China vs Thailand

China vs Thailand: Tropical nights

Tropical nights in 2014: 41.5 nights in China and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 245 nights, or 6.91 times that in China.

nights a year · CMIP6

China vs Thailand: Tropical nightsTropical nights in 2014: 41.5 nights in China and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 245 nights, or 6.91 times that in China.
ChinaThailandCMIP6 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 China at 63.3 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearChinaThailand
201441.5286.4
201341.7289.1
201240.8286.6
201140.2286.4
201040.5286
200939.5286.9
200839.2284.8
200738.7283.2
200639.5284.3
200539.5281.7
200439.7287.5
200338.5279.3
200238.8280
200139.5285.5
200038.6283.4
199938.5282.5
199837.6282.7
199737.1284.8
199636.6279.8
199535.1278.7
199434.9280.8
199333.2275.6
199232.3268.8
199135.9276.7
199036.4279.2
198936.1278.4
198835.1279.6
198734.5277.9
198634277.5
198533.5276
198433.4277.9
198331.5273.9
198234.1275.7
198134.2277.8
198034.3277.9
197933.8278
197834.8276
197733.3277.3
197632.7275.6
197533.1274.4
197433.3276
197333.1280.6
197232.6273.9
197133273.2
197032.4276
196933.4274.8
196832.8277
196733.4270.3
196633.4274.4
196532.5275.8
196432.1271.9
196334.5274.7
196234275.4
196134.6278.5
196034.1276.2
195934274.4
195835278.7
195734.4277.4
195634.6277
195534.2274.6
195434.2275
195334.3275.4
195234.3275.1
195135.1277.5
195034.9276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearChinaThailand
201542.334.8–49.8290.6272.2–305
201642.134.4–50287.1269.8–306.2
201743.135.3–51.6290273.8–302.8
201842.335.5–49.5292.6275.1–308.7
201943.836.5–51.1291.2272.8–306.7
202043.736.8–51.1292.4272.2–307.8
202144.136–52.1294.2276.3–308.5
202244.737.5–52.7294.8277.2–311.9
202345.737.8–53.4296.1281.9–310.2
202445.738.1–54291.7275.5–307.8
202546.337.5–54.8294276.7–306.3
202646.237.6–55.5296278–309.3
202746.138–54.9295.8276.3–311.1
202846.438.4–54.3297279.3–315.1
202946.939.1–55.6300.3278.7–315
203047.138.8–55.3297.7280.2–312.5
20314738.8–56300.8282.8–317.1
203248.339.3–57.4297.2280.9–311.4
203347.939.7–56.6300281.9–315.8
203448.440.5–57.3300.8279–318.4
203549.740.8–58.6298.6281.5–317.8
20364940.1–58.2300.4279.9–316.9
20374941.2–57.6299.8280–315.1
203850.542.4–59.3304.8286.6–319.3
203949.641.2–59.2300.9281.9–317
204050.942.4–60.4301.6284.5–315.7
204151.342.5–61.1303.1285.1–318.8
204251.642–61.5303.8290–318.3
204350.742.7–61302285.8–317.9
204451.942.4–61.9304.3286.3–318.8
204551.542.8–61.1307.1287.7–324.2
20465343.7–62.7305.9285.2–321
204753.544.5–62.5306.6289.5–321.5
204853.144–62.6309.4288.9–325.7
204952.843.8–63.3308.1287.2–324.1
205053.644.4–63.8307.5291–321.5
205154.345.1–64.8312.8294.8–326
205253.444.6–63.2310.9291.2–323.4
205354.244.2–64.2308.3289.5–323.3
205454.545.3–64.8308.8292.8–322.3
20555545.1–65.8308.6290.6–325.1
205655.245.1–66.6311.3294.9–326.3
205754.844.9–65.7308.5286.7–326.4
205855.145.8–67.7308291.1–325.1
205955.345.1–67.2312.7295.8–325.3
206057.246.9–68.1313.1294.6–328.6
206156.546.6–66.3314.4289.5–331.1
206256.846.9–68.5311.4293.4–330.3
206357.247.2–68.6314.8296.9–327.3
20645747.1–67.7312.5295.4–330
206557.347.1–67.8309.6293.1–329.3
206657.347.9–68.7312.1292.6–328
206757.546.4–68.2311.2289.6–329.4
206858.748.5–70.5310.8292.4–330.6
206958.548.4–69315.5296.1–329.5
20705847.6–71.7314.2292.9–330.7
207159.347.4–71.6313.8296.4–330.8
207259.248.1–71.5314.8296–329.6
207359.849.1–70.9316.5299.9–332.1
207459.648.7–71.1317.2295–333.8
207558.748.3–71.4317.2295.3–331.4
207660.249–70.9317.4299.8–335
207760.851.1–72.4317.5297.3–335.9
207859.648.8–72.4315.9297.1–331.6
207960.750.1–72.6318.5300.5–332.3
208059.950–72.3319.8297.4–337.5
208160.950–73.2317.7299.5–334.9
20826149.8–73.3317.9294.8–333
208361.251.2–73.6315297.8–332.9
208461.749.7–74.6316295.5–330
208561.250.8–75.2322.6300.8–334.7
208661.648.9–74.5319.4295.2–335.2
208761.650.6–75320.2302.2–334.7
208862.750.5–77.1321.4299.8–334.8
208961.950–75.2318.9296.4–338.1
209062.551.4–73.7317.6304–337.4
209163.852–75.7320.1299.8–336.1
209263.251.2–75.1316.3298–336.4
209363.252–75.4316.1297.7–333.7
20946351.1–76.3323.4301.8–337.3
209563.952.8–76.4322.9302.4–338.9
209663.852.2–76.8319.6302.8–336.7
209762.750.7–75.1319.8299.1–336
209863.451.2–76.8320.5303.9–336
209963.851.9–76.1319.9303.1–334.4
210063.351.7–76.2320.8301.1–336.7

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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