瑞典与泰国对比

瑞典与泰国：热带夜

2014 年热带夜：瑞典为 0.1 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 286.3 夜，是瑞典的 5,700 倍。

在地图上查看其变化

每年夜数 · CMIP6

瑞典与泰国：热带夜2014 年热带夜：瑞典为 0.1 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 286.3 夜，是瑞典的 5,700 倍。
瑞典泰国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 年瑞典为 0.7 夜，泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份瑞典泰国
20140.1286.4
20130.1289.1
20120286.6
20110286.4
20100286
20090286.9
20080284.8
20070283.2
20060284.3
20050281.7
20040287.5
20030279.3
20020280
20010285.5
20000283.4
19990282.5
19980282.7
19970284.8
19960279.8
19950278.7
19940280.8
19930275.6
19920268.8
19910276.7
19900279.2
19890278.4
19880279.6
19870277.9
19860277.5
19850276
19840277.9
19830273.9
19820275.7
19810277.8
19800277.9
19790278
19780276
19770277.3
19760275.6
19750274.4
19740276
19730280.6
19720273.9
19710273.2
19700276
19690274.8
19680277
19670270.3
19660274.4
19650275.8
19640271.9
19630274.7
19620275.4
19610278.5
19600276.2
19590274.4
19580278.7
19570277.4
19560277
19550274.6
19540275
19530275.4
19520275.1
19510277.5
19500276.2
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份瑞典泰国
20150.10–0.3290.6272.2–305
201600–0.3287.1269.8–306.2
201700–0.4290273.8–302.8
201800–0.3292.6275.1–308.7
20190.10–0.5291.2272.8–306.7
202000–0.3292.4272.2–307.8
202100–0.3294.2276.3–308.5
20220.10–0.5294.8277.2–311.9
20230.10–0.6296.1281.9–310.2
202400–0.4291.7275.5–307.8
20250.10–1294276.7–306.3
20260.10–1296278–309.3
20270.10–0.3295.8276.3–311.1
20280.10–0.6297279.3–315.1
20290.10–0.8300.3278.7–315
20300.10–0.5297.7280.2–312.5
20310.10–0.4300.8282.8–317.1
20320.10–0.8297.2280.9–311.4
20330.10–0.8300281.9–315.8
20340.10–0.7300.8279–318.4
20350.20–0.8298.6281.5–317.8
20360.10–0.8300.4279.9–316.9
20370.10–1299.8280–315.1
20380.10–1.2304.8286.6–319.3
20390.10–0.8300.9281.9–317
20400.10–0.8301.6284.5–315.7
20410.10–1.2303.1285.1–318.8
20420.20–1.2303.8290–318.3
20430.20–1.1302285.8–317.9
20440.10–1.1304.3286.3–318.8
20450.10–0.6307.1287.7–324.2
20460.20–1.3305.9285.2–321
20470.30–2.1306.6289.5–321.5
20480.30–1.8309.4288.9–325.7
20490.20–1.6308.1287.2–324.1
20500.20–1.8307.5291–321.5
20510.20–1.7312.8294.8–326
20520.20–2310.9291.2–323.4
20530.10–1.3308.3289.5–323.3
20540.20–1.1308.8292.8–322.3
20550.20–1.6308.6290.6–325.1
20560.20–1.5311.3294.9–326.3
20570.20–1.4308.5286.7–326.4
20580.30–2.3308291.1–325.1
20590.30–1.7312.7295.8–325.3
20600.20–1.4313.1294.6–328.6
20610.40–1.6314.4289.5–331.1
20620.30.1–1.7311.4293.4–330.3
20630.20–2.1314.8296.9–327.3
20640.20–1.6312.5295.4–330
20650.30–3309.6293.1–329.3
20660.20–2.8312.1292.6–328
20670.30–2311.2289.6–329.4
20680.20–1.5310.8292.4–330.6
20690.60.1–3.1315.5296.1–329.5
20700.30–2314.2292.9–330.7
20710.30–2.7313.8296.4–330.8
20720.20–2314.8296–329.6
20730.40–4.6316.5299.9–332.1
20740.20–2.8317.2295–333.8
20750.30–2.9317.2295.3–331.4
20760.40–2.4317.4299.8–335
20770.40–2.2317.5297.3–335.9
20780.50–3.1315.9297.1–331.6
20790.40–3.1318.5300.5–332.3
20800.30–2.1319.8297.4–337.5
20810.30–3317.7299.5–334.9
20820.40–4.4317.9294.8–333
20830.50.1–3315297.8–332.9
20840.30–2.4316295.5–330
20850.40–3.3322.6300.8–334.7
20860.70–4319.4295.2–335.2
20870.60–6320.2302.2–334.7
20880.50–2.7321.4299.8–334.8
20890.50.1–3.4318.9296.4–338.1
20900.40–2.9317.6304–337.4
20910.60–3.9320.1299.8–336.1
20920.80–4.2316.3298–336.4
20930.70.1–4.8316.1297.7–333.7
20940.50–2.6323.4301.8–337.3
20950.50.1–4.3322.9302.4–338.9
20960.50–3.7319.6302.8–336.7
20970.50–4.5319.8299.1–336
20980.50.1–3.7320.5303.9–336
20990.30–3.2319.9303.1–334.4
21000.70–4.4320.8301.1–336.7

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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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