印度与尼泊尔：热带夜

2014 年热带夜：印度为 215.5 夜，尼泊尔为 65.9 夜（CMIP6 气候模型中位数模拟）。 2014 年印度的数值较高，高出 149.7 夜，是尼泊尔的 3.27 倍。

每年夜数 · CMIP6

印度尼泊尔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 250.4 夜，尼泊尔为 89.9 夜。

逐年数据

每年夜数 · CMIP6

年份	印度	尼泊尔
2014	215.5	65.9
2013	216	66.5
2012	217.4	66
2011	215.5	64.7
2010	215.2	65.7
2009	213.7	63.8
2008	213.7	64.1
2007	213.3	64.3
2006	212.5	64.4
2005	212.9	64.4
2004	214.9	64.2
2003	212.1	64.2
2002	213	65
2001	212.2	63.6
2000	210.8	63.4
1999	211.9	63.3
1998	210.3	61.8
1997	209.5	62.3
1996	207	60.9
1995	208.8	60.7
1994	207.1	59.8
1993	206	59.6
1992	203.5	57.3
1991	208	62
1990	209.9	62.1
1989	208	61
1988	207.3	59.8
1987	207.2	60.2
1986	207.2	59.9
1985	205.9	59.2
1984	206.7	59.4
1983	203.3	57.4
1982	205.7	60.2
1981	208.4	59.9
1980	205.3	60.3
1979	205.5	59.2
1978	204.1	58.8
1977	205.9	59.3
1976	204.6	58.8
1975	202.6	58.3
1974	205.3	59.8
1973	205.6	59.2
1972	203.8	57.9
1971	203.6	58.9
1970	202.6	58.1
1969	203.6	57.9
1968	201.7	57.6
1967	201.6	57.3
1966	203.9	58.8
1965	202.4	57.3
1964	201.2	57.3
1963	201.8	58.1
1962	203.8	58.8
1961	206.3	59.1
1960	206	59.8
1959	206.1	60.2
1958	204	59.1
1957	206.5	59.3
1956	204	59.1
1955	203.2	58.2
1954	206	59.3
1953	204	58.7
1952	204.4	59
1951	204.3	59.3
1950	206.3	59.1

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

年份	印度	尼泊尔
2015	216.9202.1–228.4	66.560–73.8
2016	215202.5–227.6	66.358.3–73.6
2017	216.2202.1–228.5	66.758.6–73.6
2018	218.3204.5–231.4	65.658.9–73.3
2019	217.4202.3–230.4	66.358–74.3
2020	217.6203.1–232	68.360.6–75.9
2021	219.7204.5–233.2	67.959.6–75.8
2022	220.5205.8–233	68.661–75.3
2023	220.4206.4–233.7	69.361.6–76.2
2024	222.6208.1–236.3	7063–78.7
2025	219.7202.7–236.2	68.660.3–78.1
2026	220.2204.2–236.8	69.859.8–78.5
2027	223.6207.1–239	69.761–78.1
2028	222.1205.1–235.7	70.562.6–78
2029	225.4210–240.3	70.461.7–80.6
2030	222.7207.3–235.6	7061.3–78.5
2031	223.8207.1–237.8	71.262.8–78.6
2032	225.9210–240.5	72.163.9–81.1
2033	223.8209.3–235.4	71.264.8–78
2034	225.8210–242.7	71.663.8–80.2
2035	224.9210.6–240.9	72.664.3–83
2036	224.2210.4–240.3	71.965–80.3
2037	228.3213.6–242.6	74.165.9–84.2
2038	228.1212.6–241.4	74.167–83.3
2039	227.4211.9–242.8	73.565.2–82.5
2040	227212.2–242	73.865.9–83.3
2041	227.1210.7–240.5	75.368.2–83.4
2042	229.1214.8–244.2	75.667.7–84.9
2043	228.9214.5–244	75.566.3–85
2044	229.7214.7–244.2	76.467.5–85.4
2045	231.2216.6–246.1	76.567.9–85.2
2046	232.6216.2–248.6	76.966.8–86
2047	232.4215.5–250	77.766.9–86.2
2048	235.6218.5–254.3	78.367.8–88
2049	235.3218.3–249.9	78.568.6–87.8
2050	233.5216.6–253.4	79.367.8–90
2051	234.9218.6–249.9	7970.1–88.5
2052	234219.4–249.3	79.570.4–88.6
2053	234.9219.5–252.5	79.170.1–88.4
2054	237.2219.4–253.1	79.168.9–89
2055	237.2220.7–256.6	80.571.8–89.3
2056	238.8221.2–254.9	79.771.5–89.6
2057	235.7218.5–253.8	80.671.9–89.8
2058	238.8222.8–254.1	80.771–91.5
2059	241.1224.9–256.2	80.770.6–93.7
2060	240.9225.6–255.6	82.472.9–91.7
2061	237.9220.6–253.7	80.871.4–90.4
2062	239.9221.2–259.7	82.172–93.2
2063	239.9222.3–256.1	82.271.5–92.1
2064	240223.8–256.3	82.872.6–92
2065	240.9222.9–257.3	82.672.2–93.3
2066	241.5224.1–258.6	83.772.4–94.2
2067	241.6224.8–257.9	82.771.9–93.3
2068	242.3224.6–262.1	84.772.4–95.1
2069	242.8225.4–259.1	8573–94.3
2070	240.1225.3–257.1	83.273.2–92.7
2071	241.8223.7–260.2	83.872.9–93.9
2072	242.6225.4–259.2	85.274.6–95.4
2073	243.8228–259.3	85.875.3–96.4
2074	241.6226.9–258.4	84.474.5–95.8
2075	243.5226.4–258.2	8574.2–95.4
2076	243.2224.6–259.9	85.974.8–95
2077	243.7226.6–264.6	86.775.4–97.4
2078	246.7230.1–261.5	85.775.7–96.6
2079	244.9226.4–261.3	85.973.7–96
2080	246.7227–263.7	87.576.4–97.7
2081	247.5230.4–264.8	87.577.2–98.1
2082	244.6227.9–262.3	86.877.3–98.8
2083	247.5227.8–265.1	8876.6–99.5
2084	247.3228.3–266.8	88.377.6–99.6
2085	246.5227.5–267.1	87.876.3–100.8
2086	245.6227.7–266.5	87.975.2–100.2
2087	245.5226.7–266.2	87.476.2–98.9
2088	247229.4–266.9	87.375.6–99.2
2089	248.1230–266.3	8776.2–100.1
2090	249228.9–266.4	87.977.5–99
2091	248.9230–266.5	88.877.6–101.7
2092	249.8232.3–267.8	88.477.7–101.1
2093	248.1229–266.5	88.776.8–99.9
2094	249.1230.6–268.4	88.677.6–99.5
2095	251233.2–270	89.478.8–99.7
2096	247.8231.4–269.3	89.178.6–101.7
2097	251.1231.4–268	87.976.6–99.4
2098	252.3230.8–268.3	89.678.1–100.1
2099	248.7230.1–268.3	89.778.5–100.7
2100	250.4232.9–266.7	89.980–100

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

印度与尼泊尔对比

健康

人口与社会

经济

教育

政治

冲突

冲突死亡人数印度：2022 年为 358 人死亡尼泊尔：2022 年为 0 人死亡