中国与意大利对比
中国与意大利:热带夜
2014 年热带夜:中国为 41.5 夜,意大利为 26.3 夜(CMIP6 气候模型中位数模拟)。 2014 年中国的数值较高,高出 15.2 夜,是意大利的 1.58 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,意大利为 65.1 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 中国 | 意大利 |
|---|---|---|
| 2014 | 41.5 | 26.3 |
| 2013 | 41.7 | 24.7 |
| 2012 | 40.8 | 24.8 |
| 2011 | 40.2 | 24.6 |
| 2010 | 40.5 | 27.1 |
| 2009 | 39.5 | 23.7 |
| 2008 | 39.2 | 24.1 |
| 2007 | 38.7 | 21.5 |
| 2006 | 39.5 | 24.6 |
| 2005 | 39.5 | 22.5 |
| 2004 | 39.7 | 24.5 |
| 2003 | 38.5 | 23.8 |
| 2002 | 38.8 | 20.6 |
| 2001 | 39.5 | 20.8 |
| 2000 | 38.6 | 21.7 |
| 1999 | 38.5 | 20.3 |
| 1998 | 37.6 | 18.9 |
| 1997 | 37.1 | 18.9 |
| 1996 | 36.6 | 18.9 |
| 1995 | 35.1 | 17.9 |
| 1994 | 34.9 | 17.4 |
| 1993 | 33.2 | 16.3 |
| 1992 | 32.3 | 15.1 |
| 1991 | 35.9 | 18 |
| 1990 | 36.4 | 18.2 |
| 1989 | 36.1 | 16.6 |
| 1988 | 35.1 | 15.5 |
| 1987 | 34.5 | 16 |
| 1986 | 34 | 15 |
| 1985 | 33.5 | 14.5 |
| 1984 | 33.4 | 15.7 |
| 1983 | 31.5 | 15.3 |
| 1982 | 34.1 | 14.1 |
| 1981 | 34.2 | 15.3 |
| 1980 | 34.3 | 15.9 |
| 1979 | 33.8 | 14.5 |
| 1978 | 34.8 | 16.5 |
| 1977 | 33.3 | 13.5 |
| 1976 | 32.7 | 13.8 |
| 1975 | 33.1 | 14 |
| 1974 | 33.3 | 14.8 |
| 1973 | 33.1 | 13.5 |
| 1972 | 32.6 | 13.7 |
| 1971 | 33 | 15.3 |
| 1970 | 32.4 | 14 |
| 1969 | 33.4 | 14.5 |
| 1968 | 32.8 | 13.8 |
| 1967 | 33.4 | 13.6 |
| 1966 | 33.4 | 13.2 |
| 1965 | 32.5 | 12.8 |
| 1964 | 32.1 | 13.2 |
| 1963 | 34.5 | 14.2 |
| 1962 | 34 | 15.5 |
| 1961 | 34.6 | 13.9 |
| 1960 | 34.1 | 14.9 |
| 1959 | 34 | 16.6 |
| 1958 | 35 | 14.4 |
| 1957 | 34.4 | 15.5 |
| 1956 | 34.6 | 16.7 |
| 1955 | 34.2 | 16.6 |
| 1954 | 34.2 | 15.7 |
| 1953 | 34.3 | 15.4 |
| 1952 | 34.3 | 16.6 |
| 1951 | 35.1 | 16 |
| 1950 | 34.9 | 15.3 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 中国 | 意大利 |
|---|---|---|
| 2015 | 42.334.8–49.8 | 3021.7–40.4 |
| 2016 | 42.134.4–50 | 29.618–42.2 |
| 2017 | 43.135.3–51.6 | 31.820.2–43.7 |
| 2018 | 42.335.5–49.5 | 3122–44.3 |
| 2019 | 43.836.5–51.1 | 31.521.3–43.2 |
| 2020 | 43.736.8–51.1 | 31.619.7–44.3 |
| 2021 | 44.136–52.1 | 3420.8–46.9 |
| 2022 | 44.737.5–52.7 | 37.121.3–50.6 |
| 2023 | 45.737.8–53.4 | 33.121.3–47.4 |
| 2024 | 45.738.1–54 | 35.521.6–48.4 |
| 2025 | 46.337.5–54.8 | 37.720.5–51.1 |
| 2026 | 46.237.6–55.5 | 38.926.6–52.2 |
| 2027 | 46.138–54.9 | 34.322.4–49.7 |
| 2028 | 46.438.4–54.3 | 37.724.4–53.1 |
| 2029 | 46.939.1–55.6 | 37.824.9–55 |
| 2030 | 47.138.8–55.3 | 37.925.7–54.7 |
| 2031 | 4738.8–56 | 37.223.8–51 |
| 2032 | 48.339.3–57.4 | 39.226.2–53.8 |
| 2033 | 47.939.7–56.6 | 40.426–50.3 |
| 2034 | 48.440.5–57.3 | 42.525.1–57.2 |
| 2035 | 49.740.8–58.6 | 42.728.9–58.3 |
| 2036 | 4940.1–58.2 | 41.127.7–59.9 |
| 2037 | 4941.2–57.6 | 4328.1–54.8 |
| 2038 | 50.542.4–59.3 | 41.628.5–61.3 |
| 2039 | 49.641.2–59.2 | 4129.4–56.4 |
| 2040 | 50.942.4–60.4 | 42.428.1–59.1 |
| 2041 | 51.342.5–61.1 | 41.927.2–58.7 |
| 2042 | 51.642–61.5 | 43.529.6–59 |
| 2043 | 50.742.7–61 | 4528.7–59.5 |
| 2044 | 51.942.4–61.9 | 44.929.4–59.9 |
| 2045 | 51.542.8–61.1 | 45.230.3–59.2 |
| 2046 | 5343.7–62.7 | 4627.3–62.4 |
| 2047 | 53.544.5–62.5 | 49.132.4–63.6 |
| 2048 | 53.144–62.6 | 46.228.3–65.7 |
| 2049 | 52.843.8–63.3 | 48.229.5–65.7 |
| 2050 | 53.644.4–63.8 | 49.536.4–64.4 |
| 2051 | 54.345.1–64.8 | 48.831.6–68.3 |
| 2052 | 53.444.6–63.2 | 50.330.9–68.1 |
| 2053 | 54.244.2–64.2 | 48.235.9–67 |
| 2054 | 54.545.3–64.8 | 49.435.3–66.1 |
| 2055 | 5545.1–65.8 | 52.233.7–67.7 |
| 2056 | 55.245.1–66.6 | 50.836.2–71.6 |
| 2057 | 54.844.9–65.7 | 50.232.8–65.6 |
| 2058 | 55.145.8–67.7 | 55.337.5–70.8 |
| 2059 | 55.345.1–67.2 | 51.934.5–74.1 |
| 2060 | 57.246.9–68.1 | 52.938.2–68.1 |
| 2061 | 56.546.6–66.3 | 54.338.3–69.8 |
| 2062 | 56.846.9–68.5 | 53.936.9–69 |
| 2063 | 57.247.2–68.6 | 56.437.6–72.1 |
| 2064 | 5747.1–67.7 | 55.938.5–71.3 |
| 2065 | 57.347.1–67.8 | 5537.3–73.3 |
| 2066 | 57.347.9–68.7 | 53.935.8–73.8 |
| 2067 | 57.546.4–68.2 | 61.141.2–76.6 |
| 2068 | 58.748.5–70.5 | 56.241.7–73 |
| 2069 | 58.548.4–69 | 58.741.8–73 |
| 2070 | 5847.6–71.7 | 55.738.9–74.4 |
| 2071 | 59.347.4–71.6 | 59.637.8–76.6 |
| 2072 | 59.248.1–71.5 | 59.643.5–74.6 |
| 2073 | 59.849.1–70.9 | 56.939.4–71.6 |
| 2074 | 59.648.7–71.1 | 54.836.7–73.7 |
| 2075 | 58.748.3–71.4 | 56.941.8–75.4 |
| 2076 | 60.249–70.9 | 59.941.9–77.7 |
| 2077 | 60.851.1–72.4 | 57.437.9–74.1 |
| 2078 | 59.648.8–72.4 | 60.540.5–80.7 |
| 2079 | 60.750.1–72.6 | 60.637.1–83.3 |
| 2080 | 59.950–72.3 | 59.743.1–78 |
| 2081 | 60.950–73.2 | 5943.7–78.9 |
| 2082 | 6149.8–73.3 | 63.945.5–80.2 |
| 2083 | 61.251.2–73.6 | 60.842–79.7 |
| 2084 | 61.749.7–74.6 | 62.547.3–82.1 |
| 2085 | 61.250.8–75.2 | 65.246.3–79 |
| 2086 | 61.648.9–74.5 | 64.445.6–80.1 |
| 2087 | 61.650.6–75 | 63.743.8–84 |
| 2088 | 62.750.5–77.1 | 67.247.4–84.4 |
| 2089 | 61.950–75.2 | 64.546–82.9 |
| 2090 | 62.551.4–73.7 | 65.842.8–80.5 |
| 2091 | 63.852–75.7 | 66.745.3–84.7 |
| 2092 | 63.251.2–75.1 | 64.838.5–82.3 |
| 2093 | 63.252–75.4 | 63.644.7–83 |
| 2094 | 6351.1–76.3 | 62.445–82 |
| 2095 | 63.952.8–76.4 | 6643.6–83.5 |
| 2096 | 63.852.2–76.8 | 6542.9–85.8 |
| 2097 | 62.750.7–75.1 | 65.844.9–84.4 |
| 2098 | 63.451.2–76.8 | 64.647.9–84.2 |
| 2099 | 63.851.9–76.1 | 67.742.2–81.9 |
| 2100 | 63.351.7–76.2 | 65.142.5–83.2 |
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
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军用
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- 人均军费开支中国:2025 年为 US$237意大利:2025 年为 US$813
- 军费占政府支出比例中国:2025 年为 5.1%(占政府支出)意大利:2025 年为 3.7%(占政府支出)
- 武装部队人员中国:2020 年为 254万 人意大利:2020 年为 338,000 人
- 国家实力中国:2022 年为 23.41%(占全球实力)意大利:2022 年为 0.96%(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)意大利:2020 年为 1.35%(占劳动力)
- 武器进口中国:2025 年为 2.07亿 TIV意大利:2025 年为 5.66亿 TIV
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