France vs Pakistan

France vs Pakistan: Tropical nights

Tropical nights in 2014: 3.1 nights in France and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Pakistan, by 146.8 nights, or 49 times that in France.

nights a year · CMIP6

France vs Pakistan: Tropical nightsTropical nights in 2014: 3.1 nights in France and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Pakistan, by 146.8 nights, or 49 times that in France.
FrancePakistanCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Pakistan has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts France at 19.2 nights and Pakistan at 177.6 nights in 2100.

Every year

nights a year · CMIP6

YearFrancePakistan
20143.1149.9
20133.1149.1
20122.9149.9
20112.7149
20103.9148.4
20092.5147.1
20082.4147.4
20072.1147.3
20062.6146.7
20052.9146.5
20042.7147.5
20032.6146
20021.8148.3
20012.3145.4
20001.8144.7
19992.1146.9
19981.5144.8
19971.6143.2
19961.5141.2
19951.3141.8
19941.5142.1
19931.1140.4
19921139.9
19911.8142.5
19901.9142.6
19891.2142.5
19881.2140.3
19871.3140
19860.9140
19850.9140
19841.1138.9
19831.1136.3
19821138.5
19811.1141.5
19801.2139.5
19790.9139.1
19781.3139
19770.9138.6
19760.8139.2
19750.9136.5
19741.2138.7
19730.9137.8
19720.9137.4
19711136
19700.9137.7
19691135.9
19680.9136.6
19670.8135.2
19660.8136.9
19650.7138.3
19641135.1
19630.9135.7
19621.1137
19610.9138.6
19601.1139
19591.2138.6
19581137.7
19571140
19561.2137.8
19551.1137.5
19541.3137.8
19531136.9
19521.3138.1
19511.1136.7
19501.2139.1
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearFrancePakistan
20153.61.5–8.6152.4138.7–163.3
20164.11.5–9.9150.6139.4–161.7
20173.51.3–10.2151.3138.8–162
20183.91.7–10.8152.6139.8–161.8
20194.51.6–9151.8138.1–163.3
20204.11.6–10.5153.1140.3–164.5
20214.51.3–13.2154.1140.6–165.7
202251.5–12.5153.1140.2–165.7
20234.81.6–12.5155.5141.6–165.9
20245.51.8–11.2156.8143.3–168.7
20255.81.5–12.1155.7141.5–168.6
20266.22.1–12.7155.3142.2–167.9
20275.41.7–11.2156.8140.9–168.9
20285.91.7–13.3156.5143.9–167.6
20296.31.9–12.6155.9141.5–167.7
20305.82.1–11.9156.3143.3–167.6
20315.92–11.8157.3144.4–168.1
20325.92.7–12.9157.4142.5–169.6
203372.5–13.6157.7143.6–169.4
20347.92.4–17.3159.5145.6–173.4
20356.92.4–14.4159.3146.7–170.3
20367.32.6–14.6159.1147.5–171.4
20377.32.6–13.3162.2147.5–175.3
20386.53–15.1161.4148.6–171.7
20396.92.6–14.3160148.2–170.4
20407.72.3–16160.9147.9–171.3
20418.12.6–15.2160.8146.7–171.7
20426.93–16162.3149.9–175.6
20437.92.8–15.6161.1150.3–173.8
20447.93.1–16.6163150.9–173.9
20459.23.2–19.6163149.5–174.8
20468.93.2–17.6163.5149.8–177.2
20479.74–19.2165.2151.8–178.5
20489.13.4–17166.4154.1–179.4
204910.13.7–20.8165150.8–178.2
205010.94.8–18.9166.9153.5–179.3
20519.23.5–18.4165.6150.8–180
2052103.4–21.2166.7155.4–179.5
20538.73.8–18166.3154.2–178.8
20549.74.4–19.2167.5153.9–181
20559.93.9–17.2167.8155.8–182.5
2056114.3–21.8166.3153.6–179.7
205710.94.2–19.8168.3153.9–182.3
205813.85.1–25.7167.5157–179.9
205911.23.3–25170.9155.9–183.8
206012.86.1–22170.3156.5–181.8
206112.64.7–23.2168.8156.8–179.6
206212.36.2–22.4171.6153.5–186.5
2063125.2–24.9171.3159.5–183.8
2064125.3–21.6170.2155.3–184.5
206512.53.9–30.8169.7156.4–185
206611.55.3–22.1172.2157–186.7
206718.38.1–33.3173.2160.2–186.3
2068135.4–23.4172.6157.7–186.3
206915.65.7–25.5171.8157.3–185.6
207013.55.2–29.1171.7158.9–186.7
2071154.4–30.2173.4158.7–186.8
207215.57.4–26174161.5–186.9
207313.96–29.1175.6157.2–187.9
207412.84.3–27.3173.5160–186.3
207513.96.3–25.6173161.5–187.8
2076166.1–33.8172.9158.8–186.7
207713.25–29.8175161.3–187.8
207813.75.1–33.6174.4160.9–189.3
207912.95.3–28.4172.5158.3–187.7
208014.45.4–27.9175.1160.7–189.2
208115.15.8–29.8174.9159.2–190.2
208216.46.1–33.9175.4161.8–190.6
208315.97.9–32176.5161.8–190.8
208414.16.6–27.7176.1160.9–190.5
208516.57.3–30.2176.3161.9–193.6
208619.55.5–32.4173.9160–189.1
2087196.9–38176161–193.1
208818.47.7–35.2175.4160.5–195.2
20891910.6–29.3177.2164.2–191.7
209016.36.8–33.5177.7163.9–192.2
209119.77.6–32.3177.8162.8–192.2
209217.36.1–32.7178.7162.9–192.9
2093156.5–29.8177164–191
209418.68.5–32.8176.8164.1–190.7
209519.25.9–38.9178.6163.8–193.1
209619.37.6–35.5177.8163.7–192.5
209717.36.2–36.1177.3160.4–192.5
209818.16.9–36.3178.7162.6–195.7
209920.37.4–34.6176159.9–193.2
210019.27–36.7177.6162.2–193

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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