马里与塞内加尔对比
马里与塞内加尔:热带夜
2014 年热带夜:马里为 250.2 夜,塞内加尔为 302.1 夜(CMIP6 气候模型中位数模拟)。 2014 年塞内加尔的数值较高,高出 51.9 夜,是马里的 1.21 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,塞内加尔的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年马里为 283.6 夜,塞内加尔为 347.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 马里 | 塞内加尔 |
|---|---|---|
| 2014 | 250.2 | 302.1 |
| 2013 | 247.3 | 300.9 |
| 2012 | 253.1 | 304.1 |
| 2011 | 251.9 | 302.1 |
| 2010 | 250.4 | 301.5 |
| 2009 | 248 | 302.1 |
| 2008 | 247.8 | 298.3 |
| 2007 | 248.1 | 298.5 |
| 2006 | 245.5 | 298.6 |
| 2005 | 244.3 | 298.1 |
| 2004 | 243.9 | 294.7 |
| 2003 | 247.1 | 296.1 |
| 2002 | 245.8 | 296 |
| 2001 | 245.6 | 298.9 |
| 2000 | 243.2 | 295 |
| 1999 | 242.4 | 293.2 |
| 1998 | 240.6 | 292.5 |
| 1997 | 240.7 | 288.5 |
| 1996 | 236.4 | 285.1 |
| 1995 | 238 | 285.9 |
| 1994 | 236.2 | 283.7 |
| 1993 | 235.1 | 282 |
| 1992 | 232 | 277.6 |
| 1991 | 238.7 | 286.7 |
| 1990 | 241 | 292.5 |
| 1989 | 236.3 | 282.1 |
| 1988 | 234.7 | 282.4 |
| 1987 | 236.1 | 281.8 |
| 1986 | 237.1 | 283 |
| 1985 | 235.3 | 278.1 |
| 1984 | 233 | 274.6 |
| 1983 | 231.2 | 276.3 |
| 1982 | 234.9 | 281.3 |
| 1981 | 233.9 | 277.9 |
| 1980 | 231.5 | 277.6 |
| 1979 | 233.8 | 281 |
| 1978 | 234.8 | 280.7 |
| 1977 | 233.6 | 278 |
| 1976 | 231.7 | 274.4 |
| 1975 | 232.4 | 278.4 |
| 1974 | 229.7 | 273.8 |
| 1973 | 230.3 | 274.5 |
| 1972 | 230.7 | 273.5 |
| 1971 | 229.5 | 273.4 |
| 1970 | 229.9 | 271.3 |
| 1969 | 227.3 | 271.6 |
| 1968 | 230.5 | 272.6 |
| 1967 | 229 | 275.4 |
| 1966 | 228.1 | 273.3 |
| 1965 | 230.2 | 272.8 |
| 1964 | 228.9 | 271.8 |
| 1963 | 228.2 | 272.8 |
| 1962 | 231.7 | 280.2 |
| 1961 | 231.6 | 276.9 |
| 1960 | 235.1 | 279.2 |
| 1959 | 231.8 | 277.4 |
| 1958 | 231.8 | 278.8 |
| 1957 | 233.3 | 274.4 |
| 1956 | 230.7 | 273.2 |
| 1955 | 230.6 | 273.4 |
| 1954 | 232 | 275 |
| 1953 | 228.3 | 271.7 |
| 1952 | 229.2 | 271 |
| 1951 | 231.4 | 272.9 |
| 1950 | 228.6 | 270.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 马里 | 塞内加尔 |
|---|---|---|
| 2015 | 247.9231.5–264.7 | 298.9275.9–321 |
| 2016 | 248231.3–262.6 | 302.7276.5–319 |
| 2017 | 252.7233.6–268.2 | 302.9285.4–318.6 |
| 2018 | 254.2236.4–269 | 305.6289.2–321.5 |
| 2019 | 251.6233.5–272.3 | 307.6280.6–328.1 |
| 2020 | 251.3231.2–270.7 | 305.2276.2–322.9 |
| 2021 | 254.8238.5–270 | 307.6286–325.6 |
| 2022 | 257237.8–275.3 | 312.9289.6–334.3 |
| 2023 | 254.2239.6–269.2 | 307.5292.2–328.6 |
| 2024 | 259.3242.3–276.8 | 313.2294.6–326.9 |
| 2025 | 256.2239.2–272.3 | 311.8289–329.4 |
| 2026 | 256.8237.2–277.8 | 308.3285.2–328.6 |
| 2027 | 258.5240.3–273.1 | 310.7287.8–330 |
| 2028 | 259.7243.6–273.9 | 316.3289.2–331.6 |
| 2029 | 260.8240.3–275.3 | 315.7291.2–334.2 |
| 2030 | 258.1237.5–272.6 | 311.5289.1–329.1 |
| 2031 | 262.2243.4–280.6 | 318.8296.3–335 |
| 2032 | 260.5242.1–278.2 | 316295.7–332.4 |
| 2033 | 262.1241.7–280.3 | 316.7289.6–336.4 |
| 2034 | 260.7242–275.3 | 315.4291.6–335.1 |
| 2035 | 261.5244.8–283.6 | 316.8291.1–335.3 |
| 2036 | 262.5244.6–281.1 | 320.8298.5–335.3 |
| 2037 | 264.5245.2–279.6 | 324.5303.1–337.7 |
| 2038 | 266246.7–283.2 | 323.5304.2–339.7 |
| 2039 | 262.3245–281.6 | 323.3300.9–337 |
| 2040 | 263.6247.5–279.6 | 322.4298.9–339.5 |
| 2041 | 264.6250.8–283.1 | 320.2300.1–343.6 |
| 2042 | 265.7245.9–283.5 | 320302.1–339.9 |
| 2043 | 264.8246.9–278.8 | 320.4303.7–340.4 |
| 2044 | 269.3247.4–284.7 | 326.9301.5–340.9 |
| 2045 | 265.6248.9–283.7 | 324.1304.1–340 |
| 2046 | 269.8247.5–286.4 | 325.9304.7–340.6 |
| 2047 | 271.9251.2–290.3 | 329301.4–347 |
| 2048 | 270.4254.4–288.2 | 331.1314.3–344.8 |
| 2049 | 272252.1–288.2 | 331.3308.3–343.7 |
| 2050 | 269.5250.6–286.4 | 327.6306.5–341.9 |
| 2051 | 268.8251.7–286.9 | 328307.1–344 |
| 2052 | 270.1252.7–292.1 | 325.4308.1–344.2 |
| 2053 | 269.3249.2–288.8 | 331.8304.9–347.2 |
| 2054 | 270.3251.7–290.6 | 330.1310.8–345.2 |
| 2055 | 270.9252.7–288.1 | 330.1305.5–344 |
| 2056 | 273248.6–291.4 | 331.4307.4–349.8 |
| 2057 | 275.5255.2–295 | 337306.4–351.5 |
| 2058 | 271252.7–293.2 | 333313.2–350.2 |
| 2059 | 274.5259.3–299.6 | 334315.6–353.5 |
| 2060 | 273.5258–293.7 | 334.5316.4–351.1 |
| 2061 | 275.4257–298 | 333.7307.5–352.9 |
| 2062 | 270.8251.7–291.8 | 333.3312.4–350.2 |
| 2063 | 275.9256.6–292.2 | 335.4313.2–352.8 |
| 2064 | 276.4256.6–298.4 | 335.4307.1–351.1 |
| 2065 | 275.3256–295.1 | 334.8314.1–352.8 |
| 2066 | 276.9260–296.5 | 337.3312.9–351 |
| 2067 | 272.6255.4–293.3 | 335.5309.9–349.9 |
| 2068 | 277.5258.1–296.5 | 335.5313.5–354 |
| 2069 | 276.1257.7–293.3 | 336.1316.9–351.8 |
| 2070 | 277.2256.6–296.6 | 333.3312.9–352.9 |
| 2071 | 277.2258.4–295.6 | 335.7321.1–351.9 |
| 2072 | 281.9263.8–298.9 | 342.3321–354.6 |
| 2073 | 276.8257.9–296.8 | 339.4320.1–356.1 |
| 2074 | 277.7258.7–295.9 | 335.9317.1–351.8 |
| 2075 | 278.5260.1–298.5 | 338.4320.7–354.1 |
| 2076 | 278.1261.1–294.2 | 338.7321.9–352 |
| 2077 | 283.8263.1–302.3 | 342.8314.8–357.3 |
| 2078 | 283.8263.5–299.4 | 343325.8–355.4 |
| 2079 | 278.9259.2–300.6 | 341.2322.3–357.6 |
| 2080 | 281.2262.1–299.4 | 340.9317.7–358.1 |
| 2081 | 279.1259.3–301.8 | 339.8315.5–357.1 |
| 2082 | 280.2260.2–298.4 | 341.6316.4–354.9 |
| 2083 | 280.8260.8–302.3 | 340.8324.8–356.9 |
| 2084 | 280.4263.8–301 | 340.4322.8–354.9 |
| 2085 | 284.6259.2–303 | 346.8325.6–357 |
| 2086 | 281.9262.8–302.4 | 341.7324.4–357.6 |
| 2087 | 279.7258.8–302.8 | 343.9325.9–357.7 |
| 2088 | 282.3260.7–303.3 | 341.5321.6–358.2 |
| 2089 | 283.4262.4–300.5 | 343.2324.3–355.2 |
| 2090 | 283.9259.8–301.9 | 342320.6–356 |
| 2091 | 283.1260.4–304.8 | 341.7319.8–356.4 |
| 2092 | 281.6259.7–303.1 | 339.7318.4–357.7 |
| 2093 | 284.8265.8–305.4 | 345326.8–356.4 |
| 2094 | 284.6262.8–305.6 | 344.4324.3–357.6 |
| 2095 | 283.6262–304.6 | 346.3320.6–359.4 |
| 2096 | 284.9263.3–306.3 | 344.4323.1–359.2 |
| 2097 | 280261–300.5 | 341.4321.3–353.8 |
| 2098 | 282.5262–302.1 | 345322.3–357 |
| 2099 | 285.3266.2–305.4 | 344.6322.7–357.5 |
| 2100 | 283.6262.8–304.1 | 347.3323.6–359.2 |
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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
马里与塞内加尔对比
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冲突
军用
- 军费开支马里:2025 年为 GDP 的 3.87%塞内加尔:2025 年为 GDP 的 1.56%
- 军费开支(美元)马里:2025 年为 US$8.83亿塞内加尔:2025 年为 US$5.33亿
- 人均军费开支马里:2025 年为 US$38塞内加尔:2025 年为 US$30
- 军费占政府支出比例马里:2025 年为 14.8%(占政府支出)塞内加尔:2025 年为 5.2%(占政府支出)
- 武装部队人员马里:2020 年为 41,000 人塞内加尔:2020 年为 19,000 人
- 国家实力马里:2022 年为 0.1%(占全球实力)塞内加尔:2022 年为 0.1%(占全球实力)
- 武装部队占劳动力比例马里:2020 年为 0.54%(占劳动力)塞内加尔:2020 年为 0.37%(占劳动力)
- 武器进口马里:2025 年为 6400万 TIV塞内加尔:2024 年为 7900万 TIV