巴西与越南对比
巴西与越南:热带夜
2014 年热带夜:巴西为 282 夜,越南为 242.6 夜(CMIP6 气候模型中位数模拟)。 2014 年巴西的数值较高,高出 39.4 夜,是越南的 1.16 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,巴西的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年巴西为 317.3 夜,越南为 282.7 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 巴西 | 越南 |
|---|---|---|
| 2014 | 282 | 242.6 |
| 2013 | 282.5 | 243.6 |
| 2012 | 283.6 | 242.4 |
| 2011 | 281.8 | 241.9 |
| 2010 | 280.2 | 240.9 |
| 2009 | 279.2 | 240 |
| 2008 | 277.8 | 238.7 |
| 2007 | 275.9 | 238 |
| 2006 | 275.4 | 239.1 |
| 2005 | 275.8 | 238.3 |
| 2004 | 278.5 | 241.8 |
| 2003 | 276.7 | 235.9 |
| 2002 | 276.2 | 236.3 |
| 2001 | 277.7 | 241.3 |
| 2000 | 273.3 | 237 |
| 1999 | 271 | 236 |
| 1998 | 273.6 | 236.8 |
| 1997 | 270.9 | 237.1 |
| 1996 | 264.7 | 231.4 |
| 1995 | 263.8 | 229.9 |
| 1994 | 263.6 | 231.2 |
| 1993 | 258.3 | 225.3 |
| 1992 | 252.8 | 221.9 |
| 1991 | 269.7 | 229.8 |
| 1990 | 272.5 | 233.1 |
| 1989 | 267.1 | 229.2 |
| 1988 | 264.7 | 231.7 |
| 1987 | 265.9 | 230.3 |
| 1986 | 265.7 | 230.9 |
| 1985 | 260.6 | 228 |
| 1984 | 261.1 | 230.2 |
| 1983 | 255.9 | 224.9 |
| 1982 | 264.8 | 227.5 |
| 1981 | 265.3 | 229.7 |
| 1980 | 262 | 228.1 |
| 1979 | 261.2 | 228.9 |
| 1978 | 259.7 | 227.5 |
| 1977 | 261.8 | 229 |
| 1976 | 258.4 | 225.8 |
| 1975 | 252.4 | 225.8 |
| 1974 | 258.7 | 225.7 |
| 1973 | 261 | 230.3 |
| 1972 | 258.1 | 225.6 |
| 1971 | 256.5 | 225.5 |
| 1970 | 254.5 | 226.1 |
| 1969 | 255.1 | 227 |
| 1968 | 254.9 | 227.1 |
| 1967 | 250.3 | 222.9 |
| 1966 | 254.5 | 226.8 |
| 1965 | 250.8 | 225.4 |
| 1964 | 246.2 | 222.6 |
| 1963 | 241.9 | 224.3 |
| 1962 | 257.9 | 227.8 |
| 1961 | 258.2 | 229.4 |
| 1960 | 260.3 | 228.5 |
| 1959 | 255.7 | 226.2 |
| 1958 | 258.1 | 230.9 |
| 1957 | 256.6 | 228.4 |
| 1956 | 251.2 | 228.7 |
| 1955 | 257.2 | 227.5 |
| 1954 | 258 | 226.3 |
| 1953 | 255.2 | 228.2 |
| 1952 | 255.8 | 228.5 |
| 1951 | 256.3 | 229.2 |
| 1950 | 254.4 | 228.9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 巴西 | 越南 |
|---|---|---|
| 2015 | 284257.6–299.5 | 245.8228.2–261.9 |
| 2016 | 281.5261.4–296.3 | 243.7226.1–259.4 |
| 2017 | 284.1263.2–297.8 | 247229.6–260.7 |
| 2018 | 283.4263.1–298.8 | 248.3228.8–263.3 |
| 2019 | 283.7262.9–302.4 | 248.1229.2–262.8 |
| 2020 | 286.3264.2–303.6 | 248.8229.6–262.9 |
| 2021 | 287.9266.9–302.3 | 251.1233.1–266.7 |
| 2022 | 289.6270.7–303.9 | 252.4234.3–266.8 |
| 2023 | 287.3270.5–303 | 253.4235.4–266.6 |
| 2024 | 291.5268.2–304.6 | 251.3236.7–264.6 |
| 2025 | 289.6269.1–304.8 | 252.4234.1–266.2 |
| 2026 | 289.7266.2–305.1 | 252.8232.9–268.5 |
| 2027 | 289.5269.1–303.7 | 253.2237–268.8 |
| 2028 | 291.2271.9–306 | 254.3237.7–272 |
| 2029 | 295.5276.3–309.6 | 258.1238.5–273.7 |
| 2030 | 292.2269.1–306.9 | 256.4240.9–270.1 |
| 2031 | 295.3274–308.9 | 255.9241.2–270.9 |
| 2032 | 296.8280.1–310.9 | 257.4239.1–269.9 |
| 2033 | 295.4273.3–308.5 | 258.3241.7–273.2 |
| 2034 | 294.3273.5–311.8 | 258.8240.7–275.8 |
| 2035 | 295.2274.4–310.9 | 258.6242.5–275.4 |
| 2036 | 295.1278.2–307.8 | 258.3239.1–273.8 |
| 2037 | 299.9283.7–311.3 | 258.7242.4–272.4 |
| 2038 | 299.6283.5–312.1 | 263.4247.6–277.3 |
| 2039 | 296.9279.9–311 | 260.2243.7–275.9 |
| 2040 | 298.5279.4–311.9 | 260.1242.8–274.8 |
| 2041 | 301.4282.2–314.1 | 263.1245.9–279 |
| 2042 | 300.6277.8–314.7 | 263.6246.5–279 |
| 2043 | 298.2279.8–312.7 | 261.4245.5–279.6 |
| 2044 | 300.3281.2–315.6 | 263.2245.2–277.6 |
| 2045 | 299.9279.7–313.1 | 265.5249.6–281.4 |
| 2046 | 302.8285.8–316.6 | 264.9246.8–278.1 |
| 2047 | 303.3285–316.4 | 266.9250.4–282.9 |
| 2048 | 304.4287.3–317.3 | 268250.5–283.8 |
| 2049 | 305.4288.4–318.5 | 267.8251.2–284.8 |
| 2050 | 303.9283.9–316.2 | 268251.2–283.5 |
| 2051 | 305.7287.5–317.5 | 270.9254.3–285.4 |
| 2052 | 305.9290.6–318.8 | 268.3253.3–282.8 |
| 2053 | 305.3285.9–317.5 | 268.5250.1–283.2 |
| 2054 | 306.1288.4–319.3 | 269.1250.8–283.6 |
| 2055 | 306.4290.8–319.8 | 270249.8–284.2 |
| 2056 | 306.7288.3–321.1 | 271.7254.8–290.1 |
| 2057 | 306.4287.6–321.1 | 270253–285.7 |
| 2058 | 309291–321.4 | 270.7252.9–286.5 |
| 2059 | 310.4290.7–322.8 | 273257.6–286.6 |
| 2060 | 311.6294.4–325.1 | 275.7255.6–290.6 |
| 2061 | 307.5290.3–321.2 | 273.5254.6–289.5 |
| 2062 | 309291.5–322.8 | 271.4253.1–290.2 |
| 2063 | 310.8290.6–322.8 | 272.9252.7–288.1 |
| 2064 | 309.6290.2–321.1 | 273.8254.4–288.1 |
| 2065 | 311.1291.6–323.1 | 272255.8–286.3 |
| 2066 | 312.2294.2–324.2 | 271.8254.4–287.3 |
| 2067 | 310.9291.5–323.3 | 270.8252.1–287.6 |
| 2068 | 311.5293–324.5 | 275.6256.9–292.4 |
| 2069 | 310.6292.2–323.6 | 276.4258.5–292 |
| 2070 | 312.7293–325.3 | 274.6257.8–292.8 |
| 2071 | 311.5292.1–323.9 | 276.2255.2–294.1 |
| 2072 | 313.3297.8–325.5 | 277256.8–291.4 |
| 2073 | 313.8298.6–327.2 | 278.5262.7–293.4 |
| 2074 | 311.4292.4–323.5 | 277.6259.2–295.8 |
| 2075 | 310.9291.5–324.5 | 276.4258.7–294.4 |
| 2076 | 314.2294.4–327.7 | 279.2258.5–296.6 |
| 2077 | 315.1295.6–326.8 | 280264.9–294.7 |
| 2078 | 314.9296.3–327.1 | 278.4258.6–295.5 |
| 2079 | 313292.8–326.8 | 279.3263.4–293.6 |
| 2080 | 311.9294.7–325.4 | 280261.4–296.5 |
| 2081 | 313.5295.5–325.6 | 280.4261.2–297.9 |
| 2082 | 315296.8–327.1 | 280.9258.9–296 |
| 2083 | 315.7295.3–328.7 | 278.4261.6–295 |
| 2084 | 316.6298.5–327.9 | 279257.4–293.8 |
| 2085 | 317.4299.3–329.8 | 281.3265–297.8 |
| 2086 | 315.8294–328 | 282.3260.2–297.5 |
| 2087 | 316.5297.9–328.5 | 281.9261.3–300.7 |
| 2088 | 315.6297.3–328.8 | 283.1265.7–301.5 |
| 2089 | 315296.6–327.9 | 280.8261.2–301.6 |
| 2090 | 316298.9–330.3 | 280.5264.5–297.6 |
| 2091 | 317298.1–330.6 | 283.3264.3–298.9 |
| 2092 | 317.6298.7–330.7 | 281.1261.5–299.4 |
| 2093 | 316.3297.5–328.6 | 280.5263.4–296.1 |
| 2094 | 316.4300.2–327.5 | 283264.5–300 |
| 2095 | 319299.8–330.7 | 285.5264.5–302.9 |
| 2096 | 317.7299.5–330.8 | 281.8264.8–299.8 |
| 2097 | 316.9297.8–329 | 281.5263.3–299 |
| 2098 | 318.6299.9–331.9 | 282.5263.9–301.5 |
| 2099 | 318.1300–330.2 | 282.7265.1–298 |
| 2100 | 317.3298.4–330.3 | 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
巴西与越南对比
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冲突
军用
- 军费开支巴西:2025 年为 GDP 的 1.05%越南:2025 年为 GDP 的 2.15%
- 军费开支(美元)巴西:2025 年为 US$236亿越南:2025 年为 US$109亿
- 人均军费开支巴西:2025 年为 US$113越南:2025 年为 US$104
- 军费占政府支出比例巴西:2025 年为 2.2%(占政府支出)越南:2025 年为 9.9%(占政府支出)
- 武装部队人员巴西:2020 年为 762,000 人越南:2020 年为 522,000 人
- 国家实力巴西:2022 年为 2.01%(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巴西:2020 年为 0.76%(占劳动力)越南:2020 年为 0.95%(占劳动力)
- 武器进口巴西:2025 年为 4.62亿 TIV越南:2025 年为 1.77亿 TIV
- 武器出口巴西:2025 年为 1.53亿 TIV越南:2018 年为 1000万 TIV