Israel vs Mexico

Israel vs Mexico: Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 5.8 nights, or 1.06 times that in Israel.

nights a year · CMIP6

Israel vs Mexico: Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 103.7 nights in Mexico, in the CMIP6 climate models’ median run. In 2014 the value was higher in Mexico, by 5.8 nights, or 1.06 times that in Israel.
IsraelMexicoCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Mexico has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Israel at 149.4 nights and Mexico at 142.8 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelMexico
201497.9103.7
201398103.9
201296.3102.8
201196.1102.9
201095.5101.5
200992.5101.8
200894.1100.1
200792.799.1
20069299.8
200592.399.5
200490.799.4
200393.998.3
200289.599.1
20019198.7
200089.597.9
199986.296.6
199884.895.8
199784.295.9
199683.793.8
199579.392.7
199480.190.7
199371.689
199274.988.5
199178.493.4
199080.294.9
198976.993
198876.592.1
198775.192
198678.390.2
19857490
198469.488
198368.986.7
198273.588.7
198173.591.5
198075.390.1
197968.790.8
197871.689
197772.389
197673.289.1
197570.986.8
197472.587.9
197371.988.6
197269.987.7
197173.186.8
197071.686.1
196970.687.5
196869.687.1
196766.986.7
196668.886.4
196563.584.9
196466.184.7
196370.987.1
19627388
196171.589.5
196074.989.7
19597589.6
19587389.1
195774.889
195674.388.5
195572.888.2
195471.488.4
195373.788.6
19527287.8
195175.189.4
195069.588.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelMexico
2015105.988.4–122.7106.192.9–118.4
2016104.186.9–120.1107.695–120
2017107.892.2–121.4108.696.3–119.7
201810993.8–124.210997.1–120.4
201910989.1–124.5110.396.4–123
2020111.594.8–123.5109.696.8–121.8
202111097.7–128.4111.296.9–124.1
2022111.493.6–130.2109.796–121.7
2023117.297.9–130.5111.898.6–125.3
2024114.5100.4–127.3112.298.2–126.2
2025116.698.3–129.211298.8–125.8
2026115.9104.9–126.2113.999.5–126.4
2027115.699–127.1112.999.5–128.3
2028116.3100.2–127.9115.2101.9–127.9
2029117103.1–129.2115.6101.9–127.9
2030118.6102.1–131.2115.9101.7–128.4
2031116.8104.4–132.8116.1100.9–129.9
2032121.4106.5–134.7116.1102.5–129.1
2033122.1108.9–134.7117.5102.5–131.1
2034119.7103.1–133.4117.2104.1–130.3
2035122.8105.8–138.8116.4103.1–130.3
2036120.2105.5–136.2117.8105.1–131
2037121.6106.3–139.4118.6104.3–131.7
2038126.5105.7–142.1121107.5–133.4
2039127.7110.5–147.1121.3107–135.6
2040124.2109.7–144.9121.9108.1–135.1
2041126108.4–141.5121.3105.3–134.6
2042128.5105.8–144.3122.7107.7–137.1
2043126.5111.8–144.3122.4108.1–137.5
2044125.9108.5–142.9121.9108–135.6
2045130.9117.5–148.6123.1108.8–139.2
2046131114.4–147.2123.8109.9–139.4
2047132.3116.1–145.4125.6111.9–139.4
2048129.9118.5–146.9126.3113–140.3
2049127.9108.7–143.9127111.2–140.8
2050133.3114.3–147128.1112.6–142.5
2051130.3116.7–143.9127.2113.4–140.8
2052130.3119.9–143.5126.2112.5–141.1
2053135120.4–149.7128.4111.5–142.7
2054134.1118.8–149.3128.1113.1–142.3
2055134.1115.2–150.3129114.4–144.7
2056136110.1–151.1129.5114.3–143.8
2057132.7110.9–155130.3113.5–145.9
2058135.7119.1–155.4128.8114.1–144.5
2059138.8118.5–156.7129.5114.5–144.5
2060136.1116.3–159.2131.4115.5–146.5
2061136119–150.7131.3118.4–146.8
2062139118.7–156130.8115.1–146.3
2063137.4120.1–151.2131.2115.6–147.9
2064139.3121–154.3132.2116.5–147.8
2065139.6122.3–154.3133.1115.8–148.6
2066137.3119.6–153.7133.3117.2–149.4
2067142.8126–157.8133.3117–150.3
2068141.2122.8–156.4134.6117.4–150.5
2069141.5123.7–157.6134.4117.8–150.9
2070141.8120.5–157.5134.2116.7–151.8
2071142.9124.3–161.8136.3120.8–152.7
2072144.3127–158.5137.2119.9–153.1
2073143.6127.3–159.2136.1119.1–153.6
2074138.8123–162.2136119.7–152.2
2075138.1120.8–154.6135.2118.5–151.8
2076143.2126.8–161.5136.3117.4–154.7
2077142.8120.5–161.6136.8119.6–152.8
2078143.6128.2–160.6137.1118.3–154.2
2079148.6123.7–160.2138.1121.3–157.1
2080145.5123.5–163.7137.6120.5–157.9
2081143.7128.1–161.2137.8120.7–154.7
2082145.8129.5–160.6138.7121.6–155.2
2083149.4126–163.1139.2119.3–158.8
2084148128.2–164140.3123.4–157.5
2085149127.9–162.4139.2120.9–157.2
2086148127.4–167.1139.8121–157.8
2087146.4123.7–165.7139.5121.5–157.4
2088147.6133.5–165.3141121.8–159.9
2089148.4131.4–169.1140.4121.7–158.9
2090147.6132.4–168.8141.2123–160.7
2091151.9131.7–170.6141.8123–161.6
2092148.2132–167.4141.3122.5–159.3
2093154.1135.3–172.2141.4124.3–161
2094153.2133.6–170.3142123.3–159.6
2095148.2131.4–164.1143.5124–160.7
2096150.5130.5–172.6142.3125–161.3
2097149.8134.4–172.7141.2123.2–160
2098150.9131.3–170.1142.2122.5–162
2099149.5129–166.6141.8122.4–160.7
2100149.4130.1–168.5142.8124.3–160.8

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

Israel vs Mexico

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment