科特迪瓦与马拉维对比
科特迪瓦与马拉维:热带夜
2014 年热带夜:科特迪瓦为 341.6 夜,马拉维为 138.1 夜(CMIP6 气候模型中位数模拟)。 2014 年科特迪瓦的数值较高,高出 203.5 夜,是马拉维的 2.47 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,科特迪瓦的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年科特迪瓦为 359.6 夜,马拉维为 213.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 科特迪瓦 | 马拉维 |
|---|---|---|
| 2014 | 341.6 | 138.1 |
| 2013 | 339.6 | 138.9 |
| 2012 | 342.3 | 137.4 |
| 2011 | 340.1 | 136.6 |
| 2010 | 338.6 | 132.4 |
| 2009 | 337.3 | 131.4 |
| 2008 | 337.1 | 130.8 |
| 2007 | 336.7 | 132.8 |
| 2006 | 336.6 | 129.8 |
| 2005 | 337.6 | 129.5 |
| 2004 | 334.8 | 133.4 |
| 2003 | 337.3 | 132.5 |
| 2002 | 336.1 | 130.3 |
| 2001 | 339.5 | 134 |
| 2000 | 334.6 | 126.6 |
| 1999 | 331.3 | 124.8 |
| 1998 | 332.7 | 127.1 |
| 1997 | 331.8 | 124.2 |
| 1996 | 329.9 | 121.3 |
| 1995 | 330.5 | 120.9 |
| 1994 | 327.9 | 118.4 |
| 1993 | 327.2 | 113.8 |
| 1992 | 322 | 114.1 |
| 1991 | 331.7 | 120.9 |
| 1990 | 334 | 123.8 |
| 1989 | 328.9 | 120.5 |
| 1988 | 327.5 | 120.8 |
| 1987 | 327.9 | 118.8 |
| 1986 | 329.2 | 121.1 |
| 1985 | 324.9 | 115.7 |
| 1984 | 325.8 | 116.2 |
| 1983 | 325.4 | 115.5 |
| 1982 | 324 | 115.1 |
| 1981 | 327 | 119 |
| 1980 | 323.1 | 116.9 |
| 1979 | 327.1 | 117.7 |
| 1978 | 324.2 | 114.8 |
| 1977 | 325.5 | 117.2 |
| 1976 | 321.7 | 114 |
| 1975 | 322.8 | 114 |
| 1974 | 322 | 115.2 |
| 1973 | 323.8 | 114.7 |
| 1972 | 322.4 | 113.8 |
| 1971 | 322 | 114.1 |
| 1970 | 322.2 | 115.8 |
| 1969 | 320.9 | 114.3 |
| 1968 | 319.8 | 110 |
| 1967 | 317.1 | 109.8 |
| 1966 | 318.4 | 111 |
| 1965 | 320 | 111.5 |
| 1964 | 314.7 | 106.3 |
| 1963 | 317.4 | 107.5 |
| 1962 | 324.1 | 114.7 |
| 1961 | 323.1 | 116 |
| 1960 | 325.5 | 117.4 |
| 1959 | 322.1 | 115.6 |
| 1958 | 322.4 | 116.4 |
| 1957 | 321.2 | 114.6 |
| 1956 | 321.2 | 111.4 |
| 1955 | 320.1 | 115.2 |
| 1954 | 325.6 | 113.9 |
| 1953 | 322.9 | 113 |
| 1952 | 319.4 | 113.5 |
| 1951 | 323.9 | 113.5 |
| 1950 | 317.8 | 112.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 科特迪瓦 | 马拉维 |
|---|---|---|
| 2015 | 339.1321.9–350.7 | 145.7126.7–164.3 |
| 2016 | 339.9324.6–349.1 | 139.8122.6–157.4 |
| 2017 | 340.5322.4–349.6 | 143.6127–161.8 |
| 2018 | 341.6327.4–351.6 | 143.1124.6–162.6 |
| 2019 | 338.5323.6–350.3 | 143.8128.3–161.4 |
| 2020 | 340.6324.2–352.9 | 145127.3–165.8 |
| 2021 | 340.8325.2–353.8 | 145.3128–163.6 |
| 2022 | 344327.2–353.4 | 151130.1–169.1 |
| 2023 | 341.2327.2–352.6 | 149.2129.5–171.2 |
| 2024 | 344.9331–353.9 | 152.4130–172.6 |
| 2025 | 342.4327.8–352.1 | 151.1129.7–170.4 |
| 2026 | 342.3326.6–353.3 | 151.1126.2–173.8 |
| 2027 | 343.9325.6–352.9 | 154.4135.1–173.1 |
| 2028 | 347.4333.6–355.5 | 155.5134.6–174 |
| 2029 | 347.2332.4–355.2 | 159.8139.2–178.5 |
| 2030 | 347.2332.1–353.8 | 155.6138.7–174.5 |
| 2031 | 349.3333.1–357.2 | 161.1143.4–177.6 |
| 2032 | 347.8331.5–356.9 | 160.8141.3–181.3 |
| 2033 | 348332.6–360.4 | 161.3135.6–179.2 |
| 2034 | 346.6331.7–355.8 | 160.9138.9–185 |
| 2035 | 348.9333.7–357.8 | 164.3140.4–189.5 |
| 2036 | 350.5332.7–359.1 | 163.8137.6–182.5 |
| 2037 | 349.8334.6–357.5 | 166.9144.6–189.2 |
| 2038 | 351.3338.9–358.2 | 172.2148.4–191.2 |
| 2039 | 350.6333.1–358.9 | 164.8147.3–188.2 |
| 2040 | 351.1336.2–359.6 | 164.4146.4–189.7 |
| 2041 | 350.8335.9–358 | 169.3143.7–192.5 |
| 2042 | 349.8337.3–358.6 | 169.8146.3–197.8 |
| 2043 | 348.4336.1–357.8 | 167.5147.1–193.2 |
| 2044 | 350.3337.5–359.2 | 172.6148.3–197 |
| 2045 | 351339.5–359.5 | 170.4153.1–194.7 |
| 2046 | 351.7337.6–358.6 | 176.3151.2–203.1 |
| 2047 | 352335.4–360.1 | 178.7157.8–200.9 |
| 2048 | 351.6339.9–360.3 | 180.7158.9–204.1 |
| 2049 | 353339.6–360.9 | 176.7154–205.4 |
| 2050 | 352340.6–359.3 | 180.4155.2–204.9 |
| 2051 | 353340.5–360.5 | 182.9162.1–207.4 |
| 2052 | 352339–359.8 | 184.9163.2–209.6 |
| 2053 | 352.7339–360.5 | 177.2149.6–207.4 |
| 2054 | 354.7339.5–360.9 | 185.1157.1–208 |
| 2055 | 353.4343.4–360.8 | 186.1159.2–212.6 |
| 2056 | 355.9339.6–362.8 | 184.6158.5–214.3 |
| 2057 | 356.3343–362 | 184.7159.3–212.3 |
| 2058 | 354.3344.5–361.3 | 188.5163.8–214.7 |
| 2059 | 355343.4–361.7 | 189.8166.9–218.5 |
| 2060 | 354.6343.3–362.1 | 192.6163.4–218.1 |
| 2061 | 354.6341.3–362.5 | 186.4158.8–216.8 |
| 2062 | 354.4340.8–361.3 | 192.3163.9–218.6 |
| 2063 | 355.4345.2–362.1 | 189.2165.2–220.3 |
| 2064 | 356.1344.6–362.9 | 197161.3–218 |
| 2065 | 355.5346.4–362.4 | 193.1165.8–225.2 |
| 2066 | 355.2344.5–361.2 | 201170.1–224.7 |
| 2067 | 355.3341.4–361.8 | 193.1164.2–223.7 |
| 2068 | 357.3346.3–363.6 | 198.6163.7–227.1 |
| 2069 | 355344.3–362.7 | 199.4165.8–225 |
| 2070 | 355.6344.2–362.3 | 198.7168–226.7 |
| 2071 | 356.8344.7–362.9 | 199.3167.9–233.5 |
| 2072 | 357.7346.2–363.1 | 202.3173.2–226.2 |
| 2073 | 356.6345.2–362.2 | 205.4168.2–233.4 |
| 2074 | 354.4342.1–362.7 | 198.2175.4–227.7 |
| 2075 | 356343.7–362.5 | 199.6168.9–228.3 |
| 2076 | 357.4348.5–363.3 | 198.8169.8–225.2 |
| 2077 | 358.1347.7–362.8 | 202172.2–231.2 |
| 2078 | 357.3346.8–363.2 | 203.5175.8–232.1 |
| 2079 | 357.4346.6–363.6 | 203.6172.2–236.1 |
| 2080 | 359.1349.4–364.7 | 204.7172.2–234.3 |
| 2081 | 358.8347.5–363.5 | 202.2174.9–231.3 |
| 2082 | 357346.9–363.4 | 204.3178.3–228.6 |
| 2083 | 357.8349.5–363.1 | 205.8170.7–238.3 |
| 2084 | 358.8349.3–363.4 | 208.1175.9–235.6 |
| 2085 | 359.7350.1–364 | 211.1179.4–241 |
| 2086 | 359347.7–363.8 | 203.3175.4–237 |
| 2087 | 358.8348.8–364.1 | 205.3181.2–237.7 |
| 2088 | 358347.4–363.7 | 211.6174.7–240.6 |
| 2089 | 357.4347.3–363.5 | 208.9180.5–237.8 |
| 2090 | 358.8346.1–363.9 | 209.4173.4–243 |
| 2091 | 358.3349.1–363.3 | 214.3179.7–244.8 |
| 2092 | 359.2347.5–364 | 213.2176.8–242.3 |
| 2093 | 359349.8–363.8 | 212.5177.8–242.2 |
| 2094 | 359.3350.1–363.1 | 211.8179.7–241.5 |
| 2095 | 358.1349.7–364 | 216.9185–243.8 |
| 2096 | 358.8348.3–365.1 | 213.1182–247.6 |
| 2097 | 358.9342.5–362.5 | 210.8174.9–242.1 |
| 2098 | 357.8348.1–363.6 | 214.4181.5–242.2 |
| 2099 | 359.2349.5–363.2 | 213.5181.9–244.1 |
| 2100 | 359.6348.3–363.8 | 213.3181.5–246.3 |
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
科特迪瓦与马拉维对比
健康
人口与社会
经济
教育
政治
冲突
军用
- 军费开支科特迪瓦:2025 年为 GDP 的 0.77%马拉维:2025 年为 GDP 的 1.15%
- 军费开支(美元)科特迪瓦:2025 年为 US$7.21亿马拉维:2025 年为 US$1.28亿
- 人均军费开支科特迪瓦:2025 年为 US$24马拉维:2025 年为 US$7
- 军费占政府支出比例科特迪瓦:2025 年为 3.8%(占政府支出)马拉维:2025 年为 3.8%(占政府支出)
- 武装部队人员科特迪瓦:2020 年为 27,000 人马拉维:2020 年为 15,000 人
- 国家实力科特迪瓦:2022 年为 0.16%(占全球实力)马拉维:2022 年为 0.07%(占全球实力)
- 武装部队占劳动力比例科特迪瓦:2020 年为 0.25%(占劳动力)马拉维:2020 年为 0.2%(占劳动力)
- 武器进口科特迪瓦:2025 年为 1500万 TIV马拉维:2024 年为 200万 TIV
- 武器出口科特迪瓦:1971 年为 100万 TIV马拉维:2000 年为 100万 TIV