Bangladesh vs Saudi Arabia

Bangladesh vs Saudi Arabia: Days above 35 °C

Days above 35 °C in 2014: 19.4 days in Bangladesh and 165.7 days in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 146.3 days, or 8.55 times that in Bangladesh.

days a year · CMIP6

Bangladesh vs Saudi Arabia: Days above 35 °CDays above 35 °C in 2014: 19.4 days in Bangladesh and 165.7 days in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 146.3 days, or 8.55 times that in Bangladesh.
BangladeshSaudi 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 Bangladesh at 56.8 days and Saudi Arabia at 195.8 days in 2100.

Every year

days a year · CMIP6

YearBangladeshSaudi Arabia
201419.4165.7
201314.1163.7
201217164.4
201113.4164.2
201016.9162.2
200914.4160
200814161.6
200714.3159.7
200617.8160.2
200516.1161
200414.7160.4
200315.9159.5
200217.7160.4
200116.9162
200016.6159.8
199915.6158.2
199815.4156.3
199716.8156.7
199614.2156.3
199513.2154.1
199415.2154.8
199312.4148.8
19928147
199118.8153.4
199018.5156.8
198913.7153.8
198813.5153.1
198717.9152.7
198617.9153.7
198514.4151
198419150
198314.6147.7
198216.3149.2
198115.4153.2
198014.5153
197916.7150.7
197815149.5
197714.1150.1
197617.5151.5
197514.4146.6
197417.3147.9
197317149.5
197215.7148.2
197116.9146.3
197016.5146.9
196915.5147.4
196816.2147.4
196713.5145.3
196615.6146.9
196515.4146.3
196414.7145.4
196316.1145.8
196219.1148.7
196118150.1
196019.2150.9
195918151
195817.5150.2
195718.1152.3
195619.2148.7
195516.9148.6
195419.4148.7
195321150.2
195217.2150.8
195119.9148.6
195022.3148.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBangladeshSaudi Arabia
201517.85.5–30.2168.1155.2–180.8
201617.53.9–31.5167.4155–178.2
201714.14.8–29166.4152.1–178.2
201813.92–31167.1153.7–180.7
201914.93.9–28168.2153.9–180.5
202014.94.1–36.3169.6156.7–182
202117.25.6–33168.7155.3–180.5
202217.21.4–36.6169.6153.9–183.2
202318.16.6–32.2169.7155.9–184.9
202421.24.9–36.6170.4157.8–184.5
202516.73.9–36.8171.2159.4–181.9
202618.36.7–34173.2159.7–185.5
202718.33.5–38.2173.9159.3–185.4
202818.64.2–33.2172.8158.3–185.8
202918.22.2–34.9171157.4–183.8
2030174.6–31.3174.4160.6–185.9
2031153.9–32.1175160.1–186.7
203219.33.2–34.3173.2160.2–185
203317.53.9–32176.3161.4–189.7
203416.24–29.3178.6164.5–193.4
203516.26.6–31.6176.1161.7–191.7
203617.76.3–36.6174.7162–187.2
203720.65.7–39.1177.3164.7–189.2
203821.96.6–38.5177.8163.1–191.7
203921.45.1–43.2178.3165.1–192.5
204022.86–48.8178.6165.4–188.9
204119.44.7–44.5177.4162.3–190
204222.86.3–50.6180165.1–193.2
204325.17.2–47179.6161.2–192.6
204424.77.9–45180.4167.3–191
204524.110–42.5182.8167.9–195.9
204628.57.8–55.7182168–195.8
204726.47.4–50.6182.6170–195
204830.28–52.9184.1169.5–199.4
204929.511.3–54.1182.9169.7–195.4
205026.810.4–47.8184.9170.6–196.8
205132.713.4–54.3185.3171.5–197.6
205229.313–59.8184.2170–196.6
205326.79.4–54.9181.7168.3–195.1
205429.910.9–57.7183.9167.9–197.3
205534.613.5–60.8187.7171.8–200.3
205634.215.2–59183.5168.6–196.2
20573912.3–72.8186.6172.5–201.3
205838.917–69.9184.9169.7–198.2
205935.914.6–66184.3169.9–199.3
206036.818.6–65.3188.1174–198.7
206138.919.6–65.9187.6174–198.4
206235.115.8–63.8186.9170.4–201.9
206342.114.5–66.9188.8174.6–201.8
206437.317–62.7187.2174.3–201.1
206535.618.5–60.2186.3171–200.8
206635.812.3–64.7188.6174.6–204.2
206732.612.9–61.8190.8177.1–204.4
206840.717.5–76.4188.1176.8–201.4
206943.915.7–73.3189.2174–202.2
207033.714.7–63190.4177.1–204.1
207142.817.7–73.9193.2174.7–207.4
207242.718.2–68.1190.3174.7–203.7
207344.423.8–82.3192.8177.3–207.7
20744214.1–71.6189.9174.1–206.8
207541.515.2–70.1190.3174.8–206.1
207639.914.1–81.2190.9175–206.9
207742.723.6–83.6193.3176.6–206.1
207844.424.7–79.2192.2178.3–207.4
207943.923.1–74.7192177.9–203.8
208052.224.5–83192.9177.3–209.4
208150.628.6–83193.1174.9–208
208249.322.9–92.1192.8177.3–208.2
208349.218.9–88.7194.3178.4–208.7
208450.421.6–92.6193.4181.1–208.4
208549.920.5–104.5193.9178.3–211
208650.922.5–100.6193.2177.7–211.5
208753.125–82.1194.6180.8–208.8
208846.314.7–108.4195178.3–211.9
208952.722.8–107.6195.7180.6–209.9
209055.216.3–89.2194.9178.8–210.6
209151.331.2–98195.9182.4–210.1
209255.422.1–101.2195.7181.2–210.7
209347.718.8–94.6194.4178.8–210.4
209451.225.3–87.3195.7181.7–209.9
209557.624.4–95.1196.2182.1–210.7
209650.820–91.8196.8178.8–213.1
209748.923.7–96195.2178–211.1
209852.926.4–94.7196.3177.7–212.9
209948.722.9–82195.3181.5–210.6
210056.822.9–95.8195.8182.5–210.3

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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