Morocco vs Yemen

Morocco vs Yemen: Tropical nights

Tropical nights in 2014: 59.6 nights in Morocco and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 116.2 nights, or 2.95 times that in Morocco.

nights a year · CMIP6

Morocco vs Yemen: Tropical nightsTropical nights in 2014: 59.6 nights in Morocco and 175.8 nights in Yemen, in the CMIP6 climate models’ median run. In 2014 the value was higher in Yemen, by 116.2 nights, or 2.95 times that in Morocco.
MoroccoYemenCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Yemen has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Morocco at 103.8 nights and Yemen at 225.7 nights in 2100.

Every year

nights a year · CMIP6

YearMoroccoYemen
201459.6175.8
201360.7176.9
201258.8178.4
201158.4178.3
201056.7174.9
200958.6173.4
200858.5174
200754.8173.9
200657.5173.6
200556.9172.4
200456.1174.3
200354.6173.5
200255.5171.8
200156.4172.7
200052.8167.9
199953.6168.6
199851.9168.7
199751.2168.8
199650.4166
199548164.3
199447.9161.6
199344.6161.2
199240.6157.2
199148.7166.5
199052.5168.3
198948.3164.3
198848.8163.7
198747.3160.7
198643.6162.3
198543.5158.2
198443.6159.8
198342.1155.4
198243.7161.5
198143.6161.7
198042.9158.5
197945.9160.1
197844158.9
197745161.2
197640.1157.5
197542.5156.9
197442157.8
197343.5158.1
197242.2157.5
197140.7156.7
197041.3156.9
196940.7157.5
196842154.5
196741.1152.1
196640.5155.1
196539.4153.5
196442.5154
196341.7154.7
196243.1155.9
196142.7158.7
196043160.1
195943.3156.1
195842.7158.5
195742158.1
195643.8156.2
195545.5157.4
195442.3156.1
195342.8155.1
195243.8157
195144.1155.4
195045.1157.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearMoroccoYemen
201562.147.1–77180.9163.8–197.8
201662.747.4–77.9178.4162.7–194.6
201763.749–78.1179.8162.3–196.8
201864.449.6–80.6183.2165.3–198.6
201967.950.6–82.7179162–200.4
202065.649.2–82181.5163.1–195.9
202166.351–84.5184.6170.2–202.6
202270.554.8–87.8184.1167.5–203.7
202367.653.2–82.4186.8170.1–200.5
202470.456.5–85.5185.3168.8–206.4
202568.652.1–87186.5164.7–211.8
202668.754.7–84.2187.8167.9–208.8
202772.957.6–88.1186.5167.9–205.3
202873.253.6–89.6188.2172.3–203.6
202970.754.6–90.5193175.7–211.5
203071.453.4–86189.4171.6–207.4
203173.354.3–89.9193.4176.6–211.5
203274.160–88.7192.7173.2–213.2
203373.857.6–88.9191.2173–209.1
203477.761–94.3193.1172.1–214.9
203575.857.8–92.8193.1174.5–214.1
203675.660.5–91.7194177.6–213.5
203776.458–94.8195.9180.3–212.8
203877.962.2–97.3197.6178.5–217.1
203978.262.7–94.7194.8179.8–215.4
204073.957.1–97.5196.4178.8–220.1
204176.560.4–90.6198.5176.5–216.9
204278.663.1–96.4197.3174.4–225.8
204380.161.4–96.9198.3179.3–221
204479.362.3–96.1198.7180.5–221.9
204582.265.9–98.5199.8181.6–220.3
204682.260.8–98.7202.2181.7–229.3
204783.963.8–101205182.7–229.8
204882.667.6–99.2207.4188.8–229.5
204985.366.9–101.9203.6186.1–222.5
205085.368.4–104.6202.8186.2–226.3
205184.366.5–103.5204.6185.1–229.1
205286.164.4–105.4207.2186.9–227.7
205384.165.5–106.1203.9186.1–226.9
205484.764.8–103.4208.4188.3–234.9
205587.769.1–104.2208.3190.7–228
205688.369.2–104.6208.6188.5–236.3
20578971.1–108.8208.4190.1–233.1
205887.368.2–106.5207.2184.7–236
205987.169.2–108.1213.3191.6–239.3
206090.873.5–108.9215194.1–235.3
20619274.9–111.9209.8189.8–233.3
206287.868.3–110.2211.4189.6–246.5
206395.174.5–114.4215.9193.5–239.5
206488.969.9–113.6212.6194.7–231.7
206591.270.6–112.5212.5191.7–241.4
206694.275.6–115.8215.6196.9–241.3
206791.273.1–113.3214.6192.2–242.5
206893.573.6–114.5217192.5–243.8
206995.873.9–113.3216.7196.5–240.8
20709677.9–115.5214.6189–244.5
207193.977.5–115.9221.2192.7–244.8
207295.974.8–115.6217.5194.7–239.4
207396.277.3–119.2220.5197.7–248.2
207497.377.3–117215.3193.3–240.1
207594.972.5–115.4220.7195.5–247.6
207697.575.2–117.6219.5196.2–243.5
207797.773.1–119.7220.8193.8–249.9
207898.678.4–118.2220.7198.9–246.9
207997.376.8–118.8219.4195.2–249.3
208097.374.3–117.5221.7197.8–246
208196.974.9–120.1222.4199.1–247
208298.678.3–115.8220.1198.5–243
2083101.378.9–120.3217.4195.3–258.9
208499.577.9–119.5223.7195.6–246
2085100.778.1–126.4225.1203.3–254.4
2086101.576.9–123.5223.1196.5–256
2087101.280.6–126.2225.8201.1–255.8
2088103.379–126224197.1–259.9
2089101.581.2–123225.6200.2–255.2
2090102.982.6–122.1225.1201.5–253
2091103.378.7–124.2228.1201.9–261.8
2092101.981.8–120.9227.3200.1–261.6
2093100.480.6–121.2223.6200.9–258.9
2094103.977.9–123.4223200.3–250.5
2095103.380.5–126228205.2–255.9
2096105.378.9–125.5225.1201.6–257.9
2097104.984–123.6222.6200.1–251.1
2098103.776.7–126.2225.6199.6–261
2099105.283.3–128.4223.2200.6–251.1
2100103.880.4–125.6225.7204.7–259.7

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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