Iran vs Saudi Arabia

Iran vs Saudi Arabia: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 90.7 nights, or 2 times that in Iran.

nights a year · CMIP6

Iran vs Saudi Arabia: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 181.5 nights in Saudi Arabia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Saudi Arabia, by 90.7 nights, or 2 times that in Iran.
IranSaudi 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 Iran at 124.4 nights and Saudi Arabia at 218.7 nights in 2100.

Every year

nights a year · CMIP6

YearIranSaudi Arabia
201490.8181.5
201390.6180.4
201290.3182.8
201189.8182.7
201087179.2
200987.2177.1
200888180.3
200787.9178.9
200688.2177.5
200587.1177.9
200486.4177.6
200385.9177.4
200287.7175.6
200186.6178.1
200086.5176.4
199985.1173.2
199883.8173.4
199784.3173.8
199682.4172
199581.6169.2
199480.6170.4
199377.7164.6
199277165.9
199181.9169.2
199083.1172.7
198981.7168.9
198880.4166.8
198779.8167.3
198680.1169.4
198579.7166
198478.8165
198375.5163.5
198277.9164.7
198180.2168.9
198079.4166.8
197980.2165.3
197878.1164.8
197777.8165.6
197677.2165.9
197576.6161.2
197476.4162.9
197376.9163.7
197277.4163.7
197175160.4
197075.3162.5
196975.6161.3
196876.3162.7
196776.1159.5
196675.5159.5
196575.3159.5
196475.3159.9
196376.4160.2
196277.5163.2
196177.7163.7
196077.6165.7
195976.8164.4
195878.4164.1
195778.2165.5
195676.2163.6
195576.5162
195477.6161.2
195377.3162.5
195278.2163.4
195176.6161.2
195077.7161.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranSaudi Arabia
201594.482.7–106184.9169.4–198.7
201694.183.1–105.3183167.7–195.7
201793.981.7–104182.6168.1–196.7
201894.183–106.3186.8173.1–199.4
201995.183.4–105.8184.1168.8–199.1
202095.985.5–107.5185.3171.8–198.9
202197.286–107.7188.6173.6–202.8
202296.285.2–108.3187.6170.7–202
202398.485.7–110.6188.6173–203.8
20249885.1–110.5187.1172.9–203.9
202598.787.2–110.5191.5176–206.1
202699.186.7–111.7191.8177.1–205.5
2027100.288.7–112.1191.2176.6–206.8
202899.686.2–111.6191.9175.5–205.1
202999.386.7–109.9192.2176.6–205.7
2030100.889.8–111.6193.3178.4–206.3
2031102.990.1–114.8194.7179.1–207.6
2032101.289–113.9192.2175.2–206
2033102.889.9–115.1192.6177.5–206.9
2034104.690.7–117.3196.7181.6–213
203510592.1–116.2196.5179.9–211.6
2036103.591.4–115.2194.1180–209.7
203710693.1–119.4197183.7–209.9
2038105.993.2–116.5198.4182.3–213.3
2039104.392.9–116.6198184.4–213.6
2040105.592.3–118.4199.2182.1–212.7
2041104.892.5–116.4197.7181.4–211.7
2042107.793.4–120.7198.3181.2–217
204310692.9–118.8198.2182.3–215.3
2044106.893.6–121.2199.2185.5–213.5
2045108.795.1–121.8202187.1–216.8
2046109.296.1–121.9204.1185.3–219.4
2047110.596.9–123.3204.1187.4–220
2048111.498.6–124206.1190.7–220
204911095.7–123.4201.6187.7–216.2
2050112.199.6–125.1205.7190.2–219.3
2051111.797.6–124.1204.3188.8–222.1
205211298.3–126203.8189.6–218
2053111.597.5–124203.8186.3–218.8
2054111.899–126.3207.6188.3–222.3
2055114.6101.4–128207.8190.8–221
2056113.1100.2–126.2203.7186.6–220.1
2057113.899.9–128.9207.5188.8–224.2
2058114.2100–127.7205.9189.2–221.4
2059113.498.9–126.3207.3191.6–226.9
2060116.3100.3–129.5206.9192.7–222.8
2061115100.5–127.6206.5190.4–220.9
2062115.799.7–131.1208.1189.4–228.3
2063117103.7–130.3210.4193–227.1
2064115.1101.7–130.3207.5191.9–223.3
2065117.3102.8–132.3208.9193.9–226.1
2066117.7103.7–132.1210.3194.9–228
2067119103–133.5210.9193.1–228.6
2068118.1104.3–131.4209.8194.6–228.6
2069118.4103.8–133.2208.9194.5–226.3
2070118.2104.9–132.9211.2191.2–229
2071119.3105.1–135.3215.1196.3–233.3
2072119103.2–135.1213.6195.3–229.3
2073120.6104.9–137.7213.7194.1–231.6
2074119.1104.4–134.5210.5191.9–229.3
2075119.7105.9–135.5212.1196.6–231.8
2076118.9102.6–137212.8194.8–230.3
2077120.3104.3–135.3215.1196.6–233.9
2078119.2105.3–136215.5197.6–230.7
2079120.1103.2–135.6213.6197–229
2080120.4106.1–139.5213.6197.1–233.9
2081120.5104.3–137.1214.7194.4–231.6
2082122.5107.5–137.7214198.9–230.9
2083122.6105.8–140.4214.2198.5–238
2084123.7107.6–139.1217.4197.4–233.1
2085121.3106.6–140.6217.4199.6–237.9
2086122.1107.9–139.8217197.4–237.4
2087123.7108–140.7217.3199.7–238.7
2088124106.5–142.2216.1198.2–243.1
2089124.1109–139.7217.6199.5–239
2090122.5105.4–141.9217.3198.5–239.2
2091124.3108–140.5218.5202.8–238.4
2092125.5110.1–140218.5198.5–241.6
2093124.5109–139.3216.6197.8–236.3
2094125108.7–142.9218.8202–236.9
2095125.3108.5–141219.4204.2–237.4
2096125.8109–142.4219.9197.7–239.6
2097123.6106.9–141.8216.7196.8–239.7
2098125.8109.4–143.8219.7199.6–241.3
2099123.1107.8–140.1216.8200.8–236.8
2100124.4107.9–143.7218.7202.3–241

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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