Germany vs Kazakhstan

Germany vs Kazakhstan: Tropical nights

Tropical nights in 2014: 0.8 nights in Germany and 22.4 nights in Kazakhstan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Kazakhstan, by 21.6 nights, or 27 times that in Germany.

nights a year · CMIP6

Germany vs Kazakhstan: Tropical nightsTropical nights in 2014: 0.8 nights in Germany and 22.4 nights in Kazakhstan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Kazakhstan, by 21.6 nights, or 27 times that in Germany.
GermanyKazakhstanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Kazakhstan has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Germany at 8.8 nights and Kazakhstan at 47.9 nights in 2100.

Every year

nights a year · CMIP6

YearGermanyKazakhstan
20140.822.4
20130.721.3
20120.921.7
20110.519.6
20100.918.7
20090.520
20080.220.2
20070.319.9
20060.319.2
20050.619.4
20040.718
20030.618.9
20020.219.5
20010.518.1
20000.217.2
19990.217.4
19980.116.9
19970.118.3
19960.215.7
19950.115
1994014.7
1993012.3
1992012.3
19910.115
19900.116
19890.114.1
1988014
1987015
1986012.9
19850.114.6
19840.112.1
198309.9
1982014.1
1981014.1
1980012.7
1979013.5
19780.112
1977013.3
1976012.5
1975012.1
19740.111.9
1973011.7
1972012.3
1971012.1
19700.111.7
1969011.9
1968012.2
1967011.7
1966011.9
1965011.3
1964010.9
1963012.2
1962012.4
1961012.1
1960012.2
19590.112.5
1958013.9
1957014
1956012.9
1955012.5
19540.113.1
1953012.4
1952013.5
1951012.7
1950013.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearGermanyKazakhstan
20150.50–425.415.1–35.8
20160.80–4.322.815–34.3
20170.70–5.123.214.5–32
20180.70–3.524.314.7–35.8
20191.20–524.115.9–33.9
20201.20–5.723.115.4–32.5
202110–623.315–32.4
20221.40–5.725.216.7–34.9
20231.10–5.725.516.4–35.3
20241.20–5.225.515.5–35.1
20251.90–8.226.218.1–35.9
20261.90.1–6.525.617.5–35.3
20271.40–4.72718.5–38
20281.50.1–5.527.818.2–38.7
202920.1–6.425.516.8–38.6
20301.60–6.127.616.5–38.2
20311.40–5.430.420.5–40.9
20321.50.1–7.630.320.4–40.3
20331.70–6.829.120.2–40.7
20342.10.2–8.32817.6–39.7
20351.70.1–6.930.719.3–42.8
20362.80.1–7.830.520.6–41.5
20372.50–9.229.120.2–39.5
20382.20.1–9.731.420.5–42.6
203930–8.93020.9–42.7
20402.30.1–7.132.719.8–42.5
20412.40.1–7.932.421.8–46.2
20422.90.4–8.932.220.2–45.8
20433.10.1–8.731.922.5–42.3
20443.10.2–10.133.620.2–45
204530.1–8.732.221.7–44.6
20463.10.5–10.934.423.3–48.5
20474.30.3–10.634.621.7–48.7
20483.70.2–12.93520.9–46
20494.40.2–11.835.624.5–47.8
20503.10.6–9.337.324.5–48.4
20512.70.1–9.535.523.6–49.7
20523.60.2–11.535.522.7–47.2
20532.30.4–8.736.123–48.3
20543.50.4–10.334.822.6–49.1
20553.30.4–11.33625.6–48.9
20564.50.7–14.337.725.6–50.3
205740.4–11.339.226.6–51.3
20585.80.7–15.535.323.7–51.2
20595.10.1–15.638.426.6–54.2
20604.40.6–12.339.626.9–52.2
20615.31–12.337.926.2–51.3
20625.51.6–14.237.924.7–54.3
20635.20.8–13.839.825.5–54.5
20644.10.5–12.237.222.3–54.8
20654.90.3–15.841.928.2–55.4
20665.30.7–11.838.826.8–53
20677.21.4–17.538.325.1–54.2
20683.90.9–11.342.427.4–55.9
20696.11.6–154128.5–57
20705.80.6–14.940.328.2–55.9
20716.30.6–16.442.128.7–57.3
20726.21.9–1341.429.5–55.6
20735.51.3–16.240.926.9–59.4
20745.50.5–16.743.929–60.2
20756.21.4–18.342.929.1–58.3
20767.41.1–20.141.328–54.9
20776.31.1–17.442.429.5–58.4
20786.50.7–21.443.930.9–56.8
20796.70.6–22.743.528.7–57.6
20806.51.2–14.941.827.4–57.2
20816.60.9–18.542.629.1–56.8
20827.91.4–22.544.427.6–57.3
20837.61.3–16.844.531.7–60.4
20845.91.1–15.941.826.8–58.4
20856.50.9–17.643.828.7–61.5
20867.90.8–2343.228.3–56.5
20879.91.1–24.143.529.7–59.3
20888.92–18.443.629.7–61.9
20898.31.9–19.244.132–59.5
20906.20.8–24.145.431.4–62
20919.31.3–23.545.630.5–64
20928.61.7–19.247.228.9–62.8
20936.20.8–18.245.929.9–62.9
20949.32.4–20.445.931.4–64.4
20959.51.1–2446.431.4–63.6
20968.10.2–21.447.934.2–66.4
20976.40.5–20.148.633.7–65
20989.31.4–22.14832.2–65.5
20998.11.4–20.847.130.3–64.2
21008.81.9–21.147.933–65.8

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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