Israel vs Philippines

Israel vs Philippines: Tropical nights

Tropical nights in 2014: 97.9 nights in Israel and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 233.6 nights, or 3.39 times that in Israel.

Watch it change on the map

nights a year · CMIP6

Israel vs Philippines: Tropical nightsTropical nights in 2014: 97.9 nights in Israel and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 233.6 nights, or 3.39 times that in Israel.
IsraelPhilippinesCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Philippines 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 Philippines at 351.3 nights in 2100.

Every year

nights a year · CMIP6

YearIsraelPhilippines
201497.9331.5
201398330.9
201296.3331.1
201196.1329.8
201095.5330.6
200992.5329
200894.1327.5
200792.7327.8
200692328.7
200592.3329.7
200490.7329.4
200393.9327.1
200289.5328.9
200191327.8
200089.5326.8
199986.2327.5
199884.8326.5
199784.2325.4
199683.7324.6
199579.3324.2
199480.1321.5
199371.6319.5
199274.9318.4
199178.4324.1
199080.2323.5
198976.9322.5
198876.5324
198775.1323.1
198678.3322.1
198574321.4
198469.4321.7
198368.9319.4
198273.5320.5
198173.5320.4
198075.3322.7
197968.7321.2
197871.6320.6
197772.3319.8
197673.2319.6
197570.9319.6
197472.5320
197371.9319.4
197269.9318.9
197173.1318.8
197071.6319
196970.6318.7
196869.6317.2
196766.9317.4
196668.8318.8
196563.5317.2
196466.1314.9
196370.9317.2
196273318.6
196171.5319.3
196074.9318.6
195975320.5
195873321.8
195774.8319.4
195674.3320
195572.8319.3
195471.4317.7
195373.7320
195272319
195175.1319.8
195069.5320.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIsraelPhilippines
2015105.988.4–122.7333319.8–339.5
2016104.186.9–120.1334.2322.8–340.7
2017107.892.2–121.4333.4319.7–339.8
201810993.8–124.2333.2320.1–340.1
201910989.1–124.5334.1323.4–341.2
2020111.594.8–123.5334.6322.6–341.8
202111097.7–128.4335.6323.3–341.1
2022111.493.6–130.2335.7323.3–342.1
2023117.297.9–130.5336.7324.8–343.2
2024114.5100.4–127.3337.2325.7–343.9
2025116.698.3–129.2336.3326.2–342.8
2026115.9104.9–126.2336.5322.9–343
2027115.699–127.1336.2325.7–342.3
2028116.3100.2–127.9337.1325.5–343.8
2029117103.1–129.2338.1327.2–344.6
2030118.6102.1–131.2337.7326.2–344.4
2031116.8104.4–132.8337.1325.6–343.8
2032121.4106.5–134.7339.4329.5–346.1
2033122.1108.9–134.7339.7329.6–345.5
2034119.7103.1–133.4338.8328.8–345
2035122.8105.8–138.8338.6327.5–346.4
2036120.2105.5–136.2339.6327.8–346.9
2037121.6106.3–139.4339.8329.1–345.5
2038126.5105.7–142.1341.9330.7–347.7
2039127.7110.5–147.1341.2330.4–346.9
2040124.2109.7–144.9340.4328.1–347.6
2041126108.4–141.5341.1329.1–346.7
2042128.5105.8–144.3342331.4–347.7
2043126.5111.8–144.3341.3329–348.1
2044125.9108.5–142.9342.8329.9–349.8
2045130.9117.5–148.6343.4333.8–348.7
2046131114.4–147.2342.7330.2–348.7
2047132.3116.1–145.4343.2331.7–350.6
2048129.9118.5–146.9343.3332.7–350.6
2049127.9108.7–143.9343.2332.5–349.5
2050133.3114.3–147344.3332.6–349.9
2051130.3116.7–143.9344.4334.9–350.8
2052130.3119.9–143.5344.1333.5–350.9
2053135120.4–149.7344.3333.6–350.3
2054134.1118.8–149.3343.4332–349.9
2055134.1115.2–150.3344.3334.4–350.5
2056136110.1–151.1345334.6–352.6
2057132.7110.9–155345.5335.1–351.5
2058135.7119.1–155.4345.8334.3–351.3
2059138.8118.5–156.7345.5333.7–351.6
2060136.1116.3–159.2346.8335.5–353.5
2061136119–150.7345.9335–351.8
2062139118.7–156346335.2–353.5
2063137.4120.1–151.2346.6336.2–352.8
2064139.3121–154.3346.9335.3–353
2065139.6122.3–154.3346.1335.9–351.9
2066137.3119.6–153.7346.5335.4–352.4
2067142.8126–157.8346.1335.4–352
2068141.2122.8–156.4347.1335.1–354.1
2069141.5123.7–157.6347333.8–353.6
2070141.8120.5–157.5346.7336.1–352.7
2071142.9124.3–161.8347.6336.2–353.9
2072144.3127–158.5347334.4–353.8
2073143.6127.3–159.2348.4336.7–355
2074138.8123–162.2348.6337–354.9
2075138.1120.8–154.6347.9337.2–354
2076143.2126.8–161.5348.4337–355.1
2077142.8120.5–161.6348.7337–354.8
2078143.6128.2–160.6348.4338.2–354.7
2079148.6123.7–160.2348.8337.6–354.7
2080145.5123.5–163.7349.1338.4–355.9
2081143.7128.1–161.2348.8336.9–355.1
2082145.8129.5–160.6349.6338–354.9
2083149.4126–163.1349.9337.9–356.1
2084148128.2–164349.5336.7–356.4
2085149127.9–162.4349.1338.2–355.4
2086148127.4–167.1349.4337.5–354.9
2087146.4123.7–165.7349.7338.7–356
2088147.6133.5–165.3349.9338.9–356.1
2089148.4131.4–169.1350.2339.8–355.2
2090147.6132.4–168.8350.1339.7–355.9
2091151.9131.7–170.6349.5339.5–356.3
2092148.2132–167.4350.5339.3–356.1
2093154.1135.3–172.2350.4337.9–356.5
2094153.2133.6–170.3350.5338.4–355.9
2095148.2131.4–164.1350.5338.3–355.7
2096150.5130.5–172.6351.1339–358
2097149.8134.4–172.7350.2339.3–355.6
2098150.9131.3–170.1350.3337.4–355.2
2099149.5129–166.6350.6339.3–356.4
2100149.4130.1–168.5351.3340.2–356.3

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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