印度与斯里兰卡对比

印度与斯里兰卡：热带夜

2014 年热带夜：印度为 215.5 夜，斯里兰卡为 337.9 夜（CMIP6 气候模型中位数模拟）。 2014 年斯里兰卡的数值较高，高出 122.4 夜，是印度的 1.57 倍。

在地图上查看其变化

每年夜数 · CMIP6

印度与斯里兰卡：热带夜2014 年热带夜：印度为 215.5 夜，斯里兰卡为 337.9 夜（CMIP6 气候模型中位数模拟）。 2014 年斯里兰卡的数值较高，高出 122.4 夜，是印度的 1.57 倍。
印度斯里兰卡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，斯里兰卡的数值都更高。
  • 根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年印度为 250.4 夜，斯里兰卡为 356.1 夜。

逐年数据

每年夜数 · CMIP6

年份印度斯里兰卡
2014215.5337.9
2013216338.4
2012217.4336.9
2011215.5336.8
2010215.2336.2
2009213.7337.2
2008213.7335.4
2007213.3333.4
2006212.5335.8
2005212.9335.4
2004214.9336
2003212.1334.5
2002213335.5
2001212.2335
2000210.8332.9
1999211.9332.1
1998210.3334.3
1997209.5330.9
1996207331.1
1995208.8331.2
1994207.1328.8
1993206326.3
1992203.5324.5
1991208331.7
1990209.9332.5
1989208330.1
1988207.3330.7
1987207.2329.7
1986207.2329.1
1985205.9328
1984206.7328.3
1983203.3324
1982205.7328
1981208.4330.5
1980205.3328.6
1979205.5328.3
1978204.1326.9
1977205.9328.8
1976204.6325.9
1975202.6325.6
1974205.3326.3
1973205.6326.9
1972203.8325.1
1971203.6326.9
1970202.6324.4
1969203.6324.5
1968201.7323.2
1967201.6322.4
1966203.9324.6
1965202.4324.1
1964201.2324.6
1963201.8322.6
1962203.8327.7
1961206.3326.8
1960206326.4
1959206.1326.1
1958204327.2
1957206.5325.5
1956204324.6
1955203.2326.1
1954206324.6
1953204324.4
1952204.4325.9
1951204.3326.3
1950206.3328.4
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份印度斯里兰卡
2015216.9202.1–228.4339.4328.1–347.4
2016215202.5–227.6339326.4–346.7
2017216.2202.1–228.5339.5327.6–346.8
2018218.3204.5–231.4340.4328.3–347
2019217.4202.3–230.4340.4328.1–346.4
2020217.6203.1–232341.6331.3–348.4
2021219.7204.5–233.2341.5327.8–347.3
2022220.5205.8–233340.6329.7–347.9
2023220.4206.4–233.7342.4331–349.4
2024222.6208.1–236.3343.6332.7–349.8
2025219.7202.7–236.2342.3331–348.4
2026220.2204.2–236.8341.7328.8–350.2
2027223.6207.1–239344334.3–351.2
2028222.1205.1–235.7344.3334.6–350.5
2029225.4210–240.3344333.2–350
2030222.7207.3–235.6345.4334.7–351.4
2031223.8207.1–237.8344.1331.4–351.1
2032225.9210–240.5344.5332.2–352.3
2033223.8209.3–235.4346.1333.6–351.7
2034225.8210–242.7346.2334.9–352.2
2035224.9210.6–240.9345.6337.6–353
2036224.2210.4–240.3347.3335.8–353.1
2037228.3213.6–242.6347332.5–352.5
2038228.1212.6–241.4348338.7–353.5
2039227.4211.9–242.8347.7338.1–352.8
2040227212.2–242347.7337.4–353.8
2041227.1210.7–240.5347.8336.6–353.4
2042229.1214.8–244.2347.4336.7–353.8
2043228.9214.5–244348.1337.1–353.8
2044229.7214.7–244.2347.5338.5–354.6
2045231.2216.6–246.1348.5339.9–354.9
2046232.6216.2–248.6350339–355.4
2047232.4215.5–250350.1339.2–355.3
2048235.6218.5–254.3350.9339.3–356.1
2049235.3218.3–249.9351.7340.7–355.9
2050233.5216.6–253.4350.2339.4–356.3
2051234.9218.6–249.9350.4340.3–356.3
2052234219.4–249.3351.5341.3–356.8
2053234.9219.5–252.5350.6341.6–356.1
2054237.2219.4–253.1351.2339.9–357.3
2055237.2220.7–256.6351.2342.2–356.7
2056238.8221.2–254.9352.4341–358.2
2057235.7218.5–253.8352.2341–357
2058238.8222.8–254.1351.2340.8–358.1
2059241.1224.9–256.2352.4343–357.5
2060240.9225.6–255.6354342.7–358.8
2061237.9220.6–253.7351.9340.9–357.2
2062239.9221.2–259.7352.6341.4–358.1
2063239.9222.3–256.1353341.7–358.6
2064240223.8–256.3353.4342.5–358.9
2065240.9222.9–257.3353.2343.7–357.9
2066241.5224.1–258.6353.9342.3–358.5
2067241.6224.8–257.9352.9342.4–358.9
2068242.3224.6–262.1353.4343–359.6
2069242.8225.4–259.1354344.3–359.1
2070240.1225.3–257.1354.3342.8–358.6
2071241.8223.7–260.2353.5343.4–359.4
2072242.6225.4–259.2354.7345.5–359.2
2073243.8228–259.3353.6343.3–359
2074241.6226.9–258.4354.1345–359.7
2075243.5226.4–258.2354.7344.7–359.5
2076243.2224.6–259.9354.7341.4–360.4
2077243.7226.6–264.6354.9343.5–359.9
2078246.7230.1–261.5353.6342.5–359.6
2079244.9226.4–261.3354.2343.4–360
2080246.7227–263.7354.8343–361.4
2081247.5230.4–264.8355.4345.4–360.3
2082244.6227.9–262.3355.3345–359.4
2083247.5227.8–265.1355.7344.3–360.1
2084247.3228.3–266.8355.9346.4–361.2
2085246.5227.5–267.1354.7345.1–360.5
2086245.6227.7–266.5356344.9–360.4
2087245.5226.7–266.2355.2344.8–360.4
2088247229.4–266.9355.7345–361.9
2089248.1230–266.3356346.1–360.1
2090249228.9–266.4355.6345.5–360.8
2091248.9230–266.5356.2343.4–360.7
2092249.8232.3–267.8356.2345.3–361.5
2093248.1229–266.5355.8343.7–360.9
2094249.1230.6–268.4356344.9–360.6
2095251233.2–270357.1345.9–361
2096247.8231.4–269.3356.2346.8–362.3
2097251.1231.4–268356.6344.6–360.4
2098252.3230.8–268.3356.8344.4–361.1
2099248.7230.1–268.3355.9344.9–361.1
2100250.4232.9–266.7356.1346.8–360.4

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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

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