Australia vs Mexico

Australia vs Mexico: Tropical nights

Tropical nights in 2014: 135.1 nights in Australia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Australia, by 31.4 nights, or 1.3 times that in Mexico.

nights a year · CMIP6

Australia vs Mexico: Tropical nightsTropical nights in 2014: 135.1 nights in Australia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Australia, by 31.4 nights, or 1.3 times that in Mexico.
AustraliaMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Australia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Australia at 169.9 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearAustraliaMexico
2014135.1103.7
2013133103.9
2012132.9102.8
2011133.8102.9
2010134.2101.5
2009132.3101.8
2008132.3100.1
2007131.899.1
2006128.199.8
2005131.799.5
2004131.499.4
2003132.498.3
2002129.799.1
2001130.198.7
2000129.797.9
1999127.796.6
1998128.195.8
1997124.595.9
1996123.993.8
1995123.592.7
1994124.490.7
1993121.489
1992116.788.5
1991125.193.4
199012694.9
1989124.493
1988125.292.1
1987124.492
1986124.990.2
1985122.790
1984123.988
1983122.586.7
1982124.788.7
1981123.391.5
1980123.790.1
1979122.390.8
1978121.289
1977120.689
1976121.189.1
1975118.686.8
1974119.787.9
1973123.388.6
1972120.287.7
1971120.486.8
1970118.586.1
1969120.987.5
1968118.987.1
1967118.686.7
1966116.586.4
1965116.584.9
1964112.584.7
1963114.687.1
196211988
1961121.989.5
1960120.789.7
1959120.389.6
1958121.889.1
1957119.889
1956119.988.5
1955117.588.2
1954119.988.4
1953118.588.6
1952119.987.8
1951119.689.4
1950119.788.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearAustraliaMexico
2015134116.5–149.2106.192.9–118.4
2016134.8118.2–149.5107.695–120
2017136.1119.3–149.5108.696.3–119.7
2018135.8118.4–151.410997.1–120.4
2019136.6120.4–151.6110.396.4–123
2020136119.8–151.4109.696.8–121.8
2021135.6118.6–151.2111.296.9–124.1
2022138.6121.4–155.1109.796–121.7
2023139.9123.6–155.2111.898.6–125.3
2024141122.4–156.1112.298.2–126.2
2025140.9121–159.311298.8–125.8
2026139.4121.9–157.8113.999.5–126.4
2027140.4123.7–156112.999.5–128.3
2028141.8125.4–158.7115.2101.9–127.9
2029143.3126–159.6115.6101.9–127.9
2030140.1125.4–156.4115.9101.7–128.4
2031141.6124.9–156.9116.1100.9–129.9
2032144.6128.6–162.1116.1102.5–129.1
2033144.5127.7–159.2117.5102.5–131.1
2034145129.2–161.3117.2104.1–130.3
2035146.5128.8–161.8116.4103.1–130.3
2036146.9128–161.8117.8105.1–131
2037146.6130.1–161.6118.6104.3–131.7
2038148.2131.2–164121107.5–133.4
2039146.9130.3–163.4121.3107–135.6
2040147.9130.6–164.6121.9108.1–135.1
2041147.6130.5–165.9121.3105.3–134.6
2042148.2129.2–166.5122.7107.7–137.1
2043148.9133.1–164.5122.4108.1–137.5
2044151135.2–166.3121.9108–135.6
2045149.3130.9–164.3123.1108.8–139.2
2046151.2135.4–168123.8109.9–139.4
2047153.5132.9–169.5125.6111.9–139.4
2048154.1135.2–171.4126.3113–140.3
2049153.4137.4–170.1127111.2–140.8
2050152.3133–170.6128.1112.6–142.5
2051154.5135.1–171.8127.2113.4–140.8
2052154.7134.9–175.7126.2112.5–141.1
2053153.8131.8–173128.4111.5–142.7
2054152.8134.4–172.4128.1113.1–142.3
2055155.2138.1–174.8129114.4–144.7
2056157139.6–173.6129.5114.3–143.8
2057156.3137.4–172.3130.3113.5–145.9
2058158.3135.3–176.6128.8114.1–144.5
2059157.9138.9–174.7129.5114.5–144.5
2060158.4140.3–176.8131.4115.5–146.5
2061158.8139.6–175.2131.3118.4–146.8
2062156.1137.8–172.7130.8115.1–146.3
2063160.2140–178.6131.2115.6–147.9
2064159.3140.5–177.9132.2116.5–147.8
2065156.7136.6–177.5133.1115.8–148.6
2066161.6142–180.6133.3117.2–149.4
2067162.5141.6–183.1133.3117–150.3
2068162.4140.7–180.1134.6117.4–150.5
2069162.6143.3–181134.4117.8–150.9
2070161.4140.4–180.3134.2116.7–151.8
2071162.1142–181.9136.3120.8–152.7
2072162.2142.3–179.6137.2119.9–153.1
2073163.8144.6–182.6136.1119.1–153.6
2074162.2142.8–181.6136119.7–152.2
2075163.1143–180.9135.2118.5–151.8
2076163.2141.1–181.9136.3117.4–154.7
2077163.1141.8–181.8136.8119.6–152.8
2078163.9145.8–181.3137.1118.3–154.2
2079163.3143.1–186138.1121.3–157.1
2080163142.7–183.3137.6120.5–157.9
2081165.8142.9–185.5137.8120.7–154.7
2082164.6145–182.6138.7121.6–155.2
2083164.2141.3–187139.2119.3–158.8
2084165.6140.7–187.4140.3123.4–157.5
2085167.2143.9–187.5139.2120.9–157.2
2086166.8143.2–186.2139.8121–157.8
2087165.2142.9–189.1139.5121.5–157.4
2088167.5146–187.8141121.8–159.9
2089166.3146.9–184.2140.4121.7–158.9
2090168.6145–188.3141.2123–160.7
2091168.3145.8–186.5141.8123–161.6
2092167.4144.8–185.2141.3122.5–159.3
2093168.2146–191.5141.4124.3–161
2094169146.8–187.2142123.3–159.6
2095169.5146.9–189.1143.5124–160.7
2096170.2145.3–192.8142.3125–161.3
2097168.2145.9–187.4141.2123.2–160
2098169.7149.4–190.8142.2122.5–162
2099167.1147.5–187.7141.8122.4–160.7
2100169.9149.9–190.1142.8124.3–160.8

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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