Russia vs Tanzania

Russia vs Tanzania: Tropical nights

Tropical nights in 2014: 1.4 nights in Russia and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 104.9 nights, or 78 times that in Russia.

nights a year · CMIP6

Russia vs Tanzania: Tropical nightsTropical nights in 2014: 1.4 nights in Russia and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tanzania, by 104.9 nights, or 78 times that in Russia.
RussiaTanzaniaCMIP6 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 Russia at 5.9 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearRussiaTanzania
20141.4106.3
20131.2105.5
20121.1108.4
20111.1109
20101.2103.9
20091101.1
20081.1100.3
2007199.5
20061.1100.4
20051.298.7
20041100.4
2003199.6
20020.998.4
20011101.5
20000.994.9
19990.894.2
19980.896.8
19970.993.5
19960.789.6
19950.788.5
19940.685.4
19930.581.2
19920.480.1
19910.689.6
19900.691.1
19890.689.1
19880.587.6
19870.688.5
19860.689.4
19850.683
19840.483.1
19830.382.1
19820.584.8
19810.588
19800.585
19790.585.5
19780.582.9
19770.584.1
19760.581
19750.480.8
19740.582.2
19730.583.6
19720.481.4
19710.580.7
19700.481.8
19690.479.5
19680.679.1
19670.577.5
19660.478.1
19650.578
19640.473.8
19630.573.1
19620.481.1
19610.582.6
19600.583.9
19590.581.4
19580.582.1
19570.580.9
19560.580
19550.581.6
19540.581.4
19530.680.6
19520.581.4
19510.582.1
19500.580.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearRussiaTanzania
20151.60.6–3.9114.895.2–137.4
20161.30.6–3.5108.391.6–125.6
20171.40.5–3.6114.893.6–137.8
20181.70.6–4.1116.497.4–137.1
20191.50.7–3.9113.495.2–133.2
20201.50.7–3.6119.396.2–143.5
20211.40.6–3.6119.5100.9–147.1
20221.80.6–4.4124.4105.3–147.4
20231.80.6–4.5122.1102.1–147.8
20241.70.7–4.1126.2100–150.1
202520.7–5.2124.6100.9–154
20261.70.7–4.4126.999.1–155.6
20271.90.8–4.7128102.9–147.7
20281.70.8–4.4129.9106.4–152.1
202920.9–5.3134.1111–156.5
20301.80.6–4.8129.4106.4–151.1
20312.11–5.1136.4115.9–158.4
20322.20.9–5.8135.1114–166.8
20332.11.1–5.4135.2110.9–161.9
20341.90.8–4.9134.7112.5–166.3
20352.21–5.8140.2114.6–165
20362.41.1–5.9137.8113.3–165.5
20372.31–6.1142.9121.5–168.9
20382.51.1–5.8147.9124.3–169.3
20392.71.2–6.8144.3117.6–171.3
20402.50.9–5.8140.5117–178
20412.61.1–6.6149.1121.7–175.6
20422.61–6.8146.3120.5–185.3
20432.81.4–7144.6117–173
20442.81–7.5147.7121.2–175.8
20452.61.1–7.1150.1125.2–183.4
20462.81.1–7.5161.5128.6–192.2
20472.91.1–8.3160.2129.7–194.4
20483.41.1–7.9158.8132.7–193.1
20493.21.4–8157.6131.1–196
20503.51.3–8.2159.7127.8–192
20513.41.3–8.9163.2135.5–197.8
205231.2–8.1161.9136.2–199.1
20533.11.3–7.5160.6127.5–197.7
20543.21.1–7.7163.2131.5–200.2
20553.31.2–9167.4137–208.3
20563.51.3–8.8166.4130.8–209.7
20573.71.5–9.1168134.6–208.3
20583.61.5–10.2168.7134.9–210.3
20593.81.5–9.3174.7144.9–219.5
20603.41.4–8.9181.7138.1–219.8
20613.91.5–9.3171.8135.5–218.1
20623.71.4–10.1177.5139.9–224
20634.11.4–10.3181.4140.1–213.8
20643.61.2–10.1185.3140.1–215.2
20654.21.4–10.4183.5141.1–221.8
206641.4–10.5181.9146.3–219.3
20673.91.3–9.9178.8138.8–229.2
20684.21.4–10.3186144.2–228.4
20694.61.7–11.6183.7141.7–225.3
20703.81.3–11.8180.7140.4–228.2
207141.4–11.5184.9146.9–235.2
20724.51.8–10.9191.3155–226.1
20734.61.5–11.7191.6152.4–235.6
20744.41.7–11.7183.3149.7–231.7
20754.31.6–11.3183.8144.8–233
20764.91.8–12191.1150.9–233.2
20774.81.9–10.9191.3152.6–238.2
20784.92.1–12189156.6–233.8
20795.42–12.7190.5147–237.3
20804.91.8–12.5197.3150.7–241.2
20815.12.1–12.5195.6153.4–237.4
208251.9–13.9194.5157.3–237.3
20835.42.2–13.2193.2151–249.8
20845.42–12.2201.1152.2–246.7
20855.21.7–13.3204.2162.3–252.3
20865.31.8–14.1195156–248.7
20875.31.9–13.6196.7160.8–244.5
20885.51.9–13.6208.4154.7–246.9
20895.22.2–12.5201.3158.6–248.2
20905.42–12197.9160.7–253.6
20915.91.9–15.4210161.6–256
20925.92–13.2205.8158.3–253.6
20935.61.8–14207.2161.2–251.9
20946.12.2–15.1207.9161.3–250.6
20955.62.1–14.7214.2166.4–258.5
20966.22.2–14.9205.3159.8–257.4
20976.21.9–14.7206.6158.4–256.8
20986.12.1–14.3209.1161–258.3
20995.61.8–14.7208.5160.1–256
21005.92.2–14.8208158.6–258.6

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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