尼日利亚与泰国：35 °C 以上天数

2014 年35 °C 以上天数：尼日利亚为 107.4 天，泰国为 39.9 天（CMIP6 气候模型中位数模拟）。 2014 年尼日利亚的数值较高，高出 67.5 天，是泰国的 2.69 倍。

每年天数 · CMIP6

尼日利亚泰国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 年尼日利亚为 163.6 天，泰国为 95.9 天。

逐年数据

每年天数 · CMIP6

年份	尼日利亚	泰国
2014	107.4	39.9
2013	104.3	42.1
2012	104.4	40.1
2011	103.7	39.9
2010	101.1	39.8
2009	99.4	37.9
2008	98.6	36
2007	97.4	33
2006	97.9	39.2
2005	97.2	34.9
2004	99.2	39.4
2003	98.2	34.1
2002	98.3	36.3
2001	102.2	37.8
2000	96.3	32.5
1999	92.3	29.7
1998	91.6	33.3
1997	95.2	33.7
1996	89.5	31.3
1995	90.2	33.5
1994	86.1	33.5
1993	83.5	30.4
1992	81.3	25.5
1991	94.2	35.4
1990	95	37.7
1989	89.3	29.3
1988	93.4	30.6
1987	90.4	31.2
1986	93.2	34.3
1985	87	29.3
1984	89.5	32.4
1983	88.5	30.4
1982	89.6	33.1
1981	91.9	29.5
1980	89.5	28.8
1979	89.8	32.4
1978	88	26.1
1977	88.4	31.5
1976	83.6	29.7
1975	87.3	25
1974	84.9	31.5
1973	88.3	34.5
1972	87.1	30.3
1971	84.5	27.1
1970	87.3	28.7
1969	87.1	29.9
1968	84.9	29.4
1967	84.8	28.3
1966	85.7	25.4
1965	85.7	27.1
1964	77.7	26.6
1963	81.7	26
1962	89.3	28.7
1961	91.6	31.1
1960	91.4	32.9
1959	88.3	24.4
1958	89.9	33
1957	91.2	27.8
1956	84.6	27.1
1955	88.4	31.2
1954	88.8	30.3
1953	91.7	28.2
1952	87.9	34.1
1951	92.1	33
1950	88.9	28.5

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

年份	尼日利亚	泰国
2015	105.581.2–130.1	41.123.5–66.3
2016	101.478.2–120.6	38.915.7–61.2
2017	10680.5–130.9	41.420.8–64.9
2018	105.177.2–129	43.521.7–65.5
2019	104.378.3–130.3	40.916.5–61.9
2020	104.778.2–130.2	45.617.3–66.6
2021	104.885.2–128.6	43.720.7–70.7
2022	111.184.4–135.5	47.826.4–73.3
2023	106.585.6–130.6	41.822.3–67.2
2024	114.493.3–136.4	44.726.9–70.9
2025	112.191.1–132	50.227.3–77
2026	108.574.8–133.8	44.425.2–80.5
2027	114.581.7–136.4	47.126.2–75.6
2028	113.487.6–141.8	51.123.1–73.3
2029	116.591.5–141	56.733.9–84.7
2030	117.785.5–145.3	50.726.1–78.9
2031	116.388.2–141.7	50.531.5–81.2
2032	118.785.8–144.2	49.823.6–85.7
2033	118.490.6–146	53.432–73.7
2034	117.689–144.4	51.531.6–83.4
2035	12087.5–144.3	52.228.9–89.2
2036	116.889.2–143.5	53.335.2–77.4
2037	124.790.9–151.6	57.632–82.5
2038	126.696.2–152.6	62.238.5–91.5
2039	122.697–147.4	55.127.8–78.8
2040	121.193.5–153.7	53.728.4–91.3
2041	127.599.5–154.2	6337.5–86.6
2042	12896.1–152.5	54.826.4–94.7
2043	124.298.9–149.7	57.129.8–85.3
2044	125.496.3–152.8	57.336.7–95.7
2045	129.499.4–156.4	54.934.2–90.2
2046	135.999.9–158.5	62.736.4–102.1
2047	135.299–159.5	63.635–98.5
2048	133.1103.7–160.3	72.237.4–110.4
2049	135.4104.4–161.8	66.240.8–98.3
2050	131.3102–166.4	64.536.9–95.3
2051	131.6106.2–166.5	66.135.5–97.1
2052	139.6101.6–171.1	74.339.3–108.1
2053	135.1105–166.8	64.635–106.7
2054	139102.4–172.2	69.144.2–112.1
2055	140113.8–172.2	71.445.3–107.6
2056	141.8102.8–177.8	70.536.5–117.7
2057	148.8113.3–178.3	7240–104.6
2058	140112–171.9	73.140.6–107.3
2059	142.3114.3–176.6	77.251.2–121.4
2060	144.3110.6–176.5	80.946–117
2061	145109.2–180.3	77.335.3–117.8
2062	146111.1–181.8	73.535.5–125.8
2063	147.1114.5–182.6	83.640.3–122.6
2064	146.4112.8–179.9	74.746.9–111.8
2065	149.2116.8–179	69.939.5–124.8
2066	148.8117.8–185.3	80.250.7–122.7
2067	142.6114.9–185.1	69.437.9–116
2068	152.4114.1–187.8	76.445.8–131.7
2069	148.2114.1–185.4	77.747.4–128.7
2070	151.6111–187.8	73.839.2–129.5
2071	155.2117.6–192.8	80.642.2–131.6
2072	155.2118.4–190.6	81.347.5–135.3
2073	154.8115.7–196.8	88.854.2–133.4
2074	151.6114.2–195.8	8444.3–128.1
2075	158.4117.9–190.2	82.838.3–123.9
2076	154.5120–193.1	82.937.1–132.9
2077	164121.3–203.7	8849.4–132.4
2078	158.9117–196.9	91.252–137
2079	157.6123.7–192.5	85.749.5–144.4
2080	161.3118.7–197.4	88.552.7–143.6
2081	158.9119.1–200.5	87.150.9–135.1
2082	156.9118.5–201.5	89.953.5–133.6
2083	160.4121.6–203.2	87.145.8–149.7
2084	157.7118.3–198.5	8447.7–131
2085	165.1122.6–201.9	93.853.8–141.8
2086	160.4122–201.3	87.745.8–139.2
2087	164.1121.4–199.1	86.447.4–139.2
2088	162.3124.7–205.8	90.441.7–153.2
2089	157.8122.5–206.2	90.149–151.2
2090	163124.3–204.5	87.853.3–154.1
2091	167.5124.5–204.5	8648.2–148.6
2092	173.2125.1–206.7	92.650.2–149.9
2093	166.1126.9–212.1	89.854.6–159
2094	167.8130.5–205.1	95.549.6–143.6
2095	173.9123–212.7	103.458.2–156.3
2096	164.5127.5–213	89.951.3–155.4
2097	161.2123.5–206.8	94.550.2–142.6
2098	167.8128.2–206.2	89.851.6–149.6
2099	171129.1–212.5	88.244.7–147.4
2100	163.6126.1–210.4	95.951.1–153.3

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

尼日利亚与泰国对比

健康

人口与社会

经济

教育

政治

冲突

冲突死亡人数尼日利亚：2022 年为 2,803 人死亡泰国：2022 年为 46 人死亡