孟加拉国与越南对比
孟加拉国与越南:热带夜
2014 年热带夜:孟加拉国为 239.9 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 2.7 夜,是孟加拉国的 1.01 倍。
每年夜数 · CMIP6
数据解读
- 自 2011 年超过孟加拉国以来,越南的数值一直更高。
- 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,越南为 282.7 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 孟加拉国 | 越南 |
|---|---|---|
| 2014 | 239.9 | 242.6 |
| 2013 | 239 | 243.6 |
| 2012 | 240.4 | 242.4 |
| 2011 | 240.5 | 241.9 |
| 2010 | 241 | 240.9 |
| 2009 | 238.6 | 240 |
| 2008 | 236.7 | 238.7 |
| 2007 | 236.9 | 238 |
| 2006 | 238.9 | 239.1 |
| 2005 | 238.2 | 238.3 |
| 2004 | 238.7 | 241.8 |
| 2003 | 236.5 | 235.9 |
| 2002 | 237.6 | 236.3 |
| 2001 | 237.2 | 241.3 |
| 2000 | 239.3 | 237 |
| 1999 | 236.6 | 236 |
| 1998 | 235.5 | 236.8 |
| 1997 | 235.5 | 237.1 |
| 1996 | 235.5 | 231.4 |
| 1995 | 234.8 | 229.9 |
| 1994 | 233.6 | 231.2 |
| 1993 | 232.2 | 225.3 |
| 1992 | 228 | 221.9 |
| 1991 | 233.4 | 229.8 |
| 1990 | 234.6 | 233.1 |
| 1989 | 235.7 | 229.2 |
| 1988 | 235.1 | 231.7 |
| 1987 | 236.4 | 230.3 |
| 1986 | 233.8 | 230.9 |
| 1985 | 233.6 | 228 |
| 1984 | 236 | 230.2 |
| 1983 | 230 | 224.9 |
| 1982 | 232.3 | 227.5 |
| 1981 | 235.9 | 229.7 |
| 1980 | 233.4 | 228.1 |
| 1979 | 234.5 | 228.9 |
| 1978 | 231.8 | 227.5 |
| 1977 | 232.3 | 229 |
| 1976 | 232 | 225.8 |
| 1975 | 231.3 | 225.8 |
| 1974 | 232.9 | 225.7 |
| 1973 | 232.1 | 230.3 |
| 1972 | 234.3 | 225.6 |
| 1971 | 233.1 | 225.5 |
| 1970 | 232.5 | 226.1 |
| 1969 | 231.1 | 227 |
| 1968 | 229.7 | 227.1 |
| 1967 | 231.6 | 222.9 |
| 1966 | 232.6 | 226.8 |
| 1965 | 232.5 | 225.4 |
| 1964 | 229.3 | 222.6 |
| 1963 | 233.8 | 224.3 |
| 1962 | 231.9 | 227.8 |
| 1961 | 236.2 | 229.4 |
| 1960 | 232.5 | 228.5 |
| 1959 | 234.7 | 226.2 |
| 1958 | 233.5 | 230.9 |
| 1957 | 232.5 | 228.4 |
| 1956 | 234.3 | 228.7 |
| 1955 | 230.2 | 227.5 |
| 1954 | 232.9 | 226.3 |
| 1953 | 234 | 228.2 |
| 1952 | 230.3 | 228.5 |
| 1951 | 233.5 | 229.2 |
| 1950 | 233.9 | 228.9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 孟加拉国 | 越南 |
|---|---|---|
| 2015 | 241.2227–252.4 | 245.8228.2–261.9 |
| 2016 | 237.9226.6–249.3 | 243.7226.1–259.4 |
| 2017 | 239.8227.5–249.4 | 247229.6–260.7 |
| 2018 | 242.6227–255 | 248.3228.8–263.3 |
| 2019 | 241.2228.5–251.9 | 248.1229.2–262.8 |
| 2020 | 242.6229.3–254.4 | 248.8229.6–262.9 |
| 2021 | 244.3230.4–254.4 | 251.1233.1–266.7 |
| 2022 | 243.8231.5–254.2 | 252.4234.3–266.8 |
| 2023 | 243.5229.2–254.5 | 253.4235.4–266.6 |
| 2024 | 245.7231.4–257.1 | 251.3236.7–264.6 |
| 2025 | 242.5229.4–253.9 | 252.4234.1–266.2 |
| 2026 | 243.9227.9–258.1 | 252.8232.9–268.5 |
| 2027 | 247.1232.8–259.3 | 253.2237–268.8 |
| 2028 | 244.2232.2–254.4 | 254.3237.7–272 |
| 2029 | 247.3232.7–261.5 | 258.1238.5–273.7 |
| 2030 | 243.9232.3–255.2 | 256.4240.9–270.1 |
| 2031 | 245.1232.9–262.3 | 255.9241.2–270.9 |
| 2032 | 247.6236.6–257.8 | 257.4239.1–269.9 |
| 2033 | 245.3231.7–256.6 | 258.3241.7–273.2 |
| 2034 | 246.3233.2–260.4 | 258.8240.7–275.8 |
| 2035 | 246.4234.1–260.9 | 258.6242.5–275.4 |
| 2036 | 246.2228.6–260.4 | 258.3239.1–273.8 |
| 2037 | 247.7235.4–260.2 | 258.7242.4–272.4 |
| 2038 | 249232.1–261 | 263.4247.6–277.3 |
| 2039 | 250234.4–262.7 | 260.2243.7–275.9 |
| 2040 | 248.9235.5–260.5 | 260.1242.8–274.8 |
| 2041 | 248.3235.6–261.9 | 263.1245.9–279 |
| 2042 | 252.5237.8–265.3 | 263.6246.5–279 |
| 2043 | 250.8234.7–263.4 | 261.4245.5–279.6 |
| 2044 | 251.8239.1–265.2 | 263.2245.2–277.6 |
| 2045 | 250.3239.1–265.6 | 265.5249.6–281.4 |
| 2046 | 252.7238.9–267.8 | 264.9246.8–278.1 |
| 2047 | 253.9239.4–267.1 | 266.9250.4–282.9 |
| 2048 | 254.4242.7–270.5 | 268250.5–283.8 |
| 2049 | 253.7241.5–266.4 | 267.8251.2–284.8 |
| 2050 | 254.6242.5–269.2 | 268251.2–283.5 |
| 2051 | 254.7242.7–270.1 | 270.9254.3–285.4 |
| 2052 | 252.3240.2–264.6 | 268.3253.3–282.8 |
| 2053 | 256.9244–272.4 | 268.5250.1–283.2 |
| 2054 | 255.9243.5–269.4 | 269.1250.8–283.6 |
| 2055 | 255.2243.8–273.6 | 270249.8–284.2 |
| 2056 | 259.1243.6–274.7 | 271.7254.8–290.1 |
| 2057 | 257.5243.8–273.7 | 270253–285.7 |
| 2058 | 257.4245.6–274.2 | 270.7252.9–286.5 |
| 2059 | 258.3246.4–271.8 | 273257.6–286.6 |
| 2060 | 259.2246.1–272.6 | 275.7255.6–290.6 |
| 2061 | 257.7244.8–270.1 | 273.5254.6–289.5 |
| 2062 | 260.4246.4–274.2 | 271.4253.1–290.2 |
| 2063 | 259.9241.3–272.7 | 272.9252.7–288.1 |
| 2064 | 260.2245.9–273.1 | 273.8254.4–288.1 |
| 2065 | 259.8244.1–274.7 | 272255.8–286.3 |
| 2066 | 260246.6–274.6 | 271.8254.4–287.3 |
| 2067 | 261.4246.4–272.3 | 270.8252.1–287.6 |
| 2068 | 260.1245.8–274.8 | 275.6256.9–292.4 |
| 2069 | 263.3249.8–276.6 | 276.4258.5–292 |
| 2070 | 259.6245.8–272.6 | 274.6257.8–292.8 |
| 2071 | 262.2248.7–283.4 | 276.2255.2–294.1 |
| 2072 | 259.8248.6–276 | 277256.8–291.4 |
| 2073 | 264.1246.6–277.2 | 278.5262.7–293.4 |
| 2074 | 262.6248.3–276.6 | 277.6259.2–295.8 |
| 2075 | 263.6248.5–277.7 | 276.4258.7–294.4 |
| 2076 | 261.6251–276.9 | 279.2258.5–296.6 |
| 2077 | 264251.1–279.8 | 280264.9–294.7 |
| 2078 | 265251.6–281.6 | 278.4258.6–295.5 |
| 2079 | 263.8248.5–277.2 | 279.3263.4–293.6 |
| 2080 | 266.8251.9–280.3 | 280261.4–296.5 |
| 2081 | 266.5250.7–279.9 | 280.4261.2–297.9 |
| 2082 | 264249.6–277.3 | 280.9258.9–296 |
| 2083 | 266.6251.8–282.8 | 278.4261.6–295 |
| 2084 | 264.8253.1–284.2 | 279257.4–293.8 |
| 2085 | 265.4251.2–283.4 | 281.3265–297.8 |
| 2086 | 268.2252.8–285.3 | 282.3260.2–297.5 |
| 2087 | 265.7251.3–280.8 | 281.9261.3–300.7 |
| 2088 | 267.2252.6–284.4 | 283.1265.7–301.5 |
| 2089 | 267.1252.5–286.7 | 280.8261.2–301.6 |
| 2090 | 267.9254.9–283.4 | 280.5264.5–297.6 |
| 2091 | 267.7254.5–282.2 | 283.3264.3–298.9 |
| 2092 | 268.8253.6–281.7 | 281.1261.5–299.4 |
| 2093 | 268.1251.7–287 | 280.5263.4–296.1 |
| 2094 | 267.4251.3–287.4 | 283264.5–300 |
| 2095 | 270.8253.7–284.9 | 285.5264.5–302.9 |
| 2096 | 267.9250.5–285.8 | 281.8264.8–299.8 |
| 2097 | 269.3254.9–287.3 | 281.5263.3–299 |
| 2098 | 268.8252.4–284.9 | 282.5263.9–301.5 |
| 2099 | 269253–282.3 | 282.7265.1–298 |
| 2100 | 269.8254.8–284.9 | 282.7261–298.2 |
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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
孟加拉国与越南对比
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人口与社会
经济
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冲突
军用
- 军费开支孟加拉国:2025 年为 GDP 的 0.81%越南:2025 年为 GDP 的 2.15%
- 军费开支(美元)孟加拉国:2025 年为 US$36.7亿越南:2025 年为 US$109亿
- 人均军费开支孟加拉国:2025 年为 US$22越南:2025 年为 US$104
- 军费占政府支出比例孟加拉国:2025 年为 7.1%(占政府支出)越南:2025 年为 9.9%(占政府支出)
- 武装部队人员孟加拉国:2020 年为 227,000 人越南:2020 年为 522,000 人
- 国家实力孟加拉国:2022 年为 1.01%(占全球实力)越南:2022 年为 1.11%(占全球实力)
- 武装部队占劳动力比例孟加拉国:2020 年为 0.32%(占劳动力)越南:2020 年为 0.95%(占劳动力)
- 武器进口孟加拉国:2025 年为 3200万 TIV越南:2025 年为 1.77亿 TIV
- 武器出口孟加拉国:1984 年为 200万 TIV越南:2018 年为 1000万 TIV