Italy vs Tanzania

Italy vs Tanzania: Tropical nights

Tropical nights in 2014: 26.3 nights in Italy and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 80 nights, or 4.04 times that in Italy.

nights a year · CMIP6

Italy vs Tanzania: Tropical nightsTropical nights in 2014: 26.3 nights in Italy and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 80 nights, or 4.04 times that in Italy.
ItalyTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Tanzania has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Italy at 65.1 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearItalyTanzania
201426.3106.3
201324.7105.5
201224.8108.4
201124.6109
201027.1103.9
200923.7101.1
200824.1100.3
200721.599.5
200624.6100.4
200522.598.7
200424.5100.4
200323.899.6
200220.698.4
200120.8101.5
200021.794.9
199920.394.2
199818.996.8
199718.993.5
199618.989.6
199517.988.5
199417.485.4
199316.381.2
199215.180.1
19911889.6
199018.291.1
198916.689.1
198815.587.6
19871688.5
19861589.4
198514.583
198415.783.1
198315.382.1
198214.184.8
198115.388
198015.985
197914.585.5
197816.582.9
197713.584.1
197613.881
19751480.8
197414.882.2
197313.583.6
197213.781.4
197115.380.7
19701481.8
196914.579.5
196813.879.1
196713.677.5
196613.278.1
196512.878
196413.273.8
196314.273.1
196215.581.1
196113.982.6
196014.983.9
195916.681.4
195814.482.1
195715.580.9
195616.780
195516.681.6
195415.781.4
195315.480.6
195216.681.4
19511682.1
195015.380.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearItalyTanzania
20153021.7–40.4114.895.2–137.4
201629.618–42.2108.391.6–125.6
201731.820.2–43.7114.893.6–137.8
20183122–44.3116.497.4–137.1
201931.521.3–43.2113.495.2–133.2
202031.619.7–44.3119.396.2–143.5
20213420.8–46.9119.5100.9–147.1
202237.121.3–50.6124.4105.3–147.4
202333.121.3–47.4122.1102.1–147.8
202435.521.6–48.4126.2100–150.1
202537.720.5–51.1124.6100.9–154
202638.926.6–52.2126.999.1–155.6
202734.322.4–49.7128102.9–147.7
202837.724.4–53.1129.9106.4–152.1
202937.824.9–55134.1111–156.5
203037.925.7–54.7129.4106.4–151.1
203137.223.8–51136.4115.9–158.4
203239.226.2–53.8135.1114–166.8
203340.426–50.3135.2110.9–161.9
203442.525.1–57.2134.7112.5–166.3
203542.728.9–58.3140.2114.6–165
203641.127.7–59.9137.8113.3–165.5
20374328.1–54.8142.9121.5–168.9
203841.628.5–61.3147.9124.3–169.3
20394129.4–56.4144.3117.6–171.3
204042.428.1–59.1140.5117–178
204141.927.2–58.7149.1121.7–175.6
204243.529.6–59146.3120.5–185.3
20434528.7–59.5144.6117–173
204444.929.4–59.9147.7121.2–175.8
204545.230.3–59.2150.1125.2–183.4
20464627.3–62.4161.5128.6–192.2
204749.132.4–63.6160.2129.7–194.4
204846.228.3–65.7158.8132.7–193.1
204948.229.5–65.7157.6131.1–196
205049.536.4–64.4159.7127.8–192
205148.831.6–68.3163.2135.5–197.8
205250.330.9–68.1161.9136.2–199.1
205348.235.9–67160.6127.5–197.7
205449.435.3–66.1163.2131.5–200.2
205552.233.7–67.7167.4137–208.3
205650.836.2–71.6166.4130.8–209.7
205750.232.8–65.6168134.6–208.3
205855.337.5–70.8168.7134.9–210.3
205951.934.5–74.1174.7144.9–219.5
206052.938.2–68.1181.7138.1–219.8
206154.338.3–69.8171.8135.5–218.1
206253.936.9–69177.5139.9–224
206356.437.6–72.1181.4140.1–213.8
206455.938.5–71.3185.3140.1–215.2
20655537.3–73.3183.5141.1–221.8
206653.935.8–73.8181.9146.3–219.3
206761.141.2–76.6178.8138.8–229.2
206856.241.7–73186144.2–228.4
206958.741.8–73183.7141.7–225.3
207055.738.9–74.4180.7140.4–228.2
207159.637.8–76.6184.9146.9–235.2
207259.643.5–74.6191.3155–226.1
207356.939.4–71.6191.6152.4–235.6
207454.836.7–73.7183.3149.7–231.7
207556.941.8–75.4183.8144.8–233
207659.941.9–77.7191.1150.9–233.2
207757.437.9–74.1191.3152.6–238.2
207860.540.5–80.7189156.6–233.8
207960.637.1–83.3190.5147–237.3
208059.743.1–78197.3150.7–241.2
20815943.7–78.9195.6153.4–237.4
208263.945.5–80.2194.5157.3–237.3
208360.842–79.7193.2151–249.8
208462.547.3–82.1201.1152.2–246.7
208565.246.3–79204.2162.3–252.3
208664.445.6–80.1195156–248.7
208763.743.8–84196.7160.8–244.5
208867.247.4–84.4208.4154.7–246.9
208964.546–82.9201.3158.6–248.2
209065.842.8–80.5197.9160.7–253.6
209166.745.3–84.7210161.6–256
209264.838.5–82.3205.8158.3–253.6
209363.644.7–83207.2161.2–251.9
209462.445–82207.9161.3–250.6
20956643.6–83.5214.2166.4–258.5
20966542.9–85.8205.3159.8–257.4
209765.844.9–84.4206.6158.4–256.8
209864.647.9–84.2209.1161–258.3
209967.742.2–81.9208.5160.1–256
210065.142.5–83.2208158.6–258.6

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

Italy vs Tanzania

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment