North Korea vs Philippines

North Korea vs Philippines: Tropical nights

Tropical nights in 2014: 29.3 nights in North Korea and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 302.2 nights, or 11 times that in North Korea.

nights a year · CMIP6

North Korea vs Philippines: Tropical nightsTropical nights in 2014: 29.3 nights in North Korea and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 302.2 nights, or 11 times that in North Korea.
North KoreaPhilippinesCMIP6 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 North Korea at 54.8 nights and Philippines at 351.3 nights in 2100.

Every year

nights a year · CMIP6

YearNorth KoreaPhilippines
201429.3331.5
201329330.9
201228331.1
201126.3329.8
201027.3330.6
200926.8329
200825.2327.5
200726.1327.8
200626.7328.7
200526.6329.7
200426.6329.4
200325.2327.1
200225.4328.9
200125327.8
200024.3326.8
199925.2327.5
199823.3326.5
199722.9325.4
199622.5324.6
199519.6324.2
199420.6321.5
199316.4319.5
199216.5318.4
199121.3324.1
199021.9323.5
198921.3322.5
198820.8324
198718.2323.1
198618.6322.1
198519321.4
198417.2321.7
198315.6319.4
198218.9320.5
198119.3320.4
198018.1322.7
197917.8321.2
197820.3320.6
197717.8319.8
197619.2319.6
197518.7319.6
197418.6320
197316.2319.4
197218318.9
197117.1318.8
197017.5319
196919.5318.7
196817.2317.2
196721.2317.4
196618.3318.8
196518.3317.2
196417.8314.9
196321.2317.2
196219.2318.6
196120.5319.3
196019318.6
195919.7320.5
195820.5321.8
195719.5319.4
195621.9320
195519.3319.3
195419.5317.7
195319.8320
195220.6319
195118.5319.8
195021.7320.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearNorth KoreaPhilippines
20153020.9–39.9333319.8–339.5
201628.319.1–38.6334.2322.8–340.7
201731.722.5–41.4333.4319.7–339.8
201829.419.8–40.4333.2320.1–340.1
201932.524.9–43.3334.1323.4–341.2
202030.622.9–40.9334.6322.6–341.8
202130.219–44335.6323.3–341.1
202233.225.3–40335.7323.3–342.1
202335.424.8–44.5336.7324.8–343.2
202433.123.4–44.2337.2325.7–343.9
202535.526–46.5336.3326.2–342.8
202634.125.7–46.4336.5322.9–343
202734.526–47.8336.2325.7–342.3
202834.924–44.4337.1325.5–343.8
202934.726.7–45.2338.1327.2–344.6
203035.225.2–45.6337.7326.2–344.4
203133.926.2–47.1337.1325.6–343.8
203236.125.7–49.1339.4329.5–346.1
203337.225.8–49.9339.7329.6–345.5
203436.328.6–44.6338.8328.8–345
203539.127.3–49.2338.6327.5–346.4
203640.426.7–52.8339.6327.8–346.9
203737.126.8–48.8339.8329.1–345.5
203837.826.9–50.2341.9330.7–347.7
203937.328–48.6341.2330.4–346.9
204040.328–54.9340.4328.1–347.6
204140.128.8–54.2341.1329.1–346.7
20424030.8–51.4342331.4–347.7
204340.929.4–53.8341.3329–348.1
204442.429.2–53.6342.8329.9–349.8
204541.130.7–52343.4333.8–348.7
204643.627.7–52.7342.7330.2–348.7
204742.230.2–55.6343.2331.7–350.6
20484029–56343.3332.7–350.6
204941.629.8–55343.2332.5–349.5
205040.831.5–53.9344.3332.6–349.9
205142.531–57.3344.4334.9–350.8
205242.129.7–55.5344.1333.5–350.9
205344.231.3–57.8344.3333.6–350.3
205442.332.5–55.4343.4332–349.9
205545.433–60.9344.3334.4–350.5
205643.933.5–56.4345334.6–352.6
205744.934.5–59345.5335.1–351.5
205845.334.8–59.4345.8334.3–351.3
205945.430.9–58.8345.5333.7–351.6
206045.130.4–61.9346.8335.5–353.5
206147.135.9–61.5345.9335–351.8
206244.934.3–60.2346335.2–353.5
206344.433.8–60.5346.6336.2–352.8
206444.332.7–60.5346.9335.3–353
206547.835.3–62.1346.1335.9–351.9
206647.434–59.6346.5335.4–352.4
206749.333.1–61.2346.1335.4–352
206847.234.1–63.4347.1335.1–354.1
206947.432.6–58.7347333.8–353.6
20704933.9–66.5346.7336.1–352.7
207148.634.2–65.8347.6336.2–353.9
207248.834.5–64.9347334.4–353.8
207349.633.9–62.9348.4336.7–355
207449.635–65.3348.6337–354.9
207549.734.6–64347.9337.2–354
20765034.9–65.1348.4337–355.1
207752.437.4–64.6348.7337–354.8
207848.435.4–66.5348.4338.2–354.7
207949.737–64.5348.8337.6–354.7
208050.139.7–68.2349.1338.4–355.9
208149.938.1–69.4348.8336.9–355.1
208252.738.5–70.3349.6338–354.9
208351.638.9–68.2349.9337.9–356.1
208449.836.9–66.8349.5336.7–356.4
208550.638.2–69349.1338.2–355.4
208652.737.2–68349.4337.5–354.9
208751.937.3–71.1349.7338.7–356
208852.636.7–67.4349.9338.9–356.1
208952.839–67.7350.2339.8–355.2
209053.738.3–65.3350.1339.7–355.9
209153.740–67.5349.5339.5–356.3
209253.438.6–67.8350.5339.3–356.1
209353.537.2–69.1350.4337.9–356.5
209452.936.2–73350.5338.4–355.9
209552.741.1–68.9350.5338.3–355.7
209658.337.8–73351.1339–358
209755.239–69350.2339.3–355.6
20985440.5–67.9350.3337.4–355.2
209952.537.3–67.2350.6339.3–356.4
210054.837.2–70.2351.3340.2–356.3

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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