印度尼西亚与泰国：热带夜

2014 年热带夜：印度尼西亚为 306.5 夜，泰国为 286.4 夜（CMIP6 气候模型中位数模拟）。 2014 年印度尼西亚的数值较高，高出 20.1 夜，是泰国的 1.07 倍。

每年夜数 · CMIP6

印度尼西亚泰国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，印度尼西亚的数值都更高。
根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年印度尼西亚为 334.7 夜，泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份	印度尼西亚	泰国
2014	306.5	286.4
2013	306.4	289.1
2012	306.3	286.6
2011	304.6	286.4
2010	305.6	286
2009	303.9	286.9
2008	303.4	284.8
2007	302.8	283.2
2006	302.8	284.3
2005	303.1	281.7
2004	303.8	287.5
2003	301.9	279.3
2002	301.5	280
2001	302.5	285.5
2000	300.9	283.4
1999	300.4	282.5
1998	299.1	282.7
1997	297.9	284.8
1996	296.9	279.8
1995	296.7	278.7
1994	294.6	280.8
1993	291.6	275.6
1992	288.5	268.8
1991	297.5	276.7
1990	298.6	279.2
1989	296	278.4
1988	296.5	279.6
1987	295.6	277.9
1986	295.8	277.5
1985	292.8	276
1984	293.4	277.9
1983	290.1	273.9
1982	294.4	275.7
1981	294.8	277.8
1980	294.5	277.9
1979	294.1	278
1978	292.4	276
1977	293.4	277.3
1976	290.8	275.6
1975	290.7	274.4
1974	291.5	276
1973	293	280.6
1972	290.7	273.9
1971	291.2	273.2
1970	288.9	276
1969	290.4	274.8
1968	289.1	277
1967	288.4	270.3
1966	290.5	274.4
1965	288.1	275.8
1964	286.2	271.9
1963	286.4	274.7
1962	291.2	275.4
1961	292.9	278.5
1960	292.8	276.2
1959	291.9	274.4
1958	293.3	278.7
1957	290.8	277.4
1956	291.5	277
1955	292.4	274.6
1954	290	275
1953	291.4	275.4
1952	291.7	275.1
1951	291.7	277.5
1950	291.8	276.2

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

年份	印度尼西亚	泰国
2015	308295.7–315.1	290.6272.2–305
2016	307.5296.9–315.6	287.1269.8–306.2
2017	308.4295.5–315.6	290273.8–302.8
2018	308.9296.4–316.6	292.6275.1–308.7
2019	309.9297.8–316.7	291.2272.8–306.7
2020	310.9299–318.6	292.4272.2–307.8
2021	310.4298.7–316.4	294.2276.3–308.5
2022	311.4300–319.6	294.8277.2–311.9
2023	311.4300.1–320.6	296.1281.9–310.2
2024	313.2302–321.2	291.7275.5–307.8
2025	312300.2–321.9	294276.7–306.3
2026	312.6299.9–322.8	296278–309.3
2027	312.7301–321.6	295.8276.3–311.1
2028	313.8302.4–321.9	297279.3–315.1
2029	315.5303.9–324.1	300.3278.7–315
2030	314.2303.1–322.6	297.7280.2–312.5
2031	314.4301.6–321.9	300.8282.8–317.1
2032	316.9304.8–325.8	297.2280.9–311.4
2033	316.6305.4–323.3	300281.9–315.8
2034	315.4303.9–323.9	300.8279–318.4
2035	316.3305.6–327.9	298.6281.5–317.8
2036	317.7305.2–326.2	300.4279.9–316.9
2037	318.1306.6–325.2	299.8280–315.1
2038	319.3307.6–326.7	304.8286.6–319.3
2039	319.4307.7–326.7	300.9281.9–317
2040	318.5306.5–329	301.6284.5–315.7
2041	320.2308.3–328	303.1285.1–318.8
2042	320308.7–329.2	303.8290–318.3
2043	318.6306.6–327.8	302285.8–317.9
2044	321309–329.6	304.3286.3–318.8
2045	320.8308.6–329.8	307.1287.7–324.2
2046	322.8308.8–331	305.9285.2–321
2047	323.2308.8–333	306.6289.5–321.5
2048	322.3310.5–332.3	309.4288.9–325.7
2049	323.8311.6–334.1	308.1287.2–324.1
2050	323.3310.3–333.5	307.5291–321.5
2051	323.6311.2–334.4	312.8294.8–326
2052	325.1311.7–334.7	310.9291.2–323.4
2053	323.9310.9–333.8	308.3289.5–323.3
2054	324.4311.9–335.4	308.8292.8–322.3
2055	325.3312.6–335	308.6290.6–325.1
2056	325.9312.4–337.2	311.3294.9–326.3
2057	326.9311.9–335.2	308.5286.7–326.4
2058	326.4313–336.3	308291.1–325.1
2059	326.4313.9–337.8	312.7295.8–325.3
2060	329.5314.9–338.2	313.1294.6–328.6
2061	327.9313.6–336.9	314.4289.5–331.1
2062	327.6312.4–339.1	311.4293.4–330.3
2063	327.6313.9–339.4	314.8296.9–327.3
2064	328.8314.4–338.6	312.5295.4–330
2065	327.6314.3–337.9	309.6293.1–329.3
2066	328.6314.7–338.5	312.1292.6–328
2067	328.8314.3–338	311.2289.6–329.4
2068	329.8314.4–339.9	310.8292.4–330.6
2069	329.5315.5–339.3	315.5296.1–329.5
2070	328.6315.1–338.8	314.2292.9–330.7
2071	331.4315.5–340.4	313.8296.4–330.8
2072	330.3315.9–339.4	314.8296–329.6
2073	331.4317.7–341	316.5299.9–332.1
2074	329.9316.8–341.1	317.2295–333.8
2075	330.5315.2–340.2	317.2295.3–331.4
2076	331.5316.2–341.2	317.4299.8–335
2077	332315.9–341.8	317.5297.3–335.9
2078	331.4318.2–340.9	315.9297.1–331.6
2079	331.5316.6–341.5	318.5300.5–332.3
2080	332.4317.4–343.2	319.8297.4–337.5
2081	332.3318.4–341.8	317.7299.5–334.9
2082	332.8317.8–340.4	317.9294.8–333
2083	333.1318.7–342.6	315297.8–332.9
2084	333317.8–342.7	316295.5–330
2085	332.6318.1–342.7	322.6300.8–334.7
2086	333.1318.9–342.3	319.4295.2–335.2
2087	332.6318–343.2	320.2302.2–334.7
2088	334.5319.5–343.1	321.4299.8–334.8
2089	333.6319–342.6	318.9296.4–338.1
2090	333.3319.6–343.3	317.6304–337.4
2091	334.5318.2–343.9	320.1299.8–336.1
2092	335.1319.7–343.6	316.3298–336.4
2093	333.9320–344.9	316.1297.7–333.7
2094	335.6320.4–342.8	323.4301.8–337.3
2095	335.4319.7–343	322.9302.4–338.9
2096	334.3319.4–346.1	319.6302.8–336.7
2097	334.2319.5–343.3	319.8299.1–336
2098	334.9319.4–343.4	320.5303.9–336
2099	334.4319.4–344.6	319.9303.1–334.4
2100	334.7318.7–343.3	320.8301.1–336.7

分别查看各国

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

印度尼西亚与泰国对比

健康

人口与社会

经济

教育

政治

冲突

冲突死亡人数印度尼西亚：2022 年为 46 人死亡泰国：2022 年为 46 人死亡