Guatemala vs Peru

Guatemala vs Peru: Tropical nights

Tropical nights in 2014: 171.5 nights in Guatemala and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Guatemala, by 7 nights, or 1.04 times that in Peru.

Watch it change on the map

nights a year · CMIP6

Guatemala vs Peru: Tropical nightsTropical nights in 2014: 171.5 nights in Guatemala and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Guatemala, by 7 nights, or 1.04 times that in Peru.
GuatemalaPeruCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Guatemala has been higher since 1987, when it overtook Peru.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Guatemala at 230.9 nights and Peru at 192.3 nights in 2100.

Every year

nights a year · CMIP6

YearGuatemalaPeru
2014171.5164.5
2013175.4163.1
2012171.8164.8
2011173.8164.3
2010171.4163.3
2009169.7162.3
2008167.8162
2007167.6159.8
2006167.2159.1
2005169.2159.3
2004167.4161.8
2003165.8160.5
2002165.7159.9
2001165.3160.7
2000163.6158
1999162155.7
1998162.1157.4
1997160.7156.1
1996157.9152.2
1995153.5152.1
1994155150.8
1993153.5148.5
1992151.7144
1991158.2156
1990161.9158.3
1989157.5153.2
1988154.2151.2
1987154.7152
1986153.1153.4
1985150.7149
1984150.3148.3
1983148.1145.4
1982151.3151.4
1981156.7153.1
1980152.3150.9
1979153150.5
1978149.5149.1
1977150.6150.3
1976151.6147.5
1975147.4142.1
1974150.2148.6
1973149.6151.5
1972148.2147.6
1971145.5145.7
1970145.4145.6
1969146.8147
1968146.7146
1967142.7142.3
1966145.9145.7
1965143.3143.3
1964143141.6
1963144.6135.9
1962149.5148.9
1961149.8146.5
1960151.4149.8
1959147.4146.1
1958150.5149.1
1957151.1148.7
1956148.2144
1955152.5148.3
1954150.4148.7
1953149.3148.2
1952150.3148.1
1951151.8147.2
1950148.6147.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearGuatemalaPeru
2015177158.4–194.6164.3148.5–174.9
2016178.5161.5–195.5163.4149.8–171.5
2017182.8166.6–194.9165.5155–175.2
2018180.2165–196.4165152.9–176.6
2019181.7159.3–199.5163.7151–176.8
2020184.1161.8–198.6165.3151.6–176.2
2021184.4168.1–201.1167.6154.7–177.3
2022184.6165.7–198.4169.5156.6–179.2
2023186.3171.1–207167.1156.3–178.4
2024187.1169.9–207.3170.6157.3–180.2
2025187.4169.7–205.6168.6155–179.9
2026190.9167.9–211167.8153.3–179.7
2027188.4171.9–210.9168.3155.2–178.8
2028191.3175.8–208.5169.8158.3–179.9
2029192.7175.6–208.8174162.8–181.7
2030191173.3–207.9168.1153.2–180.6
2031193.6175.3–211.4172.5156.2–183.7
2032196.4178.7–214.8173.2162.7–184.7
2033193.3174.6–208.5172156.5–181
2034193.5176.2–214.4171.6158.7–185.6
2035193.4177.7–212.8172159.3–184.1
2036194.4180.5–212.8172.5160.7–183.2
2037199.1180–216.2175.6166.3–185.3
2038202.6184.8–216.7175.8164.6–184.9
2039199181.6–217.6174.1162.7–185
2040200.3182.9–217.9175.4163.9–187
2041200.7182.1–218.2176.5165.3–186.1
2042201.6180.3–222.1176.3161.9–189.7
2043201.7182.3–226.4174.8163.7–185.3
2044200.8184.9–222.3175.3161.9–188.2
2045203.6188.7–225.1177.3165.5–186.9
2046204.5183.3–227.5180.3167.4–189.9
2047207.5190.3–227.5178.6167.5–189
2048208.2188.9–229.4181.2168.2–192.2
2049210.1188.7–227.4180.4168.1–189.8
2050211.4188–230.7178.6166.4–190.8
2051208.1192.7–229.2180.3168.5–190.6
2052207.7193–227.9181.5170.8–191.7
2053209.8186.4–233.2179.5168.3–190.8
2054209.5194.7–233.2180.1167.3–193.9
2055212.4196.2–231.9181.7171–194.8
2056210.9193.3–233.1182.2170–193
2057213.3193.7–232.4181.6168.7–193
2058211.7192.3–238.1183.1169.4–195.5
2059214.5190.4–237.4184.6169.7–195.3
2060217.4196.4–237.3185.6171.1–197.1
2061213.9193.7–237.1182.7169.9–195.8
2062216.3194–237.3184.3168.7–196.9
2063217.2197–240.8184.6170.8–196.9
2064214.5196.1–236.1184.4170.1–194.8
2065217.3195.2–238.2186.3173.3–196.9
2066217.9195.2–240185.6172.3–197.4
2067216.4194.1–241.1184.3169.4–198.2
2068221200.2–243.4186.1172.1–198.3
2069219.9200.5–241.9184.9169–198.3
2070219.6199.9–242.6185.4171.8–198.4
2071222.5203.4–243187.3173.3–198.7
2072225.6200.4–247.6188.1174.9–199.8
2073224.4199.9–248.3187.6175.9–202.1
2074222.5202.2–245.9186.4169.5–198.9
2075220.2198.7–242.6186.4170.6–198.3
2076222.9195.4–247.7188.8174.2–201
2077225.2198.3–245.9189.1174.7–201.8
2078225.4197.8–245.9188.4175.6–202.3
2079223.4199.3–248.2188172–199.7
2080223.4201–250.7189.1172.8–201.7
2081224202.5–246.6188.4173.6–201.8
2082224.8201.3–245.9188.8174.8–199.7
2083225202.3–250.5189.9175.7–204.7
2084227.9204.9–249.9190.7176.3–204.4
2085227.7199.2–251.3192176.2–204.6
2086224.9202.3–249.6189.1175.4–204
2087227.1197.8–249.7189.1175.9–203.6
2088230.6207.4–255.5191.1174.7–204.9
2089229.7207.4–251.4190.1174.3–203
2090228.2210–253.4190.4177–206.2
2091231.4206.6–255.4192.6174.4–205.9
2092230.1207.4–253.4192.6176.6–204.7
2093226.7206–255.5190.6176–206
2094227.3204.4–251.7192.3178.2–204.1
2095231.1207.7–255.5193.4176.5–207.3
2096229.9206.3–255.5191.4176.2–207.6
2097226.7208.6–249.5190.7174.9–202.2
2098231.1202.9–259.1192.9177.8–208.9
2099230.2203.1–256.5191.5176.8–205
2100230.9208.9–255.1192.3176.6–205.6

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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