South Korea vs Vietnam

South Korea vs Vietnam: Tropical nights

Tropical nights in 2014: 68.9 nights in South Korea and 242.6 nights in Vietnam, in the CMIP6 climate models’ median run. In 2014 the value was higher in Vietnam, by 173.7 nights, or 3.52 times that in South Korea.

nights a year · CMIP6

South Korea vs Vietnam: Tropical nightsTropical nights in 2014: 68.9 nights in South Korea and 242.6 nights in Vietnam, in the CMIP6 climate models’ median run. In 2014 the value was higher in Vietnam, by 173.7 nights, or 3.52 times that in South Korea.
South KoreaVietnamCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Vietnam has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts South Korea at 96.3 nights and Vietnam at 282.7 nights in 2100.

Every year

nights a year · CMIP6

YearSouth KoreaVietnam
201468.9242.6
201369.7243.6
201267.7242.4
201165.3241.9
201068.3240.9
200965.8240
200863.7238.7
200764.2238
200664.8239.1
200565.1238.3
200466.8241.8
200363.2235.9
200263.3236.3
200163.4241.3
200061.7237
199964.2236
199860.7236.8
199760.4237.1
199661.2231.4
199555.2229.9
199454.8231.2
199349.2225.3
199250.7221.9
199156.9229.8
199058.8233.1
198958.7229.2
198855.6231.7
198752.6230.3
198651.4230.9
198553.1228
198450.4230.2
198346.8224.9
198254227.5
198153.9229.7
198051.6228.1
197952.6228.9
197856.4227.5
197751.8229
197652.8225.8
197554.6225.8
197452.7225.7
197350.4230.3
197251.8225.6
197149.7225.5
197050.4226.1
196955.2227
196851.7227.1
196757.3222.9
196652.9226.8
196552.8225.4
196452.2222.6
196357.9224.3
196253.3227.8
196158.2229.4
196055.2228.5
195954.8226.2
195856230.9
195755.8228.4
195659.1228.7
195555.7227.5
195454226.3
195355.4228.2
195257228.5
195154.7229.2
195059.8228.9
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearSouth KoreaVietnam
201568.656.8–82245.8228.2–261.9
201670.353.5–81.8243.7226.1–259.4
201770.559.5–82.9247229.6–260.7
201869.156.9–81.2248.3228.8–263.3
201974.663.1–84.4248.1229.2–262.8
20207157.6–83248.8229.6–262.9
202170.252.7–84.1251.1233.1–266.7
202272.563–81.2252.4234.3–266.8
202374.563.2–84.2253.4235.4–266.6
202473.558.6–87.1251.3236.7–264.6
202575.762.3–87.1252.4234.1–266.2
20267564–88.4252.8232.9–268.5
202774.163.4–88.9253.2237–268.8
202877.361.5–87.9254.3237.7–272
202975.463.1–86.7258.1238.5–273.7
203075.364.5–87.6256.4240.9–270.1
203176.763.6–87.3255.9241.2–270.9
203276.761–89.2257.4239.1–269.9
203378.860–92.7258.3241.7–273.2
203477.264.7–87.2258.8240.7–275.8
20358168.9–92.1258.6242.5–275.4
203681.964.1–95258.3239.1–273.8
203778.465.8–89.3258.7242.4–272.4
203878.866.9–89.4263.4247.6–277.3
203977.564.7–89.2260.2243.7–275.9
204080.567.4–92.7260.1242.8–274.8
204180.966.4–97.7263.1245.9–279
204282.469.1–95263.6246.5–279
204383.268.5–97.9261.4245.5–279.6
204483.169.3–91.6263.2245.2–277.6
20458170.4–92.2265.5249.6–281.4
20468668.3–95.2264.9246.8–278.1
204783.469.7–96.7266.9250.4–282.9
204882.769.2–95.2268250.5–283.8
204981.669–96.8267.8251.2–284.8
205081.569.8–93.8268251.2–283.5
205184.572.7–98.8270.9254.3–285.4
205283.167.8–98.5268.3253.3–282.8
205386.969.8–98.1268.5250.1–283.2
205484.773.3–97.5269.1250.8–283.6
205586.570.8–101.3270249.8–284.2
205685.874.5–99.8271.7254.8–290.1
205787.976.1–100.7270253–285.7
205886.275.2–99.4270.7252.9–286.5
205986.766.9–100.4273257.6–286.6
206086.371.9–101.9275.7255.6–290.6
20618974.8–99.5273.5254.6–289.5
206287.772.3–102.2271.4253.1–290.2
206386.774.6–101.2272.9252.7–288.1
206486.673.6–100.3273.8254.4–288.1
206591.575.3–102.2272255.8–286.3
206689.272.6–100.5271.8254.4–287.3
206790.372.7–102.6270.8252.1–287.6
206890.473.8–106.4275.6256.9–292.4
20699174.5–102.5276.4258.5–292
207089.774.6–107274.6257.8–292.8
207192.674.9–107.9276.2255.2–294.1
207290.976.6–103.9277256.8–291.4
207391.376.2–104278.5262.7–293.4
207491.974.6–107277.6259.2–295.8
207594.576.4–103.7276.4258.7–294.4
207693.477.5–105.6279.2258.5–296.6
207795.776.3–107.2280264.9–294.7
207893.576.9–110.5278.4258.6–295.5
207991.179.2–105.7279.3263.4–293.6
208092.481.7–107.1280261.4–296.5
208193.878–108.8280.4261.2–297.9
208296.279.9–110.1280.9258.9–296
208394.481.1–108278.4261.6–295
208491.574.4–107.3279257.4–293.8
20859481.4–107.4281.3265–297.8
208693.678.5–111.5282.3260.2–297.5
208794.480.9–113.5281.9261.3–300.7
208893.779.8–108.5283.1265.7–301.5
208994.478.9–107280.8261.2–301.6
209097.979.5–109280.5264.5–297.6
209195.280.6–107.7283.3264.3–298.9
20929580–106.3281.1261.5–299.4
209395.379.5–109.9280.5263.4–296.1
209492.279.8–111283264.5–300
209594.884–112.2285.5264.5–302.9
2096100.481–113.2281.8264.8–299.8
209797.278.6–108.8281.5263.3–299
209897.479.9–110.4282.5263.9–301.5
209995.879.9–109.3282.7265.1–298
210096.381.6–113.8282.7261–298.2

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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