Colombia vs Peru

Colombia vs Peru: Tropical nights

Tropical nights in 2014: 279.9 nights in Colombia and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Colombia, by 115.4 nights, or 1.7 times that in Peru.

nights a year · CMIP6

Colombia vs Peru: Tropical nightsTropical nights in 2014: 279.9 nights in Colombia and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Colombia, by 115.4 nights, or 1.7 times that in Peru.
ColombiaPeruCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Colombia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Colombia at 297.4 nights and Peru at 192.3 nights in 2100.

Every year

nights a year · CMIP6

YearColombiaPeru
2014279.9164.5
2013279.8163.1
2012280.7164.8
2011280164.3
2010279.1163.3
2009279.3162.3
2008278.4162
2007277.3159.8
2006277.5159.1
2005277.7159.3
2004278.2161.8
2003277.5160.5
2002277.3159.9
2001278160.7
2000276.2158
1999274.6155.7
1998275.2157.4
1997274.4156.1
1996271.2152.2
1995271.3152.1
1994270.4150.8
1993268148.5
1992264.7144
1991273.9156
1990275.6158.3
1989271.9153.2
1988270.3151.2
1987271.8152
1986271.4153.4
1985268.4149
1984268.2148.3
1983265.1145.4
1982269.2151.4
1981272.1153.1
1980270.2150.9
1979269.3150.5
1978268.3149.1
1977269.6150.3
1976266.1147.5
1975261.6142.1
1974266.6148.6
1973269.9151.5
1972266.6147.6
1971265.7145.7
1970265.4145.6
1969266147
1968264.6146
1967261.7142.3
1966263.7145.7
1965263.2143.3
1964260.3141.6
1963254.8135.9
1962266.7148.9
1961267146.5
1960268.6149.8
1959265.5146.1
1958268149.1
1957267.4148.7
1956263.3144
1955267.7148.3
1954267.2148.7
1953267.9148.2
1952268.1148.1
1951267.2147.2
1950266.5147.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearColombiaPeru
2015280.4265.9–286.4164.3148.5–174.9
2016279.9267.9–285.6163.4149.8–171.5
2017281.7270.6–286.3165.5155–175.2
2018281.5271.8–286.3165152.9–176.6
2019281.1269.5–286.9163.7151–176.8
2020282.1270.6–287.9165.3151.6–176.2
2021283.2273.9–287.8167.6154.7–177.3
2022283.7273.6–288.5169.5156.6–179.2
2023282.6274.2–288.8167.1156.3–178.4
2024284.7274.7–289.8170.6157.3–180.2
2025283.5273.3–289.7168.6155–179.9
2026283.4272.7–289.7167.8153.3–179.7
2027283.9273.4–289.2168.3155.2–178.8
2028285275.1–290.7169.8158.3–179.9
2029285.8276–290.3174162.8–181.7
2030284.2273.4–289.8168.1153.2–180.6
2031285.8274.8–291.2172.5156.2–183.7
2032286.7278.3–292.6173.2162.7–184.7
2033285.7274.7–290.3172156.5–181
2034285275.8–292.8171.6158.7–185.6
2035285.9277.3–292172159.3–184.1
2036286276.9–291.6172.5160.7–183.2
2037287.5279.3–291.9175.6166.3–185.3
2038288279.7–292.4175.8164.6–184.9
2039287.6278.8–292.7174.1162.7–185
2040287.6279.3–294.5175.4163.9–187
2041288.2279.9–292.7176.5165.3–186.1
2042288.2278.3–295176.3161.9–189.7
2043287.7277.7–293.4174.8163.7–185.3
2044287.8278.5–295.1175.3161.9–188.2
2045288.8280.5–293.9177.3165.5–186.9
2046290.4281–295.5180.3167.4–189.9
2047289.9280.6–294.6178.6167.5–189
2048290.7281.4–296.8181.2168.2–192.2
2049290.9282–295.3180.4168.1–189.8
2050290.1280.8–296178.6166.4–190.8
2051290.6280.9–295.7180.3168.5–190.6
2052290.9281.9–296.7181.5170.8–191.7
2053290.5280.8–296.3179.5168.3–190.8
2054290.8281.3–297.2180.1167.3–193.9
2055291.1282.6–298181.7171–194.8
2056291.5281.5–298.6182.2170–193
2057291.5281.2–297.3181.6168.7–193
2058291.8281.7–298.9183.1169.4–195.5
2059292.8282–299.2184.6169.7–195.3
2060293.2283–300.1185.6171.1–197.1
2061292.2281.9–298.7182.7169.9–195.8
2062292.6282.4–299.7184.3168.7–196.9
2063293.6282.3–298.6184.6170.8–196.9
2064292.7282.9–299.1184.4170.1–194.8
2065293.8283.6–299.4186.3173.3–196.9
2066293.1283.4–299.8185.6172.3–197.4
2067292.9281.8–299.6184.3169.4–198.2
2068294.2282.5–300.6186.1172.1–198.3
2069292.9282.4–300184.9169–198.3
2070292.9282.8–300.8185.4171.8–198.4
2071294.2282.8–301.5187.3173.3–198.7
2072294.9285.1–301.9188.1174.9–199.8
2073294.9285.5–302.2187.6175.9–202.1
2074293.9283.3–300.3186.4169.5–198.9
2075294.1283.2–300.6186.4170.6–198.3
2076294.9284.6–302188.8174.2–201
2077295.3284.3–301.9189.1174.7–201.8
2078294.4285–302188.4175.6–202.3
2079294.8283.7–301.8188172–199.7
2080295.1283.4–302.8189.1172.8–201.7
2081295.1284.8–302.6188.4173.6–201.8
2082295.1284.9–301.3188.8174.8–199.7
2083295.4284.5–304.6189.9175.7–204.7
2084296285.1–304.4190.7176.3–204.4
2085296.6285–305192176.2–204.6
2086295.6284.8–303.6189.1175.4–204
2087295.3284.1–303.4189.1175.9–203.6
2088295.9284.5–305.5191.1174.7–204.9
2089295.6285–304.5190.1174.3–203
2090295.7285.8–304.6190.4177–206.2
2091297285–304.9192.6174.4–205.9
2092296.8286–305.7192.6176.6–204.7
2093296.3285.6–305.3190.6176–206
2094296.4285.8–305192.3178.2–204.1
2095297.9285.6–304.9193.4176.5–207.3
2096296285.9–307.5191.4176.2–207.6
2097296.5284.8–303.4190.7174.9–202.2
2098296.6286–307.3192.9177.8–208.9
2099297284.6–305.4191.5176.8–205
2100297.4286.5–305.2192.3176.6–205.6

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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