Japan vs Thailand

Japan vs Thailand: Tropical nights

Tropical nights in 2014: 58.6 nights in Japan and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 227.8 nights, or 4.89 times that in Japan.

nights a year · CMIP6

Japan vs Thailand: Tropical nightsTropical nights in 2014: 58.6 nights in Japan and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 227.8 nights, or 4.89 times that in Japan.
JapanThailandCMIP6 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 Japan at 87.7 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearJapanThailand
201458.6286.4
201359.9289.1
201259.3286.6
201157.9286.4
201059.6286
200957.6286.9
200857.3284.8
200756.6283.2
200657.5284.3
200557.2281.7
200456.7287.5
200356.1279.3
200256280
200154.2285.5
200053.8283.4
199955.3282.5
199852.4282.7
199752.4284.8
199652.9279.8
199549.7278.7
199449.5280.8
199345.4275.6
199245.1268.8
199149.4276.7
199050.7279.2
198951.4278.4
198848.1279.6
198747.7277.9
198646.1277.5
198546.7276
198444.8277.9
198341.9273.9
198246.4275.7
198145.9277.8
198046.5277.9
197946.7278
197847.6276
197745.8277.3
197646275.6
197546.9274.4
197445.6276
197344.3280.6
197245.8273.9
197144.8273.2
197044276
196946.9274.8
196845.7277
196748.3270.3
196645.9274.4
196545.8275.8
196444.9271.9
196348.3274.7
196245.6275.4
196148.9278.5
196046.4276.2
195946.9274.4
195848.8278.7
195749.2277.4
195650.6277
195547.9274.6
195446.9275
195349.2275.4
195249.5275.1
195146.2277.5
195049.9276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearJapanThailand
201560.649.3–74.4290.6272.2–305
201661.547.9–73.9287.1269.8–306.2
201762.352.1–75.8290273.8–302.8
201860.548.5–73.8292.6275.1–308.7
201964.152.1–80.1291.2272.8–306.7
202063.151–74.5292.4272.2–307.8
202162.348.5–78.8294.2276.3–308.5
202264.653.8–76.5294.8277.2–311.9
202365.951.7–78296.1281.9–310.2
202465.352.9–80.7291.7275.5–307.8
202565.652.8–80.4294276.7–306.3
202665.554.2–81.2296278–309.3
202766.452.9–79.5295.8276.3–311.1
202865.352.4–80.1297279.3–315.1
202968.555–80.4300.3278.7–315
203066.552.3–80.6297.7280.2–312.5
203166.554.7–80300.8282.8–317.1
20326650.8–82.1297.2280.9–311.4
203370.354.7–84.8300281.9–315.8
203468.553.9–81.7300.8279–318.4
203572.960.4–84.6298.6281.5–317.8
203672.556.1–89.7300.4279.9–316.9
203767.656.7–82.5299.8280–315.1
203870.558.6–83.8304.8286.6–319.3
203970.455.6–85.7300.9281.9–317
204073.657.4–89.3301.6284.5–315.7
204172.955.6–88.5303.1285.1–318.8
204271.258.1–86.4303.8290–318.3
204373.357.9–88.1302285.8–317.9
204472.657.8–85.5304.3286.3–318.8
204572.959.5–86.7307.1287.7–324.2
204676.261–90.3305.9285.2–321
204775.656.6–89.3306.6289.5–321.5
204874.858.5–89.4309.4288.9–325.7
204974.359.7–90.8308.1287.2–324.1
205075.160.8–89.3307.5291–321.5
205175.861.1–92.4312.8294.8–326
205274.557.9–90.4310.9291.2–323.4
205378.559.6–91.6308.3289.5–323.3
205475.959.6–89.3308.8292.8–322.3
205576.862.2–95.1308.6290.6–325.1
205677.861.9–93.7311.3294.9–326.3
205779.962.8–94.4308.5286.7–326.4
205879.263.7–94.9308291.1–325.1
205979.858–95.6312.7295.8–325.3
206078.261.1–95.1313.1294.6–328.6
206180.865.7–96.7314.4289.5–331.1
20628063.6–96.3311.4293.4–330.3
20638064.1–96.5314.8296.9–327.3
206477.661.4–95.2312.5295.4–330
206581.763–97.4309.6293.1–329.3
206680.363.8–94.2312.1292.6–328
206781.363.2–97.1311.2289.6–329.4
206879.861.4–99.3310.8292.4–330.6
206982.365–96.1315.5296.1–329.5
207083.360.2–102.3314.2292.9–330.7
207183.663.6–99.2313.8296.4–330.8
207284.363.3–99.1314.8296–329.6
207383.564.9–97.4316.5299.9–332.1
207484.366.8–100.9317.2295–333.8
207585.664.1–99.8317.2295.3–331.4
207683.968.8–99.3317.4299.8–335
207786.467.6–102.4317.5297.3–335.9
207884.167.7–103.2315.9297.1–331.6
207986.168.3–99.4318.5300.5–332.3
208084.767.6–103.7319.8297.4–337.5
208183.668.5–104.3317.7299.5–334.9
208286.469.4–107.7317.9294.8–333
208385.966.5–105.7315297.8–332.9
208485.867.4–102.3316295.5–330
208587.568.9–102.8322.6300.8–334.7
208684.668.6–105.3319.4295.2–335.2
208787.270.3–107320.2302.2–334.7
208886.866.3–102.5321.4299.8–334.8
208985.765.9–103.8318.9296.4–338.1
209089.469.5–104.4317.6304–337.4
209188.367.4–103.1320.1299.8–336.1
20928667.7–102.3316.3298–336.4
209388.969.8–107.4316.1297.7–333.7
209487.569.3–103.7323.4301.8–337.3
20958872.4–104.9322.9302.4–338.9
209690.771–107.3319.6302.8–336.7
209789.471–103.1319.8299.1–336
209888.571–106.5320.5303.9–336
209988.370.8–102.4319.9303.1–334.4
210087.769.2–106.2320.8301.1–336.7

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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