Ethiopia vs Mexico

Ethiopia vs Mexico: Tropical nights

Tropical nights in 2014: 144.9 nights in Ethiopia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ethiopia, by 41.2 nights, or 1.4 times that in Mexico.

nights a year · CMIP6

Ethiopia vs Mexico: Tropical nightsTropical nights in 2014: 144.9 nights in Ethiopia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ethiopia, by 41.2 nights, or 1.4 times that in Mexico.
EthiopiaMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Ethiopia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Ethiopia at 201.7 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearEthiopiaMexico
2014144.9103.7
2013145.1103.9
2012144.4102.8
2011145.6102.9
2010142.4101.5
2009140.3101.8
2008137.1100.1
2007138.299.1
2006138.799.8
2005138.199.5
2004139.199.4
2003138.898.3
2002137.499.1
2001139.298.7
2000135.597.9
1999132.696.6
1998132.995.8
1997132.795.9
1996129.793.8
1995127.892.7
1994126.390.7
1993122.589
1992119.788.5
1991129.593.4
1990132.794.9
1989129.493
1988128.292.1
1987126.492
1986128.190.2
1985122.890
1984124.888
1983120.686.7
1982126.388.7
198112791.5
1980124.990.1
1979125.190.8
1978124.789
1977125.889
197612289.1
1975119.586.8
197412487.9
1973125.288.6
1972122.387.7
1971120.686.8
1970121.386.1
1969120.487.5
1968119.187.1
1967118.186.7
1966119.586.4
1965117.484.9
1964116.684.7
1963115.787.1
1962121.688
1961124.289.5
1960124.589.7
1959121.689.6
1958124.189.1
1957123.289
1956120.988.5
1955122.888.2
1954121.688.4
1953121.288.6
1952122.887.8
195112389.4
195012288.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearEthiopiaMexico
2015146.6129.4–163.9106.192.9–118.4
2016144.1127–160.6107.695–120
2017148.3129.2–164.9108.696.3–119.7
2018149.6131.6–16610997.1–120.4
2019146.2129.3–166110.396.4–123
2020149.4129.6–168.5109.696.8–121.8
2021150.7132.1–170111.296.9–124.1
2022154135.7–171.2109.796–121.7
2023153.5135.4–171.4111.898.6–125.3
2024156.5135.9–175.6112.298.2–126.2
2025154132.6–175.511298.8–125.8
2026153132–175113.999.5–126.4
2027154.2134.4–175.3112.999.5–128.3
2028157.5138.3–177.4115.2101.9–127.9
2029159.2141.8–176.8115.6101.9–127.9
2030156.8136.3–175.7115.9101.7–128.4
2031161.4142.4–179.1116.1100.9–129.9
2032161.7143.1–182.5116.1102.5–129.1
2033161.8140–180.9117.5102.5–131.1
2034158.8141.5–184.3117.2104.1–130.3
2035162141.7–184.2116.4103.1–130.3
2036160.5143.6–179.4117.8105.1–131
2037165145.8–184.5118.6104.3–131.7
2038167.1146.5–186.7121107.5–133.4
2039164.5143.9–186121.3107–135.6
2040165.9146.2–190.1121.9108.1–135.1
2041167.9146.3–189.3121.3105.3–134.6
2042167.7146–194.3122.7107.7–137.1
2043167.3145.5–190.8122.4108.1–137.5
2044168.2148.2–189.9121.9108–135.6
2045170.7149.1–192.3123.1108.8–139.2
2046175.3150–198.6123.8109.9–139.4
2047176.9151.8–197.5125.6111.9–139.4
2048177.5155.4–199.1126.3113–140.3
2049177.5157.9–198.4127111.2–140.8
2050176.4153.8–199128.1112.6–142.5
2051176.6155.3–199.7127.2113.4–140.8
2052177155.6–200.7126.2112.5–141.1
2053176.7154.2–201.6128.4111.5–142.7
2054177.6156.9–201.1128.1113.1–142.3
2055180.6155.2–202.3129114.4–144.7
2056177.3155–205.4129.5114.3–143.8
2057180.3159.3–205.5130.3113.5–145.9
2058182.6153.7–209.4128.8114.1–144.5
2059185.7160.1–210.6129.5114.5–144.5
2060185.9160.3–210.4131.4115.5–146.5
2061183.3158.3–211.7131.3118.4–146.8
2062183.8155.4–213130.8115.1–146.3
2063184.5159.1–208.6131.2115.6–147.9
2064186.7160.6–207.2132.2116.5–147.8
2065183.7162.4–212.9133.1115.8–148.6
2066187.1165.4–210.1133.3117.2–149.4
2067187.1160.7–214.5133.3117–150.3
2068187.6160.4–215.8134.6117.4–150.5
2069187.8165.4–215.8134.4117.8–150.9
2070187.9161.6–216.9134.2116.7–151.8
2071192.7165.2–219.5136.3120.8–152.7
2072193.6167.4–214.5137.2119.9–153.1
2073193.3169.7–218.7136.1119.1–153.6
2074188.5163.9–219136119.7–152.2
2075191.9162.7–218.6135.2118.5–151.8
2076195166.9–218.9136.3117.4–154.7
2077194.1169.3–223.3136.8119.6–152.8
2078192.1168.4–218.6137.1118.3–154.2
2079193.4166.6–220.9138.1121.3–157.1
2080196.1169.2–222.4137.6120.5–157.9
2081194.6171–221.4137.8120.7–154.7
2082195.4168.8–219.9138.7121.6–155.2
2083194.6168.2–228.7139.2119.3–158.8
2084198.5170.7–224.2140.3123.4–157.5
2085198.4173.1–226.3139.2120.9–157.2
2086198.6172.3–228.4139.8121–157.8
2087199170.6–226.6139.5121.5–157.4
2088199170.7–227.7141121.8–159.9
2089198.6171.2–226.2140.4121.7–158.9
2090198.6173.4–227.7141.2123–160.7
2091203.6171.9–232.1141.8123–161.6
2092200.7172.5–229.7141.3122.5–159.3
2093201.4175.2–228.6141.4124.3–161
2094200.2174–228.9142123.3–159.6
2095203.9175.7–231.9143.5124–160.7
2096199.1170.5–230.8142.3125–161.3
2097198.4171.8–229.3141.2123.2–160
2098198.7172.1–231.5142.2122.5–162
2099201.8172.8–233.3141.8122.4–160.7
2100201.7175.1–231.8142.8124.3–160.8

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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