Kenya vs Mexico

Kenya vs Mexico: Tropical nights

Tropical nights in 2014: 245.6 nights in Kenya and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Kenya, by 141.9 nights, or 2.37 times that in Mexico.

nights a year · CMIP6

Kenya vs Mexico: Tropical nightsTropical nights in 2014: 245.6 nights in Kenya and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Kenya, by 141.9 nights, or 2.37 times that in Mexico.
KenyaMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Kenya has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Kenya at 277 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearKenyaMexico
2014245.6103.7
2013245.4103.9
2012244.7102.8
2011245102.9
2010243.8101.5
2009242.3101.8
2008240.3100.1
2007240.999.1
2006241.599.8
2005241.299.5
2004241.899.4
2003240.898.3
2002240.799.1
200124298.7
2000239.597.9
1999237.896.6
1998239.295.8
1997236.995.9
1996234.293.8
1995232.992.7
1994231.990.7
1993227.489
1992224.888.5
1991233.893.4
1990236.494.9
1989234.593
1988233.192.1
1987232.692
198623390.2
1985228.790
1984230.288
1983226.786.7
1982230.688.7
1981232.991.5
1980231.390.1
1979229.690.8
1978228.789
1977229.989
1976227.889.1
1975225.986.8
1974230.587.9
1973230.488.6
1972228.787.7
197122686.8
1970226.386.1
1969225.987.5
1968222.987.1
196722486.7
1966225.286.4
1965224.284.9
1964221.884.7
1963220.287.1
1962227.288
1961228.389.5
1960228.889.7
1959228.389.6
1958229.189.1
195722889
1956225.588.5
1955228.788.2
1954227.488.4
1953227.688.6
1952228.587.8
1951228.389.4
1950226.388.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearKenyaMexico
2015246.9232.3–256.1106.192.9–118.4
2016244.9230.1–255107.695–120
2017248.1233.1–257.7108.696.3–119.7
2018248.7237–257.410997.1–120.4
2019247.1234.8–256.7110.396.4–123
2020248.6233.2–259.2109.696.8–121.8
2021249.5236.3–258.1111.296.9–124.1
2022251.5239.7–259.5109.796–121.7
2023251.8239–260.8111.898.6–125.3
2024254.2239.1–263112.298.2–126.2
2025251.5238.1–261.811298.8–125.8
2026252.2237.2–263.3113.999.5–126.4
2027252.8238.4–263.8112.999.5–128.3
2028254.9241.9–264.2115.2101.9–127.9
2029256243.4–264.6115.6101.9–127.9
2030253.6240.6–263.1115.9101.7–128.4
2031256244.7–264.4116.1100.9–129.9
2032257243.8–267.1116.1102.5–129.1
2033256241.8–265.9117.5102.5–131.1
2034256.2241.2–267.9117.2104.1–130.3
2035256.7243.3–266.7116.4103.1–130.3
2036256.2242.4–266.7117.8105.1–131
2037258.7245.9–268.4118.6104.3–131.7
2038260.3244.5–268.9121107.5–133.4
2039259244.4–268121.3107–135.6
2040258.3246.2–269.8121.9108.1–135.1
2041260.7244.8–271.2121.3105.3–134.6
2042260.3246.5–272.7122.7107.7–137.1
2043259246.6–270.5122.4108.1–137.5
2044261.2248.8–270.9121.9108–135.6
2045261.8248.7–272.9123.1108.8–139.2
2046264.8249.6–275.3123.8109.9–139.4
2047264.4249.8–275.3125.6111.9–139.4
2048264.2252.3–274.9126.3113–140.3
2049265.2252.8–275.6127111.2–140.8
2050263.9249.8–275.1128.1112.6–142.5
2051265.4252.1–275.1127.2113.4–140.8
2052266.3252.6–276.2126.2112.5–141.1
2053265.2251–275.4128.4111.5–142.7
2054265.2250.2–277.2128.1113.1–142.3
2055266.8251.6–277.6129114.4–144.7
2056266.2251.2–277.8129.5114.3–143.8
2057266.8253–278130.3113.5–145.9
2058266.7251.5–277.9128.8114.1–144.5
2059269.8254.7–280.5129.5114.5–144.5
2060271.1253.9–280.7131.4115.5–146.5
2061267.5253.9–281.7131.3118.4–146.8
2062268.1254–281.2130.8115.1–146.3
2063268.9255–280.1131.2115.6–147.9
2064270254.1–279.8132.2116.5–147.8
2065269.4255.8–282.3133.1115.8–148.6
2066270.6258.1–281133.3117.2–149.4
2067270.7256.1–283133.3117–150.3
2068270.2256–283134.6117.4–150.5
2069269.8256.1–283.3134.4117.8–150.9
2070270.1255.8–282.6134.2116.7–151.8
2071271.9257.9–284.4136.3120.8–152.7
2072273.5260.3–283.8137.2119.9–153.1
2073273.1259.9–285.4136.1119.1–153.6
2074271.9257.5–285.4136119.7–152.2
2075271.1256.5–284.7135.2118.5–151.8
2076274.1258.6–285.8136.3117.4–154.7
2077273.4259–286.6136.8119.6–152.8
2078273.1260–284.4137.1118.3–154.2
2079273.3258.7–286.6138.1121.3–157.1
2080275.5259.4–286.9137.6120.5–157.9
2081274.7259.8–285.6137.8120.7–154.7
2082274.8261.3–286.4138.7121.6–155.2
2083274259.6–289.3139.2119.3–158.8
2084276.8259–288.8140.3123.4–157.5
2085276.2261.5–289.1139.2120.9–157.2
2086275.1260–289.1139.8121–157.8
2087276.2260.3–288.5139.5121.5–157.4
2088276.8261.6–289.7141121.8–159.9
2089275.9260.3–288.8140.4121.7–158.9
2090275.3260.5–290.5141.2123–160.7
2091277.7260.4–290.9141.8123–161.6
2092276.2261.2–290.7141.3122.5–159.3
2093276.9262–290.1141.4124.3–161
2094277262.8–288.9142123.3–159.6
2095278.4262.3–290.4143.5124–160.7
2096277.6260.5–292142.3125–161.3
2097277261–290.2141.2123.2–160
2098277.6262.3–291.5142.2122.5–162
2099277.9260.8–292.4141.8122.4–160.7
2100277261.8–290.4142.8124.3–160.8

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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