巴基斯坦与坦桑尼亚对比
巴基斯坦与坦桑尼亚:热带夜
2014 年热带夜:巴基斯坦为 149.9 夜,坦桑尼亚为 106.3 夜(CMIP6 气候模型中位数模拟)。 2014 年巴基斯坦的数值较高,高出 43.6 夜,是坦桑尼亚的 1.41 倍。
每年夜数 · CMIP6
数据解读
- 自 1950 年以来,在两国都有数据的每一年,巴基斯坦的数值都更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年巴基斯坦为 177.6 夜,坦桑尼亚为 208 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 巴基斯坦 | 坦桑尼亚 |
|---|---|---|
| 2014 | 149.9 | 106.3 |
| 2013 | 149.1 | 105.5 |
| 2012 | 149.9 | 108.4 |
| 2011 | 149 | 109 |
| 2010 | 148.4 | 103.9 |
| 2009 | 147.1 | 101.1 |
| 2008 | 147.4 | 100.3 |
| 2007 | 147.3 | 99.5 |
| 2006 | 146.7 | 100.4 |
| 2005 | 146.5 | 98.7 |
| 2004 | 147.5 | 100.4 |
| 2003 | 146 | 99.6 |
| 2002 | 148.3 | 98.4 |
| 2001 | 145.4 | 101.5 |
| 2000 | 144.7 | 94.9 |
| 1999 | 146.9 | 94.2 |
| 1998 | 144.8 | 96.8 |
| 1997 | 143.2 | 93.5 |
| 1996 | 141.2 | 89.6 |
| 1995 | 141.8 | 88.5 |
| 1994 | 142.1 | 85.4 |
| 1993 | 140.4 | 81.2 |
| 1992 | 139.9 | 80.1 |
| 1991 | 142.5 | 89.6 |
| 1990 | 142.6 | 91.1 |
| 1989 | 142.5 | 89.1 |
| 1988 | 140.3 | 87.6 |
| 1987 | 140 | 88.5 |
| 1986 | 140 | 89.4 |
| 1985 | 140 | 83 |
| 1984 | 138.9 | 83.1 |
| 1983 | 136.3 | 82.1 |
| 1982 | 138.5 | 84.8 |
| 1981 | 141.5 | 88 |
| 1980 | 139.5 | 85 |
| 1979 | 139.1 | 85.5 |
| 1978 | 139 | 82.9 |
| 1977 | 138.6 | 84.1 |
| 1976 | 139.2 | 81 |
| 1975 | 136.5 | 80.8 |
| 1974 | 138.7 | 82.2 |
| 1973 | 137.8 | 83.6 |
| 1972 | 137.4 | 81.4 |
| 1971 | 136 | 80.7 |
| 1970 | 137.7 | 81.8 |
| 1969 | 135.9 | 79.5 |
| 1968 | 136.6 | 79.1 |
| 1967 | 135.2 | 77.5 |
| 1966 | 136.9 | 78.1 |
| 1965 | 138.3 | 78 |
| 1964 | 135.1 | 73.8 |
| 1963 | 135.7 | 73.1 |
| 1962 | 137 | 81.1 |
| 1961 | 138.6 | 82.6 |
| 1960 | 139 | 83.9 |
| 1959 | 138.6 | 81.4 |
| 1958 | 137.7 | 82.1 |
| 1957 | 140 | 80.9 |
| 1956 | 137.8 | 80 |
| 1955 | 137.5 | 81.6 |
| 1954 | 137.8 | 81.4 |
| 1953 | 136.9 | 80.6 |
| 1952 | 138.1 | 81.4 |
| 1951 | 136.7 | 82.1 |
| 1950 | 139.1 | 80.7 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 巴基斯坦 | 坦桑尼亚 |
|---|---|---|
| 2015 | 152.4138.7–163.3 | 114.895.2–137.4 |
| 2016 | 150.6139.4–161.7 | 108.391.6–125.6 |
| 2017 | 151.3138.8–162 | 114.893.6–137.8 |
| 2018 | 152.6139.8–161.8 | 116.497.4–137.1 |
| 2019 | 151.8138.1–163.3 | 113.495.2–133.2 |
| 2020 | 153.1140.3–164.5 | 119.396.2–143.5 |
| 2021 | 154.1140.6–165.7 | 119.5100.9–147.1 |
| 2022 | 153.1140.2–165.7 | 124.4105.3–147.4 |
| 2023 | 155.5141.6–165.9 | 122.1102.1–147.8 |
| 2024 | 156.8143.3–168.7 | 126.2100–150.1 |
| 2025 | 155.7141.5–168.6 | 124.6100.9–154 |
| 2026 | 155.3142.2–167.9 | 126.999.1–155.6 |
| 2027 | 156.8140.9–168.9 | 128102.9–147.7 |
| 2028 | 156.5143.9–167.6 | 129.9106.4–152.1 |
| 2029 | 155.9141.5–167.7 | 134.1111–156.5 |
| 2030 | 156.3143.3–167.6 | 129.4106.4–151.1 |
| 2031 | 157.3144.4–168.1 | 136.4115.9–158.4 |
| 2032 | 157.4142.5–169.6 | 135.1114–166.8 |
| 2033 | 157.7143.6–169.4 | 135.2110.9–161.9 |
| 2034 | 159.5145.6–173.4 | 134.7112.5–166.3 |
| 2035 | 159.3146.7–170.3 | 140.2114.6–165 |
| 2036 | 159.1147.5–171.4 | 137.8113.3–165.5 |
| 2037 | 162.2147.5–175.3 | 142.9121.5–168.9 |
| 2038 | 161.4148.6–171.7 | 147.9124.3–169.3 |
| 2039 | 160148.2–170.4 | 144.3117.6–171.3 |
| 2040 | 160.9147.9–171.3 | 140.5117–178 |
| 2041 | 160.8146.7–171.7 | 149.1121.7–175.6 |
| 2042 | 162.3149.9–175.6 | 146.3120.5–185.3 |
| 2043 | 161.1150.3–173.8 | 144.6117–173 |
| 2044 | 163150.9–173.9 | 147.7121.2–175.8 |
| 2045 | 163149.5–174.8 | 150.1125.2–183.4 |
| 2046 | 163.5149.8–177.2 | 161.5128.6–192.2 |
| 2047 | 165.2151.8–178.5 | 160.2129.7–194.4 |
| 2048 | 166.4154.1–179.4 | 158.8132.7–193.1 |
| 2049 | 165150.8–178.2 | 157.6131.1–196 |
| 2050 | 166.9153.5–179.3 | 159.7127.8–192 |
| 2051 | 165.6150.8–180 | 163.2135.5–197.8 |
| 2052 | 166.7155.4–179.5 | 161.9136.2–199.1 |
| 2053 | 166.3154.2–178.8 | 160.6127.5–197.7 |
| 2054 | 167.5153.9–181 | 163.2131.5–200.2 |
| 2055 | 167.8155.8–182.5 | 167.4137–208.3 |
| 2056 | 166.3153.6–179.7 | 166.4130.8–209.7 |
| 2057 | 168.3153.9–182.3 | 168134.6–208.3 |
| 2058 | 167.5157–179.9 | 168.7134.9–210.3 |
| 2059 | 170.9155.9–183.8 | 174.7144.9–219.5 |
| 2060 | 170.3156.5–181.8 | 181.7138.1–219.8 |
| 2061 | 168.8156.8–179.6 | 171.8135.5–218.1 |
| 2062 | 171.6153.5–186.5 | 177.5139.9–224 |
| 2063 | 171.3159.5–183.8 | 181.4140.1–213.8 |
| 2064 | 170.2155.3–184.5 | 185.3140.1–215.2 |
| 2065 | 169.7156.4–185 | 183.5141.1–221.8 |
| 2066 | 172.2157–186.7 | 181.9146.3–219.3 |
| 2067 | 173.2160.2–186.3 | 178.8138.8–229.2 |
| 2068 | 172.6157.7–186.3 | 186144.2–228.4 |
| 2069 | 171.8157.3–185.6 | 183.7141.7–225.3 |
| 2070 | 171.7158.9–186.7 | 180.7140.4–228.2 |
| 2071 | 173.4158.7–186.8 | 184.9146.9–235.2 |
| 2072 | 174161.5–186.9 | 191.3155–226.1 |
| 2073 | 175.6157.2–187.9 | 191.6152.4–235.6 |
| 2074 | 173.5160–186.3 | 183.3149.7–231.7 |
| 2075 | 173161.5–187.8 | 183.8144.8–233 |
| 2076 | 172.9158.8–186.7 | 191.1150.9–233.2 |
| 2077 | 175161.3–187.8 | 191.3152.6–238.2 |
| 2078 | 174.4160.9–189.3 | 189156.6–233.8 |
| 2079 | 172.5158.3–187.7 | 190.5147–237.3 |
| 2080 | 175.1160.7–189.2 | 197.3150.7–241.2 |
| 2081 | 174.9159.2–190.2 | 195.6153.4–237.4 |
| 2082 | 175.4161.8–190.6 | 194.5157.3–237.3 |
| 2083 | 176.5161.8–190.8 | 193.2151–249.8 |
| 2084 | 176.1160.9–190.5 | 201.1152.2–246.7 |
| 2085 | 176.3161.9–193.6 | 204.2162.3–252.3 |
| 2086 | 173.9160–189.1 | 195156–248.7 |
| 2087 | 176161–193.1 | 196.7160.8–244.5 |
| 2088 | 175.4160.5–195.2 | 208.4154.7–246.9 |
| 2089 | 177.2164.2–191.7 | 201.3158.6–248.2 |
| 2090 | 177.7163.9–192.2 | 197.9160.7–253.6 |
| 2091 | 177.8162.8–192.2 | 210161.6–256 |
| 2092 | 178.7162.9–192.9 | 205.8158.3–253.6 |
| 2093 | 177164–191 | 207.2161.2–251.9 |
| 2094 | 176.8164.1–190.7 | 207.9161.3–250.6 |
| 2095 | 178.6163.8–193.1 | 214.2166.4–258.5 |
| 2096 | 177.8163.7–192.5 | 205.3159.8–257.4 |
| 2097 | 177.3160.4–192.5 | 206.6158.4–256.8 |
| 2098 | 178.7162.6–195.7 | 209.1161–258.3 |
| 2099 | 176159.9–193.2 | 208.5160.1–256 |
| 2100 | 177.6162.2–193 | 208158.6–258.6 |
分别查看各国
须知
- 一年中气温始终高于 20 °C 的夜晚数,取全国平均。
- 来源:World Bank Climate Change Knowledge Portal, CMIP6 multi-model median。
- 虚线为CMIP6 模型中位数(SSP2-4.5,中间路径),是一种情景而非预报;阴影带为其模型第 10–90 百分位。
- 气候模型值为 CMIP6 各模型的中位数:2014 年及以前按历史排放模拟,此后按中间路径 SSP2-4.5 模拟;它们并非实测数据。
各图层如何运作、数据从何而来,以及它们无法告诉你什么: 历年各国数据
巴基斯坦与坦桑尼亚对比
健康
人口与社会
经济
教育
政治
冲突
军用
- 军费开支巴基斯坦:2025 年为 GDP 的 2.91%坦桑尼亚:2025 年为 GDP 的 1.16%
- 军费开支(美元)巴基斯坦:2025 年为 US$115亿坦桑尼亚:2025 年为 US$9.83亿
- 人均军费开支巴基斯坦:2025 年为 US$47坦桑尼亚:2025 年为 US$15
- 军费占政府支出比例巴基斯坦:2025 年为 13.8%(占政府支出)坦桑尼亚:2025 年为 5.8%(占政府支出)
- 武装部队人员巴基斯坦:2020 年为 943,000 人坦桑尼亚:2020 年为 28,000 人
- 国家实力巴基斯坦:2022 年为 1.77%(占全球实力)坦桑尼亚:2022 年为 0.25%(占全球实力)
- 武装部队占劳动力比例巴基斯坦:2020 年为 1.25%(占劳动力)坦桑尼亚:2020 年为 0.1%(占劳动力)
- 武器进口巴基斯坦:2025 年为 7.06亿 TIV坦桑尼亚:2025 年为 400万 TIV