165150.8–178.2
2050254.6242.5–269.2166.9153.5–179.3
2051254.7242.7–270.1165.6150.8–180
2052252.3240.2–264.6166.7155.4–179.5
2053256.9244–272.4166.3154.2–178.8
2054255.9243.5–269.4167.5153.9–181
2055255.2243.8–273.6167.8155.8–182.5
2056259.1243.6–274.7166.3153.6–179.7
2057257.5243.8–273.7168.3153.9–182.3
2058257.4245.6–274.2167.5157–179.9
2059258.3246.4–271.8170.9155.9–183.8
2060259.2246.1–272.6170.3156.5–181.8
2061257.7244.8–270.1168.8156.8–179.6
2062260.4246.4–274.2171.6153.5–186.5
2063259.9241.3–272.7171.3159.5–183.8
2064260.2245.9–273.1170.2155.3–184.5
2065259.8244.1–274.7169.7156.4–185
2066260246.6–274.6172.2157–186.7
2067261.4246.4–272.3173.2160.2–186.3
2068260.1245.8–274.8172.6157.7–186.3
2069263.3249.8–276.6171.8157.3–185.6
2070259.6245.8–272.6171.7158.9–186.7
2071262.2248.7–283.4173.4158.7–186.8
2072259.8248.6–276174161.5–186.9
2073264.1246.6–277.2175.6157.2–187.9
2074262.6248.3–276.6173.5160–186.3
2075263.6248.5–277.7173161.5–187.8
2076261.6251–276.9172.9158.8–186.7
2077264251.1–279.8175161.3–187.8
2078265251.6–281.6174.4160.9–189.3
2079263.8248.5–277.2172.5158.3–187.7
2080266.8251.9–280.3175.1160.7–189.2
2081266.5250.7–279.9174.9159.2–190.2
2082264249.6–277.3175.4161.8–190.6
2083266.6251.8–282.8176.5161.8–190.8
2084264.8253.1–284.2176.1160.9–190.5
2085265.4251.2–283.4176.3161.9–193.6
2086268.2252.8–285.3173.9160–189.1
2087265.7251.3–280.8176161–193.1
2088267.2252.6–284.4175.4160.5–195.2
2089267.1252.5–286.7177.2164.2–191.7
2090267.9254.9–283.4177.7163.9–192.2
2091267.7254.5–282.2177.8162.8–192.2
2092268.8253.6–281.7178.7162.9–192.9
2093268.1251.7–287177164–191
2094267.4251.3–287.4176.8164.1–190.7
2095270.8253.7–284.9178.6163.8–193.1
2096267.9250.5–285.8177.8163.7–192.5
2097269.3254.9–287.3177.3160.4–192.5
2098268.8252.4–284.9178.7162.6–195.7
2099269253–282.3176159.9–193.2
2100269.8254.8–284.9177.6162.2–193

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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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