Algeria vs Iran

Algeria vs Iran: Tropical nights

Tropical nights in 2014: 147.8 nights in Algeria and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Algeria, by 57 nights, or 1.63 times that in Iran.

nights a year · CMIP6

Algeria vs Iran: Tropical nightsTropical nights in 2014: 147.8 nights in Algeria and 90.8 nights in Iran, in the CMIP6 climate models’ median run. In 2014 the value was higher in Algeria, by 57 nights, or 1.63 times that in Iran.
AlgeriaIranCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Algeria has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Algeria at 177.5 nights and Iran at 124.4 nights in 2100.

Every year

nights a year · CMIP6

YearAlgeriaIran
2014147.890.8
2013149.290.6
2012149.190.3
2011149.889.8
2010148.787
2009146.587.2
2008148.388
2007146.687.9
2006146.488.2
2005145.587.1
200414686.4
200314585.9
2002144.987.7
2001144.786.6
200014486.5
1999141.485.1
1998142.283.8
1997141.484.3
1996139.682.4
1995137.581.6
199413880.6
1993135.377.7
1992131.677
1991138.781.9
1990141.683.1
1989137.681.7
1988137.380.4
1987136.479.8
1986136.280.1
1985133.479.7
1984135.278.8
1983133.975.5
1982136.577.9
1981134.780.2
1980133.579.4
197913580.2
1978134.878.1
1977133.377.8
1976133.877.2
197513476.6
197413076.4
1973133.876.9
1972133.377.4
1971130.875
1970128.775.3
1969131.575.6
1968131.376.3
196713176.1
196613175.5
1965127.275.3
1964131.775.3
196313176.4
1962132.677.5
1961132.477.7
1960134.477.6
1959134.376.8
1958133.878.4
1957134.678.2
1956132.876.2
1955133.276.5
1954130.277.6
1953130.177.3
1952132.878.2
1951133.776.6
1950131.777.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearAlgeriaIran
2015149.7136.5–163.394.482.7–106
2016148.4136.2–163.894.183.1–105.3
2017155139.3–169.493.981.7–104
2018154.4138.5–167.494.183–106.3
2019153.9139.9–167.995.183.4–105.8
2020152.8138.9–166.495.985.5–107.5
2021156.2142.9–168.297.286–107.7
2022157.3142.1–173.696.285.2–108.3
2023153.8139.7–166.798.485.7–110.6
2024157.2145.1–170.49885.1–110.5
2025156142.2–17098.787.2–110.5
2026158145.8–170.599.186.7–111.7
2027157.9144.9–172100.288.7–112.1
2028159.1145.3–170.699.686.2–111.6
2029158.6145.9–17199.386.7–109.9
2030157.3142.8–169.1100.889.8–111.6
2031158.9145.5–174.1102.990.1–114.8
2032162.1151.7–174.9101.289–113.9
2033161.3144.7–173.9102.889.9–115.1
2034161.5145.2–176.1104.690.7–117.3
2035162.6149.6–177.810592.1–116.2
2036161.7149.4–175.3103.591.4–115.2
2037161.9147.5–176.410693.1–119.4
2038164148–178105.993.2–116.5
2039163.4147.7–179.3104.392.9–116.6
2040163.8149.7–179105.592.3–118.4
2041162.1147.9–175.2104.892.5–116.4
2042165.2151.6–180.4107.793.4–120.7
2043163.7150.7–174.110692.9–118.8
2044164.1150.7–177.7106.893.6–121.2
2045166.3153.8–177.7108.795.1–121.8
2046165.5151.5–178.8109.296.1–121.9
2047166.9151.1–182.8110.596.9–123.3
2048166.9154.5–180.8111.498.6–124
2049166.2153.1–178.711095.7–123.4
2050168.1152.8–180.9112.199.6–125.1
2051166.4152.8–181.4111.797.6–124.1
2052167.9155.5–185.311298.3–126
2053167.8153.5–183111.597.5–124
2054169.9154.7–184.1111.899–126.3
2055171.2156.6–185114.6101.4–128
2056169.6154.7–185113.1100.2–126.2
2057169.5154.9–186.3113.899.9–128.9
2058168.8154.9–187.6114.2100–127.7
2059171157–188.4113.498.9–126.3
2060171.7156.6–186.7116.3100.3–129.5
2061174160.5–186.9115100.5–127.6
2062170154.4–189.1115.799.7–131.1
2063173.1158.9–187.6117103.7–130.3
2064171.3156.5–187.5115.1101.7–130.3
2065172.4158.1–185.8117.3102.8–132.3
2066172.7157.8–189.5117.7103.7–132.1
2067173.3158.5–188119103–133.5
2068174.6157.3–191.3118.1104.3–131.4
2069174.7158.7–188.1118.4103.8–133.2
2070173.3159.4–186.8118.2104.9–132.9
2071173.9159.5–192.1119.3105.1–135.3
2072176.4160–191119103.2–135.1
2073175.3160.4–192.4120.6104.9–137.7
2074176.7157.1–191.8119.1104.4–134.5
2075174.3158.7–193.2119.7105.9–135.5
2076176.3161.3–192.1118.9102.6–137
2077175.9160.3–194120.3104.3–135.3
2078180164.9–191.9119.2105.3–136
2079178157.2–194.5120.1103.2–135.6
2080178160.3–192.5120.4106.1–139.5
2081175.3161.2–192.8120.5104.3–137.1
2082177.2160.2–192.3122.5107.5–137.7
2083178.5161.1–195.6122.6105.8–140.4
2084180.1164.6–192.9123.7107.6–139.1
2085179.6159.9–197.5121.3106.6–140.6
2086179.8163.9–196.8122.1107.9–139.8
2087179160.6–195.3123.7108–140.7
2088179.3163.3–198.8124106.5–142.2
2089178.9163.6–197.4124.1109–139.7
2090180.5161.9–196.8122.5105.4–141.9
2091179.6164.9–197.5124.3108–140.5
2092181.6164.7–195.6125.5110.1–140
2093181.1162.6–199.4124.5109–139.3
2094180.6164.4–193.7125108.7–142.9
2095181.1164.5–195.8125.3108.5–141
2096180.7165.8–199.4125.8109–142.4
2097178.3162.2–193.1123.6106.9–141.8
2098180.4164.5–198.3125.8109.4–143.8
2099182165.3–199.3123.1107.8–140.1
2100177.5163.3–199.1124.4107.9–143.7

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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