阿根廷与孟加拉国对比
阿根廷与孟加拉国:35 °C 以上天数
2014 年35 °C 以上天数:阿根廷为 13.5 天,孟加拉国为 19.4 天(CMIP6 气候模型中位数模拟)。 2014 年孟加拉国的数值较高,高出 5.9 天,是阿根廷的 1.44 倍。
每年天数 · CMIP6
数据解读
- 自 1993 年超过阿根廷以来,孟加拉国的数值一直更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年阿根廷为 27.2 天,孟加拉国为 56.8 天。
逐年数据
每年天数 · CMIP6
| 年份 | 阿根廷 | 孟加拉国 |
|---|---|---|
| 2014 | 13.5 | 19.4 |
| 2013 | 13.2 | 14.1 |
| 2012 | 14.1 | 17 |
| 2011 | 13.3 | 13.4 |
| 2010 | 13.1 | 16.9 |
| 2009 | 12.6 | 14.4 |
| 2008 | 12.4 | 14 |
| 2007 | 11.7 | 14.3 |
| 2006 | 11.3 | 17.8 |
| 2005 | 11.5 | 16.1 |
| 2004 | 12 | 14.7 |
| 2003 | 11.2 | 15.9 |
| 2002 | 12.7 | 17.7 |
| 2001 | 12.7 | 16.9 |
| 2000 | 10.9 | 16.6 |
| 1999 | 11 | 15.6 |
| 1998 | 11.3 | 15.4 |
| 1997 | 12.8 | 16.8 |
| 1996 | 11.6 | 14.2 |
| 1995 | 9.6 | 13.2 |
| 1994 | 9.2 | 15.2 |
| 1993 | 9.1 | 12.4 |
| 1992 | 9 | 8 |
| 1991 | 9.6 | 18.8 |
| 1990 | 8.8 | 18.5 |
| 1989 | 10.9 | 13.7 |
| 1988 | 10.5 | 13.5 |
| 1987 | 10.5 | 17.9 |
| 1986 | 10.4 | 17.9 |
| 1985 | 10.7 | 14.4 |
| 1984 | 9.6 | 19 |
| 1983 | 9.6 | 14.6 |
| 1982 | 9.5 | 16.3 |
| 1981 | 10.9 | 15.4 |
| 1980 | 10.8 | 14.5 |
| 1979 | 11.2 | 16.7 |
| 1978 | 10.6 | 15 |
| 1977 | 9.7 | 14.1 |
| 1976 | 10.4 | 17.5 |
| 1975 | 9.5 | 14.4 |
| 1974 | 10.5 | 17.3 |
| 1973 | 9 | 17 |
| 1972 | 9.7 | 15.7 |
| 1971 | 9.2 | 16.9 |
| 1970 | 9.9 | 16.5 |
| 1969 | 9.4 | 15.5 |
| 1968 | 9 | 16.2 |
| 1967 | 8.6 | 13.5 |
| 1966 | 9.9 | 15.6 |
| 1965 | 8.9 | 15.4 |
| 1964 | 7.1 | 14.7 |
| 1963 | 8.8 | 16.1 |
| 1962 | 11 | 19.1 |
| 1961 | 10.2 | 18 |
| 1960 | 11.1 | 19.2 |
| 1959 | 10.5 | 18 |
| 1958 | 9.6 | 17.5 |
| 1957 | 10.7 | 18.1 |
| 1956 | 10.6 | 19.2 |
| 1955 | 9.8 | 16.9 |
| 1954 | 9.6 | 19.4 |
| 1953 | 10.9 | 21 |
| 1952 | 10.7 | 17.2 |
| 1951 | 10.5 | 19.9 |
| 1950 | 9.4 | 22.3 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 阿根廷 | 孟加拉国 |
|---|---|---|
| 2015 | 14.78.1–22.2 | 17.85.5–30.2 |
| 2016 | 13.66.8–22 | 17.53.9–31.5 |
| 2017 | 14.26.9–22.4 | 14.14.8–29 |
| 2018 | 13.35.6–21.6 | 13.92–31 |
| 2019 | 14.56.9–23 | 14.93.9–28 |
| 2020 | 15.88.4–24.8 | 14.94.1–36.3 |
| 2021 | 15.38–24.6 | 17.25.6–33 |
| 2022 | 13.36.7–22.2 | 17.21.4–36.6 |
| 2023 | 14.99.3–22.1 | 18.16.6–32.2 |
| 2024 | 15.87.6–24 | 21.24.9–36.6 |
| 2025 | 16.410.2–23.4 | 16.73.9–36.8 |
| 2026 | 189.4–26.5 | 18.36.7–34 |
| 2027 | 16.49.1–26.2 | 18.33.5–38.2 |
| 2028 | 15.67.6–26.5 | 18.64.2–33.2 |
| 2029 | 15.97.3–26.3 | 18.22.2–34.9 |
| 2030 | 16.39.8–27.4 | 174.6–31.3 |
| 2031 | 15.88.1–24.9 | 153.9–32.1 |
| 2032 | 15.78.9–25.4 | 19.33.2–34.3 |
| 2033 | 16.18.4–25.7 | 17.53.9–32 |
| 2034 | 16.110.4–24.9 | 16.24–29.3 |
| 2035 | 16.810.2–27.5 | 16.26.6–31.6 |
| 2036 | 18.310.9–27.9 | 17.76.3–36.6 |
| 2037 | 18.310.2–27.3 | 20.65.7–39.1 |
| 2038 | 16.89.1–24.7 | 21.96.6–38.5 |
| 2039 | 17.39–25.8 | 21.45.1–43.2 |
| 2040 | 18.311.3–28.3 | 22.86–48.8 |
| 2041 | 19.310.7–29.3 | 19.44.7–44.5 |
| 2042 | 189.9–27.1 | 22.86.3–50.6 |
| 2043 | 189.5–27.5 | 25.17.2–47 |
| 2044 | 19.49.7–30.2 | 24.77.9–45 |
| 2045 | 20.511.8–30.1 | 24.110–42.5 |
| 2046 | 19.612–28.2 | 28.57.8–55.7 |
| 2047 | 19.78.9–31.3 | 26.47.4–50.6 |
| 2048 | 19.610.8–28.6 | 30.28–52.9 |
| 2049 | 20.411.6–30.7 | 29.511.3–54.1 |
| 2050 | 19.910.4–28.4 | 26.810.4–47.8 |
| 2051 | 20.511.5–30.8 | 32.713.4–54.3 |
| 2052 | 21.610.9–33.4 | 29.313–59.8 |
| 2053 | 20.411.3–30.2 | 26.79.4–54.9 |
| 2054 | 19.712–31.9 | 29.910.9–57.7 |
| 2055 | 21.310.1–34.1 | 34.613.5–60.8 |
| 2056 | 20.510.5–32.4 | 34.215.2–59 |
| 2057 | 21.711.5–34.7 | 3912.3–72.8 |
| 2058 | 21.312.4–33.2 | 38.917–69.9 |
| 2059 | 21.612.4–32.7 | 35.914.6–66 |
| 2060 | 2211.2–33.3 | 36.818.6–65.3 |
| 2061 | 2310.8–34.9 | 38.919.6–65.9 |
| 2062 | 2212.1–32.7 | 35.115.8–63.8 |
| 2063 | 24.114–33.8 | 42.114.5–66.9 |
| 2064 | 24.115.3–39.2 | 37.317–62.7 |
| 2065 | 23.712.7–34.9 | 35.618.5–60.2 |
| 2066 | 24.715.7–35.1 | 35.812.3–64.7 |
| 2067 | 24.912.6–37 | 32.612.9–61.8 |
| 2068 | 23.712.3–36.3 | 40.717.5–76.4 |
| 2069 | 2514–35.5 | 43.915.7–73.3 |
| 2070 | 24.413.3–37.1 | 33.714.7–63 |
| 2071 | 23.913.1–36.8 | 42.817.7–73.9 |
| 2072 | 23.814.5–38.9 | 42.718.2–68.1 |
| 2073 | 25.314.6–39.1 | 44.423.8–82.3 |
| 2074 | 24.511.6–36.9 | 4214.1–71.6 |
| 2075 | 25.312.9–38.6 | 41.515.2–70.1 |
| 2076 | 23.713.4–36.3 | 39.914.1–81.2 |
| 2077 | 24.615.3–36.4 | 42.723.6–83.6 |
| 2078 | 26.213.8–39.4 | 44.424.7–79.2 |
| 2079 | 23.913.4–36.8 | 43.923.1–74.7 |
| 2080 | 25.413.8–40.8 | 52.224.5–83 |
| 2081 | 2514.2–38 | 50.628.6–83 |
| 2082 | 2413.3–36.3 | 49.322.9–92.1 |
| 2083 | 25.415–39.2 | 49.218.9–88.7 |
| 2084 | 22.512.1–36 | 50.421.6–92.6 |
| 2085 | 23.412.2–36.2 | 49.920.5–104.5 |
| 2086 | 25.214–39.1 | 50.922.5–100.6 |
| 2087 | 2614.4–37.2 | 53.125–82.1 |
| 2088 | 26.214.9–40.2 | 46.314.7–108.4 |
| 2089 | 27.315.3–38.2 | 52.722.8–107.6 |
| 2090 | 27.115.8–41.5 | 55.216.3–89.2 |
| 2091 | 28.315.4–42.5 | 51.331.2–98 |
| 2092 | 29.316–42 | 55.422.1–101.2 |
| 2093 | 2615.1–44.6 | 47.718.8–94.6 |
| 2094 | 27.714.9–41 | 51.225.3–87.3 |
| 2095 | 26.713.8–43.1 | 57.624.4–95.1 |
| 2096 | 27.114.5–42.2 | 50.820–91.8 |
| 2097 | 2715.3–41.1 | 48.923.7–96 |
| 2098 | 26.715.9–42.2 | 52.926.4–94.7 |
| 2099 | 27.615.3–41 | 48.722.9–82 |
| 2100 | 27.214.1–45.4 | 56.822.9–95.8 |
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须知
- 一年中最高气温超过 35 °C 的天数,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
阿根廷与孟加拉国对比
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军用
- 军费开支阿根廷:2025 年为 GDP 的 0.56%孟加拉国:2025 年为 GDP 的 0.81%
- 军费开支(美元)阿根廷:2025 年为 US$37.3亿孟加拉国:2025 年为 US$36.7亿
- 人均军费开支阿根廷:2025 年为 US$85孟加拉国:2025 年为 US$22
- 军费占政府支出比例阿根廷:2025 年为 1.8%(占政府支出)孟加拉国:2025 年为 7.1%(占政府支出)
- 武装部队人员阿根廷:2020 年为 103,000 人孟加拉国:2020 年为 227,000 人
- 国家实力阿根廷:2022 年为 0.45%(占全球实力)孟加拉国:2022 年为 1.01%(占全球实力)
- 武装部队占劳动力比例阿根廷:2020 年为 0.53%(占劳动力)孟加拉国:2020 年为 0.32%(占劳动力)
- 武器进口阿根廷:2025 年为 1.08亿 TIV孟加拉国:2025 年为 3200万 TIV
- 武器出口阿根廷:2011 年为 100万 TIV孟加拉国:1984 年为 200万 TIV