马达加斯加与马拉维对比
马达加斯加与马拉维:热带夜
2014 年热带夜:马达加斯加为 138.3 夜,马拉维为 138.1 夜(CMIP6 气候模型中位数模拟)。 2014 年马达加斯加的数值较高,高出 0.2 夜,是马拉维的 1 倍。
每年夜数 · CMIP6
数据解读
- 自 2014 年超过马拉维以来,马达加斯加的数值一直更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年马达加斯加为 198.5 夜,马拉维为 213.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 马达加斯加 | 马拉维 |
|---|---|---|
| 2014 | 138.3 | 138.1 |
| 2013 | 138 | 138.9 |
| 2012 | 138.3 | 137.4 |
| 2011 | 136.8 | 136.6 |
| 2010 | 134.2 | 132.4 |
| 2009 | 133.5 | 131.4 |
| 2008 | 132.3 | 130.8 |
| 2007 | 133.1 | 132.8 |
| 2006 | 131.6 | 129.8 |
| 2005 | 130.3 | 129.5 |
| 2004 | 133.5 | 133.4 |
| 2003 | 131 | 132.5 |
| 2002 | 131.8 | 130.3 |
| 2001 | 131.7 | 134 |
| 2000 | 127.4 | 126.6 |
| 1999 | 128.4 | 124.8 |
| 1998 | 128.6 | 127.1 |
| 1997 | 125.3 | 124.2 |
| 1996 | 121.8 | 121.3 |
| 1995 | 123.3 | 120.9 |
| 1994 | 121.8 | 118.4 |
| 1993 | 116 | 113.8 |
| 1992 | 116.6 | 114.1 |
| 1991 | 124.9 | 120.9 |
| 1990 | 126.2 | 123.8 |
| 1989 | 124 | 120.5 |
| 1988 | 123.8 | 120.8 |
| 1987 | 122.8 | 118.8 |
| 1986 | 123.8 | 121.1 |
| 1985 | 120 | 115.7 |
| 1984 | 118.6 | 116.2 |
| 1983 | 116.5 | 115.5 |
| 1982 | 121.8 | 115.1 |
| 1981 | 122.1 | 119 |
| 1980 | 120.3 | 116.9 |
| 1979 | 120.7 | 117.7 |
| 1978 | 119.3 | 114.8 |
| 1977 | 119 | 117.2 |
| 1976 | 117.4 | 114 |
| 1975 | 116.5 | 114 |
| 1974 | 119.5 | 115.2 |
| 1973 | 119 | 114.7 |
| 1972 | 117 | 113.8 |
| 1971 | 116.3 | 114.1 |
| 1970 | 117 | 115.8 |
| 1969 | 116.3 | 114.3 |
| 1968 | 113.1 | 110 |
| 1967 | 113 | 109.8 |
| 1966 | 114.1 | 111 |
| 1965 | 112.2 | 111.5 |
| 1964 | 109.6 | 106.3 |
| 1963 | 109.7 | 107.5 |
| 1962 | 115.3 | 114.7 |
| 1961 | 118.5 | 116 |
| 1960 | 118.2 | 117.4 |
| 1959 | 119 | 115.6 |
| 1958 | 118.7 | 116.4 |
| 1957 | 117.6 | 114.6 |
| 1956 | 115.5 | 111.4 |
| 1955 | 116.6 | 115.2 |
| 1954 | 115.9 | 113.9 |
| 1953 | 116.4 | 113 |
| 1952 | 117.4 | 113.5 |
| 1951 | 116 | 113.5 |
| 1950 | 116.3 | 112.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 马达加斯加 | 马拉维 |
|---|---|---|
| 2015 | 142.8126.7–159.3 | 145.7126.7–164.3 |
| 2016 | 137.8122.2–156 | 139.8122.6–157.4 |
| 2017 | 143.1125.6–159.4 | 143.6127–161.8 |
| 2018 | 143.7125.9–160.3 | 143.1124.6–162.6 |
| 2019 | 143.4124.4–162.3 | 143.8128.3–161.4 |
| 2020 | 143.4125.2–159 | 145127.3–165.8 |
| 2021 | 145.4128.8–160.4 | 145.3128–163.6 |
| 2022 | 150.4133.4–165.2 | 151130.1–169.1 |
| 2023 | 149.7132.1–166 | 149.2129.5–171.2 |
| 2024 | 150.7131.4–167.9 | 152.4130–172.6 |
| 2025 | 149128.8–169.1 | 151.1129.7–170.4 |
| 2026 | 150.1127.4–169.9 | 151.1126.2–173.8 |
| 2027 | 151.8131.9–170.8 | 154.4135.1–173.1 |
| 2028 | 154.9137.7–173.1 | 155.5134.6–174 |
| 2029 | 155.7135.2–173.8 | 159.8139.2–178.5 |
| 2030 | 154.8136.4–171.3 | 155.6138.7–174.5 |
| 2031 | 158.1141.3–174.8 | 161.1143.4–177.6 |
| 2032 | 157.9136.2–178.4 | 160.8141.3–181.3 |
| 2033 | 158.9136.7–177.8 | 161.3135.6–179.2 |
| 2034 | 158.6140.6–179.6 | 160.9138.9–185 |
| 2035 | 161.1140.2–181.6 | 164.3140.4–189.5 |
| 2036 | 159.5139.4–177.1 | 163.8137.6–182.5 |
| 2037 | 165.8144.7–182.8 | 166.9144.6–189.2 |
| 2038 | 166.5149.3–183.9 | 172.2148.4–191.2 |
| 2039 | 164.1145.1–183.9 | 164.8147.3–188.2 |
| 2040 | 162.8144.5–184.8 | 164.4146.4–189.7 |
| 2041 | 165.8143.5–183.9 | 169.3143.7–192.5 |
| 2042 | 165.1144.3–188.4 | 169.8146.3–197.8 |
| 2043 | 165.6148.5–184.7 | 167.5147.1–193.2 |
| 2044 | 167.3145.8–187 | 172.6148.3–197 |
| 2045 | 166.9147.1–187.1 | 170.4153.1–194.7 |
| 2046 | 171.4149.6–193 | 176.3151.2–203.1 |
| 2047 | 171.7148.8–193.4 | 178.7157.8–200.9 |
| 2048 | 173.7151.7–193.6 | 180.7158.9–204.1 |
| 2049 | 172.2151.4–192.9 | 176.7154–205.4 |
| 2050 | 174.4150.5–193.6 | 180.4155.2–204.9 |
| 2051 | 175154.3–195.1 | 182.9162.1–207.4 |
| 2052 | 176153.8–196.7 | 184.9163.2–209.6 |
| 2053 | 176.6151.1–197.8 | 177.2149.6–207.4 |
| 2054 | 175.5152.8–199.2 | 185.1157.1–208 |
| 2055 | 179.2157.3–196.8 | 186.1159.2–212.6 |
| 2056 | 178.8156.5–199.7 | 184.6158.5–214.3 |
| 2057 | 177.7155.5–201 | 184.7159.3–212.3 |
| 2058 | 180.5158.9–202.4 | 188.5163.8–214.7 |
| 2059 | 181.8158.3–202.5 | 189.8166.9–218.5 |
| 2060 | 185.1159.5–207.8 | 192.6163.4–218.1 |
| 2061 | 180.6157.6–203.8 | 186.4158.8–216.8 |
| 2062 | 180.6157.1–205.6 | 192.3163.9–218.6 |
| 2063 | 185156.8–210.7 | 189.2165.2–220.3 |
| 2064 | 184.7159.1–205.7 | 197161.3–218 |
| 2065 | 183.8157.1–208.5 | 193.1165.8–225.2 |
| 2066 | 187.3159.6–211 | 201170.1–224.7 |
| 2067 | 184.9155.9–208.9 | 193.1164.2–223.7 |
| 2068 | 187.5161.7–211.1 | 198.6163.7–227.1 |
| 2069 | 187.5162–211.3 | 199.4165.8–225 |
| 2070 | 187.8160.4–213.6 | 198.7168–226.7 |
| 2071 | 190.7162.7–216.6 | 199.3167.9–233.5 |
| 2072 | 191.8168.2–215.8 | 202.3173.2–226.2 |
| 2073 | 191.4168.7–214.5 | 205.4168.2–233.4 |
| 2074 | 189.4162.6–217.7 | 198.2175.4–227.7 |
| 2075 | 189.3163.8–214.2 | 199.6168.9–228.3 |
| 2076 | 191.1164.3–214 | 198.8169.8–225.2 |
| 2077 | 191.9168.8–217.1 | 202172.2–231.2 |
| 2078 | 190.1166.5–219.3 | 203.5175.8–232.1 |
| 2079 | 190.1163.7–216.2 | 203.6172.2–236.1 |
| 2080 | 194.8167.7–219.4 | 204.7172.2–234.3 |
| 2081 | 191.7166.7–218.1 | 202.2174.9–231.3 |
| 2082 | 193.8169.2–216.7 | 204.3178.3–228.6 |
| 2083 | 194.6166.1–218.1 | 205.8170.7–238.3 |
| 2084 | 197.9170–219.7 | 208.1175.9–235.6 |
| 2085 | 197.8172.3–223.7 | 211.1179.4–241 |
| 2086 | 192.9169.6–220 | 203.3175.4–237 |
| 2087 | 195.2170.4–220.1 | 205.3181.2–237.7 |
| 2088 | 198.1165.1–225.5 | 211.6174.7–240.6 |
| 2089 | 196.3167.9–227.6 | 208.9180.5–237.8 |
| 2090 | 197.5172.4–228.1 | 209.4173.4–243 |
| 2091 | 199.2172.7–226.7 | 214.3179.7–244.8 |
| 2092 | 202.4170.7–226.6 | 213.2176.8–242.3 |
| 2093 | 202.1172.3–230.5 | 212.5177.8–242.2 |
| 2094 | 198.3168.6–224 | 211.8179.7–241.5 |
| 2095 | 200.7171.7–225.1 | 216.9185–243.8 |
| 2096 | 199.8173.6–226.3 | 213.1182–247.6 |
| 2097 | 201.2170–227.6 | 210.8174.9–242.1 |
| 2098 | 201.1170.7–227.2 | 214.4181.5–242.2 |
| 2099 | 198.3173.8–225.8 | 213.5181.9–244.1 |
| 2100 | 198.5173.3–227.7 | 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
马达加斯加与马拉维对比
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人口与社会
经济
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冲突
军用
- 军费开支马达加斯加:2025 年为 GDP 的 0.62%马拉维:2025 年为 GDP 的 1.15%
- 军费开支(美元)马达加斯加:2025 年为 US$1.11亿马拉维:2025 年为 US$1.28亿
- 人均军费开支马达加斯加:2025 年为 US$4马拉维:2025 年为 US$7
- 军费占政府支出比例马达加斯加:2025 年为 3.8%(占政府支出)马拉维:2025 年为 3.8%(占政府支出)
- 武装部队人员马达加斯加:2020 年为 22,000 人马拉维:2020 年为 15,000 人
- 国家实力马达加斯加:2022 年为 0.11%(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马达加斯加:2020 年为 0.15%(占劳动力)马拉维:2020 年为 0.2%(占劳动力)
- 武器进口马达加斯加:2025 年为 300万 TIV马拉维:2024 年为 200万 TIV