India vs Israel

India vs Israel: Tropical nights

Tropical nights in 2014: 215.5 nights in India and 97.9 nights in Israel, in the CMIP6 climate models’ median run. In 2014 the value was higher in India, by 117.6 nights, or 2.2 times that in Israel.

Watch it change on the map

nights a year · CMIP6

India vs Israel: Tropical nightsTropical nights in 2014: 215.5 nights in India and 97.9 nights in Israel, in the CMIP6 climate models’ median run. In 2014 the value was higher in India, by 117.6 nights, or 2.2 times that in Israel.
IndiaIsraelCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • India has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts India at 250.4 nights and Israel at 149.4 nights in 2100.

Every year

nights a year · CMIP6

YearIndiaIsrael
2014215.597.9
201321698
2012217.496.3
2011215.596.1
2010215.295.5
2009213.792.5
2008213.794.1
2007213.392.7
2006212.592
2005212.992.3
2004214.990.7
2003212.193.9
200221389.5
2001212.291
2000210.889.5
1999211.986.2
1998210.384.8
1997209.584.2
199620783.7
1995208.879.3
1994207.180.1
199320671.6
1992203.574.9
199120878.4
1990209.980.2
198920876.9
1988207.376.5
1987207.275.1
1986207.278.3
1985205.974
1984206.769.4
1983203.368.9
1982205.773.5
1981208.473.5
1980205.375.3
1979205.568.7
1978204.171.6
1977205.972.3
1976204.673.2
1975202.670.9
1974205.372.5
1973205.671.9
1972203.869.9
1971203.673.1
1970202.671.6
1969203.670.6
1968201.769.6
1967201.666.9
1966203.968.8
1965202.463.5
1964201.266.1
1963201.870.9
1962203.873
1961206.371.5
196020674.9
1959206.175
195820473
1957206.574.8
195620474.3
1955203.272.8
195420671.4
195320473.7
1952204.472
1951204.375.1
1950206.369.5
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIndiaIsrael
2015216.9202.1–228.4105.988.4–122.7
2016215202.5–227.6104.186.9–120.1
2017216.2202.1–228.5107.892.2–121.4
2018218.3204.5–231.410993.8–124.2
2019217.4202.3–230.410989.1–124.5
2020217.6203.1–232111.594.8–123.5
2021219.7204.5–233.211097.7–128.4
2022220.5205.8–233111.493.6–130.2
2023220.4206.4–233.7117.297.9–130.5
2024222.6208.1–236.3114.5100.4–127.3
2025219.7202.7–236.2116.698.3–129.2
2026220.2204.2–236.8115.9104.9–126.2
2027223.6207.1–239115.699–127.1
2028222.1205.1–235.7116.3100.2–127.9
2029225.4210–240.3117103.1–129.2
2030222.7207.3–235.6118.6102.1–131.2
2031223.8207.1–237.8116.8104.4–132.8
2032225.9210–240.5121.4106.5–134.7
2033223.8209.3–235.4122.1108.9–134.7
2034225.8210–242.7119.7103.1–133.4
2035224.9210.6–240.9122.8105.8–138.8
2036224.2210.4–240.3120.2105.5–136.2
2037228.3213.6–242.6121.6106.3–139.4
2038228.1212.6–241.4126.5105.7–142.1
2039227.4211.9–242.8127.7110.5–147.1
2040227212.2–242124.2109.7–144.9
2041227.1210.7–240.5126108.4–141.5
2042229.1214.8–244.2128.5105.8–144.3
2043228.9214.5–244126.5111.8–144.3
2044229.7214.7–244.2125.9108.5–142.9
2045231.2216.6–246.1130.9117.5–148.6
2046232.6216.2–248.6131114.4–147.2
2047232.4215.5–250132.3116.1–145.4
2048235.6218.5–254.3129.9118.5–146.9
2049235.3218.3–249.9127.9108.7–143.9
2050233.5216.6–253.4133.3114.3–147
2051234.9218.6–249.9130.3116.7–143.9
2052234219.4–249.3130.3119.9–143.5
2053234.9219.5–252.5135120.4–149.7
2054237.2219.4–253.1134.1118.8–149.3
2055237.2220.7–256.6134.1115.2–150.3
2056238.8221.2–254.9136110.1–151.1
2057235.7218.5–253.8132.7110.9–155
2058238.8222.8–254.1135.7119.1–155.4
2059241.1224.9–256.2138.8118.5–156.7
2060240.9225.6–255.6136.1116.3–159.2
2061237.9220.6–253.7136119–150.7
2062239.9221.2–259.7139118.7–156
2063239.9222.3–256.1137.4120.1–151.2
2064240223.8–256.3139.3121–154.3
2065240.9222.9–257.3139.6122.3–154.3
2066241.5224.1–258.6137.3119.6–153.7
2067241.6224.8–257.9142.8126–157.8
2068242.3224.6–262.1141.2122.8–156.4
2069242.8225.4–259.1141.5123.7–157.6
2070240.1225.3–257.1141.8120.5–157.5
2071241.8223.7–260.2142.9124.3–161.8
2072242.6225.4–259.2144.3127–158.5
2073243.8228–259.3143.6127.3–159.2
2074241.6226.9–258.4138.8123–162.2
2075243.5226.4–258.2138.1120.8–154.6
2076243.2224.6–259.9143.2126.8–161.5
2077243.7226.6–264.6142.8120.5–161.6
2078246.7230.1–261.5143.6128.2–160.6
2079244.9226.4–261.3148.6123.7–160.2
2080246.7227–263.7145.5123.5–163.7
2081247.5230.4–264.8143.7128.1–161.2
2082244.6227.9–262.3145.8129.5–160.6
2083247.5227.8–265.1149.4126–163.1
2084247.3228.3–266.8148128.2–164
2085246.5227.5–267.1149127.9–162.4
2086245.6227.7–266.5148127.4–167.1
2087245.5226.7–266.2146.4123.7–165.7
2088247229.4–266.9147.6133.5–165.3
2089248.1230–266.3148.4131.4–169.1
2090249228.9–266.4147.6132.4–168.8
2091248.9230–266.5151.9131.7–170.6
2092249.8232.3–267.8148.2132–167.4
2093248.1229–266.5154.1135.3–172.2
2094249.1230.6–268.4153.2133.6–170.3
2095251233.2–270148.2131.4–164.1
2096247.8231.4–269.3150.5130.5–172.6
2097251.1231.4–268149.8134.4–172.7
2098252.3230.8–268.3150.9131.3–170.1
2099248.7230.1–268.3149.5129–166.6
2100250.4232.9–266.7149.4130.1–168.5

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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