Iraq vs Pakistan

Iraq vs Pakistan: Tropical nights

Tropical nights in 2014: 151.4 nights in Iraq and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Iraq, by 1.5 nights, or 1.01 times that in Pakistan.

nights a year · CMIP6

Iraq vs Pakistan: Tropical nightsTropical nights in 2014: 151.4 nights in Iraq and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Iraq, by 1.5 nights, or 1.01 times that in Pakistan.
IraqPakistanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Iraq has been higher since 2011, when it overtook Pakistan.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Iraq at 178.7 nights and Pakistan at 177.6 nights in 2100.

Every year

nights a year · CMIP6

YearIraqPakistan
2014151.4149.9
2013151.3149.1
2012150.9149.9
2011150.7149
2010147.5148.4
2009146.1147.1
2008149.9147.4
2007148147.3
2006146.9146.7
2005147.7146.5
2004147.3147.5
2003145.4146
2002147.2148.3
2001146.6145.4
2000148144.7
1999143.6146.9
1998142.6144.8
1997144.5143.2
1996143.7141.2
1995139.1141.8
1994141.6142.1
1993136.6140.4
1992136.6139.9
1991138.1142.5
1990142.7142.6
1989141.6142.5
1988138.2140.3
1987138.9140
1986140.9140
1985137.6140
1984135.5138.9
1983135136.3
1982135.8138.5
1981140.3141.5
1980139.4139.5
1979136.4139.1
1978136.8139
1977137.7138.6
1976138.2139.2
1975134.1136.5
1974135.8138.7
1973136.1137.8
1972135.8137.4
1971133.7136
1970135.5137.7
1969135.5135.9
1968134.3136.6
1967133.6135.2
1966132.9136.9
1965132.9138.3
1964134.2135.1
1963135.1135.7
1962137.7137
1961138.2138.6
1960136.7139
1959139138.6
1958138.4137.7
1957137.3140
1956136.6137.8
1955134.7137.5
1954136.1137.8
1953137136.9
1952136.7138.1
1951137.3136.7
1950134.9139.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIraqPakistan
2015154.9143.1–165.8152.4138.7–163.3
2016152.1139.6–164.5150.6139.4–161.7
2017154.1139.5–165.6151.3138.8–162
2018153.8142.3–165152.6139.8–161.8
2019153.3141–166.9151.8138.1–163.3
2020155.1144.8–166153.1140.3–164.5
2021155.8144.5–166.5154.1140.6–165.7
2022155.9144.3–168153.1140.2–165.7
2023157.1146.3–168.5155.5141.6–165.9
2024155.9145.1–167.7156.8143.3–168.7
2025156.8145.6–168.8155.7141.5–168.6
2026158.1147.1–168.2155.3142.2–167.9
2027159.5148.6–169.8156.8140.9–168.9
2028157.5145.7–169.4156.5143.9–167.6
2029158.5149.2–167.6155.9141.5–167.7
2030157.9147.4–169.7156.3143.3–167.6
2031160.1146.9–171.3157.3144.4–168.1
2032160146.9–170.6157.4142.5–169.6
2033161.6151.5–172157.7143.6–169.4
2034161148.9–173.9159.5145.6–173.4
2035161.8150.3–173.6159.3146.7–170.3
2036158.5146.3–170.6159.1147.5–171.4
2037161.2148.6–173.5162.2147.5–175.3
2038165.1152.5–174.7161.4148.6–171.7
2039164.6152.2–177.7160148.2–170.4
2040165153.4–175.3160.9147.9–171.3
2041163.3151.3–172.5160.8146.7–171.7
2042165.3153–176.8162.3149.9–175.6
2043164.6151.4–175.3161.1150.3–173.8
2044164.6155.1–175.2163150.9–173.9
2045167.8152.2–180.1163149.5–174.8
2046167.6155–178.8163.5149.8–177.2
2047167.1156.3–177.3165.2151.8–178.5
2048165.8155.5–179.1166.4154.1–179.4
2049165.6155.1–177.4165150.8–178.2
2050170.8156.9–181.9166.9153.5–179.3
2051168.8155.6–181.1165.6150.8–180
2052167.8154.5–180.4166.7155.4–179.5
2053168.5155.9–181.1166.3154.2–178.8
2054170.4155.7–181.4167.5153.9–181
2055171.2158.7–181.8167.8155.8–182.5
2056168152.6–178.6166.3153.6–179.7
2057169.2153.3–186.3168.3153.9–182.3
2058170.7157.1–185.5167.5157–179.9
2059169.8157–187.5170.9155.9–183.8
2060169.5157.6–185.7170.3156.5–181.8
2061170.2157.8–180.7168.8156.8–179.6
2062171.2158.1–183171.6153.5–186.5
2063170.6156.5–183.6171.3159.5–183.8
2064170159.8–182.8170.2155.3–184.5
2065171.7160.9–185.3169.7156.4–185
2066172.4158.6–184.5172.2157–186.7
2067173.9161.8–187.6173.2160.2–186.3
2068172.6159.5–185172.6157.7–186.3
2069174.3160.8–186.2171.8157.3–185.6
2070175.4162.3–186.7171.7158.9–186.7
2071176.1161.2–188.9173.4158.7–186.8
2072174.1161.5–187.3174161.5–186.9
2073176.1159.9–190.6175.6157.2–187.9
2074173.5157.8–187173.5160–186.3
2075171.3158.5–186.4173161.5–187.8
2076173.1158.7–186.3172.9158.8–186.7
2077176.7160.9–189.8175161.3–187.8
2078176.2163.1–188.2174.4160.9–189.3
2079175.2160.1–188172.5158.3–187.7
2080172.9160.7–190.1175.1160.7–189.2
2081175.5161.6–189.9174.9159.2–190.2
2082176.9162.8–188.2175.4161.8–190.6
2083179.2161.9–191.4176.5161.8–190.8
2084179.7164.5–191176.1160.9–190.5
2085177.9162.3–190.8176.3161.9–193.6
2086178.4166.1–189.5173.9160–189.1
2087178.1161.8–194.1176161–193.1
2088178.1163.4–194.1175.4160.5–195.2
2089177.5162.8–192.6177.2164.2–191.7
2090176.1163.1–191.9177.7163.9–192.2
2091178.7163.4–192.6177.8162.8–192.2
2092179.2164.9–191.4178.7162.9–192.9
2093179.3165.6–193.8177164–191
2094181.3169.4–192.9176.8164.1–190.7
2095181.2166.6–193.1178.6163.8–193.1
2096179.2163.8–193.2177.8163.7–192.5
2097180.7162.7–194.4177.3160.4–192.5
2098178.4163.1–199178.7162.6–195.7
2099178.9166.7–191.9176159.9–193.2
2100178.7165.8–191.9177.6162.2–193

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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