Niger vs Tanzania

Niger vs Tanzania: Tropical nights

Tropical nights in 2014: 221.6 nights in Niger and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Niger, by 115.3 nights, or 2.08 times that in Tanzania.

Watch it change on the map

nights a year · CMIP6

Niger vs Tanzania: Tropical nightsTropical nights in 2014: 221.6 nights in Niger and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Niger, by 115.3 nights, or 2.08 times that in Tanzania.
NigerTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Niger has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Niger at 251.1 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearNigerTanzania
2014221.6106.3
2013216.1105.5
2012220.8108.4
2011220.1109
2010219.1103.9
2009217.2101.1
2008216.8100.3
2007216.999.5
2006214.3100.4
2005213.698.7
2004213.6100.4
2003215.599.6
2002214.698.4
2001213.4101.5
2000211.294.9
1999210.494.2
1998207.796.8
1997211.593.5
1996208.689.6
1995208.388.5
1994207.885.4
1993202.681.2
1992203.480.1
1991209.489.6
1990208.191.1
198920689.1
198820387.6
1987204.988.5
1986206.889.4
1985203.983
1984201.883.1
1983200.582.1
1982201.984.8
1981204.388
1980200.685
1979200.585.5
197820282.9
1977203.884.1
1976201.781
197519980.8
1974200.682.2
1973202.683.6
1972200.781.4
1971200.880.7
1970199.881.8
1969196.179.5
1968200.379.1
1967196.677.5
1966198.278.1
196519978
1964199.273.8
1963196.773.1
1962201.181.1
1961198.282.6
1960203.283.9
1959201.681.4
1958199.282.1
1957201.180.9
1956199.680
1955199.781.6
1954201.181.4
1953196.580.6
1952197.981.4
1951199.882.1
1950200.880.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearNigerTanzania
2015218.8202.8–235.8114.895.2–137.4
2016217.7201.8–230.6108.391.6–125.6
2017222.4205.2–237.4114.893.6–137.8
2018220.5206.3–238.8116.497.4–137.1
2019219.1201.8–238.1113.495.2–133.2
2020220.9206.9–234.7119.396.2–143.5
2021222.8208.2–240.2119.5100.9–147.1
2022226.3209.7–239.2124.4105.3–147.4
2023223.2206.6–238.4122.1102.1–147.8
2024228.4214.3–242.9126.2100–150.1
2025226.7211.2–241124.6100.9–154
2026226.3210–243.1126.999.1–155.6
2027228.5209.9–241.1128102.9–147.7
2028227.1211.9–240.2129.9106.4–152.1
2029230.4213.3–247.1134.1111–156.5
2030226.4211.6–242.2129.4106.4–151.1
2031230.1210.8–247.1136.4115.9–158.4
2032228.7212.3–241135.1114–166.8
2033229.9214.9–245.4135.2110.9–161.9
2034229.5212.1–244.9134.7112.5–166.3
2035232.3217.5–248140.2114.6–165
2036230.2213.7–244.6137.8113.3–165.5
2037233.2215.1–246.5142.9121.5–168.9
2038234.3218.2–249.7147.9124.3–169.3
2039231214.2–247.1144.3117.6–171.3
2040230.8214.8–247.5140.5117–178
2041232.6218.6–252.9149.1121.7–175.6
2042233.8216.2–250.5146.3120.5–185.3
2043232.5217.8–245.8144.6117–173
2044233.8218.2–250.1147.7121.2–175.8
2045233.6218.1–249.7150.1125.2–183.4
2046234.3217–250.2161.5128.6–192.2
2047238.4224.3–253.1160.2129.7–194.4
2048238221.4–254158.8132.7–193.1
2049237.7217.4–253157.6131.1–196
2050238.2220.7–254.5159.7127.8–192
2051236.3220.6–254.7163.2135.5–197.8
2052239.5224.3–255.8161.9136.2–199.1
2053236.3223.9–255.6160.6127.5–197.7
2054239.4220.2–257.9163.2131.5–200.2
2055238.6223.7–254.7167.4137–208.3
2056239214.7–260.3166.4130.8–209.7
2057240.4223–256.3168134.6–208.3
2058238.2220.2–255.7168.7134.9–210.3
2059243.9224.6–262.7174.7144.9–219.5
2060239.8222.6–260181.7138.1–219.8
2061242.5224.9–258.5171.8135.5–218.1
2062241.6222.4–259.8177.5139.9–224
2063241.3220.9–255.2181.4140.1–213.8
2064244.4225.9–259.5185.3140.1–215.2
2065242.8226.5–262.4183.5141.1–221.8
2066245.6227–263.5181.9146.3–219.3
2067240.7224.9–262178.8138.8–229.2
2068244224.3–265.4186144.2–228.4
2069243.9225.5–261.6183.7141.7–225.3
2070243.1225.6–261.3180.7140.4–228.2
2071246.1230.3–264184.9146.9–235.2
2072247.9229.9–263.7191.3155–226.1
2073243.4225.4–262.8191.6152.4–235.6
2074243.2224.4–264.6183.3149.7–231.7
2075244.3230.2–263.3183.8144.8–233
2076246.5228.5–266.6191.1150.9–233.2
2077250.1232.3–267.4191.3152.6–238.2
2078249.2230.8–264.5189156.6–233.8
2079244.4228.7–263.8190.5147–237.3
2080248.8230.4–267197.3150.7–241.2
2081247227.8–268.1195.6153.4–237.4
2082247230.6–264.4194.5157.3–237.3
2083247.3230.7–267.5193.2151–249.8
2084247.7229.4–265.2201.1152.2–246.7
2085248.9227–264.2204.2162.3–252.3
2086250.4230.9–269.5195156–248.7
2087245.8226.2–266.9196.7160.8–244.5
2088248.3226.7–271.1208.4154.7–246.9
2089251.9232.5–269.5201.3158.6–248.2
2090249.7227.7–267.4197.9160.7–253.6
2091248.9230.5–272.2210161.6–256
2092251229.8–274205.8158.3–253.6
2093249.9234.8–267207.2161.2–251.9
2094252.2234–267.5207.9161.3–250.6
2095251.1233–270.7214.2166.4–258.5
2096250.8234.8–270.4205.3159.8–257.4
2097250.2227.8–270.8206.6158.4–256.8
2098250.1228.1–268.5209.1161–258.3
2099251.9232.2–268.2208.5160.1–256
2100251.1234.5–271.5208158.6–258.6

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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