墨西哥与泰国：35 °C 以上天数

2014 年35 °C 以上天数：墨西哥为 32.8 天，泰国为 39.9 天（CMIP6 气候模型中位数模拟）。 2014 年泰国的数值较高，高出 7.1 天，是墨西哥的 1.22 倍。

每年天数 · CMIP6

墨西哥泰国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，泰国的数值都更高。
根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年墨西哥为 67.8 天，泰国为 95.9 天。

逐年数据

每年天数 · CMIP6

年份	墨西哥	泰国
2014	32.8	39.9
2013	31.6	42.1
2012	30.4	40.1
2011	30.5	39.9
2010	31.8	39.8
2009	30.6	37.9
2008	30.7	36
2007	29	33
2006	28.6	39.2
2005	29.2	34.9
2004	29.4	39.4
2003	27.2	34.1
2002	27.8	36.3
2001	29.6	37.8
2000	27.9	32.5
1999	26.4	29.7
1998	27	33.3
1997	26.7	33.7
1996	25.7	31.3
1995	25.1	33.5
1994	24.1	33.5
1993	21.9	30.4
1992	20.9	25.5
1991	26.5	35.4
1990	26.5	37.7
1989	24	29.3
1988	23.9	30.6
1987	25.7	31.2
1986	24.1	34.3
1985	21.9	29.3
1984	22	32.4
1983	20.7	30.4
1982	22.1	33.1
1981	23.4	29.5
1980	22.5	28.8
1979	24	32.4
1978	22.5	26.1
1977	22.8	31.5
1976	22.2	29.7
1975	21.3	25
1974	22.6	31.5
1973	21.7	34.5
1972	22.5	30.3
1971	21.2	27.1
1970	22.3	28.7
1969	23.1	29.9
1968	21.7	29.4
1967	22.8	28.3
1966	21.9	25.4
1965	20.3	27.1
1964	20.6	26.6
1963	22.1	26
1962	22.7	28.7
1961	23.5	31.1
1960	23.2	32.9
1959	23.7	24.4
1958	22.9	33
1957	22.3	27.8
1956	22.8	27.1
1955	23.1	31.2
1954	22.1	30.3
1953	22.5	28.2
1952	21.4	34.1
1951	22.1	33
1950	22.3	28.5

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

年份	墨西哥	泰国
2015	35.225.3–48.5	41.123.5–66.3
2016	33.924.5–44.6	38.915.7–61.2
2017	35.424.4–46.9	41.420.8–64.9
2018	3625.2–47.9	43.521.7–65.5
2019	36.726–51.6	40.916.5–61.9
2020	37.325.8–50.6	45.617.3–66.6
2021	37.726.7–51.1	43.720.7–70.7
2022	37.225.5–52	47.826.4–73.3
2023	38.426.6–52.5	41.822.3–67.2
2024	42.228.1–55.6	44.726.9–70.9
2025	39.627.6–53.3	50.227.3–77
2026	39.126.4–51.8	44.425.2–80.5
2027	37.926.5–53.6	47.126.2–75.6
2028	40.127.8–55.7	51.123.1–73.3
2029	41.727.6–56.7	56.733.9–84.7
2030	39.325.9–53	50.726.1–78.9
2031	4127.8–56.3	50.531.5–81.2
2032	42.527.6–55.9	49.823.6–85.7
2033	42.530.2–57.1	53.432–73.7
2034	40.427.8–56.6	51.531.6–83.4
2035	40.528.2–56.9	52.228.9–89.2
2036	41.428.9–55.3	53.335.2–77.4
2037	44.230–59.6	57.632–82.5
2038	45.130.6–59.7	62.238.5–91.5
2039	4732.9–63.1	55.127.8–78.8
2040	46.933.9–61.8	53.728.4–91.3
2041	44.530.9–60.8	6337.5–86.6
2042	48.633.8–64.3	54.826.4–94.7
2043	46.632.5–63.4	57.129.8–85.3
2044	47.234.1–63.7	57.336.7–95.7
2045	48.333.7–65.3	54.934.2–90.2
2046	5035.6–64.3	62.736.4–102.1
2047	51.537.2–67	63.635–98.5
2048	50.235.3–67.1	72.237.4–110.4
2049	52.336.1–69.5	66.240.8–98.3
2050	50.234.4–66.5	64.536.9–95.3
2051	50.436.9–66.9	66.135.5–97.1
2052	5235.5–68.6	74.339.3–108.1
2053	5336.9–70.2	64.635–106.7
2054	52.835.8–69.3	69.144.2–112.1
2055	54.437.3–71.1	71.445.3–107.6
2056	52.837.6–69.6	70.536.5–117.7
2057	55.937–72	7240–104.6
2058	51.536.7–70.5	73.140.6–107.3
2059	55.340.6–72.6	77.251.2–121.4
2060	55.739.5–73.4	80.946–117
2061	57.642.1–73.9	77.335.3–117.8
2062	5535.6–77	73.535.5–125.8
2063	57.641.7–77.2	83.640.3–122.6
2064	58.242.8–75	74.746.9–111.8
2065	59.540.3–79	69.939.5–124.8
2066	57.940.6–76.3	80.250.7–122.7
2067	5841.9–76.7	69.437.9–116
2068	60.343.2–79.1	76.445.8–131.7
2069	58.339.8–80.5	77.747.4–128.7
2070	60.239.8–80.8	73.839.2–129.5
2071	61.344.6–81.4	80.642.2–131.6
2072	63.144–80.9	81.347.5–135.3
2073	62.842.3–85.4	88.854.2–133.4
2074	6043.5–80.9	8444.3–128.1
2075	60.842.2–80.8	82.838.3–123.9
2076	61.242.4–83.6	82.937.1–132.9
2077	60.843.2–79.8	8849.4–132.4
2078	64.744.4–86.4	91.252–137
2079	6646.1–87.4	85.749.5–144.4
2080	64.744–84.6	88.552.7–143.6
2081	64.845.7–84.4	87.150.9–135.1
2082	63.643.2–82.2	89.953.5–133.6
2083	65.140.9–89.7	87.145.8–149.7
2084	65.446.4–86.3	8447.7–131
2085	65.744.8–85.9	93.853.8–141.8
2086	64.644.8–85.1	87.745.8–139.2
2087	64.644.4–84.2	86.447.4–139.2
2088	6545.7–86.5	90.441.7–153.2
2089	66.644.2–87.9	90.149–151.2
2090	66.246–89	87.853.3–154.1
2091	6946.6–92.4	8648.2–148.6
2092	67.746–86.5	92.650.2–149.9
2093	66.846.9–91.6	89.854.6–159
2094	67.546.7–92.1	95.549.6–143.6
2095	70.149.8–93.9	103.458.2–156.3
2096	68.547.9–91.7	89.951.3–155.4
2097	67.346–89.7	94.550.2–142.6
2098	71.348.2–95.2	89.851.6–149.6
2099	68.349.1–91.5	88.244.7–147.4
2100	67.846.4–88.6	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

墨西哥与泰国对比

健康

人口与社会

经济

教育

政治

冲突

冲突死亡人数墨西哥：2022 年为 14,210 人死亡泰国：2022 年为 46 人死亡