Iran vs Philippines

Iran vs Philippines: Tropical nights

Tropical nights in 2014: 90.8 nights in Iran and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 240.7 nights, or 3.65 times that in Iran.

nights a year · CMIP6

Iran vs Philippines: Tropical nightsTropical nights in 2014: 90.8 nights in Iran and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 240.7 nights, or 3.65 times that in Iran.
IranPhilippinesCMIP6 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 Iran at 124.4 nights and Philippines at 351.3 nights in 2100.

Every year

nights a year · CMIP6

YearIranPhilippines
201490.8331.5
201390.6330.9
201290.3331.1
201189.8329.8
201087330.6
200987.2329
200888327.5
200787.9327.8
200688.2328.7
200587.1329.7
200486.4329.4
200385.9327.1
200287.7328.9
200186.6327.8
200086.5326.8
199985.1327.5
199883.8326.5
199784.3325.4
199682.4324.6
199581.6324.2
199480.6321.5
199377.7319.5
199277318.4
199181.9324.1
199083.1323.5
198981.7322.5
198880.4324
198779.8323.1
198680.1322.1
198579.7321.4
198478.8321.7
198375.5319.4
198277.9320.5
198180.2320.4
198079.4322.7
197980.2321.2
197878.1320.6
197777.8319.8
197677.2319.6
197576.6319.6
197476.4320
197376.9319.4
197277.4318.9
197175318.8
197075.3319
196975.6318.7
196876.3317.2
196776.1317.4
196675.5318.8
196575.3317.2
196475.3314.9
196376.4317.2
196277.5318.6
196177.7319.3
196077.6318.6
195976.8320.5
195878.4321.8
195778.2319.4
195676.2320
195576.5319.3
195477.6317.7
195377.3320
195278.2319
195176.6319.8
195077.7320.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearIranPhilippines
201594.482.7–106333319.8–339.5
201694.183.1–105.3334.2322.8–340.7
201793.981.7–104333.4319.7–339.8
201894.183–106.3333.2320.1–340.1
201995.183.4–105.8334.1323.4–341.2
202095.985.5–107.5334.6322.6–341.8
202197.286–107.7335.6323.3–341.1
202296.285.2–108.3335.7323.3–342.1
202398.485.7–110.6336.7324.8–343.2
20249885.1–110.5337.2325.7–343.9
202598.787.2–110.5336.3326.2–342.8
202699.186.7–111.7336.5322.9–343
2027100.288.7–112.1336.2325.7–342.3
202899.686.2–111.6337.1325.5–343.8
202999.386.7–109.9338.1327.2–344.6
2030100.889.8–111.6337.7326.2–344.4
2031102.990.1–114.8337.1325.6–343.8
2032101.289–113.9339.4329.5–346.1
2033102.889.9–115.1339.7329.6–345.5
2034104.690.7–117.3338.8328.8–345
203510592.1–116.2338.6327.5–346.4
2036103.591.4–115.2339.6327.8–346.9
203710693.1–119.4339.8329.1–345.5
2038105.993.2–116.5341.9330.7–347.7
2039104.392.9–116.6341.2330.4–346.9
2040105.592.3–118.4340.4328.1–347.6
2041104.892.5–116.4341.1329.1–346.7
2042107.793.4–120.7342331.4–347.7
204310692.9–118.8341.3329–348.1
2044106.893.6–121.2342.8329.9–349.8
2045108.795.1–121.8343.4333.8–348.7
2046109.296.1–121.9342.7330.2–348.7
2047110.596.9–123.3343.2331.7–350.6
2048111.498.6–124343.3332.7–350.6
204911095.7–123.4343.2332.5–349.5
2050112.199.6–125.1344.3332.6–349.9
2051111.797.6–124.1344.4334.9–350.8
205211298.3–126344.1333.5–350.9
2053111.597.5–124344.3333.6–350.3
2054111.899–126.3343.4332–349.9
2055114.6101.4–128344.3334.4–350.5
2056113.1100.2–126.2345334.6–352.6
2057113.899.9–128.9345.5335.1–351.5
2058114.2100–127.7345.8334.3–351.3
2059113.498.9–126.3345.5333.7–351.6
2060116.3100.3–129.5346.8335.5–353.5
2061115100.5–127.6345.9335–351.8
2062115.799.7–131.1346335.2–353.5
2063117103.7–130.3346.6336.2–352.8
2064115.1101.7–130.3346.9335.3–353
2065117.3102.8–132.3346.1335.9–351.9
2066117.7103.7–132.1346.5335.4–352.4
2067119103–133.5346.1335.4–352
2068118.1104.3–131.4347.1335.1–354.1
2069118.4103.8–133.2347333.8–353.6
2070118.2104.9–132.9346.7336.1–352.7
2071119.3105.1–135.3347.6336.2–353.9
2072119103.2–135.1347334.4–353.8
2073120.6104.9–137.7348.4336.7–355
2074119.1104.4–134.5348.6337–354.9
2075119.7105.9–135.5347.9337.2–354
2076118.9102.6–137348.4337–355.1
2077120.3104.3–135.3348.7337–354.8
2078119.2105.3–136348.4338.2–354.7
2079120.1103.2–135.6348.8337.6–354.7
2080120.4106.1–139.5349.1338.4–355.9
2081120.5104.3–137.1348.8336.9–355.1
2082122.5107.5–137.7349.6338–354.9
2083122.6105.8–140.4349.9337.9–356.1
2084123.7107.6–139.1349.5336.7–356.4
2085121.3106.6–140.6349.1338.2–355.4
2086122.1107.9–139.8349.4337.5–354.9
2087123.7108–140.7349.7338.7–356
2088124106.5–142.2349.9338.9–356.1
2089124.1109–139.7350.2339.8–355.2
2090122.5105.4–141.9350.1339.7–355.9
2091124.3108–140.5349.5339.5–356.3
2092125.5110.1–140350.5339.3–356.1
2093124.5109–139.3350.4337.9–356.5
2094125108.7–142.9350.5338.4–355.9
2095125.3108.5–141350.5338.3–355.7
2096125.8109–142.4351.1339–358
2097123.6106.9–141.8350.2339.3–355.6
2098125.8109.4–143.8350.3337.4–355.2
2099123.1107.8–140.1350.6339.3–356.4
2100124.4107.9–143.7351.3340.2–356.3

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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