Haiti vs Peru

Haiti vs Peru: Tropical nights

Tropical nights in 2014: 298.9 nights in Haiti and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 134.4 nights, or 1.82 times that in Peru.

nights a year · CMIP6

Haiti vs Peru: Tropical nightsTropical nights in 2014: 298.9 nights in Haiti and 164.5 nights in Peru, in the CMIP6 climate models’ median run. In 2014 the value was higher in Haiti, by 134.4 nights, or 1.82 times that in Peru.
HaitiPeruCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Haiti has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Haiti at 346.8 nights and Peru at 192.3 nights in 2100.

Every year

nights a year · CMIP6

YearHaitiPeru
2014298.9164.5
2013301.1163.1
2012301.5164.8
2011301164.3
2010298.6163.3
2009298.7162.3
2008296.4162
2007293.6159.8
2006294.2159.1
2005295.3159.3
2004298161.8
2003295.4160.5
2002295.6159.9
2001296160.7
2000291158
1999290.8155.7
1998291.4157.4
1997288156.1
1996287152.2
1995283.1152.1
1994282.6150.8
1993278.8148.5
1992277.7144
1991286.2156
1990291.1158.3
1989286.3153.2
1988282.7151.2
1987282.9152
1986281153.4
1985277.9149
1984277.7148.3
1983276.1145.4
1982280.4151.4
1981281.3153.1
1980280.2150.9
1979280.2150.5
1978277.8149.1
1977280.4150.3
1976276147.5
1975275.1142.1
1974278.1148.6
1973278.3151.5
1972276.6147.6
1971275.5145.7
1970272.2145.6
1969275.5147
1968274.5146
1967275142.3
1966277.8145.7
1965274.1143.3
1964274.8141.6
1963274.2135.9
1962278.6148.9
1961278.2146.5
1960278.2149.8
1959278.6146.1
1958281.6149.1
1957278148.7
1956277.9144
1955280.7148.3
1954277.6148.7
1953276.8148.2
1952279.7148.1
1951277.9147.2
1950276.8147.8
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearHaitiPeru
2015305.5285.9–322.7164.3148.5–174.9
2016306288.9–319.7163.4149.8–171.5
2017307.5292–322.8165.5155–175.2
2018308.8294.3–322.5165152.9–176.6
2019307.1290.7–322.4163.7151–176.8
2020307.4293.2–321.3165.3151.6–176.2
2021311.8296.6–324.5167.6154.7–177.3
2022312.1298–329.1169.5156.6–179.2
2023311.6297.9–324.7167.1156.3–178.4
2024312.3294.2–326.9170.6157.3–180.2
2025314.6291.3–328.7168.6155–179.9
2026316.3297.5–332.3167.8153.3–179.7
2027316.4293.9–332.7168.3155.2–178.8
2028316.4299.6–334.9169.8158.3–179.9
2029316.5298.3–333.6174162.8–181.7
2030314.8301.6–331.6168.1153.2–180.6
2031317.8303.5–333.7172.5156.2–183.7
2032321.4303.7–333.1173.2162.7–184.7
2033319.5302–332.4172156.5–181
2034319.5298.9–337.1171.6158.7–185.6
2035322.6304.3–335.1172159.3–184.1
2036321.3304.1–335.4172.5160.7–183.2
2037325310.6–336175.6166.3–185.3
2038322305.4–338.2175.8164.6–184.9
2039322.3305.5–339.8174.1162.7–185
2040324.1309.7–338.7175.4163.9–187
2041323.8310.9–339.7176.5165.3–186.1
2042325307.1–339.2176.3161.9–189.7
2043325.4306.3–339.9174.8163.7–185.3
2044326.8308.2–345.7175.3161.9–188.2
2045327312.5–341.6177.3165.5–186.9
2046330.7312.9–342.1180.3167.4–189.9
2047327.3313.3–343.2178.6167.5–189
2048331.4313.9–344.2181.2168.2–192.2
2049333.3314.4–344.6180.4168.1–189.8
2050331.2312.1–348178.6166.4–190.8
2051331.4314–342.3180.3168.5–190.6
2052331.5314.8–346181.5170.8–191.7
2053332.8314.2–342.8179.5168.3–190.8
2054331.7315.8–348.4180.1167.3–193.9
2055331.2317.8–348.8181.7171–194.8
2056330317.4–348.3182.2170–193
2057335.7314–347.6181.6168.7–193
2058335.3316.4–350.6183.1169.4–195.5
2059336.7319.6–349184.6169.7–195.3
2060337.6318.4–350185.6171.1–197.1
2061336.4318.8–349.6182.7169.9–195.8
2062336.1317.5–349.7184.3168.7–196.9
2063338320.8–354184.6170.8–196.9
2064336.6319.4–350.9184.4170.1–194.8
2065335.5318.9–349186.3173.3–196.9
2066338.8321.1–351.7185.6172.3–197.4
2067337.2317.8–350.8184.3169.4–198.2
2068340.4321.9–353.8186.1172.1–198.3
2069337.2320.2–351.6184.9169–198.3
2070339.5319.8–351.4185.4171.8–198.4
2071339.8320.1–353.6187.3173.3–198.7
2072342.6319.9–353.2188.1174.9–199.8
2073340.9320.2–353.6187.6175.9–202.1
2074340.9324.7–353.4186.4169.5–198.9
2075338.8321.7–353.5186.4170.6–198.3
2076344.1322–355.4188.8174.2–201
2077340.8321.6–354189.1174.7–201.8
2078340.6325.1–354.5188.4175.6–202.3
2079341.6323.7–354.4188172–199.7
2080340.3322.6–354.3189.1172.8–201.7
2081340322.6–353.4188.4173.6–201.8
2082342.4326.5–353.5188.8174.8–199.7
2083342.2326.4–352.5189.9175.7–204.7
2084345.5326.2–354.6190.7176.3–204.4
2085344325–355.4192176.2–204.6
2086344.9326.6–355.1189.1175.4–204
2087342.6322.5–354.4189.1175.9–203.6
2088342.5328.2–356.1191.1174.7–204.9
2089345.8326.6–358190.1174.3–203
2090343.2328.2–355.8190.4177–206.2
2091344.7323.1–357.7192.6174.4–205.9
2092346.5326.6–356.5192.6176.6–204.7
2093341.4324.8–356.7190.6176–206
2094341.4327.9–355.8192.3178.2–204.1
2095345.6326.2–356.1193.4176.5–207.3
2096344327.2–358.3191.4176.2–207.6
2097344.2330–356.7190.7174.9–202.2
2098343.8324.3–358.4192.9177.8–208.9
2099346.6323.1–358.1191.5176.8–205
2100346.8326.2–356.3192.3176.6–205.6

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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