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
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 |
|---|---|---|
| 2014 | 239.9 | 201.9 |
| 2013 | 239 | 203.1 |
| 2012 | 240.4 | 201.1 |
| 2011 | 240.5 | 200.9 |
| 2010 | 241 | 202.1 |
| 2009 | 238.6 | 199 |
| 2008 | 236.7 | 198.1 |
| 2007 | 236.9 | 196.8 |
| 2006 | 238.9 | 198.2 |
| 2005 | 238.2 | 196.7 |
| 2004 | 238.7 | 200.3 |
| 2003 | 236.5 | 195.3 |
| 2002 | 237.6 | 196.6 |
| 2001 | 237.2 | 199 |
| 2000 | 239.3 | 197.2 |
| 1999 | 236.6 | 196.4 |
| 1998 | 235.5 | 194.7 |
| 1997 | 235.5 | 194.4 |
| 1996 | 235.5 | 191.4 |
| 1995 | 234.8 | 189.9 |
| 1994 | 233.6 | 188.8 |
| 1993 | 232.2 | 185 |
| 1992 | 228 | 180.5 |
| 1991 | 233.4 | 191.7 |
| 1990 | 234.6 | 191.5 |
| 1989 | 235.7 | 190.3 |
| 1988 | 235.1 | 190.7 |
| 1987 | 236.4 | 190.8 |
| 1986 | 233.8 | 189.7 |
| 1985 | 233.6 | 187.4 |
| 1984 | 236 | 189.1 |
| 1983 | 230 | 182.3 |
| 1982 | 232.3 | 186.7 |
| 1981 | 235.9 | 188.4 |
| 1980 | 233.4 | 189 |
| 1979 | 234.5 | 189.8 |
| 1978 | 231.8 | 186.8 |
| 1977 | 232.3 | 187.4 |
| 1976 | 232 | 185.8 |
| 1975 | 231.3 | 183.6 |
| 1974 | 232.9 | 185.5 |
| 1973 | 232.1 | 187.5 |
| 1972 | 234.3 | 184.8 |
| 1971 | 233.1 | 185.2 |
| 1970 | 232.5 | 184.9 |
| 1969 | 231.1 | 184.3 |
| 1968 | 229.7 | 183.7 |
| 1967 | 231.6 | 182.3 |
| 1966 | 232.6 | 186.2 |
| 1965 | 232.5 | 182.9 |
| 1964 | 229.3 | 180.6 |
| 1963 | 233.8 | 183.1 |
| 1962 | 231.9 | 187.3 |
| 1961 | 236.2 | 188.7 |
| 1960 | 232.5 | 187.1 |
| 1959 | 234.7 | 186.5 |
| 1958 | 233.5 | 187.1 |
| 1957 | 232.5 | 186.2 |
| 1956 | 234.3 | 187.9 |
| 1955 | 230.2 | 185.9 |
| 1954 | 232.9 | 185.7 |
| 1953 | 234 | 185 |
| 1952 | 230.3 | 186.1 |
| 1951 | 233.5 | 187.1 |
| 1950 | 233.9 | 186.9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 孟加拉国 | 缅甸 |
|---|---|---|
| 2015 | 241.2227–252.4 | 205.2186.4–218.9 |
| 2016 | 237.9226.6–249.3 | 202.8186.2–218.8 |
| 2017 | 239.8227.5–249.4 | 203.4187.3–218.3 |
| 2018 | 242.6227–255 | 205.5190.9–219.9 |
| 2019 | 241.2228.5–251.9 | 205.2186.7–222.2 |
| 2020 | 242.6229.3–254.4 | 208.2188.5–223.5 |
| 2021 | 244.3230.4–254.4 | 208.9191.2–224.1 |
| 2022 | 243.8231.5–254.2 | 209.9192.7–224.9 |
| 2023 | 243.5229.2–254.5 | 210.6195.4–226.3 |
| 2024 | 245.7231.4–257.1 | 210.4193.8–226.6 |
| 2025 | 242.5229.4–253.9 | 209.9190.3–225.2 |
| 2026 | 243.9227.9–258.1 | 212.2194.3–229.2 |
| 2027 | 247.1232.8–259.3 | 212195.6–228.6 |
| 2028 | 244.2232.2–254.4 | 213195.7–227.2 |
| 2029 | 247.3232.7–261.5 | 215.3193.9–231.9 |
| 2030 | 243.9232.3–255.2 | 212.2194.9–228 |
| 2031 | 245.1232.9–262.3 | 214.3197.2–230.8 |
| 2032 | 247.6236.6–257.8 | 215199.3–229.6 |
| 2033 | 245.3231.7–256.6 | 215.5198.5–230.1 |
| 2034 | 246.3233.2–260.4 | 214.9198.4–233.5 |
| 2035 | 246.4234.1–260.9 | 214.9199.2–236.8 |
| 2036 | 246.2228.6–260.4 | 216198.7–234.5 |
| 2037 | 247.7235.4–260.2 | 217.2199.6–233.5 |
| 2038 | 249232.1–261 | 220.7204.8–235.1 |
| 2039 | 250234.4–262.7 | 219.7202.4–234.3 |
| 2040 | 248.9235.5–260.5 | 219.2202.9–235 |
| 2041 | 248.3235.6–261.9 | 220.7203.9–237.7 |
| 2042 | 252.5237.8–265.3 | 221.8206.1–237.2 |
| 2043 | 250.8234.7–263.4 | 219.5201.2–237.1 |
| 2044 | 251.8239.1–265.2 | 221.4201.6–239.6 |
| 2045 | 250.3239.1–265.6 | 223.7204.8–241.5 |
| 2046 | 252.7238.9–267.8 | 223.2203.2–240.2 |
| 2047 | 253.9239.4–267.1 | 224.3204.8–241.1 |
| 2048 | 254.4242.7–270.5 | 226.4207.7–243.8 |
| 2049 | 253.7241.5–266.4 | 226.5205.6–242.8 |
| 2050 | 254.6242.5–269.2 | 227209.3–243.5 |
| 2051 | 254.7242.7–270.1 | 229.6212.4–246.4 |
| 2052 | 252.3240.2–264.6 | 227.2208.6–244.2 |
| 2053 | 256.9244–272.4 | 227.9208.7–247.7 |
| 2054 | 255.9243.5–269.4 | 227.9209.6–244.8 |
| 2055 | 255.2243.8–273.6 | 229.1209.8–247.5 |
| 2056 | 259.1243.6–274.7 | 231.8210.4–252.1 |
| 2057 | 257.5243.8–273.7 | 228.6208–249 |
| 2058 | 257.4245.6–274.2 | 228.9208.8–249 |
| 2059 | 258.3246.4–271.8 | 230.7212.1–247.5 |
| 2060 | 259.2246.1–272.6 | 234.7211.1–251.5 |
| 2061 | 257.7244.8–270.1 | 231.9213–247.7 |
| 2062 | 260.4246.4–274.2 | 233.6209.9–252.8 |
| 2063 | 259.9241.3–272.7 | 233215.4–250.5 |
| 2064 | 260.2245.9–273.1 | 233.2214.4–251.3 |
| 2065 | 259.8244.1–274.7 | 230.7210.4–250.7 |
| 2066 | 260246.6–274.6 | 233.5214.3–251.2 |
| 2067 | 261.4246.4–272.3 | 233211.5–253.3 |
| 2068 | 260.1245.8–274.8 | 233.1212.4–253.7 |
| 2069 | 263.3249.8–276.6 | 236.1214.6–253.4 |
| 2070 | 259.6245.8–272.6 | 235.9218.1–253.4 |
| 2071 | 262.2248.7–283.4 | 235.1213.5–259.6 |
| 2072 | 259.8248.6–276 | 234.6216.1–252.6 |
| 2073 | 264.1246.6–277.2 | 237.2219.3–257.2 |
| 2074 | 262.6248.3–276.6 | 236.4215.7–254.5 |
| 2075 | 263.6248.5–277.7 | 236.7214.4–255.9 |
| 2076 | 261.6251–276.9 | 237.7216–257 |
| 2077 | 264251.1–279.8 | 237.5219–258.7 |
| 2078 | 265251.6–281.6 | 238.5217.3–257.8 |
| 2079 | 263.8248.5–277.2 | 238.5219.2–257.2 |
| 2080 | 266.8251.9–280.3 | 240.5218.8–258.3 |
| 2081 | 266.5250.7–279.9 | 240219.7–260.9 |
| 2082 | 264249.6–277.3 | 239.4217.1–258.8 |
| 2083 | 266.6251.8–282.8 | 239.1220.5–259.2 |
| 2084 | 264.8253.1–284.2 | 241.3218.9–260.6 |
| 2085 | 265.4251.2–283.4 | 241.7218.8–260.7 |
| 2086 | 268.2252.8–285.3 | 241.7217.4–262.7 |
| 2087 | 265.7251.3–280.8 | 241.4220.5–260.9 |
| 2088 | 267.2252.6–284.4 | 241.8222.3–261.5 |
| 2089 | 267.1252.5–286.7 | 240.7221.2–262.6 |
| 2090 | 267.9254.9–283.4 | 241.3224.4–260.9 |
| 2091 | 267.7254.5–282.2 | 242.6220.3–262.5 |
| 2092 | 268.8253.6–281.7 | 241.9221.6–263.3 |
| 2093 | 268.1251.7–287 | 242.1220.2–260 |
| 2094 | 267.4251.3–287.4 | 242.5222.5–261.9 |
| 2095 | 270.8253.7–284.9 | 244.9224–264.4 |
| 2096 | 267.9250.5–285.8 | 243.9221.1–266.5 |
| 2097 | 269.3254.9–287.3 | 243.6219.6–264.2 |
| 2098 | 268.8252.4–284.9 | 243.6222.5–263.9 |
| 2099 | 269253–282.3 | 244.7221.8–263.5 |
| 2100 | 269.8254.8–284.9 | 244.5223.2–261.8 |
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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
孟加拉国与缅甸对比
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军用
- 军费开支孟加拉国:2025 年为 GDP 的 0.81%缅甸:2024 年为 GDP 的 6.61%
- 军费开支(美元)孟加拉国:2025 年为 US$36.7亿缅甸:2024 年为 US$46.5亿
- 人均军费开支孟加拉国:2025 年为 US$22缅甸:2024 年为 US$92
- 军费占政府支出比例孟加拉国:2025 年为 7.1%(占政府支出)缅甸:2024 年为 32%(占政府支出)
- 武装部队人员孟加拉国:2020 年为 227,000 人缅甸:2020 年为 463,000 人
- 国家实力孟加拉国:2022 年为 1.01%(占全球实力)缅甸:2022 年为 0.53%(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)缅甸:2020 年为 1.94%(占劳动力)
- 武器进口孟加拉国:2025 年为 3200万 TIV缅甸:2025 年为 7000万 TIV