墨西哥与泰国：热带夜

2014 年热带夜：墨西哥为 103.7 夜，泰国为 286.4 夜（CMIP6 气候模型中位数模拟）。 2014 年泰国的数值较高，高出 182.7 夜，是墨西哥的 2.76 倍。

每年夜数 · 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 142.8 夜，泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份	墨西哥	泰国
2014	103.7	286.4
2013	103.9	289.1
2012	102.8	286.6
2011	102.9	286.4
2010	101.5	286
2009	101.8	286.9
2008	100.1	284.8
2007	99.1	283.2
2006	99.8	284.3
2005	99.5	281.7
2004	99.4	287.5
2003	98.3	279.3
2002	99.1	280
2001	98.7	285.5
2000	97.9	283.4
1999	96.6	282.5
1998	95.8	282.7
1997	95.9	284.8
1996	93.8	279.8
1995	92.7	278.7
1994	90.7	280.8
1993	89	275.6
1992	88.5	268.8
1991	93.4	276.7
1990	94.9	279.2
1989	93	278.4
1988	92.1	279.6
1987	92	277.9
1986	90.2	277.5
1985	90	276
1984	88	277.9
1983	86.7	273.9
1982	88.7	275.7
1981	91.5	277.8
1980	90.1	277.9
1979	90.8	278
1978	89	276
1977	89	277.3
1976	89.1	275.6
1975	86.8	274.4
1974	87.9	276
1973	88.6	280.6
1972	87.7	273.9
1971	86.8	273.2
1970	86.1	276
1969	87.5	274.8
1968	87.1	277
1967	86.7	270.3
1966	86.4	274.4
1965	84.9	275.8
1964	84.7	271.9
1963	87.1	274.7
1962	88	275.4
1961	89.5	278.5
1960	89.7	276.2
1959	89.6	274.4
1958	89.1	278.7
1957	89	277.4
1956	88.5	277
1955	88.2	274.6
1954	88.4	275
1953	88.6	275.4
1952	87.8	275.1
1951	89.4	277.5
1950	88.1	276.2

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

年份	墨西哥	泰国
2015	106.192.9–118.4	290.6272.2–305
2016	107.695–120	287.1269.8–306.2
2017	108.696.3–119.7	290273.8–302.8
2018	10997.1–120.4	292.6275.1–308.7
2019	110.396.4–123	291.2272.8–306.7
2020	109.696.8–121.8	292.4272.2–307.8
2021	111.296.9–124.1	294.2276.3–308.5
2022	109.796–121.7	294.8277.2–311.9
2023	111.898.6–125.3	296.1281.9–310.2
2024	112.298.2–126.2	291.7275.5–307.8
2025	11298.8–125.8	294276.7–306.3
2026	113.999.5–126.4	296278–309.3
2027	112.999.5–128.3	295.8276.3–311.1
2028	115.2101.9–127.9	297279.3–315.1
2029	115.6101.9–127.9	300.3278.7–315
2030	115.9101.7–128.4	297.7280.2–312.5
2031	116.1100.9–129.9	300.8282.8–317.1
2032	116.1102.5–129.1	297.2280.9–311.4
2033	117.5102.5–131.1	300281.9–315.8
2034	117.2104.1–130.3	300.8279–318.4
2035	116.4103.1–130.3	298.6281.5–317.8
2036	117.8105.1–131	300.4279.9–316.9
2037	118.6104.3–131.7	299.8280–315.1
2038	121107.5–133.4	304.8286.6–319.3
2039	121.3107–135.6	300.9281.9–317
2040	121.9108.1–135.1	301.6284.5–315.7
2041	121.3105.3–134.6	303.1285.1–318.8
2042	122.7107.7–137.1	303.8290–318.3
2043	122.4108.1–137.5	302285.8–317.9
2044	121.9108–135.6	304.3286.3–318.8
2045	123.1108.8–139.2	307.1287.7–324.2
2046	123.8109.9–139.4	305.9285.2–321
2047	125.6111.9–139.4	306.6289.5–321.5
2048	126.3113–140.3	309.4288.9–325.7
2049	127111.2–140.8	308.1287.2–324.1
2050	128.1112.6–142.5	307.5291–321.5
2051	127.2113.4–140.8	312.8294.8–326
2052	126.2112.5–141.1	310.9291.2–323.4
2053	128.4111.5–142.7	308.3289.5–323.3
2054	128.1113.1–142.3	308.8292.8–322.3
2055	129114.4–144.7	308.6290.6–325.1
2056	129.5114.3–143.8	311.3294.9–326.3
2057	130.3113.5–145.9	308.5286.7–326.4
2058	128.8114.1–144.5	308291.1–325.1
2059	129.5114.5–144.5	312.7295.8–325.3
2060	131.4115.5–146.5	313.1294.6–328.6
2061	131.3118.4–146.8	314.4289.5–331.1
2062	130.8115.1–146.3	311.4293.4–330.3
2063	131.2115.6–147.9	314.8296.9–327.3
2064	132.2116.5–147.8	312.5295.4–330
2065	133.1115.8–148.6	309.6293.1–329.3
2066	133.3117.2–149.4	312.1292.6–328
2067	133.3117–150.3	311.2289.6–329.4
2068	134.6117.4–150.5	310.8292.4–330.6
2069	134.4117.8–150.9	315.5296.1–329.5
2070	134.2116.7–151.8	314.2292.9–330.7
2071	136.3120.8–152.7	313.8296.4–330.8
2072	137.2119.9–153.1	314.8296–329.6
2073	136.1119.1–153.6	316.5299.9–332.1
2074	136119.7–152.2	317.2295–333.8
2075	135.2118.5–151.8	317.2295.3–331.4
2076	136.3117.4–154.7	317.4299.8–335
2077	136.8119.6–152.8	317.5297.3–335.9
2078	137.1118.3–154.2	315.9297.1–331.6
2079	138.1121.3–157.1	318.5300.5–332.3
2080	137.6120.5–157.9	319.8297.4–337.5
2081	137.8120.7–154.7	317.7299.5–334.9
2082	138.7121.6–155.2	317.9294.8–333
2083	139.2119.3–158.8	315297.8–332.9
2084	140.3123.4–157.5	316295.5–330
2085	139.2120.9–157.2	322.6300.8–334.7
2086	139.8121–157.8	319.4295.2–335.2
2087	139.5121.5–157.4	320.2302.2–334.7
2088	141121.8–159.9	321.4299.8–334.8
2089	140.4121.7–158.9	318.9296.4–338.1
2090	141.2123–160.7	317.6304–337.4
2091	141.8123–161.6	320.1299.8–336.1
2092	141.3122.5–159.3	316.3298–336.4
2093	141.4124.3–161	316.1297.7–333.7
2094	142123.3–159.6	323.4301.8–337.3
2095	143.5124–160.7	322.9302.4–338.9
2096	142.3125–161.3	319.6302.8–336.7
2097	141.2123.2–160	319.8299.1–336
2098	142.2122.5–162	320.5303.9–336
2099	141.8122.4–160.7	319.9303.1–334.4
2100	142.8124.3–160.8	320.8301.1–336.7

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须知

一年中气温始终高于 20 °C 的夜晚数，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

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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