埃塞俄比亚与缅甸对比
埃塞俄比亚与缅甸:热带夜
2014 年热带夜:埃塞俄比亚为 144.9 夜,缅甸为 201.9 夜(CMIP6 气候模型中位数模拟)。 2014 年缅甸的数值较高,高出 57 夜,是埃塞俄比亚的 1.39 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,缅甸的数值都更高。
- 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,缅甸为 244.5 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 埃塞俄比亚 | 缅甸 |
|---|---|---|
| 2014 | 144.9 | 201.9 |
| 2013 | 145.1 | 203.1 |
| 2012 | 144.4 | 201.1 |
| 2011 | 145.6 | 200.9 |
| 2010 | 142.4 | 202.1 |
| 2009 | 140.3 | 199 |
| 2008 | 137.1 | 198.1 |
| 2007 | 138.2 | 196.8 |
| 2006 | 138.7 | 198.2 |
| 2005 | 138.1 | 196.7 |
| 2004 | 139.1 | 200.3 |
| 2003 | 138.8 | 195.3 |
| 2002 | 137.4 | 196.6 |
| 2001 | 139.2 | 199 |
| 2000 | 135.5 | 197.2 |
| 1999 | 132.6 | 196.4 |
| 1998 | 132.9 | 194.7 |
| 1997 | 132.7 | 194.4 |
| 1996 | 129.7 | 191.4 |
| 1995 | 127.8 | 189.9 |
| 1994 | 126.3 | 188.8 |
| 1993 | 122.5 | 185 |
| 1992 | 119.7 | 180.5 |
| 1991 | 129.5 | 191.7 |
| 1990 | 132.7 | 191.5 |
| 1989 | 129.4 | 190.3 |
| 1988 | 128.2 | 190.7 |
| 1987 | 126.4 | 190.8 |
| 1986 | 128.1 | 189.7 |
| 1985 | 122.8 | 187.4 |
| 1984 | 124.8 | 189.1 |
| 1983 | 120.6 | 182.3 |
| 1982 | 126.3 | 186.7 |
| 1981 | 127 | 188.4 |
| 1980 | 124.9 | 189 |
| 1979 | 125.1 | 189.8 |
| 1978 | 124.7 | 186.8 |
| 1977 | 125.8 | 187.4 |
| 1976 | 122 | 185.8 |
| 1975 | 119.5 | 183.6 |
| 1974 | 124 | 185.5 |
| 1973 | 125.2 | 187.5 |
| 1972 | 122.3 | 184.8 |
| 1971 | 120.6 | 185.2 |
| 1970 | 121.3 | 184.9 |
| 1969 | 120.4 | 184.3 |
| 1968 | 119.1 | 183.7 |
| 1967 | 118.1 | 182.3 |
| 1966 | 119.5 | 186.2 |
| 1965 | 117.4 | 182.9 |
| 1964 | 116.6 | 180.6 |
| 1963 | 115.7 | 183.1 |
| 1962 | 121.6 | 187.3 |
| 1961 | 124.2 | 188.7 |
| 1960 | 124.5 | 187.1 |
| 1959 | 121.6 | 186.5 |
| 1958 | 124.1 | 187.1 |
| 1957 | 123.2 | 186.2 |
| 1956 | 120.9 | 187.9 |
| 1955 | 122.8 | 185.9 |
| 1954 | 121.6 | 185.7 |
| 1953 | 121.2 | 185 |
| 1952 | 122.8 | 186.1 |
| 1951 | 123 | 187.1 |
| 1950 | 122 | 186.9 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 埃塞俄比亚 | 缅甸 |
|---|---|---|
| 2015 | 146.6129.4–163.9 | 205.2186.4–218.9 |
| 2016 | 144.1127–160.6 | 202.8186.2–218.8 |
| 2017 | 148.3129.2–164.9 | 203.4187.3–218.3 |
| 2018 | 149.6131.6–166 | 205.5190.9–219.9 |
| 2019 | 146.2129.3–166 | 205.2186.7–222.2 |
| 2020 | 149.4129.6–168.5 | 208.2188.5–223.5 |
| 2021 | 150.7132.1–170 | 208.9191.2–224.1 |
| 2022 | 154135.7–171.2 | 209.9192.7–224.9 |
| 2023 | 153.5135.4–171.4 | 210.6195.4–226.3 |
| 2024 | 156.5135.9–175.6 | 210.4193.8–226.6 |
| 2025 | 154132.6–175.5 | 209.9190.3–225.2 |
| 2026 | 153132–175 | 212.2194.3–229.2 |
| 2027 | 154.2134.4–175.3 | 212195.6–228.6 |
| 2028 | 157.5138.3–177.4 | 213195.7–227.2 |
| 2029 | 159.2141.8–176.8 | 215.3193.9–231.9 |
| 2030 | 156.8136.3–175.7 | 212.2194.9–228 |
| 2031 | 161.4142.4–179.1 | 214.3197.2–230.8 |
| 2032 | 161.7143.1–182.5 | 215199.3–229.6 |
| 2033 | 161.8140–180.9 | 215.5198.5–230.1 |
| 2034 | 158.8141.5–184.3 | 214.9198.4–233.5 |
| 2035 | 162141.7–184.2 | 214.9199.2–236.8 |
| 2036 | 160.5143.6–179.4 | 216198.7–234.5 |
| 2037 | 165145.8–184.5 | 217.2199.6–233.5 |
| 2038 | 167.1146.5–186.7 | 220.7204.8–235.1 |
| 2039 | 164.5143.9–186 | 219.7202.4–234.3 |
| 2040 | 165.9146.2–190.1 | 219.2202.9–235 |
| 2041 | 167.9146.3–189.3 | 220.7203.9–237.7 |
| 2042 | 167.7146–194.3 | 221.8206.1–237.2 |
| 2043 | 167.3145.5–190.8 | 219.5201.2–237.1 |
| 2044 | 168.2148.2–189.9 | 221.4201.6–239.6 |
| 2045 | 170.7149.1–192.3 | 223.7204.8–241.5 |
| 2046 | 175.3150–198.6 | 223.2203.2–240.2 |
| 2047 | 176.9151.8–197.5 | 224.3204.8–241.1 |
| 2048 | 177.5155.4–199.1 | 226.4207.7–243.8 |
| 2049 | 177.5157.9–198.4 | 226.5205.6–242.8 |
| 2050 | 176.4153.8–199 | 227209.3–243.5 |
| 2051 | 176.6155.3–199.7 | 229.6212.4–246.4 |
| 2052 | 177155.6–200.7 | 227.2208.6–244.2 |
| 2053 | 176.7154.2–201.6 | 227.9208.7–247.7 |
| 2054 | 177.6156.9–201.1 | 227.9209.6–244.8 |
| 2055 | 180.6155.2–202.3 | 229.1209.8–247.5 |
| 2056 | 177.3155–205.4 | 231.8210.4–252.1 |
| 2057 | 180.3159.3–205.5 | 228.6208–249 |
| 2058 | 182.6153.7–209.4 | 228.9208.8–249 |
| 2059 | 185.7160.1–210.6 | 230.7212.1–247.5 |
| 2060 | 185.9160.3–210.4 | 234.7211.1–251.5 |
| 2061 | 183.3158.3–211.7 | 231.9213–247.7 |
| 2062 | 183.8155.4–213 | 233.6209.9–252.8 |
| 2063 | 184.5159.1–208.6 | 233215.4–250.5 |
| 2064 | 186.7160.6–207.2 | 233.2214.4–251.3 |
| 2065 | 183.7162.4–212.9 | 230.7210.4–250.7 |
| 2066 | 187.1165.4–210.1 | 233.5214.3–251.2 |
| 2067 | 187.1160.7–214.5 | 233211.5–253.3 |
| 2068 | 187.6160.4–215.8 | 233.1212.4–253.7 |
| 2069 | 187.8165.4–215.8 | 236.1214.6–253.4 |
| 2070 | 187.9161.6–216.9 | 235.9218.1–253.4 |
| 2071 | 192.7165.2–219.5 | 235.1213.5–259.6 |
| 2072 | 193.6167.4–214.5 | 234.6216.1–252.6 |
| 2073 | 193.3169.7–218.7 | 237.2219.3–257.2 |
| 2074 | 188.5163.9–219 | 236.4215.7–254.5 |
| 2075 | 191.9162.7–218.6 | 236.7214.4–255.9 |
| 2076 | 195166.9–218.9 | 237.7216–257 |
| 2077 | 194.1169.3–223.3 | 237.5219–258.7 |
| 2078 | 192.1168.4–218.6 | 238.5217.3–257.8 |
| 2079 | 193.4166.6–220.9 | 238.5219.2–257.2 |
| 2080 | 196.1169.2–222.4 | 240.5218.8–258.3 |
| 2081 | 194.6171–221.4 | 240219.7–260.9 |
| 2082 | 195.4168.8–219.9 | 239.4217.1–258.8 |
| 2083 | 194.6168.2–228.7 | 239.1220.5–259.2 |
| 2084 | 198.5170.7–224.2 | 241.3218.9–260.6 |
| 2085 | 198.4173.1–226.3 | 241.7218.8–260.7 |
| 2086 | 198.6172.3–228.4 | 241.7217.4–262.7 |
| 2087 | 199170.6–226.6 | 241.4220.5–260.9 |
| 2088 | 199170.7–227.7 | 241.8222.3–261.5 |
| 2089 | 198.6171.2–226.2 | 240.7221.2–262.6 |
| 2090 | 198.6173.4–227.7 | 241.3224.4–260.9 |
| 2091 | 203.6171.9–232.1 | 242.6220.3–262.5 |
| 2092 | 200.7172.5–229.7 | 241.9221.6–263.3 |
| 2093 | 201.4175.2–228.6 | 242.1220.2–260 |
| 2094 | 200.2174–228.9 | 242.5222.5–261.9 |
| 2095 | 203.9175.7–231.9 | 244.9224–264.4 |
| 2096 | 199.1170.5–230.8 | 243.9221.1–266.5 |
| 2097 | 198.4171.8–229.3 | 243.6219.6–264.2 |
| 2098 | 198.7172.1–231.5 | 243.6222.5–263.9 |
| 2099 | 201.8172.8–233.3 | 244.7221.8–263.5 |
| 2100 | 201.7175.1–231.8 | 244.5223.2–261.8 |
分别查看各国
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
埃塞俄比亚与缅甸对比
健康
人口与社会
经济
教育
政治
冲突
军用
- 军费开支埃塞俄比亚:2025 年为 GDP 的 0.49%缅甸:2024 年为 GDP 的 6.61%
- 军费开支(美元)埃塞俄比亚:2025 年为 US$7.85亿缅甸:2024 年为 US$46.5亿
- 人均军费开支埃塞俄比亚:2025 年为 US$4缅甸:2024 年为 US$92
- 军费占政府支出比例埃塞俄比亚:2025 年为 4.1%(占政府支出)缅甸:2024 年为 32%(占政府支出)
- 武装部队人员埃塞俄比亚:2020 年为 138,000 人缅甸:2020 年为 463,000 人
- 国家实力埃塞俄比亚:2022 年为 0.85%(占全球实力)缅甸:2022 年为 0.53%(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)缅甸:2020 年为 1.94%(占劳动力)
- 武器进口埃塞俄比亚:2025 年为 6300万 TIV缅甸:2025 年为 7000万 TIV