中国与尼泊尔对比
中国与尼泊尔:热带夜
2014 年热带夜:中国为 41.5 夜,尼泊尔为 65.9 夜(CMIP6 气候模型中位数模拟)。 2014 年尼泊尔的数值较高,高出 24.4 夜,是中国的 1.59 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,尼泊尔的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年中国为 63.3 夜,尼泊尔为 89.9 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 中国 | 尼泊尔 |
|---|---|---|
| 2014 | 41.5 | 65.9 |
| 2013 | 41.7 | 66.5 |
| 2012 | 40.8 | 66 |
| 2011 | 40.2 | 64.7 |
| 2010 | 40.5 | 65.7 |
| 2009 | 39.5 | 63.8 |
| 2008 | 39.2 | 64.1 |
| 2007 | 38.7 | 64.3 |
| 2006 | 39.5 | 64.4 |
| 2005 | 39.5 | 64.4 |
| 2004 | 39.7 | 64.2 |
| 2003 | 38.5 | 64.2 |
| 2002 | 38.8 | 65 |
| 2001 | 39.5 | 63.6 |
| 2000 | 38.6 | 63.4 |
| 1999 | 38.5 | 63.3 |
| 1998 | 37.6 | 61.8 |
| 1997 | 37.1 | 62.3 |
| 1996 | 36.6 | 60.9 |
| 1995 | 35.1 | 60.7 |
| 1994 | 34.9 | 59.8 |
| 1993 | 33.2 | 59.6 |
| 1992 | 32.3 | 57.3 |
| 1991 | 35.9 | 62 |
| 1990 | 36.4 | 62.1 |
| 1989 | 36.1 | 61 |
| 1988 | 35.1 | 59.8 |
| 1987 | 34.5 | 60.2 |
| 1986 | 34 | 59.9 |
| 1985 | 33.5 | 59.2 |
| 1984 | 33.4 | 59.4 |
| 1983 | 31.5 | 57.4 |
| 1982 | 34.1 | 60.2 |
| 1981 | 34.2 | 59.9 |
| 1980 | 34.3 | 60.3 |
| 1979 | 33.8 | 59.2 |
| 1978 | 34.8 | 58.8 |
| 1977 | 33.3 | 59.3 |
| 1976 | 32.7 | 58.8 |
| 1975 | 33.1 | 58.3 |
| 1974 | 33.3 | 59.8 |
| 1973 | 33.1 | 59.2 |
| 1972 | 32.6 | 57.9 |
| 1971 | 33 | 58.9 |
| 1970 | 32.4 | 58.1 |
| 1969 | 33.4 | 57.9 |
| 1968 | 32.8 | 57.6 |
| 1967 | 33.4 | 57.3 |
| 1966 | 33.4 | 58.8 |
| 1965 | 32.5 | 57.3 |
| 1964 | 32.1 | 57.3 |
| 1963 | 34.5 | 58.1 |
| 1962 | 34 | 58.8 |
| 1961 | 34.6 | 59.1 |
| 1960 | 34.1 | 59.8 |
| 1959 | 34 | 60.2 |
| 1958 | 35 | 59.1 |
| 1957 | 34.4 | 59.3 |
| 1956 | 34.6 | 59.1 |
| 1955 | 34.2 | 58.2 |
| 1954 | 34.2 | 59.3 |
| 1953 | 34.3 | 58.7 |
| 1952 | 34.3 | 59 |
| 1951 | 35.1 | 59.3 |
| 1950 | 34.9 | 59.1 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 中国 | 尼泊尔 |
|---|---|---|
| 2015 | 42.334.8–49.8 | 66.560–73.8 |
| 2016 | 42.134.4–50 | 66.358.3–73.6 |
| 2017 | 43.135.3–51.6 | 66.758.6–73.6 |
| 2018 | 42.335.5–49.5 | 65.658.9–73.3 |
| 2019 | 43.836.5–51.1 | 66.358–74.3 |
| 2020 | 43.736.8–51.1 | 68.360.6–75.9 |
| 2021 | 44.136–52.1 | 67.959.6–75.8 |
| 2022 | 44.737.5–52.7 | 68.661–75.3 |
| 2023 | 45.737.8–53.4 | 69.361.6–76.2 |
| 2024 | 45.738.1–54 | 7063–78.7 |
| 2025 | 46.337.5–54.8 | 68.660.3–78.1 |
| 2026 | 46.237.6–55.5 | 69.859.8–78.5 |
| 2027 | 46.138–54.9 | 69.761–78.1 |
| 2028 | 46.438.4–54.3 | 70.562.6–78 |
| 2029 | 46.939.1–55.6 | 70.461.7–80.6 |
| 2030 | 47.138.8–55.3 | 7061.3–78.5 |
| 2031 | 4738.8–56 | 71.262.8–78.6 |
| 2032 | 48.339.3–57.4 | 72.163.9–81.1 |
| 2033 | 47.939.7–56.6 | 71.264.8–78 |
| 2034 | 48.440.5–57.3 | 71.663.8–80.2 |
| 2035 | 49.740.8–58.6 | 72.664.3–83 |
| 2036 | 4940.1–58.2 | 71.965–80.3 |
| 2037 | 4941.2–57.6 | 74.165.9–84.2 |
| 2038 | 50.542.4–59.3 | 74.167–83.3 |
| 2039 | 49.641.2–59.2 | 73.565.2–82.5 |
| 2040 | 50.942.4–60.4 | 73.865.9–83.3 |
| 2041 | 51.342.5–61.1 | 75.368.2–83.4 |
| 2042 | 51.642–61.5 | 75.667.7–84.9 |
| 2043 | 50.742.7–61 | 75.566.3–85 |
| 2044 | 51.942.4–61.9 | 76.467.5–85.4 |
| 2045 | 51.542.8–61.1 | 76.567.9–85.2 |
| 2046 | 5343.7–62.7 | 76.966.8–86 |
| 2047 | 53.544.5–62.5 | 77.766.9–86.2 |
| 2048 | 53.144–62.6 | 78.367.8–88 |
| 2049 | 52.843.8–63.3 | 78.568.6–87.8 |
| 2050 | 53.644.4–63.8 | 79.367.8–90 |
| 2051 | 54.345.1–64.8 | 7970.1–88.5 |
| 2052 | 53.444.6–63.2 | 79.570.4–88.6 |
| 2053 | 54.244.2–64.2 | 79.170.1–88.4 |
| 2054 | 54.545.3–64.8 | 79.168.9–89 |
| 2055 | 5545.1–65.8 | 80.571.8–89.3 |
| 2056 | 55.245.1–66.6 | 79.771.5–89.6 |
| 2057 | 54.844.9–65.7 | 80.671.9–89.8 |
| 2058 | 55.145.8–67.7 | 80.771–91.5 |
| 2059 | 55.345.1–67.2 | 80.770.6–93.7 |
| 2060 | 57.246.9–68.1 | 82.472.9–91.7 |
| 2061 | 56.546.6–66.3 | 80.871.4–90.4 |
| 2062 | 56.846.9–68.5 | 82.172–93.2 |
| 2063 | 57.247.2–68.6 | 82.271.5–92.1 |
| 2064 | 5747.1–67.7 | 82.872.6–92 |
| 2065 | 57.347.1–67.8 | 82.672.2–93.3 |
| 2066 | 57.347.9–68.7 | 83.772.4–94.2 |
| 2067 | 57.546.4–68.2 | 82.771.9–93.3 |
| 2068 | 58.748.5–70.5 | 84.772.4–95.1 |
| 2069 | 58.548.4–69 | 8573–94.3 |
| 2070 | 5847.6–71.7 | 83.273.2–92.7 |
| 2071 | 59.347.4–71.6 | 83.872.9–93.9 |
| 2072 | 59.248.1–71.5 | 85.274.6–95.4 |
| 2073 | 59.849.1–70.9 | 85.875.3–96.4 |
| 2074 | 59.648.7–71.1 | 84.474.5–95.8 |
| 2075 | 58.748.3–71.4 | 8574.2–95.4 |
| 2076 | 60.249–70.9 | 85.974.8–95 |
| 2077 | 60.851.1–72.4 | 86.775.4–97.4 |
| 2078 | 59.648.8–72.4 | 85.775.7–96.6 |
| 2079 | 60.750.1–72.6 | 85.973.7–96 |
| 2080 | 59.950–72.3 | 87.576.4–97.7 |
| 2081 | 60.950–73.2 | 87.577.2–98.1 |
| 2082 | 6149.8–73.3 | 86.877.3–98.8 |
| 2083 | 61.251.2–73.6 | 8876.6–99.5 |
| 2084 | 61.749.7–74.6 | 88.377.6–99.6 |
| 2085 | 61.250.8–75.2 | 87.876.3–100.8 |
| 2086 | 61.648.9–74.5 | 87.975.2–100.2 |
| 2087 | 61.650.6–75 | 87.476.2–98.9 |
| 2088 | 62.750.5–77.1 | 87.375.6–99.2 |
| 2089 | 61.950–75.2 | 8776.2–100.1 |
| 2090 | 62.551.4–73.7 | 87.977.5–99 |
| 2091 | 63.852–75.7 | 88.877.6–101.7 |
| 2092 | 63.251.2–75.1 | 88.477.7–101.1 |
| 2093 | 63.252–75.4 | 88.776.8–99.9 |
| 2094 | 6351.1–76.3 | 88.677.6–99.5 |
| 2095 | 63.952.8–76.4 | 89.478.8–99.7 |
| 2096 | 63.852.2–76.8 | 89.178.6–101.7 |
| 2097 | 62.750.7–75.1 | 87.976.6–99.4 |
| 2098 | 63.451.2–76.8 | 89.678.1–100.1 |
| 2099 | 63.851.9–76.1 | 89.778.5–100.7 |
| 2100 | 63.351.7–76.2 | 89.980–100 |
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
中国与尼泊尔对比
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军用
- 军费开支中国:2025 年为 GDP 的 1.73%尼泊尔:2025 年为 GDP 的 0.97%
- 军费开支(美元)中国:2025 年为 US$3350亿尼泊尔:2025 年为 US$4.29亿
- 人均军费开支中国:2025 年为 US$237尼泊尔:2025 年为 US$14
- 军费占政府支出比例中国:2025 年为 5.1%(占政府支出)尼泊尔:2025 年为 4.5%(占政府支出)
- 武装部队人员中国:2020 年为 254万 人尼泊尔:2020 年为 112,000 人
- 国家实力中国:2022 年为 23.41%(占全球实力)尼泊尔:2022 年为 0.18%(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)尼泊尔:2020 年为 1.4%(占劳动力)
- 武器进口中国:2025 年为 2.07亿 TIV尼泊尔:2025 年为 600万 TIV