印度与泰国对比

印度与泰国：热带夜

2014 年热带夜：印度为 215.5 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 70.9 夜，是印度的 1.33 倍。

在地图上查看其变化

每年夜数 · CMIP6

印度与泰国：热带夜2014 年热带夜：印度为 215.5 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 70.9 夜，是印度的 1.33 倍。
印度泰国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 年印度为 250.4 夜，泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份印度泰国
2014215.5286.4
2013216289.1
2012217.4286.6
2011215.5286.4
2010215.2286
2009213.7286.9
2008213.7284.8
2007213.3283.2
2006212.5284.3
2005212.9281.7
2004214.9287.5
2003212.1279.3
2002213280
2001212.2285.5
2000210.8283.4
1999211.9282.5
1998210.3282.7
1997209.5284.8
1996207279.8
1995208.8278.7
1994207.1280.8
1993206275.6
1992203.5268.8
1991208276.7
1990209.9279.2
1989208278.4
1988207.3279.6
1987207.2277.9
1986207.2277.5
1985205.9276
1984206.7277.9
1983203.3273.9
1982205.7275.7
1981208.4277.8
1980205.3277.9
1979205.5278
1978204.1276
1977205.9277.3
1976204.6275.6
1975202.6274.4
1974205.3276
1973205.6280.6
1972203.8273.9
1971203.6273.2
1970202.6276
1969203.6274.8
1968201.7277
1967201.6270.3
1966203.9274.4
1965202.4275.8
1964201.2271.9
1963201.8274.7
1962203.8275.4
1961206.3278.5
1960206276.2
1959206.1274.4
1958204278.7
1957206.5277.4
1956204277
1955203.2274.6
1954206275
1953204275.4
1952204.4275.1
1951204.3277.5
1950206.3276.2
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份印度泰国
2015216.9202.1–228.4290.6272.2–305
2016215202.5–227.6287.1269.8–306.2
2017216.2202.1–228.5290273.8–302.8
2018218.3204.5–231.4292.6275.1–308.7
2019217.4202.3–230.4291.2272.8–306.7
2020217.6203.1–232292.4272.2–307.8
2021219.7204.5–233.2294.2276.3–308.5
2022220.5205.8–233294.8277.2–311.9
2023220.4206.4–233.7296.1281.9–310.2
2024222.6208.1–236.3291.7275.5–307.8
2025219.7202.7–236.2294276.7–306.3
2026220.2204.2–236.8296278–309.3
2027223.6207.1–239295.8276.3–311.1
2028222.1205.1–235.7297279.3–315.1
2029225.4210–240.3300.3278.7–315
2030222.7207.3–235.6297.7280.2–312.5
2031223.8207.1–237.8300.8282.8–317.1
2032225.9210–240.5297.2280.9–311.4
2033223.8209.3–235.4300281.9–315.8
2034225.8210–242.7300.8279–318.4
2035224.9210.6–240.9298.6281.5–317.8
2036224.2210.4–240.3300.4279.9–316.9
2037228.3213.6–242.6299.8280–315.1
2038228.1212.6–241.4304.8286.6–319.3
2039227.4211.9–242.8300.9281.9–317
2040227212.2–242301.6284.5–315.7
2041227.1210.7–240.5303.1285.1–318.8
2042229.1214.8–244.2303.8290–318.3
2043228.9214.5–244302285.8–317.9
2044229.7214.7–244.2304.3286.3–318.8
2045231.2216.6–246.1307.1287.7–324.2
2046232.6216.2–248.6305.9285.2–321
2047232.4215.5–250306.6289.5–321.5
2048235.6218.5–254.3309.4288.9–325.7
2049235.3218.3–249.9308.1287.2–324.1
2050233.5216.6–253.4307.5291–321.5
2051234.9218.6–249.9312.8294.8–326
2052234219.4–249.3310.9291.2–323.4
2053234.9219.5–252.5308.3289.5–323.3
2054237.2219.4–253.1308.8292.8–322.3
2055237.2220.7–256.6308.6290.6–325.1
2056238.8221.2–254.9311.3294.9–326.3
2057235.7218.5–253.8308.5286.7–326.4
2058238.8222.8–254.1308291.1–325.1
2059241.1224.9–256.2312.7295.8–325.3
2060240.9225.6–255.6313.1294.6–328.6
2061237.9220.6–253.7314.4289.5–331.1
2062239.9221.2–259.7311.4293.4–330.3
2063239.9222.3–256.1314.8296.9–327.3
2064240223.8–256.3312.5295.4–330
2065240.9222.9–257.3309.6293.1–329.3
2066241.5224.1–258.6312.1292.6–328
2067241.6224.8–257.9311.2289.6–329.4
2068242.3224.6–262.1310.8292.4–330.6
2069242.8225.4–259.1315.5296.1–329.5
2070240.1225.3–257.1314.2292.9–330.7
2071241.8223.7–260.2313.8296.4–330.8
2072242.6225.4–259.2314.8296–329.6
2073243.8228–259.3316.5299.9–332.1
2074241.6226.9–258.4317.2295–333.8
2075243.5226.4–258.2317.2295.3–331.4
2076243.2224.6–259.9317.4299.8–335
2077243.7226.6–264.6317.5297.3–335.9
2078246.7230.1–261.5315.9297.1–331.6
2079244.9226.4–261.3318.5300.5–332.3
2080246.7227–263.7319.8297.4–337.5
2081247.5230.4–264.8317.7299.5–334.9
2082244.6227.9–262.3317.9294.8–333
2083247.5227.8–265.1315297.8–332.9
2084247.3228.3–266.8316295.5–330
2085246.5227.5–267.1322.6300.8–334.7
2086245.6227.7–266.5319.4295.2–335.2
2087245.5226.7–266.2320.2302.2–334.7
2088247229.4–266.9321.4299.8–334.8
2089248.1230–266.3318.9296.4–338.1
2090249228.9–266.4317.6304–337.4
2091248.9230–266.5320.1299.8–336.1
2092249.8232.3–267.8316.3298–336.4
2093248.1229–266.5316.1297.7–333.7
2094249.1230.6–268.4323.4301.8–337.3
2095251233.2–270322.9302.4–338.9
2096247.8231.4–269.3319.6302.8–336.7
2097251.1231.4–268319.8299.1–336
2098252.3230.8–268.3320.5303.9–336
2099248.7230.1–268.3319.9303.1–334.4
2100250.4232.9–266.7320.8301.1–336.7

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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。

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