阿根廷与危地马拉对比
阿根廷与危地马拉:35 °C 以上天数
2014 年35 °C 以上天数:阿根廷为 13.5 天,危地马拉为 16.9 天(CMIP6 气候模型中位数模拟)。 2014 年危地马拉的数值较高,高出 3.5 天,是阿根廷的 1.26 倍。
每年天数 · CMIP6
数据解读
- 自 1999 年超过阿根廷以来,危地马拉的数值一直更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年阿根廷为 27.2 天,危地马拉为 47.9 天。
逐年数据
每年天数 · CMIP6
| 年份 | 阿根廷 | 危地马拉 |
|---|---|---|
| 2014 | 13.5 | 16.9 |
| 2013 | 13.2 | 15.5 |
| 2012 | 14.1 | 15.4 |
| 2011 | 13.3 | 14.9 |
| 2010 | 13.1 | 17.5 |
| 2009 | 12.6 | 13.6 |
| 2008 | 12.4 | 14.5 |
| 2007 | 11.7 | 15.2 |
| 2006 | 11.3 | 14.5 |
| 2005 | 11.5 | 14.1 |
| 2004 | 12 | 13.7 |
| 2003 | 11.2 | 13.4 |
| 2002 | 12.7 | 13.5 |
| 2001 | 12.7 | 14.5 |
| 2000 | 10.9 | 12.9 |
| 1999 | 11 | 12.6 |
| 1998 | 11.3 | 11 |
| 1997 | 12.8 | 11.9 |
| 1996 | 11.6 | 10.7 |
| 1995 | 9.6 | 9 |
| 1994 | 9.2 | 10.3 |
| 1993 | 9.1 | 11 |
| 1992 | 9 | 8.9 |
| 1991 | 9.6 | 12.5 |
| 1990 | 8.8 | 13.4 |
| 1989 | 10.9 | 10.6 |
| 1988 | 10.5 | 10.1 |
| 1987 | 10.5 | 10 |
| 1986 | 10.4 | 12.2 |
| 1985 | 10.7 | 8.2 |
| 1984 | 9.6 | 7.4 |
| 1983 | 9.6 | 9 |
| 1982 | 9.5 | 11.1 |
| 1981 | 10.9 | 12 |
| 1980 | 10.8 | 8.5 |
| 1979 | 11.2 | 10.9 |
| 1978 | 10.6 | 8.5 |
| 1977 | 9.7 | 11 |
| 1976 | 10.4 | 10.3 |
| 1975 | 9.5 | 9 |
| 1974 | 10.5 | 10.5 |
| 1973 | 9 | 8.8 |
| 1972 | 9.7 | 10.2 |
| 1971 | 9.2 | 7.9 |
| 1970 | 9.9 | 9.2 |
| 1969 | 9.4 | 10.1 |
| 1968 | 9 | 8.6 |
| 1967 | 8.6 | 8.1 |
| 1966 | 9.9 | 8.2 |
| 1965 | 8.9 | 7.4 |
| 1964 | 7.1 | 9.2 |
| 1963 | 8.8 | 9.6 |
| 1962 | 11 | 10.1 |
| 1961 | 10.2 | 10.6 |
| 1960 | 11.1 | 10 |
| 1959 | 10.5 | 9.5 |
| 1958 | 9.6 | 9.3 |
| 1957 | 10.7 | 9.3 |
| 1956 | 10.6 | 8.7 |
| 1955 | 9.8 | 9.9 |
| 1954 | 9.6 | 8.9 |
| 1953 | 10.9 | 9.2 |
| 1952 | 10.7 | 9.6 |
| 1951 | 10.5 | 8.6 |
| 1950 | 9.4 | 8.5 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 阿根廷 | 危地马拉 |
|---|---|---|
| 2015 | 14.78.1–22.2 | 19.39.9–31.9 |
| 2016 | 13.66.8–22 | 16.19.8–23.4 |
| 2017 | 14.26.9–22.4 | 17.98.3–27.3 |
| 2018 | 13.35.6–21.6 | 17.610–28.9 |
| 2019 | 14.56.9–23 | 16.88.8–30.9 |
| 2020 | 15.88.4–24.8 | 19.29.2–30 |
| 2021 | 15.38–24.6 | 18.311–28.2 |
| 2022 | 13.36.7–22.2 | 20.211.8–31.7 |
| 2023 | 14.99.3–22.1 | 18.210.7–35.1 |
| 2024 | 15.87.6–24 | 23.112.3–35.2 |
| 2025 | 16.410.2–23.4 | 21.610.6–36 |
| 2026 | 189.4–26.5 | 19.59.8–35.1 |
| 2027 | 16.49.1–26.2 | 19.310.5–34.7 |
| 2028 | 15.67.6–26.5 | 21.711.2–40.8 |
| 2029 | 15.97.3–26.3 | 22.911.9–38 |
| 2030 | 16.39.8–27.4 | 199–33.2 |
| 2031 | 15.88.1–24.9 | 20.111.1–36.5 |
| 2032 | 15.78.9–25.4 | 23.113–35.3 |
| 2033 | 16.18.4–25.7 | 20.512.3–33.2 |
| 2034 | 16.110.4–24.9 | 21.610.3–38.1 |
| 2035 | 16.810.2–27.5 | 22.211.8–31.9 |
| 2036 | 18.310.9–27.9 | 23.513.6–33.7 |
| 2037 | 18.310.2–27.3 | 25.114.3–37.8 |
| 2038 | 16.89.1–24.7 | 26.613.9–40.6 |
| 2039 | 17.39–25.8 | 26.514.9–41.2 |
| 2040 | 18.311.3–28.3 | 24.811.2–37.4 |
| 2041 | 19.310.7–29.3 | 22.411.3–40.7 |
| 2042 | 189.9–27.1 | 26.412–41.9 |
| 2043 | 189.5–27.5 | 26.815.7–50.1 |
| 2044 | 19.49.7–30.2 | 25.912.8–48 |
| 2045 | 20.511.8–30.1 | 26.412.9–47.2 |
| 2046 | 19.612–28.2 | 30.916.1–47.6 |
| 2047 | 19.78.9–31.3 | 29.918.1–49 |
| 2048 | 19.610.8–28.6 | 28.816.9–44 |
| 2049 | 20.411.6–30.7 | 32.716.4–52.8 |
| 2050 | 19.910.4–28.4 | 27.819.1–43.8 |
| 2051 | 20.511.5–30.8 | 27.717.7–50.8 |
| 2052 | 21.610.9–33.4 | 32.917.9–52.1 |
| 2053 | 20.411.3–30.2 | 30.117.5–55.3 |
| 2054 | 19.712–31.9 | 30.818.1–49.5 |
| 2055 | 21.310.1–34.1 | 3219.4–52.4 |
| 2056 | 20.510.5–32.4 | 30.316.2–54 |
| 2057 | 21.711.5–34.7 | 32.416.5–52.3 |
| 2058 | 21.312.4–33.2 | 28.318.9–55.3 |
| 2059 | 21.612.4–32.7 | 36.220.3–55.5 |
| 2060 | 2211.2–33.3 | 36.619.7–57.2 |
| 2061 | 2310.8–34.9 | 36.321.9–58.2 |
| 2062 | 2212.1–32.7 | 33.217.3–62.6 |
| 2063 | 24.114–33.8 | 36.219.3–60.3 |
| 2064 | 24.115.3–39.2 | 36.120.6–55.1 |
| 2065 | 23.712.7–34.9 | 40.717.2–60.3 |
| 2066 | 24.715.7–35.1 | 37.722.4–58.7 |
| 2067 | 24.912.6–37 | 33.120.8–57.4 |
| 2068 | 23.712.3–36.3 | 39.626.6–57.4 |
| 2069 | 2514–35.5 | 42.221–65.7 |
| 2070 | 24.413.3–37.1 | 39.319.3–58.4 |
| 2071 | 23.913.1–36.8 | 40.523.2–62.5 |
| 2072 | 23.814.5–38.9 | 4422.5–70.5 |
| 2073 | 25.314.6–39.1 | 44.826.3–67.1 |
| 2074 | 24.511.6–36.9 | 37.919–60.3 |
| 2075 | 25.312.9–38.6 | 41.122.5–67.1 |
| 2076 | 23.713.4–36.3 | 40.123.5–60.6 |
| 2077 | 24.615.3–36.4 | 38.719.4–65.5 |
| 2078 | 26.213.8–39.4 | 41.823.6–64.2 |
| 2079 | 23.913.4–36.8 | 46.120.5–67.8 |
| 2080 | 25.413.8–40.8 | 42.924.9–62.6 |
| 2081 | 2514.2–38 | 42.825–65.8 |
| 2082 | 2413.3–36.3 | 41.620.2–63.7 |
| 2083 | 25.415–39.2 | 39.921.5–70.8 |
| 2084 | 22.512.1–36 | 44.125.4–73.9 |
| 2085 | 23.412.2–36.2 | 4623.7–72.1 |
| 2086 | 25.214–39.1 | 38.521–70.1 |
| 2087 | 2614.4–37.2 | 44.324.3–73.9 |
| 2088 | 26.214.9–40.2 | 43.522.5–72.2 |
| 2089 | 27.315.3–38.2 | 37.323.7–68.2 |
| 2090 | 27.115.8–41.5 | 41.624.1–66 |
| 2091 | 28.315.4–42.5 | 46.824.7–77.3 |
| 2092 | 29.316–42 | 49.628.3–70.8 |
| 2093 | 2615.1–44.6 | 43.626.5–76.4 |
| 2094 | 27.714.9–41 | 4527.1–75.6 |
| 2095 | 26.713.8–43.1 | 46.223.2–75.6 |
| 2096 | 27.114.5–42.2 | 43.224.5–77.5 |
| 2097 | 2715.3–41.1 | 44.126.5–64.9 |
| 2098 | 26.715.9–42.2 | 49.823.6–84.5 |
| 2099 | 27.615.3–41 | 47.429.2–79.3 |
| 2100 | 27.214.1–45.4 | 47.924.4–79.7 |
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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
阿根廷与危地马拉对比
健康
人口与社会
经济
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冲突
军用
- 军费开支阿根廷:2025 年为 GDP 的 0.56%危地马拉:2025 年为 GDP 的 0.52%
- 军费开支(美元)阿根廷:2025 年为 US$37.3亿危地马拉:2025 年为 US$6.17亿
- 人均军费开支阿根廷:2025 年为 US$85危地马拉:2025 年为 US$34
- 军费占政府支出比例阿根廷:2025 年为 1.8%(占政府支出)危地马拉:2025 年为 3.5%(占政府支出)
- 武装部队人员阿根廷:2020 年为 103,000 人危地马拉:2020 年为 43,000 人
- 国家实力阿根廷:2022 年为 0.45%(占全球实力)危地马拉:2022 年为 0.09%(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)危地马拉:2020 年为 0.64%(占劳动力)
- 武器进口阿根廷:2025 年为 1.08亿 TIV危地马拉:2023 年为 600万 TIV