澳大利亚与印度：35 °C 以上天数

2014 年35 °C 以上天数：澳大利亚为 81.7 天，印度为 80.6 天（CMIP6 气候模型中位数模拟）。 2014 年澳大利亚的数值较高，高出 1 天，是印度的 1.01 倍。

每年天数 · CMIP6

澳大利亚印度CMIP6 模型中位数（SSP2-4.5，中间路径）模型第 10–90 百分位

数据解读

自 2013 年超过印度以来，澳大利亚的数值一直更高。
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，印度为 111.9 天。

逐年数据

每年天数 · CMIP6

年份	澳大利亚	印度
2014	81.7	80.6
2013	83.1	79.2
2012	80.8	81.3
2011	79.5	79.9
2010	83.2	80.8
2009	80	78.4
2008	79.5	77
2007	78.5	79
2006	76	76.2
2005	76.6	79.9
2004	82.2	80.1
2003	80.7	76.9
2002	74.3	79.2
2001	77.2	80.1
2000	78	76.6
1999	71.7	77.1
1998	78.1	76.9
1997	75.2	75.4
1996	71.1	72.1
1995	68.9	75.4
1994	69.6	76.3
1993	67.8	72.3
1992	60.6	68.7
1991	73.2	78.1
1990	75.6	76.7
1989	72.9	75.5
1988	69.8	73.9
1987	70.1	75.3
1986	72.2	76.8
1985	66.1	73
1984	71.3	75.9
1983	68.4	74.1
1982	73.4	76.1
1981	69.1	76.3
1980	71.2	75.3
1979	70.4	74.4
1978	70.8	74.4
1977	70.3	74.6
1976	69.4	76
1975	65.8	71
1974	67.7	75.8
1973	71.3	77.9
1972	65.4	71.1
1971	68.8	74.1
1970	66	73.7
1969	70	73.3
1968	67.2	72.2
1967	67.7	71.3
1966	66.9	75.3
1965	66.9	73.7
1964	64.8	68.9
1963	63.4	70.4
1962	70.7	74.2
1961	72.1	75.4
1960	71.5	75.4
1959	69.2	77.9
1958	69.6	74.8
1957	70.1	75.5
1956	67.3	75.6
1955	66.2	74.8
1954	70.4	75.3
1953	67.7	75.2
1952	71	76
1951	69.7	76.3
1950	68.6	76.5

CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100

年份	澳大利亚	印度
2015	76.853.2–96.9	81.664.7–96
2016	79.859.4–98.3	8063.1–96.1
2017	86.262–105.4	79.461.7–95.3
2018	85.863–104.5	82.461.5–95.7
2019	80.955.1–101.6	79.160.2–95.2
2020	84.756.1–104	82.262.4–99
2021	85.663.6–106.5	82.167.7–96.4
2022	89.462.5–109.3	83.962.8–100.3
2023	84.961–108.6	83.164–99.3
2024	89.263.7–109.8	84.766.4–100.3
2025	86.459.2–112.4	81.662.4–97.1
2026	88.864.7–112.2	84.866.1–101.3
2027	89.463.2–109.7	83.563.7–102
2028	93.269.5–112.9	82.862.9–99.9
2029	9476.8–115.4	89.566–105.9
2030	87.664.4–110	84.265.7–100.2
2031	92.264.8–115	85.466.7–103.4
2032	96.273.8–119.2	85.665.5–105.3
2033	92.871–113.6	83.865.8–99.8
2034	94.673.5–118.5	85.467.4–104.8
2035	93.968.1–117.2	85.766.6–105.3
2036	90.267.6–113.7	84.565.5–101.8
2037	100.677.4–120.6	89.772.2–107.5
2038	98.474.8–118.7	90.269.1–107.1
2039	9666.5–117.1	87.168.5–107.4
2040	95.971.2–117.3	87.566.6–106
2041	95.571.6–117.2	89.171.2–107.8
2042	96.367.9–119.8	95.475.7–112.9
2043	99.376.7–118.2	91.270.1–111.1
2044	97.974.6–121.5	90.471.6–110.9
2045	97.875.9–118.2	91.772–108.5
2046	98.972.9–124.7	95.469.1–117
2047	101.675.9–122.9	94.272.6–113.5
2048	105.875–127.2	97.673.2–120.5
2049	104.379.7–126.3	95.173.8–117.5
2050	103.274.6–124.4	94.474.5–117
2051	106.578.2–130.4	94.775.8–114.7
2052	103.877.1–130.6	96.876.1–116.5
2053	102.877.4–129.2	94.673.9–116.7
2054	103.979.2–132.2	96.574.3–117
2055	107.780.2–128.9	99.175.7–118
2056	10782.5–128.6	99.173.7–118.2
2057	107.880.8–128.5	100.371.9–123.9
2058	107.678.9–132.4	97.775.1–121.5
2059	109.283.2–131.6	102.380.5–127.4
2060	108.281.6–130.8	10380.3–124.4
2061	110.582.7–133.6	100.978.4–122.6
2062	103.675.5–126.2	100.175.4–126.5
2063	112.885.3–134.9	100.678.3–122.1
2064	109.485.3–132.4	10081–123.3
2065	107.679.3–129.4	103.580.5–128.2
2066	114.593.5–137.8	100.780.7–124.6
2067	111.281.6–140	99.678.4–126
2068	114.379.8–138.3	102.780.1–130.1
2069	108.782–134.9	10477.5–128.1
2070	109.479.1–140.3	101.179.7–125.6
2071	111.783–138	105.581.4–132.1
2072	113.787.6–137.3	104.384.4–128.2
2073	118.593.1–139.9	108.485.4–130
2074	112.586.3–136	105.182.9–126.8
2075	113.181–135.9	102.578.8–126
2076	114.987.1–137.5	105.582.2–134.6
2077	117.686.2–139.7	107.484.1–132.6
2078	116.193.4–136.9	107.382.8–127.7
2079	112.485.3–137.7	105.379.7–127.2
2080	11483.2–138.7	109.784.5–135.9
2081	115.882.5–139.6	108.986.2–134.4
2082	116.188.5–138.4	105.783.4–133.6
2083	113.184.1–140.2	110.287.8–135.8
2084	120.886–143.5	111.582.3–138.1
2085	116.987.7–142.3	112.381.2–143.6
2086	118.683.7–140.4	107.882.8–141.1
2087	11785.8–143	107.980.1–134
2088	120.188.6–146.1	107.984.4–143.1
2089	117.491.7–140.8	107.981.7–137.3
2090	11988.8–146.2	108.883.9–136.6
2091	118.691.2–140.5	113.486.9–144
2092	118.784.5–143.2	113.587.1–142.8
2093	122.388.6–148.2	108.482.7–144.8
2094	117.689–142.8	111.386.8–139.5
2095	12494.3–151.5	114.186.4–143.6
2096	118.390.2–145.3	10880.4–140.3
2097	120.986.4–147.2	110.385–137.8
2098	118.891.5–144.3	113.687.7–141.1
2099	123.292.1–145.4	112.585.3–137.7
2100	120.591–145.4	111.986.8–138.7

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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

澳大利亚与印度对比

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冲突

冲突死亡人数澳大利亚：2022 年为 0 人死亡印度：2022 年为 358 人死亡