澳大利亚与缅甸对比
澳大利亚与缅甸:35 °C 以上天数
2014 年35 °C 以上天数:澳大利亚为 81.7 天,缅甸为 28.8 天(CMIP6 气候模型中位数模拟)。 2014 年澳大利亚的数值较高,高出 52.9 天,是缅甸的 2.84 倍。
每年天数 · CMIP6
数据解读
- 自 1950 年以来,在两国都有数据的每一年,澳大利亚的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年澳大利亚为 120.5 天,缅甸为 57 天。
逐年数据
每年天数 · CMIP6
| 年份 | 澳大利亚 | 缅甸 |
|---|---|---|
| 2014 | 81.7 | 28.8 |
| 2013 | 83.1 | 28 |
| 2012 | 80.8 | 27.5 |
| 2011 | 79.5 | 27.4 |
| 2010 | 83.2 | 27.9 |
| 2009 | 80 | 27.3 |
| 2008 | 79.5 | 27.2 |
| 2007 | 78.5 | 25.4 |
| 2006 | 76 | 26.8 |
| 2005 | 76.6 | 25 |
| 2004 | 82.2 | 28.3 |
| 2003 | 80.7 | 26.4 |
| 2002 | 74.3 | 27.4 |
| 2001 | 77.2 | 28.4 |
| 2000 | 78 | 26.6 |
| 1999 | 71.7 | 26.1 |
| 1998 | 78.1 | 26.4 |
| 1997 | 75.2 | 26.2 |
| 1996 | 71.1 | 24.7 |
| 1995 | 68.9 | 25.5 |
| 1994 | 69.6 | 24.3 |
| 1993 | 67.8 | 23.9 |
| 1992 | 60.6 | 20.5 |
| 1991 | 73.2 | 28.4 |
| 1990 | 75.6 | 26.3 |
| 1989 | 72.9 | 23.8 |
| 1988 | 69.8 | 23.9 |
| 1987 | 70.1 | 25.4 |
| 1986 | 72.2 | 26.6 |
| 1985 | 66.1 | 23.6 |
| 1984 | 71.3 | 25.8 |
| 1983 | 68.4 | 23.2 |
| 1982 | 73.4 | 24 |
| 1981 | 69.1 | 23.8 |
| 1980 | 71.2 | 23.5 |
| 1979 | 70.4 | 25.3 |
| 1978 | 70.8 | 23.4 |
| 1977 | 70.3 | 24.1 |
| 1976 | 69.4 | 25.6 |
| 1975 | 65.8 | 22.3 |
| 1974 | 67.7 | 24.1 |
| 1973 | 71.3 | 25.9 |
| 1972 | 65.4 | 23.1 |
| 1971 | 68.8 | 22.8 |
| 1970 | 66 | 24.2 |
| 1969 | 70 | 23.6 |
| 1968 | 67.2 | 23.4 |
| 1967 | 67.7 | 24.1 |
| 1966 | 66.9 | 23.1 |
| 1965 | 66.9 | 23.3 |
| 1964 | 64.8 | 21.7 |
| 1963 | 63.4 | 23.2 |
| 1962 | 70.7 | 24.4 |
| 1961 | 72.1 | 24.9 |
| 1960 | 71.5 | 26.2 |
| 1959 | 69.2 | 22.6 |
| 1958 | 69.6 | 25 |
| 1957 | 70.1 | 24.1 |
| 1956 | 67.3 | 25 |
| 1955 | 66.2 | 24.5 |
| 1954 | 70.4 | 25.3 |
| 1953 | 67.7 | 23.5 |
| 1952 | 71 | 26.1 |
| 1951 | 69.7 | 25 |
| 1950 | 68.6 | 23.8 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 澳大利亚 | 缅甸 |
|---|---|---|
| 2015 | 76.853.2–96.9 | 28.518.5–40 |
| 2016 | 79.859.4–98.3 | 27.717.3–38.7 |
| 2017 | 86.262–105.4 | 2818.9–38.5 |
| 2018 | 85.863–104.5 | 29.818.6–41.2 |
| 2019 | 80.955.1–101.6 | 28.218.2–41.3 |
| 2020 | 84.756.1–104 | 28.616.8–41.4 |
| 2021 | 85.663.6–106.5 | 29.719.4–40.8 |
| 2022 | 89.462.5–109.3 | 31.521.7–42.7 |
| 2023 | 84.961–108.6 | 30.319.9–41.6 |
| 2024 | 89.263.7–109.8 | 31.720.1–43.7 |
| 2025 | 86.459.2–112.4 | 32.721.3–44.8 |
| 2026 | 88.864.7–112.2 | 30.420.3–44.5 |
| 2027 | 89.463.2–109.7 | 30.620.4–44.2 |
| 2028 | 93.269.5–112.9 | 31.119–43 |
| 2029 | 9476.8–115.4 | 32.720.9–46.4 |
| 2030 | 87.664.4–110 | 32.619.3–45 |
| 2031 | 92.264.8–115 | 32.721.3–45.2 |
| 2032 | 96.273.8–119.2 | 32.119.6–45.4 |
| 2033 | 92.871–113.6 | 33.322–43.8 |
| 2034 | 94.673.5–118.5 | 31.322–43.5 |
| 2035 | 93.968.1–117.2 | 32.620.4–49 |
| 2036 | 90.267.6–113.7 | 33.322.7–46.1 |
| 2037 | 100.677.4–120.6 | 34.322.6–49.1 |
| 2038 | 98.474.8–118.7 | 35.824.4–49.9 |
| 2039 | 9666.5–117.1 | 34.920.9–49 |
| 2040 | 95.971.2–117.3 | 3419.2–51.2 |
| 2041 | 95.571.6–117.2 | 3724.8–51.9 |
| 2042 | 96.367.9–119.8 | 36.223–49.9 |
| 2043 | 99.376.7–118.2 | 34.522.6–47.7 |
| 2044 | 97.974.6–121.5 | 38.222.1–51.2 |
| 2045 | 97.875.9–118.2 | 35.924.2–50.7 |
| 2046 | 98.972.9–124.7 | 38.425.2–57.1 |
| 2047 | 101.675.9–122.9 | 38.824.1–56.1 |
| 2048 | 105.875–127.2 | 40.323.4–58.7 |
| 2049 | 104.379.7–126.3 | 40.625.2–58.1 |
| 2050 | 103.274.6–124.4 | 40.226.5–55.3 |
| 2051 | 106.578.2–130.4 | 41.726.7–56.8 |
| 2052 | 103.877.1–130.6 | 40.326.3–61.2 |
| 2053 | 102.877.4–129.2 | 41.323.6–61.5 |
| 2054 | 103.979.2–132.2 | 42.426.8–60.9 |
| 2055 | 107.780.2–128.9 | 41.428.5–61.9 |
| 2056 | 10782.5–128.6 | 42.726.5–63 |
| 2057 | 107.880.8–128.5 | 43.226.3–63.2 |
| 2058 | 107.678.9–132.4 | 44.526.8–63.6 |
| 2059 | 109.283.2–131.6 | 43.729.1–65.3 |
| 2060 | 108.281.6–130.8 | 47.428.3–66 |
| 2061 | 110.582.7–133.6 | 46.729.5–64.5 |
| 2062 | 103.675.5–126.2 | 47.126.7–68.6 |
| 2063 | 112.885.3–134.9 | 46.929–66.4 |
| 2064 | 109.485.3–132.4 | 47.527.9–66.1 |
| 2065 | 107.679.3–129.4 | 42.427.5–62.4 |
| 2066 | 114.593.5–137.8 | 46.228.9–68.8 |
| 2067 | 111.281.6–140 | 4125.7–63.6 |
| 2068 | 114.379.8–138.3 | 46.928–70.4 |
| 2069 | 108.782–134.9 | 48.729.3–70.1 |
| 2070 | 109.479.1–140.3 | 43.927.5–64.3 |
| 2071 | 111.783–138 | 4926.2–71.9 |
| 2072 | 113.787.6–137.3 | 4730.6–71.4 |
| 2073 | 118.593.1–139.9 | 50.732.2–74 |
| 2074 | 112.586.3–136 | 4829.2–74 |
| 2075 | 113.181–135.9 | 49.126.1–68.9 |
| 2076 | 114.987.1–137.5 | 47.826.5–72.8 |
| 2077 | 117.686.2–139.7 | 51.832.9–76.1 |
| 2078 | 116.193.4–136.9 | 50.632.4–75.6 |
| 2079 | 112.485.3–137.7 | 50.730.5–77 |
| 2080 | 11483.2–138.7 | 53.331.3–79.5 |
| 2081 | 115.882.5–139.6 | 5235.5–79.1 |
| 2082 | 116.188.5–138.4 | 52.532.5–76.8 |
| 2083 | 113.184.1–140.2 | 51.730.5–79.6 |
| 2084 | 120.886–143.5 | 52.329.5–76 |
| 2085 | 116.987.7–142.3 | 51.232.9–79.4 |
| 2086 | 118.683.7–140.4 | 52.632.5–80.1 |
| 2087 | 11785.8–143 | 51.732.6–77.9 |
| 2088 | 120.188.6–146.1 | 50.727.2–88.8 |
| 2089 | 117.491.7–140.8 | 52.731.4–86.3 |
| 2090 | 11988.8–146.2 | 54.231.1–80.1 |
| 2091 | 118.691.2–140.5 | 53.235.4–80.1 |
| 2092 | 118.784.5–143.2 | 54.135.4–85.5 |
| 2093 | 122.388.6–148.2 | 5235.6–85 |
| 2094 | 117.689–142.8 | 54.434.9–80.7 |
| 2095 | 12494.3–151.5 | 58.535.1–84.3 |
| 2096 | 118.390.2–145.3 | 52.832.3–84.1 |
| 2097 | 120.986.4–147.2 | 53.230.4–82.8 |
| 2098 | 118.891.5–144.3 | 55.334.4–83.8 |
| 2099 | 123.292.1–145.4 | 55.233.1–84.7 |
| 2100 | 120.591–145.4 | 5734.6–84 |
分别查看各国
须知
- 一年中最高气温超过 35 °C 的天数,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
澳大利亚与缅甸对比
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军用
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- 军费开支(美元)澳大利亚:2025 年为 US$353亿缅甸:2024 年为 US$46.5亿
- 人均军费开支澳大利亚:2025 年为 US$1,316缅甸:2024 年为 US$92
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- 武装部队人员澳大利亚:2020 年为 60,000 人缅甸:2020 年为 463,000 人
- 国家实力澳大利亚:2022 年为 0.6%(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澳大利亚:2020 年为 0.44%(占劳动力)缅甸:2020 年为 1.94%(占劳动力)
- 武器进口澳大利亚:2025 年为 8.26亿 TIV缅甸:2025 年为 7000万 TIV