几内亚与马拉维对比
几内亚与马拉维:热带夜
2014 年热带夜:几内亚为 286.6 夜,马拉维为 138.1 夜(CMIP6 气候模型中位数模拟)。 2014 年几内亚的数值较高,高出 148.5 夜,是马拉维的 2.08 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,几内亚的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年几内亚为 345.3 夜,马拉维为 213.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 几内亚 | 马拉维 |
|---|---|---|
| 2014 | 286.6 | 138.1 |
| 2013 | 285.3 | 138.9 |
| 2012 | 292.9 | 137.4 |
| 2011 | 288.8 | 136.6 |
| 2010 | 285.2 | 132.4 |
| 2009 | 282.5 | 131.4 |
| 2008 | 279 | 130.8 |
| 2007 | 278.9 | 132.8 |
| 2006 | 278.8 | 129.8 |
| 2005 | 278.9 | 129.5 |
| 2004 | 276 | 133.4 |
| 2003 | 279.6 | 132.5 |
| 2002 | 277.1 | 130.3 |
| 2001 | 279.8 | 134 |
| 2000 | 273.1 | 126.6 |
| 1999 | 267 | 124.8 |
| 1998 | 268.4 | 127.1 |
| 1997 | 266.6 | 124.2 |
| 1996 | 260.4 | 121.3 |
| 1995 | 260.3 | 120.9 |
| 1994 | 255 | 118.4 |
| 1993 | 246.6 | 113.8 |
| 1992 | 242.4 | 114.1 |
| 1991 | 264.3 | 120.9 |
| 1990 | 266.4 | 123.8 |
| 1989 | 259.7 | 120.5 |
| 1988 | 256.9 | 120.8 |
| 1987 | 258.4 | 118.8 |
| 1986 | 259.9 | 121.1 |
| 1985 | 252.6 | 115.7 |
| 1984 | 249.6 | 116.2 |
| 1983 | 248.4 | 115.5 |
| 1982 | 250 | 115.1 |
| 1981 | 253.5 | 119 |
| 1980 | 251.2 | 116.9 |
| 1979 | 251.2 | 117.7 |
| 1978 | 252 | 114.8 |
| 1977 | 250.4 | 117.2 |
| 1976 | 244 | 114 |
| 1975 | 242.3 | 114 |
| 1974 | 247.2 | 115.2 |
| 1973 | 249.3 | 114.7 |
| 1972 | 246.1 | 113.8 |
| 1971 | 244.5 | 114.1 |
| 1970 | 249 | 115.8 |
| 1969 | 241.2 | 114.3 |
| 1968 | 241.5 | 110 |
| 1967 | 233.3 | 109.8 |
| 1966 | 237.7 | 111 |
| 1965 | 239.8 | 111.5 |
| 1964 | 231 | 106.3 |
| 1963 | 225.8 | 107.5 |
| 1962 | 246.9 | 114.7 |
| 1961 | 246 | 116 |
| 1960 | 250.5 | 117.4 |
| 1959 | 244.8 | 115.6 |
| 1958 | 245.6 | 116.4 |
| 1957 | 247.5 | 114.6 |
| 1956 | 242.4 | 111.4 |
| 1955 | 243.5 | 115.2 |
| 1954 | 250.2 | 113.9 |
| 1953 | 241.2 | 113 |
| 1952 | 240.3 | 113.5 |
| 1951 | 248.8 | 113.5 |
| 1950 | 240.8 | 112.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 几内亚 | 马拉维 |
|---|---|---|
| 2015 | 286.7259.9–308.5 | 145.7126.7–164.3 |
| 2016 | 288.9262.6–304 | 139.8122.6–157.4 |
| 2017 | 291.6265.5–311.4 | 143.6127–161.8 |
| 2018 | 295.6269.3–311.8 | 143.1124.6–162.6 |
| 2019 | 291.8266.8–313.6 | 143.8128.3–161.4 |
| 2020 | 291.2265.6–315.4 | 145127.3–165.8 |
| 2021 | 295.8268–316.3 | 145.3128–163.6 |
| 2022 | 299.9277.9–322.4 | 151130.1–169.1 |
| 2023 | 296273.8–318 | 149.2129.5–171.2 |
| 2024 | 302.3276.9–322.8 | 152.4130–172.6 |
| 2025 | 298.9275.2–322.4 | 151.1129.7–170.4 |
| 2026 | 302.5269.3–323.9 | 151.1126.2–173.8 |
| 2027 | 302.6276.3–320.2 | 154.4135.1–173.1 |
| 2028 | 308.2285.4–325.8 | 155.5134.6–174 |
| 2029 | 309.3280.6–327.2 | 159.8139.2–178.5 |
| 2030 | 305.5277.4–322.4 | 155.6138.7–174.5 |
| 2031 | 313.2282.2–329.6 | 161.1143.4–177.6 |
| 2032 | 307.7287.3–329.5 | 160.8141.3–181.3 |
| 2033 | 310.4282.4–337.8 | 161.3135.6–179.2 |
| 2034 | 308281.7–327.4 | 160.9138.9–185 |
| 2035 | 311.2284.9–333 | 164.3140.4–189.5 |
| 2036 | 312.8285.7–334.5 | 163.8137.6–182.5 |
| 2037 | 315.5291.8–331.1 | 166.9144.6–189.2 |
| 2038 | 317.9296.3–333.9 | 172.2148.4–191.2 |
| 2039 | 314.1291.6–336 | 164.8147.3–188.2 |
| 2040 | 316.1292.9–334.6 | 164.4146.4–189.7 |
| 2041 | 315.4296.5–335.7 | 169.3143.7–192.5 |
| 2042 | 316290.7–336.6 | 169.8146.3–197.8 |
| 2043 | 314.8291.1–332.7 | 167.5147.1–193.2 |
| 2044 | 319.8289.7–337.5 | 172.6148.3–197 |
| 2045 | 318.6296.4–339 | 170.4153.1–194.7 |
| 2046 | 321.4295.7–337 | 176.3151.2–203.1 |
| 2047 | 324.6297.9–342.8 | 178.7157.8–200.9 |
| 2048 | 324.8304.4–341.1 | 180.7158.9–204.1 |
| 2049 | 324.2302.4–340.2 | 176.7154–205.4 |
| 2050 | 322.4299.7–339.6 | 180.4155.2–204.9 |
| 2051 | 326.1300.4–342 | 182.9162.1–207.4 |
| 2052 | 324301.5–342.8 | 184.9163.2–209.6 |
| 2053 | 325.6298–345.3 | 177.2149.6–207.4 |
| 2054 | 329.5301.3–345.1 | 185.1157.1–208 |
| 2055 | 324.4305.3–342.4 | 186.1159.2–212.6 |
| 2056 | 329.6299.4–349.4 | 184.6158.5–214.3 |
| 2057 | 332.4301.5–351 | 184.7159.3–212.3 |
| 2058 | 328.8305.6–347.6 | 188.5163.8–214.7 |
| 2059 | 330.3310.8–350.5 | 189.8166.9–218.5 |
| 2060 | 328.3309.4–348.2 | 192.6163.4–218.1 |
| 2061 | 330.5304.6–352.8 | 186.4158.8–216.8 |
| 2062 | 327.7307.3–346.5 | 192.3163.9–218.6 |
| 2063 | 333.4311–349.1 | 189.2165.2–220.3 |
| 2064 | 330.9310.6–351.6 | 197161.3–218 |
| 2065 | 331.4309.7–350.6 | 193.1165.8–225.2 |
| 2066 | 331.8312.3–347.4 | 201170.1–224.7 |
| 2067 | 329.1304–348.6 | 193.1164.2–223.7 |
| 2068 | 335.4309.6–354.5 | 198.6163.7–227.1 |
| 2069 | 333.5313–351.4 | 199.4165.8–225 |
| 2070 | 331.7310.9–352.7 | 198.7168–226.7 |
| 2071 | 334.6315.6–352.4 | 199.3167.9–233.5 |
| 2072 | 338.3317–353.2 | 202.3173.2–226.2 |
| 2073 | 334309.7–351.6 | 205.4168.2–233.4 |
| 2074 | 330.2310.6–352 | 198.2175.4–227.7 |
| 2075 | 334312–352.2 | 199.6168.9–228.3 |
| 2076 | 338.4321.3–352.1 | 198.8169.8–225.2 |
| 2077 | 341.4318.4–355.6 | 202172.2–231.2 |
| 2078 | 338.1316.6–355.8 | 203.5175.8–232.1 |
| 2079 | 337.5318.8–355.3 | 203.6172.2–236.1 |
| 2080 | 339.8315.4–358 | 204.7172.2–234.3 |
| 2081 | 339.3318.2–356.6 | 202.2174.9–231.3 |
| 2082 | 337.9316.1–353.3 | 204.3178.3–228.6 |
| 2083 | 339.2320.8–355.8 | 205.8170.7–238.3 |
| 2084 | 340.5321–354.6 | 208.1175.9–235.6 |
| 2085 | 343.8319.9–358.1 | 211.1179.4–241 |
| 2086 | 342.2318.7–358.7 | 203.3175.4–237 |
| 2087 | 340.7319.9–357.6 | 205.3181.2–237.7 |
| 2088 | 341.2318.3–354.9 | 211.6174.7–240.6 |
| 2089 | 337.9318.6–354.8 | 208.9180.5–237.8 |
| 2090 | 341.1315–356 | 209.4173.4–243 |
| 2091 | 339.7319.7–355.5 | 214.3179.7–244.8 |
| 2092 | 339.7320.4–356.8 | 213.2176.8–242.3 |
| 2093 | 341.8325.1–356.2 | 212.5177.8–242.2 |
| 2094 | 342.2324–356.4 | 211.8179.7–241.5 |
| 2095 | 340.7323.5–359.3 | 216.9185–243.8 |
| 2096 | 343.2324–359.7 | 213.1182–247.6 |
| 2097 | 340.3313.8–353.8 | 210.8174.9–242.1 |
| 2098 | 339.9318.8–357 | 214.4181.5–242.2 |
| 2099 | 341.5324.6–355.9 | 213.5181.9–244.1 |
| 2100 | 345.3319.6–357.9 | 213.3181.5–246.3 |
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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
几内亚与马拉维对比
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冲突
军用
- 军费开支几内亚:2025 年为 GDP 的 2.03%马拉维:2025 年为 GDP 的 1.15%
- 军费开支(美元)几内亚:2025 年为 US$5.86亿马拉维:2025 年为 US$1.28亿
- 人均军费开支几内亚:2025 年为 US$40马拉维:2025 年为 US$7
- 军费占政府支出比例几内亚:2025 年为 10.6%(占政府支出)马拉维:2025 年为 3.8%(占政府支出)
- 武装部队人员几内亚:2020 年为 13,000 人马拉维:2020 年为 15,000 人
- 国家实力几内亚:2022 年为 0.07%(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几内亚:2020 年为 0.32%(占劳动力)马拉维:2020 年为 0.2%(占劳动力)
- 武器进口几内亚:2025 年为 600万 TIV马拉维:2024 年为 200万 TIV