China vs Philippines

China vs Philippines: Tropical nights

Tropical nights in 2014: 41.5 nights in China and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 290.1 nights, or 8 times that in China.

nights a year · CMIP6

China vs Philippines: Tropical nightsTropical nights in 2014: 41.5 nights in China and 331.5 nights in Philippines, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 290.1 nights, or 8 times that in China.
ChinaPhilippinesCMIP6 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 China at 63.3 nights and Philippines at 351.3 nights in 2100.

Every year

nights a year · CMIP6

YearChinaPhilippines
201441.5331.5
201341.7330.9
201240.8331.1
201140.2329.8
201040.5330.6
200939.5329
200839.2327.5
200738.7327.8
200639.5328.7
200539.5329.7
200439.7329.4
200338.5327.1
200238.8328.9
200139.5327.8
200038.6326.8
199938.5327.5
199837.6326.5
199737.1325.4
199636.6324.6
199535.1324.2
199434.9321.5
199333.2319.5
199232.3318.4
199135.9324.1
199036.4323.5
198936.1322.5
198835.1324
198734.5323.1
198634322.1
198533.5321.4
198433.4321.7
198331.5319.4
198234.1320.5
198134.2320.4
198034.3322.7
197933.8321.2
197834.8320.6
197733.3319.8
197632.7319.6
197533.1319.6
197433.3320
197333.1319.4
197232.6318.9
197133318.8
197032.4319
196933.4318.7
196832.8317.2
196733.4317.4
196633.4318.8
196532.5317.2
196432.1314.9
196334.5317.2
196234318.6
196134.6319.3
196034.1318.6
195934320.5
195835321.8
195734.4319.4
195634.6320
195534.2319.3
195434.2317.7
195334.3320
195234.3319
195135.1319.8
195034.9320.4
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearChinaPhilippines
201542.334.8–49.8333319.8–339.5
201642.134.4–50334.2322.8–340.7
201743.135.3–51.6333.4319.7–339.8
201842.335.5–49.5333.2320.1–340.1
201943.836.5–51.1334.1323.4–341.2
202043.736.8–51.1334.6322.6–341.8
202144.136–52.1335.6323.3–341.1
202244.737.5–52.7335.7323.3–342.1
202345.737.8–53.4336.7324.8–343.2
202445.738.1–54337.2325.7–343.9
202546.337.5–54.8336.3326.2–342.8
202646.237.6–55.5336.5322.9–343
202746.138–54.9336.2325.7–342.3
202846.438.4–54.3337.1325.5–343.8
202946.939.1–55.6338.1327.2–344.6
203047.138.8–55.3337.7326.2–344.4
20314738.8–56337.1325.6–343.8
203248.339.3–57.4339.4329.5–346.1
203347.939.7–56.6339.7329.6–345.5
203448.440.5–57.3338.8328.8–345
203549.740.8–58.6338.6327.5–346.4
20364940.1–58.2339.6327.8–346.9
20374941.2–57.6339.8329.1–345.5
203850.542.4–59.3341.9330.7–347.7
203949.641.2–59.2341.2330.4–346.9
204050.942.4–60.4340.4328.1–347.6
204151.342.5–61.1341.1329.1–346.7
204251.642–61.5342331.4–347.7
204350.742.7–61341.3329–348.1
204451.942.4–61.9342.8329.9–349.8
204551.542.8–61.1343.4333.8–348.7
20465343.7–62.7342.7330.2–348.7
204753.544.5–62.5343.2331.7–350.6
204853.144–62.6343.3332.7–350.6
204952.843.8–63.3343.2332.5–349.5
205053.644.4–63.8344.3332.6–349.9
205154.345.1–64.8344.4334.9–350.8
205253.444.6–63.2344.1333.5–350.9
205354.244.2–64.2344.3333.6–350.3
205454.545.3–64.8343.4332–349.9
20555545.1–65.8344.3334.4–350.5
205655.245.1–66.6345334.6–352.6
205754.844.9–65.7345.5335.1–351.5
205855.145.8–67.7345.8334.3–351.3
205955.345.1–67.2345.5333.7–351.6
206057.246.9–68.1346.8335.5–353.5
206156.546.6–66.3345.9335–351.8
206256.846.9–68.5346335.2–353.5
206357.247.2–68.6346.6336.2–352.8
20645747.1–67.7346.9335.3–353
206557.347.1–67.8346.1335.9–351.9
206657.347.9–68.7346.5335.4–352.4
206757.546.4–68.2346.1335.4–352
206858.748.5–70.5347.1335.1–354.1
206958.548.4–69347333.8–353.6
20705847.6–71.7346.7336.1–352.7
207159.347.4–71.6347.6336.2–353.9
207259.248.1–71.5347334.4–353.8
207359.849.1–70.9348.4336.7–355
207459.648.7–71.1348.6337–354.9
207558.748.3–71.4347.9337.2–354
207660.249–70.9348.4337–355.1
207760.851.1–72.4348.7337–354.8
207859.648.8–72.4348.4338.2–354.7
207960.750.1–72.6348.8337.6–354.7
208059.950–72.3349.1338.4–355.9
208160.950–73.2348.8336.9–355.1
20826149.8–73.3349.6338–354.9
208361.251.2–73.6349.9337.9–356.1
208461.749.7–74.6349.5336.7–356.4
208561.250.8–75.2349.1338.2–355.4
208661.648.9–74.5349.4337.5–354.9
208761.650.6–75349.7338.7–356
208862.750.5–77.1349.9338.9–356.1
208961.950–75.2350.2339.8–355.2
209062.551.4–73.7350.1339.7–355.9
209163.852–75.7349.5339.5–356.3
209263.251.2–75.1350.5339.3–356.1
209363.252–75.4350.4337.9–356.5
20946351.1–76.3350.5338.4–355.9
209563.952.8–76.4350.5338.3–355.7
209663.852.2–76.8351.1339–358
209762.750.7–75.1350.2339.3–355.6
209863.451.2–76.8350.3337.4–355.2
209963.851.9–76.1350.6339.3–356.4
210063.351.7–76.2351.3340.2–356.3

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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