Jordan vs Tunisia

Jordan vs Tunisia: Tropical nights

Tropical nights in 2014: 74.7 nights in Jordan and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 35.8 nights, or 1.48 times that in Jordan.

nights a year · CMIP6

Jordan vs Tunisia: Tropical nightsTropical nights in 2014: 74.7 nights in Jordan and 110.5 nights in Tunisia, in the CMIP6 climate models’ median run. In 2014 the value was higher in Tunisia, by 35.8 nights, or 1.48 times that in Jordan.
JordanTunisiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Tunisia has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Jordan at 131.7 nights and Tunisia at 143.8 nights in 2100.

Every year

nights a year · CMIP6

YearJordanTunisia
201474.7110.5
201372.2110.7
201271.9110
201171.4108.9
201071.4109.6
200966.9106.1
200869.4108.6
200764.6106.6
200667.7107.6
200566.2105.6
200467.4105
200368.2105.5
200263103.8
200168.3101.8
200063.8104.5
199962.2100.1
199861.8100.1
199759.2100.1
199656.699.1
199554.195.9
199454.695
199345.291.3
199248.389.9
199152.398.2
199057.798.6
198953.494.7
198850.594.2
198749.592.7
19865293.7
198547.190.6
198444.291.8
198341.590
198247.493.9
198148.393.3
198049.292.5
197941.893.8
197845.190.2
197746.788.3
197645.690.5
19754388.6
197445.188.3
197344.690.5
197244.891
197147.288.8
197044.387.3
196946.390.1
196842.688.9
196741.587.6
19664387.5
196536.884.5
196437.785.7
19634388
19624592.7
196145.488.3
196046.390.7
195946.392.2
195847.291.8
195748.792.3
195648.490
195545.592.7
195442.789.9
195347.889.4
195245.791.8
19514591.6
195041.889.6
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearJordanTunisia
201581.862.6–98.9110.796.9–126.1
201679.261.3–95.2111.596.6–130.1
201782.466.3–96.6116.5102.4–131.8
201884.868.8–102.1115.999.4–131.9
201987.467.5–100.7116.598.5–129.5
202086.866.8–102.2113.899.9–130.1
202188.273.8–101.1117.4104.1–129.3
202288.170–103.7119.7103–137.3
202392.474.7–106.4118.7102.2–131.9
202490.776.3–107.1121107.5–132.6
202594.173.1–105.2120.2100–134
202691.678.6–106.9122.1110.1–134.5
202794.475.7–108.4119103.6–134.1
202892.675.9–106.3121.1104.5–135.4
202995.381.2–107.3121.5110.2–135.8
203096.381.5–111.7121.6104–133.4
203193.876.5–110.6121.8105.7–134.9
203210086.4–110.9125.2111.6–138.9
2033100.683.6–113.6124.7107.6–137.5
203498.882.4–112.3124.6107–141.7
2035101.883.2–115.2126.3115.5–142.6
203697.885.1–116.2126112.5–141.9
203710384.6–117.8126.5110–140
2038102.386.1–122.6126.2111.1–139.1
2039107.190.5–125.7127112.5–142.3
2040106.387.8–125.5127.5112.8–144.3
2041103.787.8–123.2125.5109.1–140.4
2042108.586.5–122.3129.9114.8–145.8
2043105.791–124.9129.1111.6–142
2044105.682.8–125.1127.1112.8–141.8
204511298.8–128128.5113.8–140.8
204611395.5–127.5128.3109.9–144
2047112.293–125.7131.2113.6–147.5
2048111.893.7–129.7129.9114.9–142.3
2049110.384.7–125.6130115.4–143.5
2050112.495.9–127.2132.3117.6–147.6
2051112.397–125.6130.1112.6–148.6
2052110.697.4–125.9132.7116.8–146.7
2053113.798.2–129.9132.5119.5–149.8
2054115.492.5–130.9135.2118.4–148.8
2055115.794.8–130.2135.1119.2–151.6
2056115.394.2–130.5134.8119.6–149.5
2057115.496.7–135.6131.9118.5–148.6
2058116.196.6–136.8137.8122.5–156.5
2059120.998.5–137.1134.9117.1–152.5
2060115.898.7–138.7136.2120.5–150.1
2061118.897.1–132.3139119.4–154
206212091.6–136.4134.9119.1–155.9
2063118.7101.7–135.9138.6119.2–152.5
2064121.4103.3–135.9134.9121.1–152.7
2065120.2100.4–134.9137.1123.3–150.5
2066120.498.5–135136.6119.2–155.1
2067124106.1–139.5138.9124.4–154.3
2068123.2105.3–138.1141.7124.8–159.2
2069118.8105.4–137.2140.3123.5–154.1
2070123104–140.8137123.6–155.3
2071123.6103.8–144.3140.5123.1–156.1
2072124.5106.3–140.9142.6128–154.3
2073126.6104.8–144.4139.3124.7–154.6
2074120.9103–139.6140.1123–156.5
2075121.7103.1–138.1139.6124.5–157.1
2076124.1105.4–144.2143.4125.2–158.8
2077124.2105.3–143.9141.3119.1–158.3
2078124.7105.6–142.8143127.2–155.9
2079132107–143.6144.7123.9–158.5
2080128.9106.2–144.4143.6123.6–158.7
2081125.3108.7–144.8139.9126.3–158.8
2082128107.9–145.2145.5125.9–158.1
2083130.9108–144.7143.4124.3–158.7
2084130.5110.6–145144.8129.6–159.7
2085129.1108.8–141.7145.3124.7–159.5
2086127.5108.9–147.6144.7129.5–162.7
2087129.8106.1–148.4144125.7–159.2
2088132.2114.9–149.4147.3127.2–165.4
2089128.7113.4–148.5142.7125.3–164.8
2090128.2111.9–151.3145.2126.3–165.1
2091132.8112.5–152.1144.9127.4–164.4
2092130.6108.3–152.6148.2126.3–161.1
2093135.8116.2–154.4146.9127.2–165.6
2094135.9116.3–150.6145.7126.8–160.4
2095133112.7–149.6145.5125.4–161.5
2096130.4108.1–151.3146.3130–169.4
2097134.5113.5–155.4144.6125.7–160.6
2098132.5114.9–152.3147129.6–161.9
2099132.1115.3–145.3145.8130.3–163.7
2100131.7111.2–153.1143.8124.8–163.8

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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