Ecuador vs Peru

Ecuador vs Peru: Tropical nights

Tropical nights in 2014: 192 nights in Ecuador and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ecuador, by 27.5 nights, or 1.17 times that in Peru.

nights a year · CMIP6

Ecuador vs Peru: Tropical nightsTropical nights in 2014: 192 nights in Ecuador and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Ecuador, by 27.5 nights, or 1.17 times that in Peru.
EcuadorPeruCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Ecuador has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Ecuador at 223.3 nights and Peru at 192.3 nights in 2100.

Every year

nights a year · CMIP6

YearEcuadorPeru
2014192164.5
2013192.7163.1
2012195.6164.8
2011193.5164.3
2010191.9163.3
2009190.7162.3
2008190.2162
2007188.3159.8
2006186159.1
2005187.4159.3
2004190161.8
2003188.3160.5
2002187.2159.9
2001189160.7
2000185.3158
1999181.4155.7
1998182.7157.4
1997182.4156.1
1996176.2152.2
1995174.9152.1
1994175.8150.8
1993170.8148.5
1992166.2144
1991179.8156
1990184.5158.3
1989178.8153.2
1988173.9151.2
1987177.8152
1986177.2153.4
1985172149
1984172.1148.3
1983166.8145.4
1982170.8151.4
1981177.4153.1
1980173.2150.9
1979172.1150.5
1978172.3149.1
1977172150.3
1976170147.5
1975163.9142.1
1974169.4148.6
1973173.3151.5
1972169.5147.6
1971167.5145.7
1970169.8145.6
1969167.4147
1968168.5146
1967159.5142.3
1966162.2145.7
1965163.3143.3
1964161.2141.6
1963151.1135.9
1962168.6148.9
1961169.5146.5
1960172.4149.8
1959167.3146.1
1958170.7149.1
1957171.4148.7
1956164144
1955169148.3
1954169.5148.7
1953169.6148.2
1952170.3148.1
1951171.7147.2
1950169.5147.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearEcuadorPeru
2015193.3172.3–205.7164.3148.5–174.9
2016192.7172.2–203.6163.4149.8–171.5
2017195.3178.7–206.8165.5155–175.2
2018194.8178–206.5165152.9–176.6
2019193.3173.9–207.6163.7151–176.8
2020196.2179.1–208165.3151.6–176.2
2021198.7183.8–209167.6154.7–177.3
2022200.5181.4–209.9169.5156.6–179.2
2023198.3180.6–210.1167.1156.3–178.4
2024201.5181.4–210.7170.6157.3–180.2
2025199.9180–212168.6155–179.9
2026200.2180.5–211.7167.8153.3–179.7
2027199.8181.7–210.8168.3155.2–178.8
2028203.4187–212.4169.8158.3–179.9
2029204.6189.9–213174162.8–181.7
2030200.4183–212.8168.1153.2–180.6
2031204.9187.3–214.1172.5156.2–183.7
2032205.8191.8–216.5173.2162.7–184.7
2033203.3184.3–213.1172156.5–181
2034203.3189.6–218.3171.6158.7–185.6
2035204.3187.8–214.4172159.3–184.1
2036204.8189.9–214.6172.5160.7–183.2
2037207.9195.6–216.5175.6166.3–185.3
2038208.5195.8–216.1175.8164.6–184.9
2039206.5190.8–217.1174.1162.7–185
2040208.7193.7–219.1175.4163.9–187
2041208.8194.8–218.1176.5165.3–186.1
2042208.6192.5–219.7176.3161.9–189.7
2043207.2192.5–217.3174.8163.7–185.3
2044207190.4–220.2175.3161.9–188.2
2045209.7196–219177.3165.5–186.9
2046213.1196.1–221.1180.3167.4–189.9
2047211.9198.3–219.3178.6167.5–189
2048214.1200.7–222.9181.2168.2–192.2
2049212.8200–221180.4168.1–189.8
2050211.6197.6–222.2178.6166.4–190.8
2051213.8197.8–221.4180.3168.5–190.6
2052213.3202.2–222.7181.5170.8–191.7
2053212.5198.8–221.7179.5168.3–190.8
2054213.5201–224.3180.1167.3–193.9
2055213.9203–224.9181.7171–194.8
2056215.6199.8–223.9182.2170–193
2057214.5198.6–224181.6168.7–193
2058215.1199.9–225.9183.1169.4–195.5
2059217.2200.1–225.2184.6169.7–195.3
2060217.1204.7–226.8185.6171.1–197.1
2061215.6201.9–225.8182.7169.9–195.8
2062216.8201.4–226.9184.3168.7–196.9
2063217202.6–226.3184.6170.8–196.9
2064216.7203–225184.4170.1–194.8
2065217.7204.7–227186.3173.3–196.9
2066217.2205.6–227.3185.6172.3–197.4
2067217.4201.5–226.7184.3169.4–198.2
2068218.9203.9–228.3186.1172.1–198.3
2069216.8201.7–228184.9169–198.3
2070216.8204.3–228.3185.4171.8–198.4
2071219.5205.5–228.7187.3173.3–198.7
2072220208.3–229188.1174.9–199.8
2073219.5208.1–230.7187.6175.9–202.1
2074218.4202.8–228186.4169.5–198.9
2075218.8203.6–227.8186.4170.6–198.3
2076220.7207.7–229.9188.8174.2–201
2077220.7206.9–230.5189.1174.7–201.8
2078220207.5–231188.4175.6–202.3
2079220.4205.4–229.2188172–199.7
2080220.2204.8–230.7189.1172.8–201.7
2081220.2205.5–230.9188.4173.6–201.8
2082220.1207.8–229.2188.8174.8–199.7
2083221.5208.5–232.9189.9175.7–204.7
2084222.3207.1–232.6190.7176.3–204.4
2085222.4208.4–234.3192176.2–204.6
2086219.9207.1–232.4189.1175.4–204
2087220.9206.1–231.9189.1175.9–203.6
2088221.7206.1–234.8191.1174.7–204.9
2089221.3206.9–232.8190.1174.3–203
2090221.6208.8–234.3190.4177–206.2
2091223.8207.5–233.5192.6174.4–205.9
2092222.7209.7–234.9192.6176.6–204.7
2093221.7208.7–235.5190.6176–206
2094223209.9–234.4192.3178.2–204.1
2095223.9209.9–235.4193.4176.5–207.3
2096221.9209.7–237.3191.4176.2–207.6
2097221.6208.4–232.3190.7174.9–202.2
2098222.1210.2–238.2192.9177.8–208.9
2099222.2207.1–234.4191.5176.8–205
2100223.3209.1–235.3192.3176.6–205.6

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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