乍得与马拉维对比
乍得与马拉维:热带夜
2014 年热带夜:乍得为 237.6 夜,马拉维为 138.1 夜(CMIP6 气候模型中位数模拟)。 2014 年乍得的数值较高,高出 99.5 夜,是马拉维的 1.72 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,乍得的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年乍得为 273.4 夜,马拉维为 213.3 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 乍得 | 马拉维 |
|---|---|---|
| 2014 | 237.6 | 138.1 |
| 2013 | 231.8 | 138.9 |
| 2012 | 237.9 | 137.4 |
| 2011 | 236.2 | 136.6 |
| 2010 | 234.8 | 132.4 |
| 2009 | 231.5 | 131.4 |
| 2008 | 230.8 | 130.8 |
| 2007 | 229.6 | 132.8 |
| 2006 | 229.5 | 129.8 |
| 2005 | 228.8 | 129.5 |
| 2004 | 228 | 133.4 |
| 2003 | 230.9 | 132.5 |
| 2002 | 229.8 | 130.3 |
| 2001 | 230.2 | 134 |
| 2000 | 226.4 | 126.6 |
| 1999 | 225.1 | 124.8 |
| 1998 | 222.9 | 127.1 |
| 1997 | 226.3 | 124.2 |
| 1996 | 222.4 | 121.3 |
| 1995 | 222.3 | 120.9 |
| 1994 | 221.4 | 118.4 |
| 1993 | 215.6 | 113.8 |
| 1992 | 214.4 | 114.1 |
| 1991 | 223 | 120.9 |
| 1990 | 222.8 | 123.8 |
| 1989 | 220 | 120.5 |
| 1988 | 219.9 | 120.8 |
| 1987 | 218.4 | 118.8 |
| 1986 | 222.6 | 121.1 |
| 1985 | 218 | 115.7 |
| 1984 | 216.1 | 116.2 |
| 1983 | 213.7 | 115.5 |
| 1982 | 214.8 | 115.1 |
| 1981 | 218.1 | 119 |
| 1980 | 215 | 116.9 |
| 1979 | 214.5 | 117.7 |
| 1978 | 216 | 114.8 |
| 1977 | 216.2 | 117.2 |
| 1976 | 215.7 | 114 |
| 1975 | 212.2 | 114 |
| 1974 | 213.8 | 115.2 |
| 1973 | 216.9 | 114.7 |
| 1972 | 215.2 | 113.8 |
| 1971 | 212.6 | 114.1 |
| 1970 | 214.3 | 115.8 |
| 1969 | 210.3 | 114.3 |
| 1968 | 212.8 | 110 |
| 1967 | 209.1 | 109.8 |
| 1966 | 210.8 | 111 |
| 1965 | 210.3 | 111.5 |
| 1964 | 210.6 | 106.3 |
| 1963 | 207.5 | 107.5 |
| 1962 | 214.7 | 114.7 |
| 1961 | 212.3 | 116 |
| 1960 | 217.3 | 117.4 |
| 1959 | 212.5 | 115.6 |
| 1958 | 213.8 | 116.4 |
| 1957 | 214 | 114.6 |
| 1956 | 213.4 | 111.4 |
| 1955 | 213.8 | 115.2 |
| 1954 | 214.3 | 113.9 |
| 1953 | 211.3 | 113 |
| 1952 | 213.1 | 113.5 |
| 1951 | 213.8 | 113.5 |
| 1950 | 213.1 | 112.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 乍得 | 马拉维 |
|---|---|---|
| 2015 | 235.8215.6–253.1 | 145.7126.7–164.3 |
| 2016 | 233.3212.8–247.7 | 139.8122.6–157.4 |
| 2017 | 237.6218.6–253.1 | 143.6127–161.8 |
| 2018 | 235.8217.8–254.4 | 143.1124.6–162.6 |
| 2019 | 235.2213.3–255.6 | 143.8128.3–161.4 |
| 2020 | 237217.1–255 | 145127.3–165.8 |
| 2021 | 239.6220–258.2 | 145.3128–163.6 |
| 2022 | 240.4223.1–258.2 | 151130.1–169.1 |
| 2023 | 239.1216.7–256.4 | 149.2129.5–171.2 |
| 2024 | 246.7227.6–261.2 | 152.4130–172.6 |
| 2025 | 243.2223.9–259.4 | 151.1129.7–170.4 |
| 2026 | 242.9220.8–260.9 | 151.1126.2–173.8 |
| 2027 | 242.3221.2–258.6 | 154.4135.1–173.1 |
| 2028 | 242.7225.4–259.7 | 155.5134.6–174 |
| 2029 | 246.3227.2–264.1 | 159.8139.2–178.5 |
| 2030 | 244.7225.8–261.1 | 155.6138.7–174.5 |
| 2031 | 246.8224.7–264.8 | 161.1143.4–177.6 |
| 2032 | 244.3226.5–260.2 | 160.8141.3–181.3 |
| 2033 | 247.6228.7–266.1 | 161.3135.6–179.2 |
| 2034 | 247.8224.9–263.9 | 160.9138.9–185 |
| 2035 | 250.9230.3–268.9 | 164.3140.4–189.5 |
| 2036 | 246.7226.3–264.1 | 163.8137.6–182.5 |
| 2037 | 249.9230.3–266.2 | 166.9144.6–189.2 |
| 2038 | 252.4233.4–268.7 | 172.2148.4–191.2 |
| 2039 | 250230.8–267.5 | 164.8147.3–188.2 |
| 2040 | 248.9227–266.8 | 164.4146.4–189.7 |
| 2041 | 252230–270.9 | 169.3143.7–192.5 |
| 2042 | 250.4232–271.8 | 169.8146.3–197.8 |
| 2043 | 251.1232–265.5 | 167.5147.1–193.2 |
| 2044 | 251.4230.2–271.3 | 172.6148.3–197 |
| 2045 | 252.3230.8–270.2 | 170.4153.1–194.7 |
| 2046 | 253.6231.9–272.3 | 176.3151.2–203.1 |
| 2047 | 254.6236.7–274.4 | 178.7157.8–200.9 |
| 2048 | 254.4236.6–273.6 | 180.7158.9–204.1 |
| 2049 | 256235.4–272 | 176.7154–205.4 |
| 2050 | 255.9234.4–276.1 | 180.4155.2–204.9 |
| 2051 | 256.1237.8–275.9 | 182.9162.1–207.4 |
| 2052 | 258.3237.1–273.9 | 184.9163.2–209.6 |
| 2053 | 255.9234.9–275 | 177.2149.6–207.4 |
| 2054 | 260.6233–279.6 | 185.1157.1–208 |
| 2055 | 259.9239.1–276.6 | 186.1159.2–212.6 |
| 2056 | 259.4233.3–279 | 184.6158.5–214.3 |
| 2057 | 262.5240.8–278.4 | 184.7159.3–212.3 |
| 2058 | 259.3239.2–275.5 | 188.5163.8–214.7 |
| 2059 | 263.7240.5–282.9 | 189.8166.9–218.5 |
| 2060 | 259.3239.3–280 | 192.6163.4–218.1 |
| 2061 | 261.1240.7–281.2 | 186.4158.8–216.8 |
| 2062 | 261.4238.1–281.4 | 192.3163.9–218.6 |
| 2063 | 263.4239.6–278.6 | 189.2165.2–220.3 |
| 2064 | 263.9244.3–283.2 | 197161.3–218 |
| 2065 | 263.7247.7–283.1 | 193.1165.8–225.2 |
| 2066 | 265.2245.7–285.6 | 201170.1–224.7 |
| 2067 | 262.5242.8–283.8 | 193.1164.2–223.7 |
| 2068 | 266.8241.4–286.3 | 198.6163.7–227.1 |
| 2069 | 262.7242.8–283.1 | 199.4165.8–225 |
| 2070 | 264.9243.5–284.9 | 198.7168–226.7 |
| 2071 | 267.9248.5–286 | 199.3167.9–233.5 |
| 2072 | 269.2246.8–285.6 | 202.3173.2–226.2 |
| 2073 | 263.7241.6–284.2 | 205.4168.2–233.4 |
| 2074 | 264239.7–285.1 | 198.2175.4–227.7 |
| 2075 | 266.5246.7–287 | 199.6168.9–228.3 |
| 2076 | 267.8245.8–285.7 | 198.8169.8–225.2 |
| 2077 | 269.5247.1–290.8 | 202172.2–231.2 |
| 2078 | 268.6247.9–286.4 | 203.5175.8–232.1 |
| 2079 | 266.4247.9–286.3 | 203.6172.2–236.1 |
| 2080 | 269.4249.6–289.4 | 204.7172.2–234.3 |
| 2081 | 267.4247.1–291.8 | 202.2174.9–231.3 |
| 2082 | 266.7249.2–286.8 | 204.3178.3–228.6 |
| 2083 | 269.8248.9–287.6 | 205.8170.7–238.3 |
| 2084 | 268.4243.4–289.7 | 208.1175.9–235.6 |
| 2085 | 270.8251.2–287.4 | 211.1179.4–241 |
| 2086 | 270.6249.6–291.5 | 203.3175.4–237 |
| 2087 | 266.3246.2–289.2 | 205.3181.2–237.7 |
| 2088 | 269.2245.6–290.7 | 211.6174.7–240.6 |
| 2089 | 270.4251.1–289 | 208.9180.5–237.8 |
| 2090 | 270.9245.5–291.1 | 209.4173.4–243 |
| 2091 | 271.3246.1–293.5 | 214.3179.7–244.8 |
| 2092 | 270.6248.3–291.9 | 213.2176.8–242.3 |
| 2093 | 272.4254.3–289.2 | 212.5177.8–242.2 |
| 2094 | 274254.8–290.2 | 211.8179.7–241.5 |
| 2095 | 273.5251.8–291.6 | 216.9185–243.8 |
| 2096 | 273.9252.1–292.5 | 213.1182–247.6 |
| 2097 | 270.8246–292.1 | 210.8174.9–242.1 |
| 2098 | 271.1248.3–290.6 | 214.4181.5–242.2 |
| 2099 | 271.8250.5–291.1 | 213.5181.9–244.1 |
| 2100 | 273.4254–291.9 | 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
乍得与马拉维对比
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军用
- 军费开支乍得:2025 年为 GDP 的 3.19%马拉维:2025 年为 GDP 的 1.15%
- 军费开支(美元)乍得:2025 年为 US$5.98亿马拉维:2025 年为 US$1.28亿
- 人均军费开支乍得:2025 年为 US$31马拉维:2025 年为 US$7
- 军费占政府支出比例乍得:2025 年为 15.5%(占政府支出)马拉维:2025 年为 3.8%(占政府支出)
- 武装部队人员乍得:2020 年为 45,000 人马拉维:2020 年为 15,000 人
- 国家实力乍得:2022 年为 0.1%(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乍得:2020 年为 0.85%(占劳动力)马拉维:2020 年为 0.2%(占劳动力)
- 武器进口乍得:2025 年为 400万 TIV马拉维:2024 年为 200万 TIV
- 武器出口乍得:1987 年为 2000万 TIV马拉维:2000 年为 100万 TIV