Italy vs Thailand

Italy vs Thailand: Tropical nights

Tropical nights in 2014: 26.3 nights in Italy and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 260.1 nights, or 11 times that in Italy.

nights a year · CMIP6

Italy vs Thailand: Tropical nightsTropical nights in 2014: 26.3 nights in Italy and 286.4 nights in Thailand, in the CMIP6 climate models’ median run. In 2014 the value was higher in Thailand, by 260.1 nights, or 11 times that in Italy.
ItalyThailandCMIP6 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 Italy at 65.1 nights and Thailand at 320.8 nights in 2100.

Every year

nights a year · CMIP6

YearItalyThailand
201426.3286.4
201324.7289.1
201224.8286.6
201124.6286.4
201027.1286
200923.7286.9
200824.1284.8
200721.5283.2
200624.6284.3
200522.5281.7
200424.5287.5
200323.8279.3
200220.6280
200120.8285.5
200021.7283.4
199920.3282.5
199818.9282.7
199718.9284.8
199618.9279.8
199517.9278.7
199417.4280.8
199316.3275.6
199215.1268.8
199118276.7
199018.2279.2
198916.6278.4
198815.5279.6
198716277.9
198615277.5
198514.5276
198415.7277.9
198315.3273.9
198214.1275.7
198115.3277.8
198015.9277.9
197914.5278
197816.5276
197713.5277.3
197613.8275.6
197514274.4
197414.8276
197313.5280.6
197213.7273.9
197115.3273.2
197014276
196914.5274.8
196813.8277
196713.6270.3
196613.2274.4
196512.8275.8
196413.2271.9
196314.2274.7
196215.5275.4
196113.9278.5
196014.9276.2
195916.6274.4
195814.4278.7
195715.5277.4
195616.7277
195516.6274.6
195415.7275
195315.4275.4
195216.6275.1
195116277.5
195015.3276.2
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearItalyThailand
20153021.7–40.4290.6272.2–305
201629.618–42.2287.1269.8–306.2
201731.820.2–43.7290273.8–302.8
20183122–44.3292.6275.1–308.7
201931.521.3–43.2291.2272.8–306.7
202031.619.7–44.3292.4272.2–307.8
20213420.8–46.9294.2276.3–308.5
202237.121.3–50.6294.8277.2–311.9
202333.121.3–47.4296.1281.9–310.2
202435.521.6–48.4291.7275.5–307.8
202537.720.5–51.1294276.7–306.3
202638.926.6–52.2296278–309.3
202734.322.4–49.7295.8276.3–311.1
202837.724.4–53.1297279.3–315.1
202937.824.9–55300.3278.7–315
203037.925.7–54.7297.7280.2–312.5
203137.223.8–51300.8282.8–317.1
203239.226.2–53.8297.2280.9–311.4
203340.426–50.3300281.9–315.8
203442.525.1–57.2300.8279–318.4
203542.728.9–58.3298.6281.5–317.8
203641.127.7–59.9300.4279.9–316.9
20374328.1–54.8299.8280–315.1
203841.628.5–61.3304.8286.6–319.3
20394129.4–56.4300.9281.9–317
204042.428.1–59.1301.6284.5–315.7
204141.927.2–58.7303.1285.1–318.8
204243.529.6–59303.8290–318.3
20434528.7–59.5302285.8–317.9
204444.929.4–59.9304.3286.3–318.8
204545.230.3–59.2307.1287.7–324.2
20464627.3–62.4305.9285.2–321
204749.132.4–63.6306.6289.5–321.5
204846.228.3–65.7309.4288.9–325.7
204948.229.5–65.7308.1287.2–324.1
205049.536.4–64.4307.5291–321.5
205148.831.6–68.3312.8294.8–326
205250.330.9–68.1310.9291.2–323.4
205348.235.9–67308.3289.5–323.3
205449.435.3–66.1308.8292.8–322.3
205552.233.7–67.7308.6290.6–325.1
205650.836.2–71.6311.3294.9–326.3
205750.232.8–65.6308.5286.7–326.4
205855.337.5–70.8308291.1–325.1
205951.934.5–74.1312.7295.8–325.3
206052.938.2–68.1313.1294.6–328.6
206154.338.3–69.8314.4289.5–331.1
206253.936.9–69311.4293.4–330.3
206356.437.6–72.1314.8296.9–327.3
206455.938.5–71.3312.5295.4–330
20655537.3–73.3309.6293.1–329.3
206653.935.8–73.8312.1292.6–328
206761.141.2–76.6311.2289.6–329.4
206856.241.7–73310.8292.4–330.6
206958.741.8–73315.5296.1–329.5
207055.738.9–74.4314.2292.9–330.7
207159.637.8–76.6313.8296.4–330.8
207259.643.5–74.6314.8296–329.6
207356.939.4–71.6316.5299.9–332.1
207454.836.7–73.7317.2295–333.8
207556.941.8–75.4317.2295.3–331.4
207659.941.9–77.7317.4299.8–335
207757.437.9–74.1317.5297.3–335.9
207860.540.5–80.7315.9297.1–331.6
207960.637.1–83.3318.5300.5–332.3
208059.743.1–78319.8297.4–337.5
20815943.7–78.9317.7299.5–334.9
208263.945.5–80.2317.9294.8–333
208360.842–79.7315297.8–332.9
208462.547.3–82.1316295.5–330
208565.246.3–79322.6300.8–334.7
208664.445.6–80.1319.4295.2–335.2
208763.743.8–84320.2302.2–334.7
208867.247.4–84.4321.4299.8–334.8
208964.546–82.9318.9296.4–338.1
209065.842.8–80.5317.6304–337.4
209166.745.3–84.7320.1299.8–336.1
209264.838.5–82.3316.3298–336.4
209363.644.7–83316.1297.7–333.7
209462.445–82323.4301.8–337.3
20956643.6–83.5322.9302.4–338.9
20966542.9–85.8319.6302.8–336.7
209765.844.9–84.4319.8299.1–336
209864.647.9–84.2320.5303.9–336
209967.742.2–81.9319.9303.1–334.4
210065.142.5–83.2320.8301.1–336.7

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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