Japan vs Saudi Arabia

Japan vs Saudi Arabia: Tropical nights

Tropical nights in 2014: 58.6 nights in Japan and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 122.9 nights, or 3.1 times that in Japan.

nights a year · CMIP6

Japan vs Saudi Arabia: Tropical nightsTropical nights in 2014: 58.6 nights in Japan and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 122.9 nights, or 3.1 times that in Japan.
JapanSaudi ArabiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Saudi Arabia 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 Saudi Arabia at 218.7 nights in 2100.

Every year

nights a year · CMIP6

YearJapanSaudi Arabia
201458.6181.5
201359.9180.4
201259.3182.8
201157.9182.7
201059.6179.2
200957.6177.1
200857.3180.3
200756.6178.9
200657.5177.5
200557.2177.9
200456.7177.6
200356.1177.4
200256175.6
200154.2178.1
200053.8176.4
199955.3173.2
199852.4173.4
199752.4173.8
199652.9172
199549.7169.2
199449.5170.4
199345.4164.6
199245.1165.9
199149.4169.2
199050.7172.7
198951.4168.9
198848.1166.8
198747.7167.3
198646.1169.4
198546.7166
198444.8165
198341.9163.5
198246.4164.7
198145.9168.9
198046.5166.8
197946.7165.3
197847.6164.8
197745.8165.6
197646165.9
197546.9161.2
197445.6162.9
197344.3163.7
197245.8163.7
197144.8160.4
197044162.5
196946.9161.3
196845.7162.7
196748.3159.5
196645.9159.5
196545.8159.5
196444.9159.9
196348.3160.2
196245.6163.2
196148.9163.7
196046.4165.7
195946.9164.4
195848.8164.1
195749.2165.5
195650.6163.6
195547.9162
195446.9161.2
195349.2162.5
195249.5163.4
195146.2161.2
195049.9161.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearJapanSaudi Arabia
201560.649.3–74.4184.9169.4–198.7
201661.547.9–73.9183167.7–195.7
201762.352.1–75.8182.6168.1–196.7
201860.548.5–73.8186.8173.1–199.4
201964.152.1–80.1184.1168.8–199.1
202063.151–74.5185.3171.8–198.9
202162.348.5–78.8188.6173.6–202.8
202264.653.8–76.5187.6170.7–202
202365.951.7–78188.6173–203.8
202465.352.9–80.7187.1172.9–203.9
202565.652.8–80.4191.5176–206.1
202665.554.2–81.2191.8177.1–205.5
202766.452.9–79.5191.2176.6–206.8
202865.352.4–80.1191.9175.5–205.1
202968.555–80.4192.2176.6–205.7
203066.552.3–80.6193.3178.4–206.3
203166.554.7–80194.7179.1–207.6
20326650.8–82.1192.2175.2–206
203370.354.7–84.8192.6177.5–206.9
203468.553.9–81.7196.7181.6–213
203572.960.4–84.6196.5179.9–211.6
203672.556.1–89.7194.1180–209.7
203767.656.7–82.5197183.7–209.9
203870.558.6–83.8198.4182.3–213.3
203970.455.6–85.7198184.4–213.6
204073.657.4–89.3199.2182.1–212.7
204172.955.6–88.5197.7181.4–211.7
204271.258.1–86.4198.3181.2–217
204373.357.9–88.1198.2182.3–215.3
204472.657.8–85.5199.2185.5–213.5
204572.959.5–86.7202187.1–216.8
204676.261–90.3204.1185.3–219.4
204775.656.6–89.3204.1187.4–220
204874.858.5–89.4206.1190.7–220
204974.359.7–90.8201.6187.7–216.2
205075.160.8–89.3205.7190.2–219.3
205175.861.1–92.4204.3188.8–222.1
205274.557.9–90.4203.8189.6–218
205378.559.6–91.6203.8186.3–218.8
205475.959.6–89.3207.6188.3–222.3
205576.862.2–95.1207.8190.8–221
205677.861.9–93.7203.7186.6–220.1
205779.962.8–94.4207.5188.8–224.2
205879.263.7–94.9205.9189.2–221.4
205979.858–95.6207.3191.6–226.9
206078.261.1–95.1206.9192.7–222.8
206180.865.7–96.7206.5190.4–220.9
20628063.6–96.3208.1189.4–228.3
20638064.1–96.5210.4193–227.1
206477.661.4–95.2207.5191.9–223.3
206581.763–97.4208.9193.9–226.1
206680.363.8–94.2210.3194.9–228
206781.363.2–97.1210.9193.1–228.6
206879.861.4–99.3209.8194.6–228.6
206982.365–96.1208.9194.5–226.3
207083.360.2–102.3211.2191.2–229
207183.663.6–99.2215.1196.3–233.3
207284.363.3–99.1213.6195.3–229.3
207383.564.9–97.4213.7194.1–231.6
207484.366.8–100.9210.5191.9–229.3
207585.664.1–99.8212.1196.6–231.8
207683.968.8–99.3212.8194.8–230.3
207786.467.6–102.4215.1196.6–233.9
207884.167.7–103.2215.5197.6–230.7
207986.168.3–99.4213.6197–229
208084.767.6–103.7213.6197.1–233.9
208183.668.5–104.3214.7194.4–231.6
208286.469.4–107.7214198.9–230.9
208385.966.5–105.7214.2198.5–238
208485.867.4–102.3217.4197.4–233.1
208587.568.9–102.8217.4199.6–237.9
208684.668.6–105.3217197.4–237.4
208787.270.3–107217.3199.7–238.7
208886.866.3–102.5216.1198.2–243.1
208985.765.9–103.8217.6199.5–239
209089.469.5–104.4217.3198.5–239.2
209188.367.4–103.1218.5202.8–238.4
20928667.7–102.3218.5198.5–241.6
209388.969.8–107.4216.6197.8–236.3
209487.569.3–103.7218.8202–236.9
20958872.4–104.9219.4204.2–237.4
209690.771–107.3219.9197.7–239.6
209789.471–103.1216.7196.8–239.7
209888.571–106.5219.7199.6–241.3
209988.370.8–102.4216.8200.8–236.8
210087.769.2–106.2218.7202.3–241

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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