埃塞俄比亚与马里对比
埃塞俄比亚与马里:热带夜
2014 年热带夜:埃塞俄比亚为 144.9 夜,马里为 250.2 夜(CMIP6 气候模型中位数模拟)。 2014 年马里的数值较高,高出 105.3 夜,是埃塞俄比亚的 1.73 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,马里的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年埃塞俄比亚为 201.7 夜,马里为 283.6 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 埃塞俄比亚 | 马里 |
|---|---|---|
| 2014 | 144.9 | 250.2 |
| 2013 | 145.1 | 247.3 |
| 2012 | 144.4 | 253.1 |
| 2011 | 145.6 | 251.9 |
| 2010 | 142.4 | 250.4 |
| 2009 | 140.3 | 248 |
| 2008 | 137.1 | 247.8 |
| 2007 | 138.2 | 248.1 |
| 2006 | 138.7 | 245.5 |
| 2005 | 138.1 | 244.3 |
| 2004 | 139.1 | 243.9 |
| 2003 | 138.8 | 247.1 |
| 2002 | 137.4 | 245.8 |
| 2001 | 139.2 | 245.6 |
| 2000 | 135.5 | 243.2 |
| 1999 | 132.6 | 242.4 |
| 1998 | 132.9 | 240.6 |
| 1997 | 132.7 | 240.7 |
| 1996 | 129.7 | 236.4 |
| 1995 | 127.8 | 238 |
| 1994 | 126.3 | 236.2 |
| 1993 | 122.5 | 235.1 |
| 1992 | 119.7 | 232 |
| 1991 | 129.5 | 238.7 |
| 1990 | 132.7 | 241 |
| 1989 | 129.4 | 236.3 |
| 1988 | 128.2 | 234.7 |
| 1987 | 126.4 | 236.1 |
| 1986 | 128.1 | 237.1 |
| 1985 | 122.8 | 235.3 |
| 1984 | 124.8 | 233 |
| 1983 | 120.6 | 231.2 |
| 1982 | 126.3 | 234.9 |
| 1981 | 127 | 233.9 |
| 1980 | 124.9 | 231.5 |
| 1979 | 125.1 | 233.8 |
| 1978 | 124.7 | 234.8 |
| 1977 | 125.8 | 233.6 |
| 1976 | 122 | 231.7 |
| 1975 | 119.5 | 232.4 |
| 1974 | 124 | 229.7 |
| 1973 | 125.2 | 230.3 |
| 1972 | 122.3 | 230.7 |
| 1971 | 120.6 | 229.5 |
| 1970 | 121.3 | 229.9 |
| 1969 | 120.4 | 227.3 |
| 1968 | 119.1 | 230.5 |
| 1967 | 118.1 | 229 |
| 1966 | 119.5 | 228.1 |
| 1965 | 117.4 | 230.2 |
| 1964 | 116.6 | 228.9 |
| 1963 | 115.7 | 228.2 |
| 1962 | 121.6 | 231.7 |
| 1961 | 124.2 | 231.6 |
| 1960 | 124.5 | 235.1 |
| 1959 | 121.6 | 231.8 |
| 1958 | 124.1 | 231.8 |
| 1957 | 123.2 | 233.3 |
| 1956 | 120.9 | 230.7 |
| 1955 | 122.8 | 230.6 |
| 1954 | 121.6 | 232 |
| 1953 | 121.2 | 228.3 |
| 1952 | 122.8 | 229.2 |
| 1951 | 123 | 231.4 |
| 1950 | 122 | 228.6 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 埃塞俄比亚 | 马里 |
|---|---|---|
| 2015 | 146.6129.4–163.9 | 247.9231.5–264.7 |
| 2016 | 144.1127–160.6 | 248231.3–262.6 |
| 2017 | 148.3129.2–164.9 | 252.7233.6–268.2 |
| 2018 | 149.6131.6–166 | 254.2236.4–269 |
| 2019 | 146.2129.3–166 | 251.6233.5–272.3 |
| 2020 | 149.4129.6–168.5 | 251.3231.2–270.7 |
| 2021 | 150.7132.1–170 | 254.8238.5–270 |
| 2022 | 154135.7–171.2 | 257237.8–275.3 |
| 2023 | 153.5135.4–171.4 | 254.2239.6–269.2 |
| 2024 | 156.5135.9–175.6 | 259.3242.3–276.8 |
| 2025 | 154132.6–175.5 | 256.2239.2–272.3 |
| 2026 | 153132–175 | 256.8237.2–277.8 |
| 2027 | 154.2134.4–175.3 | 258.5240.3–273.1 |
| 2028 | 157.5138.3–177.4 | 259.7243.6–273.9 |
| 2029 | 159.2141.8–176.8 | 260.8240.3–275.3 |
| 2030 | 156.8136.3–175.7 | 258.1237.5–272.6 |
| 2031 | 161.4142.4–179.1 | 262.2243.4–280.6 |
| 2032 | 161.7143.1–182.5 | 260.5242.1–278.2 |
| 2033 | 161.8140–180.9 | 262.1241.7–280.3 |
| 2034 | 158.8141.5–184.3 | 260.7242–275.3 |
| 2035 | 162141.7–184.2 | 261.5244.8–283.6 |
| 2036 | 160.5143.6–179.4 | 262.5244.6–281.1 |
| 2037 | 165145.8–184.5 | 264.5245.2–279.6 |
| 2038 | 167.1146.5–186.7 | 266246.7–283.2 |
| 2039 | 164.5143.9–186 | 262.3245–281.6 |
| 2040 | 165.9146.2–190.1 | 263.6247.5–279.6 |
| 2041 | 167.9146.3–189.3 | 264.6250.8–283.1 |
| 2042 | 167.7146–194.3 | 265.7245.9–283.5 |
| 2043 | 167.3145.5–190.8 | 264.8246.9–278.8 |
| 2044 | 168.2148.2–189.9 | 269.3247.4–284.7 |
| 2045 | 170.7149.1–192.3 | 265.6248.9–283.7 |
| 2046 | 175.3150–198.6 | 269.8247.5–286.4 |
| 2047 | 176.9151.8–197.5 | 271.9251.2–290.3 |
| 2048 | 177.5155.4–199.1 | 270.4254.4–288.2 |
| 2049 | 177.5157.9–198.4 | 272252.1–288.2 |
| 2050 | 176.4153.8–199 | 269.5250.6–286.4 |
| 2051 | 176.6155.3–199.7 | 268.8251.7–286.9 |
| 2052 | 177155.6–200.7 | 270.1252.7–292.1 |
| 2053 | 176.7154.2–201.6 | 269.3249.2–288.8 |
| 2054 | 177.6156.9–201.1 | 270.3251.7–290.6 |
| 2055 | 180.6155.2–202.3 | 270.9252.7–288.1 |
| 2056 | 177.3155–205.4 | 273248.6–291.4 |
| 2057 | 180.3159.3–205.5 | 275.5255.2–295 |
| 2058 | 182.6153.7–209.4 | 271252.7–293.2 |
| 2059 | 185.7160.1–210.6 | 274.5259.3–299.6 |
| 2060 | 185.9160.3–210.4 | 273.5258–293.7 |
| 2061 | 183.3158.3–211.7 | 275.4257–298 |
| 2062 | 183.8155.4–213 | 270.8251.7–291.8 |
| 2063 | 184.5159.1–208.6 | 275.9256.6–292.2 |
| 2064 | 186.7160.6–207.2 | 276.4256.6–298.4 |
| 2065 | 183.7162.4–212.9 | 275.3256–295.1 |
| 2066 | 187.1165.4–210.1 | 276.9260–296.5 |
| 2067 | 187.1160.7–214.5 | 272.6255.4–293.3 |
| 2068 | 187.6160.4–215.8 | 277.5258.1–296.5 |
| 2069 | 187.8165.4–215.8 | 276.1257.7–293.3 |
| 2070 | 187.9161.6–216.9 | 277.2256.6–296.6 |
| 2071 | 192.7165.2–219.5 | 277.2258.4–295.6 |
| 2072 | 193.6167.4–214.5 | 281.9263.8–298.9 |
| 2073 | 193.3169.7–218.7 | 276.8257.9–296.8 |
| 2074 | 188.5163.9–219 | 277.7258.7–295.9 |
| 2075 | 191.9162.7–218.6 | 278.5260.1–298.5 |
| 2076 | 195166.9–218.9 | 278.1261.1–294.2 |
| 2077 | 194.1169.3–223.3 | 283.8263.1–302.3 |
| 2078 | 192.1168.4–218.6 | 283.8263.5–299.4 |
| 2079 | 193.4166.6–220.9 | 278.9259.2–300.6 |
| 2080 | 196.1169.2–222.4 | 281.2262.1–299.4 |
| 2081 | 194.6171–221.4 | 279.1259.3–301.8 |
| 2082 | 195.4168.8–219.9 | 280.2260.2–298.4 |
| 2083 | 194.6168.2–228.7 | 280.8260.8–302.3 |
| 2084 | 198.5170.7–224.2 | 280.4263.8–301 |
| 2085 | 198.4173.1–226.3 | 284.6259.2–303 |
| 2086 | 198.6172.3–228.4 | 281.9262.8–302.4 |
| 2087 | 199170.6–226.6 | 279.7258.8–302.8 |
| 2088 | 199170.7–227.7 | 282.3260.7–303.3 |
| 2089 | 198.6171.2–226.2 | 283.4262.4–300.5 |
| 2090 | 198.6173.4–227.7 | 283.9259.8–301.9 |
| 2091 | 203.6171.9–232.1 | 283.1260.4–304.8 |
| 2092 | 200.7172.5–229.7 | 281.6259.7–303.1 |
| 2093 | 201.4175.2–228.6 | 284.8265.8–305.4 |
| 2094 | 200.2174–228.9 | 284.6262.8–305.6 |
| 2095 | 203.9175.7–231.9 | 283.6262–304.6 |
| 2096 | 199.1170.5–230.8 | 284.9263.3–306.3 |
| 2097 | 198.4171.8–229.3 | 280261–300.5 |
| 2098 | 198.7172.1–231.5 | 282.5262–302.1 |
| 2099 | 201.8172.8–233.3 | 285.3266.2–305.4 |
| 2100 | 201.7175.1–231.8 | 283.6262.8–304.1 |
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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
埃塞俄比亚与马里对比
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军用
- 军费开支埃塞俄比亚:2025 年为 GDP 的 0.49%马里:2025 年为 GDP 的 3.87%
- 军费开支(美元)埃塞俄比亚:2025 年为 US$7.85亿马里:2025 年为 US$8.83亿
- 人均军费开支埃塞俄比亚:2025 年为 US$4马里:2025 年为 US$38
- 军费占政府支出比例埃塞俄比亚:2025 年为 4.1%(占政府支出)马里:2025 年为 14.8%(占政府支出)
- 武装部队人员埃塞俄比亚:2020 年为 138,000 人马里:2020 年为 41,000 人
- 国家实力埃塞俄比亚:2022 年为 0.85%(占全球实力)马里:2022 年为 0.1%(占全球实力)
- 武装部队占劳动力比例埃塞俄比亚:2020 年为 0.28%(占劳动力)马里:2020 年为 0.54%(占劳动力)
- 武器进口埃塞俄比亚:2025 年为 6300万 TIV马里:2025 年为 6400万 TIV