Israel vs Myanmar (Burma)

Israel vs Myanmar (Burma): Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 201.9 nights in Myanmar (Burma), in the CMIP6 climate models’ median run. In 2014 the value was higher in Myanmar (Burma), by 104 nights, or 2.06 times that in Israel.

nights a year · CMIP6

Israel vs Myanmar (Burma): Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 201.9 nights in Myanmar (Burma), in the CMIP6 climate models’ median run. In 2014 the value was higher in Myanmar (Burma), by 104 nights, or 2.06 times that in Israel.
IsraelMyanmar (Burma)CMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Myanmar (Burma) 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 Myanmar (Burma) at 244.5 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelMyanmar (Burma)
201497.9201.9
201398203.1
201296.3201.1
201196.1200.9
201095.5202.1
200992.5199
200894.1198.1
200792.7196.8
200692198.2
200592.3196.7
200490.7200.3
200393.9195.3
200289.5196.6
200191199
200089.5197.2
199986.2196.4
199884.8194.7
199784.2194.4
199683.7191.4
199579.3189.9
199480.1188.8
199371.6185
199274.9180.5
199178.4191.7
199080.2191.5
198976.9190.3
198876.5190.7
198775.1190.8
198678.3189.7
198574187.4
198469.4189.1
198368.9182.3
198273.5186.7
198173.5188.4
198075.3189
197968.7189.8
197871.6186.8
197772.3187.4
197673.2185.8
197570.9183.6
197472.5185.5
197371.9187.5
197269.9184.8
197173.1185.2
197071.6184.9
196970.6184.3
196869.6183.7
196766.9182.3
196668.8186.2
196563.5182.9
196466.1180.6
196370.9183.1
196273187.3
196171.5188.7
196074.9187.1
195975186.5
195873187.1
195774.8186.2
195674.3187.9
195572.8185.9
195471.4185.7
195373.7185
195272186.1
195175.1187.1
195069.5186.9
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelMyanmar (Burma)
2015105.988.4–122.7205.2186.4–218.9
2016104.186.9–120.1202.8186.2–218.8
2017107.892.2–121.4203.4187.3–218.3
201810993.8–124.2205.5190.9–219.9
201910989.1–124.5205.2186.7–222.2
2020111.594.8–123.5208.2188.5–223.5
202111097.7–128.4208.9191.2–224.1
2022111.493.6–130.2209.9192.7–224.9
2023117.297.9–130.5210.6195.4–226.3
2024114.5100.4–127.3210.4193.8–226.6
2025116.698.3–129.2209.9190.3–225.2
2026115.9104.9–126.2212.2194.3–229.2
2027115.699–127.1212195.6–228.6
2028116.3100.2–127.9213195.7–227.2
2029117103.1–129.2215.3193.9–231.9
2030118.6102.1–131.2212.2194.9–228
2031116.8104.4–132.8214.3197.2–230.8
2032121.4106.5–134.7215199.3–229.6
2033122.1108.9–134.7215.5198.5–230.1
2034119.7103.1–133.4214.9198.4–233.5
2035122.8105.8–138.8214.9199.2–236.8
2036120.2105.5–136.2216198.7–234.5
2037121.6106.3–139.4217.2199.6–233.5
2038126.5105.7–142.1220.7204.8–235.1
2039127.7110.5–147.1219.7202.4–234.3
2040124.2109.7–144.9219.2202.9–235
2041126108.4–141.5220.7203.9–237.7
2042128.5105.8–144.3221.8206.1–237.2
2043126.5111.8–144.3219.5201.2–237.1
2044125.9108.5–142.9221.4201.6–239.6
2045130.9117.5–148.6223.7204.8–241.5
2046131114.4–147.2223.2203.2–240.2
2047132.3116.1–145.4224.3204.8–241.1
2048129.9118.5–146.9226.4207.7–243.8
2049127.9108.7–143.9226.5205.6–242.8
2050133.3114.3–147227209.3–243.5
2051130.3116.7–143.9229.6212.4–246.4
2052130.3119.9–143.5227.2208.6–244.2
2053135120.4–149.7227.9208.7–247.7
2054134.1118.8–149.3227.9209.6–244.8
2055134.1115.2–150.3229.1209.8–247.5
2056136110.1–151.1231.8210.4–252.1
2057132.7110.9–155228.6208–249
2058135.7119.1–155.4228.9208.8–249
2059138.8118.5–156.7230.7212.1–247.5
2060136.1116.3–159.2234.7211.1–251.5
2061136119–150.7231.9213–247.7
2062139118.7–156233.6209.9–252.8
2063137.4120.1–151.2233215.4–250.5
2064139.3121–154.3233.2214.4–251.3
2065139.6122.3–154.3230.7210.4–250.7
2066137.3119.6–153.7233.5214.3–251.2
2067142.8126–157.8233211.5–253.3
2068141.2122.8–156.4233.1212.4–253.7
2069141.5123.7–157.6236.1214.6–253.4
2070141.8120.5–157.5235.9218.1–253.4
2071142.9124.3–161.8235.1213.5–259.6
2072144.3127–158.5234.6216.1–252.6
2073143.6127.3–159.2237.2219.3–257.2
2074138.8123–162.2236.4215.7–254.5
2075138.1120.8–154.6236.7214.4–255.9
2076143.2126.8–161.5237.7216–257
2077142.8120.5–161.6237.5219–258.7
2078143.6128.2–160.6238.5217.3–257.8
2079148.6123.7–160.2238.5219.2–257.2
2080145.5123.5–163.7240.5218.8–258.3
2081143.7128.1–161.2240219.7–260.9
2082145.8129.5–160.6239.4217.1–258.8
2083149.4126–163.1239.1220.5–259.2
2084148128.2–164241.3218.9–260.6
2085149127.9–162.4241.7218.8–260.7
2086148127.4–167.1241.7217.4–262.7
2087146.4123.7–165.7241.4220.5–260.9
2088147.6133.5–165.3241.8222.3–261.5
2089148.4131.4–169.1240.7221.2–262.6
2090147.6132.4–168.8241.3224.4–260.9
2091151.9131.7–170.6242.6220.3–262.5
2092148.2132–167.4241.9221.6–263.3
2093154.1135.3–172.2242.1220.2–260
2094153.2133.6–170.3242.5222.5–261.9
2095148.2131.4–164.1244.9224–264.4
2096150.5130.5–172.6243.9221.1–266.5
2097149.8134.4–172.7243.6219.6–264.2
2098150.9131.3–170.1243.6222.5–263.9
2099149.5129–166.6244.7221.8–263.5
2100149.4130.1–168.5244.5223.2–261.8

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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