Pakistan vs Yemen

Pakistan vs Yemen: Tropical nights

Tropical nights in 2014: 149.9 nights in Pakistan and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 25.9 nights, or 1.17 times that in Pakistan.

Watch it change on the map

nights a year · CMIP6

Pakistan vs Yemen: Tropical nightsTropical nights in 2014: 149.9 nights in Pakistan and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 25.9 nights, or 1.17 times that in Pakistan.
PakistanYemenCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Yemen has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Pakistan at 177.6 nights and Yemen at 225.7 nights in 2100.

Every year

nights a year · CMIP6

YearPakistanYemen
2014149.9175.8
2013149.1176.9
2012149.9178.4
2011149178.3
2010148.4174.9
2009147.1173.4
2008147.4174
2007147.3173.9
2006146.7173.6
2005146.5172.4
2004147.5174.3
2003146173.5
2002148.3171.8
2001145.4172.7
2000144.7167.9
1999146.9168.6
1998144.8168.7
1997143.2168.8
1996141.2166
1995141.8164.3
1994142.1161.6
1993140.4161.2
1992139.9157.2
1991142.5166.5
1990142.6168.3
1989142.5164.3
1988140.3163.7
1987140160.7
1986140162.3
1985140158.2
1984138.9159.8
1983136.3155.4
1982138.5161.5
1981141.5161.7
1980139.5158.5
1979139.1160.1
1978139158.9
1977138.6161.2
1976139.2157.5
1975136.5156.9
1974138.7157.8
1973137.8158.1
1972137.4157.5
1971136156.7
1970137.7156.9
1969135.9157.5
1968136.6154.5
1967135.2152.1
1966136.9155.1
1965138.3153.5
1964135.1154
1963135.7154.7
1962137155.9
1961138.6158.7
1960139160.1
1959138.6156.1
1958137.7158.5
1957140158.1
1956137.8156.2
1955137.5157.4
1954137.8156.1
1953136.9155.1
1952138.1157
1951136.7155.4
1950139.1157.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearPakistanYemen
2015152.4138.7–163.3180.9163.8–197.8
2016150.6139.4–161.7178.4162.7–194.6
2017151.3138.8–162179.8162.3–196.8
2018152.6139.8–161.8183.2165.3–198.6
2019151.8138.1–163.3179162–200.4
2020153.1140.3–164.5181.5163.1–195.9
2021154.1140.6–165.7184.6170.2–202.6
2022153.1140.2–165.7184.1167.5–203.7
2023155.5141.6–165.9186.8170.1–200.5
2024156.8143.3–168.7185.3168.8–206.4
2025155.7141.5–168.6186.5164.7–211.8
2026155.3142.2–167.9187.8167.9–208.8
2027156.8140.9–168.9186.5167.9–205.3
2028156.5143.9–167.6188.2172.3–203.6
2029155.9141.5–167.7193175.7–211.5
2030156.3143.3–167.6189.4171.6–207.4
2031157.3144.4–168.1193.4176.6–211.5
2032157.4142.5–169.6192.7173.2–213.2
2033157.7143.6–169.4191.2173–209.1
2034159.5145.6–173.4193.1172.1–214.9
2035159.3146.7–170.3193.1174.5–214.1
2036159.1147.5–171.4194177.6–213.5
2037162.2147.5–175.3195.9180.3–212.8
2038161.4148.6–171.7197.6178.5–217.1
2039160148.2–170.4194.8179.8–215.4
2040160.9147.9–171.3196.4178.8–220.1
2041160.8146.7–171.7198.5176.5–216.9
2042162.3149.9–175.6197.3174.4–225.8
2043161.1150.3–173.8198.3179.3–221
2044163150.9–173.9198.7180.5–221.9
2045163149.5–174.8199.8181.6–220.3
2046163.5149.8–177.2202.2181.7–229.3
2047165.2151.8–178.5205182.7–229.8
2048166.4154.1–179.4207.4188.8–229.5
2049165150.8–178.2203.6186.1–222.5
2050166.9153.5–179.3202.8186.2–226.3
2051165.6150.8–180204.6185.1–229.1
2052166.7155.4–179.5207.2186.9–227.7
2053166.3154.2–178.8203.9186.1–226.9
2054167.5153.9–181208.4188.3–234.9
2055167.8155.8–182.5208.3190.7–228
2056166.3153.6–179.7208.6188.5–236.3
2057168.3153.9–182.3208.4190.1–233.1
2058167.5157–179.9207.2184.7–236
2059170.9155.9–183.8213.3191.6–239.3
2060170.3156.5–181.8215194.1–235.3
2061168.8156.8–179.6209.8189.8–233.3
2062171.6153.5–186.5211.4189.6–246.5
2063171.3159.5–183.8215.9193.5–239.5
2064170.2155.3–184.5212.6194.7–231.7
2065169.7156.4–185212.5191.7–241.4
2066172.2157–186.7215.6196.9–241.3
2067173.2160.2–186.3214.6192.2–242.5
2068172.6157.7–186.3217192.5–243.8
2069171.8157.3–185.6216.7196.5–240.8
2070171.7158.9–186.7214.6189–244.5
2071173.4158.7–186.8221.2192.7–244.8
2072174161.5–186.9217.5194.7–239.4
2073175.6157.2–187.9220.5197.7–248.2
2074173.5160–186.3215.3193.3–240.1
2075173161.5–187.8220.7195.5–247.6
2076172.9158.8–186.7219.5196.2–243.5
2077175161.3–187.8220.8193.8–249.9
2078174.4160.9–189.3220.7198.9–246.9
2079172.5158.3–187.7219.4195.2–249.3
2080175.1160.7–189.2221.7197.8–246
2081174.9159.2–190.2222.4199.1–247
2082175.4161.8–190.6220.1198.5–243
2083176.5161.8–190.8217.4195.3–258.9
2084176.1160.9–190.5223.7195.6–246
2085176.3161.9–193.6225.1203.3–254.4
2086173.9160–189.1223.1196.5–256
2087176161–193.1225.8201.1–255.8
2088175.4160.5–195.2224197.1–259.9
2089177.2164.2–191.7225.6200.2–255.2
2090177.7163.9–192.2225.1201.5–253
2091177.8162.8–192.2228.1201.9–261.8
2092178.7162.9–192.9227.3200.1–261.6
2093177164–191223.6200.9–258.9
2094176.8164.1–190.7223200.3–250.5
2095178.6163.8–193.1228205.2–255.9
2096177.8163.7–192.5225.1201.6–257.9
2097177.3160.4–192.5222.6200.1–251.1
2098178.7162.6–195.7225.6199.6–261
2099176159.9–193.2223.2200.6–251.1
2100177.6162.2–193225.7204.7–259.7

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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