中国与塔吉克斯坦对比
中国与塔吉克斯坦:热带夜
2014 年热带夜:中国为 41.5 夜,塔吉克斯坦为 12.1 夜(CMIP6 气候模型中位数模拟)。 2014 年中国的数值较高,高出 29.3 夜,是塔吉克斯坦的 3.41 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,中国的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年中国为 63.3 夜,塔吉克斯坦为 21.8 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 中国 | 塔吉克斯坦 |
|---|---|---|
| 2014 | 41.5 | 12.1 |
| 2013 | 41.7 | 12.2 |
| 2012 | 40.8 | 11.7 |
| 2011 | 40.2 | 11.6 |
| 2010 | 40.5 | 11 |
| 2009 | 39.5 | 11.7 |
| 2008 | 39.2 | 11.1 |
| 2007 | 38.7 | 11.4 |
| 2006 | 39.5 | 11.3 |
| 2005 | 39.5 | 11 |
| 2004 | 39.7 | 10.9 |
| 2003 | 38.5 | 11 |
| 2002 | 38.8 | 11.5 |
| 2001 | 39.5 | 10.8 |
| 2000 | 38.6 | 10.7 |
| 1999 | 38.5 | 10.8 |
| 1998 | 37.6 | 10.4 |
| 1997 | 37.1 | 10.3 |
| 1996 | 36.6 | 10.2 |
| 1995 | 35.1 | 9.9 |
| 1994 | 34.9 | 9.8 |
| 1993 | 33.2 | 8.9 |
| 1992 | 32.3 | 8.8 |
| 1991 | 35.9 | 9.6 |
| 1990 | 36.4 | 10.1 |
| 1989 | 36.1 | 10.1 |
| 1988 | 35.1 | 9.3 |
| 1987 | 34.5 | 9.5 |
| 1986 | 34 | 8.9 |
| 1985 | 33.5 | 9 |
| 1984 | 33.4 | 8.6 |
| 1983 | 31.5 | 7.9 |
| 1982 | 34.1 | 9.2 |
| 1981 | 34.2 | 9.4 |
| 1980 | 34.3 | 9 |
| 1979 | 33.8 | 9.1 |
| 1978 | 34.8 | 8.9 |
| 1977 | 33.3 | 8.4 |
| 1976 | 32.7 | 8.4 |
| 1975 | 33.1 | 8.7 |
| 1974 | 33.3 | 8.4 |
| 1973 | 33.1 | 8.5 |
| 1972 | 32.6 | 9 |
| 1971 | 33 | 8.4 |
| 1970 | 32.4 | 8.3 |
| 1969 | 33.4 | 8.6 |
| 1968 | 32.8 | 8 |
| 1967 | 33.4 | 8.6 |
| 1966 | 33.4 | 8.3 |
| 1965 | 32.5 | 8.3 |
| 1964 | 32.1 | 8.5 |
| 1963 | 34.5 | 8.6 |
| 1962 | 34 | 8.7 |
| 1961 | 34.6 | 8.8 |
| 1960 | 34.1 | 8.8 |
| 1959 | 34 | 8.7 |
| 1958 | 35 | 9.6 |
| 1957 | 34.4 | 9 |
| 1956 | 34.6 | 9 |
| 1955 | 34.2 | 8.6 |
| 1954 | 34.2 | 9 |
| 1953 | 34.3 | 8.4 |
| 1952 | 34.3 | 9 |
| 1951 | 35.1 | 8.6 |
| 1950 | 34.9 | 9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 中国 | 塔吉克斯坦 |
|---|---|---|
| 2015 | 42.334.8–49.8 | 13.210–15.9 |
| 2016 | 42.134.4–50 | 12.910.5–16 |
| 2017 | 43.135.3–51.6 | 13.210.7–16 |
| 2018 | 42.335.5–49.5 | 12.99.7–16.3 |
| 2019 | 43.836.5–51.1 | 13.310.4–16.5 |
| 2020 | 43.736.8–51.1 | 13.410.9–17 |
| 2021 | 44.136–52.1 | 13.910.7–17.4 |
| 2022 | 44.737.5–52.7 | 14.110.9–17.6 |
| 2023 | 45.737.8–53.4 | 14.411.3–17 |
| 2024 | 45.738.1–54 | 14.510.6–17.8 |
| 2025 | 46.337.5–54.8 | 14.911.7–18.3 |
| 2026 | 46.237.6–55.5 | 1410.7–18 |
| 2027 | 46.138–54.9 | 14.411.4–18.2 |
| 2028 | 46.438.4–54.3 | 14.811.6–18.6 |
| 2029 | 46.939.1–55.6 | 14.110.9–18 |
| 2030 | 47.138.8–55.3 | 14.911.8–17.9 |
| 2031 | 4738.8–56 | 15.412.3–18.6 |
| 2032 | 48.339.3–57.4 | 15.312.1–19.1 |
| 2033 | 47.939.7–56.6 | 15.311.6–19.4 |
| 2034 | 48.440.5–57.3 | 15.211.4–19.5 |
| 2035 | 49.740.8–58.6 | 16.112–19.5 |
| 2036 | 4940.1–58.2 | 15.512.4–19.6 |
| 2037 | 4941.2–57.6 | 15.912.6–19.2 |
| 2038 | 50.542.4–59.3 | 16.112.9–19.6 |
| 2039 | 49.641.2–59.2 | 15.612.2–19.1 |
| 2040 | 50.942.4–60.4 | 16.212.5–20.4 |
| 2041 | 51.342.5–61.1 | 16.612.7–20.2 |
| 2042 | 51.642–61.5 | 16.512.6–20.2 |
| 2043 | 50.742.7–61 | 15.812.1–20.7 |
| 2044 | 51.942.4–61.9 | 16.613.6–20.7 |
| 2045 | 51.542.8–61.1 | 16.812.9–20.4 |
| 2046 | 5343.7–62.7 | 1712.8–21.9 |
| 2047 | 53.544.5–62.5 | 1713.2–21.7 |
| 2048 | 53.144–62.6 | 16.813.7–21.1 |
| 2049 | 52.843.8–63.3 | 16.913.7–21.4 |
| 2050 | 53.644.4–63.8 | 17.614–22.1 |
| 2051 | 54.345.1–64.8 | 17.513.7–22.9 |
| 2052 | 53.444.6–63.2 | 17.413.9–22.1 |
| 2053 | 54.244.2–64.2 | 17.814.4–21.5 |
| 2054 | 54.545.3–64.8 | 17.914.3–22.4 |
| 2055 | 5545.1–65.8 | 18.214.6–22.5 |
| 2056 | 55.245.1–66.6 | 18.514.2–22.9 |
| 2057 | 54.844.9–65.7 | 18.914.2–23.2 |
| 2058 | 55.145.8–67.7 | 18.314.3–23.5 |
| 2059 | 55.345.1–67.2 | 18.114.5–23.3 |
| 2060 | 57.246.9–68.1 | 18.714.3–23.3 |
| 2061 | 56.546.6–66.3 | 18.514.1–22.4 |
| 2062 | 56.846.9–68.5 | 1914.9–24.2 |
| 2063 | 57.247.2–68.6 | 1914.8–23.3 |
| 2064 | 5747.1–67.7 | 18.713.9–23.5 |
| 2065 | 57.347.1–67.8 | 19.515.3–24.9 |
| 2066 | 57.347.9–68.7 | 19.515.9–23.6 |
| 2067 | 57.546.4–68.2 | 19.915.5–25 |
| 2068 | 58.748.5–70.5 | 19.815.8–24.2 |
| 2069 | 58.548.4–69 | 19.716–24.2 |
| 2070 | 5847.6–71.7 | 19.516–25.2 |
| 2071 | 59.347.4–71.6 | 19.516–25.1 |
| 2072 | 59.248.1–71.5 | 19.315.4–25.5 |
| 2073 | 59.849.1–70.9 | 19.915.8–25.6 |
| 2074 | 59.648.7–71.1 | 20.116.7–25.4 |
| 2075 | 58.748.3–71.4 | 19.516–25.6 |
| 2076 | 60.249–70.9 | 20.114.4–25.3 |
| 2077 | 60.851.1–72.4 | 20.615.5–27 |
| 2078 | 59.648.8–72.4 | 2015.3–27.2 |
| 2079 | 60.750.1–72.6 | 19.414.9–25.5 |
| 2080 | 59.950–72.3 | 20.315.3–26.6 |
| 2081 | 60.950–73.2 | 19.815.7–25.8 |
| 2082 | 6149.8–73.3 | 20.716.3–26.1 |
| 2083 | 61.251.2–73.6 | 20.916.3–26.4 |
| 2084 | 61.749.7–74.6 | 20.615.4–26.5 |
| 2085 | 61.250.8–75.2 | 20.515.9–27.5 |
| 2086 | 61.648.9–74.5 | 20.715.6–26.8 |
| 2087 | 61.650.6–75 | 20.917.3–25.8 |
| 2088 | 62.750.5–77.1 | 21.115.5–26.9 |
| 2089 | 61.950–75.2 | 21.216.7–26.7 |
| 2090 | 62.551.4–73.7 | 2115.6–26.7 |
| 2091 | 63.852–75.7 | 2216.7–27.4 |
| 2092 | 63.251.2–75.1 | 21.416.7–26.6 |
| 2093 | 63.252–75.4 | 21.716.9–26.7 |
| 2094 | 6351.1–76.3 | 21.817–28 |
| 2095 | 63.952.8–76.4 | 21.916.8–27.4 |
| 2096 | 63.852.2–76.8 | 22.417.9–27.9 |
| 2097 | 62.750.7–75.1 | 21.817.2–27.4 |
| 2098 | 63.451.2–76.8 | 22.317–28.6 |
| 2099 | 63.851.9–76.1 | 22.217.1–27.3 |
| 2100 | 63.351.7–76.2 | 21.816.3–28.6 |
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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
中国与塔吉克斯坦对比
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军用
- 军费开支中国:2025 年为 GDP 的 1.73%塔吉克斯坦:2025 年为 GDP 的 1.47%
- 军费开支(美元)中国:2025 年为 US$3350亿塔吉克斯坦:2025 年为 US$2.2亿
- 人均军费开支中国:2025 年为 US$237塔吉克斯坦:2025 年为 US$23
- 军费占政府支出比例中国:2025 年为 5.1%(占政府支出)塔吉克斯坦:2025 年为 4.7%(占政府支出)
- 武装部队人员中国:2020 年为 254万 人塔吉克斯坦:2020 年为 17,000 人
- 国家实力中国:2022 年为 23.41%(占全球实力)塔吉克斯坦:2022 年为 0.05%(占全球实力)
- 武装部队占劳动力比例中国:2020 年为 0.33%(占劳动力)塔吉克斯坦:2020 年为 0.75%(占劳动力)
- 武器进口中国:2025 年为 2.07亿 TIV塔吉克斯坦:2025 年为 7500万 TIV