Myanmar (Burma) vs Saudi Arabia

Myanmar (Burma) vs Saudi Arabia: Days above 35 °C

Days above 35 °C in 2014: 28.8 days in Myanmar (Burma) and 165.7 days in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 136.9 days, or 5.76 times that in Myanmar (Burma).

days a year · CMIP6

Myanmar (Burma) vs Saudi Arabia: Days above 35 °CDays above 35 °C in 2014: 28.8 days in Myanmar (Burma) and 165.7 days in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 136.9 days, or 5.76 times that in Myanmar (Burma).
Myanmar (Burma)Saudi 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 Myanmar (Burma) at 57 days and Saudi Arabia at 195.8 days in 2100.

Every year

days a year · CMIP6

YearMyanmar (Burma)Saudi Arabia
201428.8165.7
201328163.7
201227.5164.4
201127.4164.2
201027.9162.2
200927.3160
200827.2161.6
200725.4159.7
200626.8160.2
200525161
200428.3160.4
200326.4159.5
200227.4160.4
200128.4162
200026.6159.8
199926.1158.2
199826.4156.3
199726.2156.7
199624.7156.3
199525.5154.1
199424.3154.8
199323.9148.8
199220.5147
199128.4153.4
199026.3156.8
198923.8153.8
198823.9153.1
198725.4152.7
198626.6153.7
198523.6151
198425.8150
198323.2147.7
198224149.2
198123.8153.2
198023.5153
197925.3150.7
197823.4149.5
197724.1150.1
197625.6151.5
197522.3146.6
197424.1147.9
197325.9149.5
197223.1148.2
197122.8146.3
197024.2146.9
196923.6147.4
196823.4147.4
196724.1145.3
196623.1146.9
196523.3146.3
196421.7145.4
196323.2145.8
196224.4148.7
196124.9150.1
196026.2150.9
195922.6151
195825150.2
195724.1152.3
195625148.7
195524.5148.6
195425.3148.7
195323.5150.2
195226.1150.8
195125148.6
195023.8148.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMyanmar (Burma)Saudi Arabia
201528.518.5–40168.1155.2–180.8
201627.717.3–38.7167.4155–178.2
20172818.9–38.5166.4152.1–178.2
201829.818.6–41.2167.1153.7–180.7
201928.218.2–41.3168.2153.9–180.5
202028.616.8–41.4169.6156.7–182
202129.719.4–40.8168.7155.3–180.5
202231.521.7–42.7169.6153.9–183.2
202330.319.9–41.6169.7155.9–184.9
202431.720.1–43.7170.4157.8–184.5
202532.721.3–44.8171.2159.4–181.9
202630.420.3–44.5173.2159.7–185.5
202730.620.4–44.2173.9159.3–185.4
202831.119–43172.8158.3–185.8
202932.720.9–46.4171157.4–183.8
203032.619.3–45174.4160.6–185.9
203132.721.3–45.2175160.1–186.7
203232.119.6–45.4173.2160.2–185
203333.322–43.8176.3161.4–189.7
203431.322–43.5178.6164.5–193.4
203532.620.4–49176.1161.7–191.7
203633.322.7–46.1174.7162–187.2
203734.322.6–49.1177.3164.7–189.2
203835.824.4–49.9177.8163.1–191.7
203934.920.9–49178.3165.1–192.5
20403419.2–51.2178.6165.4–188.9
20413724.8–51.9177.4162.3–190
204236.223–49.9180165.1–193.2
204334.522.6–47.7179.6161.2–192.6
204438.222.1–51.2180.4167.3–191
204535.924.2–50.7182.8167.9–195.9
204638.425.2–57.1182168–195.8
204738.824.1–56.1182.6170–195
204840.323.4–58.7184.1169.5–199.4
204940.625.2–58.1182.9169.7–195.4
205040.226.5–55.3184.9170.6–196.8
205141.726.7–56.8185.3171.5–197.6
205240.326.3–61.2184.2170–196.6
205341.323.6–61.5181.7168.3–195.1
205442.426.8–60.9183.9167.9–197.3
205541.428.5–61.9187.7171.8–200.3
205642.726.5–63183.5168.6–196.2
205743.226.3–63.2186.6172.5–201.3
205844.526.8–63.6184.9169.7–198.2
205943.729.1–65.3184.3169.9–199.3
206047.428.3–66188.1174–198.7
206146.729.5–64.5187.6174–198.4
206247.126.7–68.6186.9170.4–201.9
206346.929–66.4188.8174.6–201.8
206447.527.9–66.1187.2174.3–201.1
206542.427.5–62.4186.3171–200.8
206646.228.9–68.8188.6174.6–204.2
20674125.7–63.6190.8177.1–204.4
206846.928–70.4188.1176.8–201.4
206948.729.3–70.1189.2174–202.2
207043.927.5–64.3190.4177.1–204.1
20714926.2–71.9193.2174.7–207.4
20724730.6–71.4190.3174.7–203.7
207350.732.2–74192.8177.3–207.7
20744829.2–74189.9174.1–206.8
207549.126.1–68.9190.3174.8–206.1
207647.826.5–72.8190.9175–206.9
207751.832.9–76.1193.3176.6–206.1
207850.632.4–75.6192.2178.3–207.4
207950.730.5–77192177.9–203.8
208053.331.3–79.5192.9177.3–209.4
20815235.5–79.1193.1174.9–208
208252.532.5–76.8192.8177.3–208.2
208351.730.5–79.6194.3178.4–208.7
208452.329.5–76193.4181.1–208.4
208551.232.9–79.4193.9178.3–211
208652.632.5–80.1193.2177.7–211.5
208751.732.6–77.9194.6180.8–208.8
208850.727.2–88.8195178.3–211.9
208952.731.4–86.3195.7180.6–209.9
209054.231.1–80.1194.9178.8–210.6
209153.235.4–80.1195.9182.4–210.1
209254.135.4–85.5195.7181.2–210.7
20935235.6–85194.4178.8–210.4
209454.434.9–80.7195.7181.7–209.9
209558.535.1–84.3196.2182.1–210.7
209652.832.3–84.1196.8178.8–213.1
209753.230.4–82.8195.2178–211.1
209855.334.4–83.8196.3177.7–212.9
209955.233.1–84.7195.3181.5–210.6
21005734.6–84195.8182.5–210.3

Each country on its own

Good to know

  • Days in a year whose highest temperature passes 35 °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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