Mexico vs Pakistan
Mexico vs Pakistan: Tropical nights
Tropical nights in 2014: 103.7 nights in Mexico and 149.9 nights in Pakistan, in the CMIP6 climate models’ median run. In 2014 the value was higher in Pakistan, by 46.2 nights, or 1.45 times that in Mexico.
nights a year · CMIP6
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 Mexico at 142.8 nights and Pakistan at 177.6 nights in 2100.
Every year
nights a year · CMIP6
| Year | Mexico | Pakistan |
|---|---|---|
| 2014 | 103.7 | 149.9 |
| 2013 | 103.9 | 149.1 |
| 2012 | 102.8 | 149.9 |
| 2011 | 102.9 | 149 |
| 2010 | 101.5 | 148.4 |
| 2009 | 101.8 | 147.1 |
| 2008 | 100.1 | 147.4 |
| 2007 | 99.1 | 147.3 |
| 2006 | 99.8 | 146.7 |
| 2005 | 99.5 | 146.5 |
| 2004 | 99.4 | 147.5 |
| 2003 | 98.3 | 146 |
| 2002 | 99.1 | 148.3 |
| 2001 | 98.7 | 145.4 |
| 2000 | 97.9 | 144.7 |
| 1999 | 96.6 | 146.9 |
| 1998 | 95.8 | 144.8 |
| 1997 | 95.9 | 143.2 |
| 1996 | 93.8 | 141.2 |
| 1995 | 92.7 | 141.8 |
| 1994 | 90.7 | 142.1 |
| 1993 | 89 | 140.4 |
| 1992 | 88.5 | 139.9 |
| 1991 | 93.4 | 142.5 |
| 1990 | 94.9 | 142.6 |
| 1989 | 93 | 142.5 |
| 1988 | 92.1 | 140.3 |
| 1987 | 92 | 140 |
| 1986 | 90.2 | 140 |
| 1985 | 90 | 140 |
| 1984 | 88 | 138.9 |
| 1983 | 86.7 | 136.3 |
| 1982 | 88.7 | 138.5 |
| 1981 | 91.5 | 141.5 |
| 1980 | 90.1 | 139.5 |
| 1979 | 90.8 | 139.1 |
| 1978 | 89 | 139 |
| 1977 | 89 | 138.6 |
| 1976 | 89.1 | 139.2 |
| 1975 | 86.8 | 136.5 |
| 1974 | 87.9 | 138.7 |
| 1973 | 88.6 | 137.8 |
| 1972 | 87.7 | 137.4 |
| 1971 | 86.8 | 136 |
| 1970 | 86.1 | 137.7 |
| 1969 | 87.5 | 135.9 |
| 1968 | 87.1 | 136.6 |
| 1967 | 86.7 | 135.2 |
| 1966 | 86.4 | 136.9 |
| 1965 | 84.9 | 138.3 |
| 1964 | 84.7 | 135.1 |
| 1963 | 87.1 | 135.7 |
| 1962 | 88 | 137 |
| 1961 | 89.5 | 138.6 |
| 1960 | 89.7 | 139 |
| 1959 | 89.6 | 138.6 |
| 1958 | 89.1 | 137.7 |
| 1957 | 89 | 140 |
| 1956 | 88.5 | 137.8 |
| 1955 | 88.2 | 137.5 |
| 1954 | 88.4 | 137.8 |
| 1953 | 88.6 | 136.9 |
| 1952 | 87.8 | 138.1 |
| 1951 | 89.4 | 136.7 |
| 1950 | 88.1 | 139.1 |
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
| Year | Mexico | Pakistan |
|---|---|---|
| 2015 | 106.192.9–118.4 | 152.4138.7–163.3 |
| 2016 | 107.695–120 | 150.6139.4–161.7 |
| 2017 | 108.696.3–119.7 | 151.3138.8–162 |
| 2018 | 10997.1–120.4 | 152.6139.8–161.8 |
| 2019 | 110.396.4–123 | 151.8138.1–163.3 |
| 2020 | 109.696.8–121.8 | 153.1140.3–164.5 |
| 2021 | 111.296.9–124.1 | 154.1140.6–165.7 |
| 2022 | 109.796–121.7 | 153.1140.2–165.7 |
| 2023 | 111.898.6–125.3 | 155.5141.6–165.9 |
| 2024 | 112.298.2–126.2 | 156.8143.3–168.7 |
| 2025 | 11298.8–125.8 | 155.7141.5–168.6 |
| 2026 | 113.999.5–126.4 | 155.3142.2–167.9 |
| 2027 | 112.999.5–128.3 | 156.8140.9–168.9 |
| 2028 | 115.2101.9–127.9 | 156.5143.9–167.6 |
| 2029 | 115.6101.9–127.9 | 155.9141.5–167.7 |
| 2030 | 115.9101.7–128.4 | 156.3143.3–167.6 |
| 2031 | 116.1100.9–129.9 | 157.3144.4–168.1 |
| 2032 | 116.1102.5–129.1 | 157.4142.5–169.6 |
| 2033 | 117.5102.5–131.1 | 157.7143.6–169.4 |
| 2034 | 117.2104.1–130.3 | 159.5145.6–173.4 |
| 2035 | 116.4103.1–130.3 | 159.3146.7–170.3 |
| 2036 | 117.8105.1–131 | 159.1147.5–171.4 |
| 2037 | 118.6104.3–131.7 | 162.2147.5–175.3 |
| 2038 | 121107.5–133.4 | 161.4148.6–171.7 |
| 2039 | 121.3107–135.6 | 160148.2–170.4 |
| 2040 | 121.9108.1–135.1 | 160.9147.9–171.3 |
| 2041 | 121.3105.3–134.6 | 160.8146.7–171.7 |
| 2042 | 122.7107.7–137.1 | 162.3149.9–175.6 |
| 2043 | 122.4108.1–137.5 | 161.1150.3–173.8 |
| 2044 | 121.9108–135.6 | 163150.9–173.9 |
| 2045 | 123.1108.8–139.2 | 163149.5–174.8 |
| 2046 | 123.8109.9–139.4 | 163.5149.8–177.2 |
| 2047 | 125.6111.9–139.4 | 165.2151.8–178.5 |
| 2048 | 126.3113–140.3 | 166.4154.1–179.4 |
| 2049 | 127111.2–140.8 | 165150.8–178.2 |
| 2050 | 128.1112.6–142.5 | 166.9153.5–179.3 |
| 2051 | 127.2113.4–140.8 | 165.6150.8–180 |
| 2052 | 126.2112.5–141.1 | 166.7155.4–179.5 |
| 2053 | 128.4111.5–142.7 | 166.3154.2–178.8 |
| 2054 | 128.1113.1–142.3 | 167.5153.9–181 |
| 2055 | 129114.4–144.7 | 167.8155.8–182.5 |
| 2056 | 129.5114.3–143.8 | 166.3153.6–179.7 |
| 2057 | 130.3113.5–145.9 | 168.3153.9–182.3 |
| 2058 | 128.8114.1–144.5 | 167.5157–179.9 |
| 2059 | 129.5114.5–144.5 | 170.9155.9–183.8 |
| 2060 | 131.4115.5–146.5 | 170.3156.5–181.8 |
| 2061 | 131.3118.4–146.8 | 168.8156.8–179.6 |
| 2062 | 130.8115.1–146.3 | 171.6153.5–186.5 |
| 2063 | 131.2115.6–147.9 | 171.3159.5–183.8 |
| 2064 | 132.2116.5–147.8 | 170.2155.3–184.5 |
| 2065 | 133.1115.8–148.6 | 169.7156.4–185 |
| 2066 | 133.3117.2–149.4 | 172.2157–186.7 |
| 2067 | 133.3117–150.3 | 173.2160.2–186.3 |
| 2068 | 134.6117.4–150.5 | 172.6157.7–186.3 |
| 2069 | 134.4117.8–150.9 | 171.8157.3–185.6 |
| 2070 | 134.2116.7–151.8 | 171.7158.9–186.7 |
| 2071 | 136.3120.8–152.7 | 173.4158.7–186.8 |
| 2072 | 137.2119.9–153.1 | 174161.5–186.9 |
| 2073 | 136.1119.1–153.6 | 175.6157.2–187.9 |
| 2074 | 136119.7–152.2 | 173.5160–186.3 |
| 2075 | 135.2118.5–151.8 | 173161.5–187.8 |
| 2076 | 136.3117.4–154.7 | 172.9158.8–186.7 |
| 2077 | 136.8119.6–152.8 | 175161.3–187.8 |
| 2078 | 137.1118.3–154.2 | 174.4160.9–189.3 |
| 2079 | 138.1121.3–157.1 | 172.5158.3–187.7 |
| 2080 | 137.6120.5–157.9 | 175.1160.7–189.2 |
| 2081 | 137.8120.7–154.7 | 174.9159.2–190.2 |
| 2082 | 138.7121.6–155.2 | 175.4161.8–190.6 |
| 2083 | 139.2119.3–158.8 | 176.5161.8–190.8 |
| 2084 | 140.3123.4–157.5 | 176.1160.9–190.5 |
| 2085 | 139.2120.9–157.2 | 176.3161.9–193.6 |
| 2086 | 139.8121–157.8 | 173.9160–189.1 |
| 2087 | 139.5121.5–157.4 | 176161–193.1 |
| 2088 | 141121.8–159.9 | 175.4160.5–195.2 |
| 2089 | 140.4121.7–158.9 | 177.2164.2–191.7 |
| 2090 | 141.2123–160.7 | 177.7163.9–192.2 |
| 2091 | 141.8123–161.6 | 177.8162.8–192.2 |
| 2092 | 141.3122.5–159.3 | 178.7162.9–192.9 |
| 2093 | 141.4124.3–161 | 177164–191 |
| 2094 | 142123.3–159.6 | 176.8164.1–190.7 |
| 2095 | 143.5124–160.7 | 178.6163.8–193.1 |
| 2096 | 142.3125–161.3 | 177.8163.7–192.5 |
| 2097 | 141.2123.2–160 | 177.3160.4–192.5 |
| 2098 | 142.2122.5–162 | 178.7162.6–195.7 |
| 2099 | 141.8122.4–160.7 | 176159.9–193.2 |
| 2100 | 142.8124.3–160.8 | 177.6162.2–193 |
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
Mexico vs Pakistan
Health
- Life expectancyMexico: 75.1 years in 2023Pakistan: 67.7 years in 2023
- Child mortalityMexico: 1.3 per 100 live births in 2024Pakistan: 5.6 per 100 live births in 2024
- Infant mortalityMexico: 10.4 per 1,000 live births in 2023Pakistan: 49.4 per 1,000 live births in 2023
- Safe drinking waterMexico: 43% in 2022Pakistan: 50.6% in 2022
- DepressionMexico: 2.79% in 2017Pakistan: 3.33% in 2017
- Suicide rateMexico: 5.9 per 100,000 people in 2017Pakistan: 4.4 per 100,000 people in 2017
People
- PopulationMexico: 130 million people in 2023Pakistan: 248 million people in 2023
- Population growthMexico: 0.88% a year in 2023Pakistan: 1.48% a year in 2023
- Fertility rateMexico: 1.91 births per woman in 2023Pakistan: 3.61 births per woman in 2023
- Urban populationMexico: 80% in 2025Pakistan: 39.5% in 2025
- Median ageMexico: 28.9 years in 2023Pakistan: 20.3 years in 2023
- People aged 65 and overMexico: 8% in 2023Pakistan: 4.2% in 2023
- Net migration rateMexico: -0.8 per 1,000 people in 2023Pakistan: -6.5 per 1,000 people in 2023
Economy
Education
Politics
Conflict
Military
- Military spendingMexico: 0.74% of GDP in 2025Pakistan: 2.91% of GDP in 2025
- Military spending in US dollarsMexico: $13.8B in 2025Pakistan: $11.5B in 2025
- Military spending per personMexico: $104 in 2025Pakistan: $47 in 2025
- Military share of state spendingMexico: 2.5% of government spending in 2025Pakistan: 13.8% of government spending in 2025
- Armed forces personnelMexico: 341,000 people in 2020Pakistan: 943,000 people in 2020
- National powerMexico: 1.14% of world capability in 2022Pakistan: 1.77% of world capability in 2022
- Armed forces, share of workersMexico: 0.64% of the labour force in 2020Pakistan: 1.25% of the labour force in 2020
- Arms importsMexico: 9 million TIV in 2025Pakistan: 706 million TIV in 2025
- Arms exportsMexico: 1 million TIV in 2019Pakistan: 127 million TIV in 2025