阿根廷与中国对比
阿根廷与中国:热带夜
2014 年热带夜:阿根廷为 42.6 夜,中国为 41.5 夜(CMIP6 气候模型中位数模拟)。 2014 年阿根廷的数值较高,高出 1.2 夜,是中国的 1.03 倍。
每年夜数 · CMIP6
数据解读
- 自 2007 年超过中国以来,阿根廷的数值一直更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年阿根廷为 65.2 夜,中国为 63.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 阿根廷 | 中国 |
|---|---|---|
| 2014 | 42.6 | 41.5 |
| 2013 | 41.8 | 41.7 |
| 2012 | 41 | 40.8 |
| 2011 | 41.5 | 40.2 |
| 2010 | 40.8 | 40.5 |
| 2009 | 41.6 | 39.5 |
| 2008 | 41.4 | 39.2 |
| 2007 | 39.6 | 38.7 |
| 2006 | 39.3 | 39.5 |
| 2005 | 40.1 | 39.5 |
| 2004 | 40.6 | 39.7 |
| 2003 | 38.7 | 38.5 |
| 2002 | 40.2 | 38.8 |
| 2001 | 39.5 | 39.5 |
| 2000 | 39.5 | 38.6 |
| 1999 | 38.4 | 38.5 |
| 1998 | 38.8 | 37.6 |
| 1997 | 38.5 | 37.1 |
| 1996 | 37 | 36.6 |
| 1995 | 35.7 | 35.1 |
| 1994 | 34.7 | 34.9 |
| 1993 | 34.3 | 33.2 |
| 1992 | 33.4 | 32.3 |
| 1991 | 36.8 | 35.9 |
| 1990 | 36 | 36.4 |
| 1989 | 37 | 36.1 |
| 1988 | 36.9 | 35.1 |
| 1987 | 36.1 | 34.5 |
| 1986 | 36.4 | 34 |
| 1985 | 36 | 33.5 |
| 1984 | 34.7 | 33.4 |
| 1983 | 35.2 | 31.5 |
| 1982 | 35.7 | 34.1 |
| 1981 | 37.3 | 34.2 |
| 1980 | 36.3 | 34.3 |
| 1979 | 37.5 | 33.8 |
| 1978 | 35.7 | 34.8 |
| 1977 | 35.1 | 33.3 |
| 1976 | 35.7 | 32.7 |
| 1975 | 34.8 | 33.1 |
| 1974 | 35.4 | 33.3 |
| 1973 | 34.1 | 33.1 |
| 1972 | 35.5 | 32.6 |
| 1971 | 34.7 | 33 |
| 1970 | 34.9 | 32.4 |
| 1969 | 33.4 | 33.4 |
| 1968 | 34.6 | 32.8 |
| 1967 | 33 | 33.4 |
| 1966 | 34.3 | 33.4 |
| 1965 | 32.2 | 32.5 |
| 1964 | 30.3 | 32.1 |
| 1963 | 32 | 34.5 |
| 1962 | 35.2 | 34 |
| 1961 | 35.6 | 34.6 |
| 1960 | 35.6 | 34.1 |
| 1959 | 34.5 | 34 |
| 1958 | 33.3 | 35 |
| 1957 | 35.7 | 34.4 |
| 1956 | 35 | 34.6 |
| 1955 | 34.4 | 34.2 |
| 1954 | 33.6 | 34.2 |
| 1953 | 35.8 | 34.3 |
| 1952 | 34.4 | 34.3 |
| 1951 | 35.4 | 35.1 |
| 1950 | 33.9 | 34.9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 阿根廷 | 中国 |
|---|---|---|
| 2015 | 44.433.5–53.4 | 42.334.8–49.8 |
| 2016 | 43.532.4–53.4 | 42.134.4–50 |
| 2017 | 42.834.2–52.6 | 43.135.3–51.6 |
| 2018 | 42.632.7–52.6 | 42.335.5–49.5 |
| 2019 | 43.633.4–53.1 | 43.836.5–51.1 |
| 2020 | 45.735.5–57.2 | 43.736.8–51.1 |
| 2021 | 45.634.3–56.4 | 44.136–52.1 |
| 2022 | 44.633.3–56.4 | 44.737.5–52.7 |
| 2023 | 44.934.9–53.9 | 45.737.8–53.4 |
| 2024 | 45.834.2–57.5 | 45.738.1–54 |
| 2025 | 46.536–58.1 | 46.337.5–54.8 |
| 2026 | 47.936.7–57 | 46.237.6–55.5 |
| 2027 | 46.434.5–56.3 | 46.138–54.9 |
| 2028 | 46.133.5–58.5 | 46.438.4–54.3 |
| 2029 | 48.336–58.8 | 46.939.1–55.6 |
| 2030 | 47.835.4–60.3 | 47.138.8–55.3 |
| 2031 | 46.935.5–58.7 | 4738.8–56 |
| 2032 | 4837.9–59.7 | 48.339.3–57.4 |
| 2033 | 47.436.7–57.6 | 47.939.7–56.6 |
| 2034 | 47.837.8–58.9 | 48.440.5–57.3 |
| 2035 | 47.339–59 | 49.740.8–58.6 |
| 2036 | 48.939.2–58.4 | 4940.1–58.2 |
| 2037 | 5141.2–60.9 | 4941.2–57.6 |
| 2038 | 48.737.9–59.7 | 50.542.4–59.3 |
| 2039 | 48.839.1–58.4 | 49.641.2–59.2 |
| 2040 | 50.440.4–62.3 | 50.942.4–60.4 |
| 2041 | 50.740.4–61.7 | 51.342.5–61.1 |
| 2042 | 5037.3–61.1 | 51.642–61.5 |
| 2043 | 50.340.5–61 | 50.742.7–61 |
| 2044 | 5240–65 | 51.942.4–61.9 |
| 2045 | 52.441.3–65.6 | 51.542.8–61.1 |
| 2046 | 51.941.2–62.7 | 5343.7–62.7 |
| 2047 | 51.542–64 | 53.544.5–62.5 |
| 2048 | 54.542.6–65 | 53.144–62.6 |
| 2049 | 53.942.8–64.9 | 52.843.8–63.3 |
| 2050 | 52.543.6–62.4 | 53.644.4–63.8 |
| 2051 | 55.743.3–67.4 | 54.345.1–64.8 |
| 2052 | 55.642.2–67 | 53.444.6–63.2 |
| 2053 | 55.342.6–67.6 | 54.244.2–64.2 |
| 2054 | 54.743–66.7 | 54.545.3–64.8 |
| 2055 | 55.942.3–67.2 | 5545.1–65.8 |
| 2056 | 57.642.8–68.6 | 55.245.1–66.6 |
| 2057 | 56.842.3–68.7 | 54.844.9–65.7 |
| 2058 | 54.841.5–68.1 | 55.145.8–67.7 |
| 2059 | 57.844.9–70.3 | 55.345.1–67.2 |
| 2060 | 56.943.4–67.9 | 57.246.9–68.1 |
| 2061 | 56.542.3–70.6 | 56.546.6–66.3 |
| 2062 | 57.345.8–68.5 | 56.846.9–68.5 |
| 2063 | 58.244.6–70.2 | 57.247.2–68.6 |
| 2064 | 58.845.8–71.5 | 5747.1–67.7 |
| 2065 | 58.746–71.1 | 57.347.1–67.8 |
| 2066 | 59.947–68.9 | 57.347.9–68.7 |
| 2067 | 58.944.8–71.5 | 57.546.4–68.2 |
| 2068 | 57.844.3–70.3 | 58.748.5–70.5 |
| 2069 | 59.445.4–70.5 | 58.548.4–69 |
| 2070 | 61.348.2–74.3 | 5847.6–71.7 |
| 2071 | 60.148.7–73.2 | 59.347.4–71.6 |
| 2072 | 60.146.7–73.7 | 59.248.1–71.5 |
| 2073 | 60.847.6–73.5 | 59.849.1–70.9 |
| 2074 | 60.447.6–73.7 | 59.648.7–71.1 |
| 2075 | 61.347.9–73.9 | 58.748.3–71.4 |
| 2076 | 61.146.8–75.8 | 60.249–70.9 |
| 2077 | 60.647.1–73.1 | 60.851.1–72.4 |
| 2078 | 63.449.4–75.6 | 59.648.8–72.4 |
| 2079 | 59.948.7–73 | 60.750.1–72.6 |
| 2080 | 6348.1–75.5 | 59.950–72.3 |
| 2081 | 61.448.7–73.5 | 60.950–73.2 |
| 2082 | 61.747.7–75 | 6149.8–73.3 |
| 2083 | 62.148.2–75.6 | 61.251.2–73.6 |
| 2084 | 62.950.3–76 | 61.749.7–74.6 |
| 2085 | 6246.9–76.4 | 61.250.8–75.2 |
| 2086 | 62.749.4–76.4 | 61.648.9–74.5 |
| 2087 | 61.847.9–74.9 | 61.650.6–75 |
| 2088 | 64.450.8–77.5 | 62.750.5–77.1 |
| 2089 | 62.749.3–76.3 | 61.950–75.2 |
| 2090 | 64.152.5–77.1 | 62.551.4–73.7 |
| 2091 | 64.451.7–78.3 | 63.852–75.7 |
| 2092 | 65.650.8–78.3 | 63.251.2–75.1 |
| 2093 | 62.749.7–76.8 | 63.252–75.4 |
| 2094 | 63.950.1–78.5 | 6351.1–76.3 |
| 2095 | 62.948.8–77.9 | 63.952.8–76.4 |
| 2096 | 64.749.4–78.9 | 63.852.2–76.8 |
| 2097 | 64.552.4–80.1 | 62.750.7–75.1 |
| 2098 | 65.652.7–78.7 | 63.451.2–76.8 |
| 2099 | 65.249.3–80.2 | 63.851.9–76.1 |
| 2100 | 65.250–81.7 | 63.351.7–76.2 |
分别查看各国
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
阿根廷与中国对比
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军用
- 军费开支阿根廷:2025 年为 GDP 的 0.56%中国:2025 年为 GDP 的 1.73%
- 军费开支(美元)阿根廷:2025 年为 US$37.3亿中国:2025 年为 US$3350亿
- 人均军费开支阿根廷:2025 年为 US$85中国:2025 年为 US$237
- 军费占政府支出比例阿根廷:2025 年为 1.8%(占政府支出)中国:2025 年为 5.1%(占政府支出)
- 武装部队人员阿根廷:2020 年为 103,000 人中国:2020 年为 254万 人
- 国家实力阿根廷:2022 年为 0.45%(占全球实力)中国:2022 年为 23.41%(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)中国:2020 年为 0.33%(占劳动力)
- 武器进口阿根廷:2025 年为 1.08亿 TIV中国:2025 年为 2.07亿 TIV
- 武器出口阿根廷:2011 年为 100万 TIV中国:2025 年为 8.8亿 TIV