Bolivia vs Mexico

Bolivia vs Mexico: Tropical nights

Tropical nights in 2014: 179.5 nights in Bolivia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bolivia, by 75.8 nights, or 1.73 times that in Mexico.

nights a year · CMIP6

Bolivia vs Mexico: Tropical nightsTropical nights in 2014: 179.5 nights in Bolivia and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bolivia, by 75.8 nights, or 1.73 times that in Mexico.
BoliviaMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Bolivia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Bolivia at 210.8 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearBoliviaMexico
2014179.5103.7
2013176.3103.9
2012177102.8
2011177.2102.9
2010176.7101.5
2009175.9101.8
2008174.1100.1
200716999.1
2006169.899.8
2005170.599.5
2004175.599.4
2003170.698.3
2002173.399.1
2001172.998.7
200016997.9
1999167.396.6
1998170.795.8
1997167.795.9
1996163.393.8
1995164.492.7
1994162.790.7
1993160.489
1992155.488.5
1991169.793.4
199017294.9
1989164.493
1988161.592.1
1987162.592
1986163.890.2
1985157.890
1984159.888
1983156.886.7
1982164.288.7
1981166.591.5
1980162.290.1
1979162.790.8
1978161.189
197716189
1976160.189.1
1975155.586.8
1974160.587.9
1973160.588.6
1972158.887.7
1971156.786.8
1970155.186.1
1969155.787.5
1968155.987.1
1967153.386.7
1966156.786.4
1965154.284.9
1964150.784.7
1963148.487.1
1962157.988
1961158.789.5
1960160.389.7
195915989.6
1958157.589.1
1957159.389
1956154.588.5
1955160.388.2
1954159.788.4
1953157.888.6
1952159.187.8
1951157.689.4
1950158.688.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearBoliviaMexico
2015177.7162.4–194.8106.192.9–118.4
2016177.1155.9–190.7107.695–120
2017179.6164.6–190.9108.696.3–119.7
2018177.8162.1–196.310997.1–120.4
2019180.1164.5–199.9110.396.4–123
2020180.5162–200.6109.696.8–121.8
2021185.6169.2–197.3111.296.9–124.1
2022184.7165.7–200.5109.796–121.7
2023181.3166.6–196.7111.898.6–125.3
2024187.1168.2–202.1112.298.2–126.2
2025183.5168.8–195.711298.8–125.8
2026182.5164.8–198.1113.999.5–126.4
2027182.7165–201.6112.999.5–128.3
2028186.3169.6–200.3115.2101.9–127.9
2029192.5175.6–205.4115.6101.9–127.9
2030185.5161.7–204.2115.9101.7–128.4
2031189.2166.2–205.3116.1100.9–129.9
2032189.7173.8–209.6116.1102.5–129.1
2033188.2167.7–204.1117.5102.5–131.1
2034188172.2–207.8117.2104.1–130.3
2035186.7169.1–206.1116.4103.1–130.3
2036190.5173.5–205.2117.8105.1–131
2037195.3181.4–208.5118.6104.3–131.7
2038189.2174.7–207.8121107.5–133.4
2039192.7175.7–205.5121.3107–135.6
2040192.3176.8–204.2121.9108.1–135.1
2041193.9179–209121.3105.3–134.6
2042191.3171.9–207.6122.7107.7–137.1
2043191.2174.4–209.9122.4108.1–137.5
2044194.5179.1–209.4121.9108–135.6
2045194.4180.2–209123.1108.8–139.2
2046194.8181.4–213123.8109.9–139.4
2047196.5181.4–213.3125.6111.9–139.4
2048200.2184.6–212.8126.3113–140.3
2049199.8181.3–214.4127111.2–140.8
2050196.3173.9–210.9128.1112.6–142.5
2051198.5184.2–213.3127.2113.4–140.8
2052200.6185.7–214.8126.2112.5–141.1
2053198182.1–211128.4111.5–142.7
2054195.9179.8–211128.1113.1–142.3
2055201.2187.1–215129114.4–144.7
2056201.3181.5–216.1129.5114.3–143.8
2057200.6184.3–214.4130.3113.5–145.9
2058200.8182.8–216.5128.8114.1–144.5
2059203.2186.1–215.8129.5114.5–144.5
2060203.4186.2–219.7131.4115.5–146.5
2061197.9184–216.3131.3118.4–146.8
2062201.4186.2–219.1130.8115.1–146.3
2063201.5184.9–217131.2115.6–147.9
2064200.5184.6–216.1132.2116.5–147.8
2065204.9187.3–218.4133.1115.8–148.6
2066203.3186.8–218.1133.3117.2–149.4
2067203.6187.7–215.6133.3117–150.3
2068204.4188–218134.6117.4–150.5
2069203.8184.5–219134.4117.8–150.9
2070205.1188.3–221.4134.2116.7–151.8
2071203186.9–214.6136.3120.8–152.7
2072206186.6–221.5137.2119.9–153.1
2073206.5193.2–220.7136.1119.1–153.6
2074204.5184.1–219.5136119.7–152.2
2075203.8185.8–217.9135.2118.5–151.8
2076206.5190.1–220.4136.3117.4–154.7
2077209.1185.4–221.4136.8119.6–152.8
2078208.1192.7–222.9137.1118.3–154.2
2079204.7186.2–218.6138.1121.3–157.1
2080208.7192.4–221.1137.6120.5–157.9
2081208.1190.7–221.1137.8120.7–154.7
2082208.2189.7–220.1138.7121.6–155.2
2083209.3192.8–222.6139.2119.3–158.8
2084208.2193.3–223.1140.3123.4–157.5
2085210.4194–225139.2120.9–157.2
2086210.4189.7–225.4139.8121–157.8
2087207.9193.8–222139.5121.5–157.4
2088210.3193.4–225.2141121.8–159.9
2089208.2191.3–222.9140.4121.7–158.9
2090209.7195.5–225.2141.2123–160.7
2091209.7192.5–227.1141.8123–161.6
2092209.8192.1–223.9141.3122.5–159.3
2093209.4195.7–222.1141.4124.3–161
2094208.9194.6–222.7142123.3–159.6
2095210.3191.2–225.3143.5124–160.7
2096211.6193.9–225142.3125–161.3
2097208.6189.8–220.3141.2123.2–160
2098211.7196.2–226.5142.2122.5–162
2099211.2195.3–224141.8122.4–160.7
2100210.8195.8–226.8142.8124.3–160.8

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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