印度与尼日利亚：35 °C 以上天数

2014 年35 °C 以上天数：印度为 80.6 天，尼日利亚为 107.4 天（CMIP6 气候模型中位数模拟）。 2014 年尼日利亚的数值较高，高出 26.8 天，是印度的 1.33 倍。

每年天数 · CMIP6

印度尼日利亚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 1950 年以来，在两国都有数据的每一年，尼日利亚的数值都更高。
根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年印度为 111.9 天，尼日利亚为 163.6 天。

逐年数据

每年天数 · CMIP6

年份	印度	尼日利亚
2014	80.6	107.4
2013	79.2	104.3
2012	81.3	104.4
2011	79.9	103.7
2010	80.8	101.1
2009	78.4	99.4
2008	77	98.6
2007	79	97.4
2006	76.2	97.9
2005	79.9	97.2
2004	80.1	99.2
2003	76.9	98.2
2002	79.2	98.3
2001	80.1	102.2
2000	76.6	96.3
1999	77.1	92.3
1998	76.9	91.6
1997	75.4	95.2
1996	72.1	89.5
1995	75.4	90.2
1994	76.3	86.1
1993	72.3	83.5
1992	68.7	81.3
1991	78.1	94.2
1990	76.7	95
1989	75.5	89.3
1988	73.9	93.4
1987	75.3	90.4
1986	76.8	93.2
1985	73	87
1984	75.9	89.5
1983	74.1	88.5
1982	76.1	89.6
1981	76.3	91.9
1980	75.3	89.5
1979	74.4	89.8
1978	74.4	88
1977	74.6	88.4
1976	76	83.6
1975	71	87.3
1974	75.8	84.9
1973	77.9	88.3
1972	71.1	87.1
1971	74.1	84.5
1970	73.7	87.3
1969	73.3	87.1
1968	72.2	84.9
1967	71.3	84.8
1966	75.3	85.7
1965	73.7	85.7
1964	68.9	77.7
1963	70.4	81.7
1962	74.2	89.3
1961	75.4	91.6
1960	75.4	91.4
1959	77.9	88.3
1958	74.8	89.9
1957	75.5	91.2
1956	75.6	84.6
1955	74.8	88.4
1954	75.3	88.8
1953	75.2	91.7
1952	76	87.9
1951	76.3	92.1
1950	76.5	88.9

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

年份	印度	尼日利亚
2015	81.664.7–96	105.581.2–130.1
2016	8063.1–96.1	101.478.2–120.6
2017	79.461.7–95.3	10680.5–130.9
2018	82.461.5–95.7	105.177.2–129
2019	79.160.2–95.2	104.378.3–130.3
2020	82.262.4–99	104.778.2–130.2
2021	82.167.7–96.4	104.885.2–128.6
2022	83.962.8–100.3	111.184.4–135.5
2023	83.164–99.3	106.585.6–130.6
2024	84.766.4–100.3	114.493.3–136.4
2025	81.662.4–97.1	112.191.1–132
2026	84.866.1–101.3	108.574.8–133.8
2027	83.563.7–102	114.581.7–136.4
2028	82.862.9–99.9	113.487.6–141.8
2029	89.566–105.9	116.591.5–141
2030	84.265.7–100.2	117.785.5–145.3
2031	85.466.7–103.4	116.388.2–141.7
2032	85.665.5–105.3	118.785.8–144.2
2033	83.865.8–99.8	118.490.6–146
2034	85.467.4–104.8	117.689–144.4
2035	85.766.6–105.3	12087.5–144.3
2036	84.565.5–101.8	116.889.2–143.5
2037	89.772.2–107.5	124.790.9–151.6
2038	90.269.1–107.1	126.696.2–152.6
2039	87.168.5–107.4	122.697–147.4
2040	87.566.6–106	121.193.5–153.7
2041	89.171.2–107.8	127.599.5–154.2
2042	95.475.7–112.9	12896.1–152.5
2043	91.270.1–111.1	124.298.9–149.7
2044	90.471.6–110.9	125.496.3–152.8
2045	91.772–108.5	129.499.4–156.4
2046	95.469.1–117	135.999.9–158.5
2047	94.272.6–113.5	135.299–159.5
2048	97.673.2–120.5	133.1103.7–160.3
2049	95.173.8–117.5	135.4104.4–161.8
2050	94.474.5–117	131.3102–166.4
2051	94.775.8–114.7	131.6106.2–166.5
2052	96.876.1–116.5	139.6101.6–171.1
2053	94.673.9–116.7	135.1105–166.8
2054	96.574.3–117	139102.4–172.2
2055	99.175.7–118	140113.8–172.2
2056	99.173.7–118.2	141.8102.8–177.8
2057	100.371.9–123.9	148.8113.3–178.3
2058	97.775.1–121.5	140112–171.9
2059	102.380.5–127.4	142.3114.3–176.6
2060	10380.3–124.4	144.3110.6–176.5
2061	100.978.4–122.6	145109.2–180.3
2062	100.175.4–126.5	146111.1–181.8
2063	100.678.3–122.1	147.1114.5–182.6
2064	10081–123.3	146.4112.8–179.9
2065	103.580.5–128.2	149.2116.8–179
2066	100.780.7–124.6	148.8117.8–185.3
2067	99.678.4–126	142.6114.9–185.1
2068	102.780.1–130.1	152.4114.1–187.8
2069	10477.5–128.1	148.2114.1–185.4
2070	101.179.7–125.6	151.6111–187.8
2071	105.581.4–132.1	155.2117.6–192.8
2072	104.384.4–128.2	155.2118.4–190.6
2073	108.485.4–130	154.8115.7–196.8
2074	105.182.9–126.8	151.6114.2–195.8
2075	102.578.8–126	158.4117.9–190.2
2076	105.582.2–134.6	154.5120–193.1
2077	107.484.1–132.6	164121.3–203.7
2078	107.382.8–127.7	158.9117–196.9
2079	105.379.7–127.2	157.6123.7–192.5
2080	109.784.5–135.9	161.3118.7–197.4
2081	108.986.2–134.4	158.9119.1–200.5
2082	105.783.4–133.6	156.9118.5–201.5
2083	110.287.8–135.8	160.4121.6–203.2
2084	111.582.3–138.1	157.7118.3–198.5
2085	112.381.2–143.6	165.1122.6–201.9
2086	107.882.8–141.1	160.4122–201.3
2087	107.980.1–134	164.1121.4–199.1
2088	107.984.4–143.1	162.3124.7–205.8
2089	107.981.7–137.3	157.8122.5–206.2
2090	108.883.9–136.6	163124.3–204.5
2091	113.486.9–144	167.5124.5–204.5
2092	113.587.1–142.8	173.2125.1–206.7
2093	108.482.7–144.8	166.1126.9–212.1
2094	111.386.8–139.5	167.8130.5–205.1
2095	114.186.4–143.6	173.9123–212.7
2096	10880.4–140.3	164.5127.5–213
2097	110.385–137.8	161.2123.5–206.8
2098	113.687.7–141.1	167.8128.2–206.2
2099	112.585.3–137.7	171129.1–212.5
2100	111.986.8–138.7	163.6126.1–210.4

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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

印度与尼日利亚对比

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冲突

冲突死亡人数印度：2022 年为 358 人死亡尼日利亚：2022 年为 2,803 人死亡