China vs India

China vs India: Tropical nights

Tropical nights in 2014: 41.5 nights in China and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in India, by 174.1 nights, or 5.2 times that in China.

nights a year · CMIP6

China vs India: Tropical nightsTropical nights in 2014: 41.5 nights in China and 215.5 nights in India, in the CMIP6 climate models’ median run. In 2014 the value was higher in India, by 174.1 nights, or 5.2 times that in China.
ChinaIndiaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • India 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 India at 250.4 nights in 2100.

Every year

nights a year · CMIP6

YearChinaIndia
201441.5215.5
201341.7216
201240.8217.4
201140.2215.5
201040.5215.2
200939.5213.7
200839.2213.7
200738.7213.3
200639.5212.5
200539.5212.9
200439.7214.9
200338.5212.1
200238.8213
200139.5212.2
200038.6210.8
199938.5211.9
199837.6210.3
199737.1209.5
199636.6207
199535.1208.8
199434.9207.1
199333.2206
199232.3203.5
199135.9208
199036.4209.9
198936.1208
198835.1207.3
198734.5207.2
198634207.2
198533.5205.9
198433.4206.7
198331.5203.3
198234.1205.7
198134.2208.4
198034.3205.3
197933.8205.5
197834.8204.1
197733.3205.9
197632.7204.6
197533.1202.6
197433.3205.3
197333.1205.6
197232.6203.8
197133203.6
197032.4202.6
196933.4203.6
196832.8201.7
196733.4201.6
196633.4203.9
196532.5202.4
196432.1201.2
196334.5201.8
196234203.8
196134.6206.3
196034.1206
195934206.1
195835204
195734.4206.5
195634.6204
195534.2203.2
195434.2206
195334.3204
195234.3204.4
195135.1204.3
195034.9206.3
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearChinaIndia
201542.334.8–49.8216.9202.1–228.4
201642.134.4–50215202.5–227.6
201743.135.3–51.6216.2202.1–228.5
201842.335.5–49.5218.3204.5–231.4
201943.836.5–51.1217.4202.3–230.4
202043.736.8–51.1217.6203.1–232
202144.136–52.1219.7204.5–233.2
202244.737.5–52.7220.5205.8–233
202345.737.8–53.4220.4206.4–233.7
202445.738.1–54222.6208.1–236.3
202546.337.5–54.8219.7202.7–236.2
202646.237.6–55.5220.2204.2–236.8
202746.138–54.9223.6207.1–239
202846.438.4–54.3222.1205.1–235.7
202946.939.1–55.6225.4210–240.3
203047.138.8–55.3222.7207.3–235.6
20314738.8–56223.8207.1–237.8
203248.339.3–57.4225.9210–240.5
203347.939.7–56.6223.8209.3–235.4
203448.440.5–57.3225.8210–242.7
203549.740.8–58.6224.9210.6–240.9
20364940.1–58.2224.2210.4–240.3
20374941.2–57.6228.3213.6–242.6
203850.542.4–59.3228.1212.6–241.4
203949.641.2–59.2227.4211.9–242.8
204050.942.4–60.4227212.2–242
204151.342.5–61.1227.1210.7–240.5
204251.642–61.5229.1214.8–244.2
204350.742.7–61228.9214.5–244
204451.942.4–61.9229.7214.7–244.2
204551.542.8–61.1231.2216.6–246.1
20465343.7–62.7232.6216.2–248.6
204753.544.5–62.5232.4215.5–250
204853.144–62.6235.6218.5–254.3
204952.843.8–63.3235.3218.3–249.9
205053.644.4–63.8233.5216.6–253.4
205154.345.1–64.8234.9218.6–249.9
205253.444.6–63.2234219.4–249.3
205354.244.2–64.2234.9219.5–252.5
205454.545.3–64.8237.2219.4–253.1
20555545.1–65.8237.2220.7–256.6
205655.245.1–66.6238.8221.2–254.9
205754.844.9–65.7235.7218.5–253.8
205855.145.8–67.7238.8222.8–254.1
205955.345.1–67.2241.1224.9–256.2
206057.246.9–68.1240.9225.6–255.6
206156.546.6–66.3237.9220.6–253.7
206256.846.9–68.5239.9221.2–259.7
206357.247.2–68.6239.9222.3–256.1
20645747.1–67.7240223.8–256.3
206557.347.1–67.8240.9222.9–257.3
206657.347.9–68.7241.5224.1–258.6
206757.546.4–68.2241.6224.8–257.9
206858.748.5–70.5242.3224.6–262.1
206958.548.4–69242.8225.4–259.1
20705847.6–71.7240.1225.3–257.1
207159.347.4–71.6241.8223.7–260.2
207259.248.1–71.5242.6225.4–259.2
207359.849.1–70.9243.8228–259.3
207459.648.7–71.1241.6226.9–258.4
207558.748.3–71.4243.5226.4–258.2
207660.249–70.9243.2224.6–259.9
207760.851.1–72.4243.7226.6–264.6
207859.648.8–72.4246.7230.1–261.5
207960.750.1–72.6244.9226.4–261.3
208059.950–72.3246.7227–263.7
208160.950–73.2247.5230.4–264.8
20826149.8–73.3244.6227.9–262.3
208361.251.2–73.6247.5227.8–265.1
208461.749.7–74.6247.3228.3–266.8
208561.250.8–75.2246.5227.5–267.1
208661.648.9–74.5245.6227.7–266.5
208761.650.6–75245.5226.7–266.2
208862.750.5–77.1247229.4–266.9
208961.950–75.2248.1230–266.3
209062.551.4–73.7249228.9–266.4
209163.852–75.7248.9230–266.5
209263.251.2–75.1249.8232.3–267.8
209363.252–75.4248.1229–266.5
20946351.1–76.3249.1230.6–268.4
209563.952.8–76.4251233.2–270
209663.852.2–76.8247.8231.4–269.3
209762.750.7–75.1251.1231.4–268
209863.451.2–76.8252.3230.8–268.3
209963.851.9–76.1248.7230.1–268.3
210063.351.7–76.2250.4232.9–266.7

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

China vs India

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment