Germany vs Thailand

Germany vs Thailand: Tropical nights

Tropical nights in 2014: 0.8 nights in Germany and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 285.6 nights, or 350 times that in Germany.

nights a year · CMIP6

Germany vs Thailand: Tropical nightsTropical nights in 2014: 0.8 nights in Germany and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 285.6 nights, or 350 times that in Germany.
GermanyThailandCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Thailand has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Germany at 8.8 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearGermanyThailand
20140.8286.4
20130.7289.1
20120.9286.6
20110.5286.4
20100.9286
20090.5286.9
20080.2284.8
20070.3283.2
20060.3284.3
20050.6281.7
20040.7287.5
20030.6279.3
20020.2280
20010.5285.5
20000.2283.4
19990.2282.5
19980.1282.7
19970.1284.8
19960.2279.8
19950.1278.7
19940280.8
19930275.6
19920268.8
19910.1276.7
19900.1279.2
19890.1278.4
19880279.6
19870277.9
19860277.5
19850.1276
19840.1277.9
19830273.9
19820275.7
19810277.8
19800277.9
19790278
19780.1276
19770277.3
19760275.6
19750274.4
19740.1276
19730280.6
19720273.9
19710273.2
19700.1276
19690274.8
19680277
19670270.3
19660274.4
19650275.8
19640271.9
19630274.7
19620275.4
19610278.5
19600276.2
19590.1274.4
19580278.7
19570277.4
19560277
19550274.6
19540.1275
19530275.4
19520275.1
19510277.5
19500276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearGermanyThailand
20150.50–4290.6272.2–305
20160.80–4.3287.1269.8–306.2
20170.70–5.1290273.8–302.8
20180.70–3.5292.6275.1–308.7
20191.20–5291.2272.8–306.7
20201.20–5.7292.4272.2–307.8
202110–6294.2276.3–308.5
20221.40–5.7294.8277.2–311.9
20231.10–5.7296.1281.9–310.2
20241.20–5.2291.7275.5–307.8
20251.90–8.2294276.7–306.3
20261.90.1–6.5296278–309.3
20271.40–4.7295.8276.3–311.1
20281.50.1–5.5297279.3–315.1
202920.1–6.4300.3278.7–315
20301.60–6.1297.7280.2–312.5
20311.40–5.4300.8282.8–317.1
20321.50.1–7.6297.2280.9–311.4
20331.70–6.8300281.9–315.8
20342.10.2–8.3300.8279–318.4
20351.70.1–6.9298.6281.5–317.8
20362.80.1–7.8300.4279.9–316.9
20372.50–9.2299.8280–315.1
20382.20.1–9.7304.8286.6–319.3
203930–8.9300.9281.9–317
20402.30.1–7.1301.6284.5–315.7
20412.40.1–7.9303.1285.1–318.8
20422.90.4–8.9303.8290–318.3
20433.10.1–8.7302285.8–317.9
20443.10.2–10.1304.3286.3–318.8
204530.1–8.7307.1287.7–324.2
20463.10.5–10.9305.9285.2–321
20474.30.3–10.6306.6289.5–321.5
20483.70.2–12.9309.4288.9–325.7
20494.40.2–11.8308.1287.2–324.1
20503.10.6–9.3307.5291–321.5
20512.70.1–9.5312.8294.8–326
20523.60.2–11.5310.9291.2–323.4
20532.30.4–8.7308.3289.5–323.3
20543.50.4–10.3308.8292.8–322.3
20553.30.4–11.3308.6290.6–325.1
20564.50.7–14.3311.3294.9–326.3
205740.4–11.3308.5286.7–326.4
20585.80.7–15.5308291.1–325.1
20595.10.1–15.6312.7295.8–325.3
20604.40.6–12.3313.1294.6–328.6
20615.31–12.3314.4289.5–331.1
20625.51.6–14.2311.4293.4–330.3
20635.20.8–13.8314.8296.9–327.3
20644.10.5–12.2312.5295.4–330
20654.90.3–15.8309.6293.1–329.3
20665.30.7–11.8312.1292.6–328
20677.21.4–17.5311.2289.6–329.4
20683.90.9–11.3310.8292.4–330.6
20696.11.6–15315.5296.1–329.5
20705.80.6–14.9314.2292.9–330.7
20716.30.6–16.4313.8296.4–330.8
20726.21.9–13314.8296–329.6
20735.51.3–16.2316.5299.9–332.1
20745.50.5–16.7317.2295–333.8
20756.21.4–18.3317.2295.3–331.4
20767.41.1–20.1317.4299.8–335
20776.31.1–17.4317.5297.3–335.9
20786.50.7–21.4315.9297.1–331.6
20796.70.6–22.7318.5300.5–332.3
20806.51.2–14.9319.8297.4–337.5
20816.60.9–18.5317.7299.5–334.9
20827.91.4–22.5317.9294.8–333
20837.61.3–16.8315297.8–332.9
20845.91.1–15.9316295.5–330
20856.50.9–17.6322.6300.8–334.7
20867.90.8–23319.4295.2–335.2
20879.91.1–24.1320.2302.2–334.7
20888.92–18.4321.4299.8–334.8
20898.31.9–19.2318.9296.4–338.1
20906.20.8–24.1317.6304–337.4
20919.31.3–23.5320.1299.8–336.1
20928.61.7–19.2316.3298–336.4
20936.20.8–18.2316.1297.7–333.7
20949.32.4–20.4323.4301.8–337.3
20959.51.1–24322.9302.4–338.9
20968.10.2–21.4319.6302.8–336.7
20976.40.5–20.1319.8299.1–336
20989.31.4–22.1320.5303.9–336
20998.11.4–20.8319.9303.1–334.4
21008.81.9–21.1320.8301.1–336.7

Each country on its own

Good to know

  • Nights in a year when the temperature stays above 20 °C, averaged over the country.
  • Source: World Bank Climate Change Knowledge Portal, CMIP6 multi-model median.
  • The dashed line is the CMIP6 model median (SSP2-4.5, middle of the road), a scenario rather than a forecast; the band is its models’ 10th–90th percentile.
  • Climate model values are the median of the CMIP6 models, run on past emissions to 2014 and on SSP2-4.5, a middle-of-the-road path, after: they are not measurements.

How the layers work, where their data comes from and what they can’t tell you: Countries through time

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