Iran vs Vietnam

Iran vs Vietnam: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 242.6 nights in Vietnam, in the CMIP6 climate models’ median run. In 2014 the value was higher in Vietnam, by 151.8 nights, or 2.67 times that in Iran.

nights a year · CMIP6

Iran vs Vietnam: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 242.6 nights in Vietnam, in the CMIP6 climate models’ median run. In 2014 the value was higher in Vietnam, by 151.8 nights, or 2.67 times that in Iran.
IranVietnamCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Vietnam 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 Vietnam at 282.7 nights in 2100.

Every year

nights a year · CMIP6

YearIranVietnam
201490.8242.6
201390.6243.6
201290.3242.4
201189.8241.9
201087240.9
200987.2240
200888238.7
200787.9238
200688.2239.1
200587.1238.3
200486.4241.8
200385.9235.9
200287.7236.3
200186.6241.3
200086.5237
199985.1236
199883.8236.8
199784.3237.1
199682.4231.4
199581.6229.9
199480.6231.2
199377.7225.3
199277221.9
199181.9229.8
199083.1233.1
198981.7229.2
198880.4231.7
198779.8230.3
198680.1230.9
198579.7228
198478.8230.2
198375.5224.9
198277.9227.5
198180.2229.7
198079.4228.1
197980.2228.9
197878.1227.5
197777.8229
197677.2225.8
197576.6225.8
197476.4225.7
197376.9230.3
197277.4225.6
197175225.5
197075.3226.1
196975.6227
196876.3227.1
196776.1222.9
196675.5226.8
196575.3225.4
196475.3222.6
196376.4224.3
196277.5227.8
196177.7229.4
196077.6228.5
195976.8226.2
195878.4230.9
195778.2228.4
195676.2228.7
195576.5227.5
195477.6226.3
195377.3228.2
195278.2228.5
195176.6229.2
195077.7228.9
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranVietnam
201594.482.7–106245.8228.2–261.9
201694.183.1–105.3243.7226.1–259.4
201793.981.7–104247229.6–260.7
201894.183–106.3248.3228.8–263.3
201995.183.4–105.8248.1229.2–262.8
202095.985.5–107.5248.8229.6–262.9
202197.286–107.7251.1233.1–266.7
202296.285.2–108.3252.4234.3–266.8
202398.485.7–110.6253.4235.4–266.6
20249885.1–110.5251.3236.7–264.6
202598.787.2–110.5252.4234.1–266.2
202699.186.7–111.7252.8232.9–268.5
2027100.288.7–112.1253.2237–268.8
202899.686.2–111.6254.3237.7–272
202999.386.7–109.9258.1238.5–273.7
2030100.889.8–111.6256.4240.9–270.1
2031102.990.1–114.8255.9241.2–270.9
2032101.289–113.9257.4239.1–269.9
2033102.889.9–115.1258.3241.7–273.2
2034104.690.7–117.3258.8240.7–275.8
203510592.1–116.2258.6242.5–275.4
2036103.591.4–115.2258.3239.1–273.8
203710693.1–119.4258.7242.4–272.4
2038105.993.2–116.5263.4247.6–277.3
2039104.392.9–116.6260.2243.7–275.9
2040105.592.3–118.4260.1242.8–274.8
2041104.892.5–116.4263.1245.9–279
2042107.793.4–120.7263.6246.5–279
204310692.9–118.8261.4245.5–279.6
2044106.893.6–121.2263.2245.2–277.6
2045108.795.1–121.8265.5249.6–281.4
2046109.296.1–121.9264.9246.8–278.1
2047110.596.9–123.3266.9250.4–282.9
2048111.498.6–124268250.5–283.8
204911095.7–123.4267.8251.2–284.8
2050112.199.6–125.1268251.2–283.5
2051111.797.6–124.1270.9254.3–285.4
205211298.3–126268.3253.3–282.8
2053111.597.5–124268.5250.1–283.2
2054111.899–126.3269.1250.8–283.6
2055114.6101.4–128270249.8–284.2
2056113.1100.2–126.2271.7254.8–290.1
2057113.899.9–128.9270253–285.7
2058114.2100–127.7270.7252.9–286.5
2059113.498.9–126.3273257.6–286.6
2060116.3100.3–129.5275.7255.6–290.6
2061115100.5–127.6273.5254.6–289.5
2062115.799.7–131.1271.4253.1–290.2
2063117103.7–130.3272.9252.7–288.1
2064115.1101.7–130.3273.8254.4–288.1
2065117.3102.8–132.3272255.8–286.3
2066117.7103.7–132.1271.8254.4–287.3
2067119103–133.5270.8252.1–287.6
2068118.1104.3–131.4275.6256.9–292.4
2069118.4103.8–133.2276.4258.5–292
2070118.2104.9–132.9274.6257.8–292.8
2071119.3105.1–135.3276.2255.2–294.1
2072119103.2–135.1277256.8–291.4
2073120.6104.9–137.7278.5262.7–293.4
2074119.1104.4–134.5277.6259.2–295.8
2075119.7105.9–135.5276.4258.7–294.4
2076118.9102.6–137279.2258.5–296.6
2077120.3104.3–135.3280264.9–294.7
2078119.2105.3–136278.4258.6–295.5
2079120.1103.2–135.6279.3263.4–293.6
2080120.4106.1–139.5280261.4–296.5
2081120.5104.3–137.1280.4261.2–297.9
2082122.5107.5–137.7280.9258.9–296
2083122.6105.8–140.4278.4261.6–295
2084123.7107.6–139.1279257.4–293.8
2085121.3106.6–140.6281.3265–297.8
2086122.1107.9–139.8282.3260.2–297.5
2087123.7108–140.7281.9261.3–300.7
2088124106.5–142.2283.1265.7–301.5
2089124.1109–139.7280.8261.2–301.6
2090122.5105.4–141.9280.5264.5–297.6
2091124.3108–140.5283.3264.3–298.9
2092125.5110.1–140281.1261.5–299.4
2093124.5109–139.3280.5263.4–296.1
2094125108.7–142.9283264.5–300
2095125.3108.5–141285.5264.5–302.9
2096125.8109–142.4281.8264.8–299.8
2097123.6106.9–141.8281.5263.3–299
2098125.8109.4–143.8282.5263.9–301.5
2099123.1107.8–140.1282.7265.1–298
2100124.4107.9–143.7282.7261–298.2

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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