巴基斯坦与菲律宾对比
巴基斯坦与菲律宾:35 °C 以上天数
2014 年35 °C 以上天数:巴基斯坦为 118.6 天,菲律宾为 1.2 天(CMIP6 气候模型中位数模拟)。 2014 年巴基斯坦的数值较高,高出 117.4 天,是菲律宾的 96 倍。
每年天数 · 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 147.6 天,菲律宾为 8.8 天。
逐年数据
每年天数 · CMIP6
| 年份 | 巴基斯坦 | 菲律宾 |
|---|---|---|
| 2014 | 118.6 | 1.2 |
| 2013 | 117.5 | 1.4 |
| 2012 | 117.5 | 1.3 |
| 2011 | 118 | 1.2 |
| 2010 | 114.3 | 1.5 |
| 2009 | 115.3 | 1.3 |
| 2008 | 115.4 | 1.1 |
| 2007 | 112.5 | 1.1 |
| 2006 | 112.9 | 1.2 |
| 2005 | 114.9 | 1.1 |
| 2004 | 116.1 | 1.1 |
| 2003 | 114.6 | 1 |
| 2002 | 115.9 | 1 |
| 2001 | 114.4 | 1.1 |
| 2000 | 114.6 | 0.9 |
| 1999 | 114.2 | 0.9 |
| 1998 | 111.7 | 1.1 |
| 1997 | 112 | 0.8 |
| 1996 | 108.3 | 0.7 |
| 1995 | 110 | 0.7 |
| 1994 | 108.6 | 0.7 |
| 1993 | 107.2 | 0.7 |
| 1992 | 105.2 | 0.5 |
| 1991 | 110.6 | 0.8 |
| 1990 | 110.7 | 1 |
| 1989 | 110.9 | 0.7 |
| 1988 | 109.8 | 0.7 |
| 1987 | 108.3 | 0.7 |
| 1986 | 108.7 | 0.8 |
| 1985 | 105.6 | 0.6 |
| 1984 | 108 | 0.7 |
| 1983 | 104.7 | 0.5 |
| 1982 | 108 | 0.8 |
| 1981 | 109.5 | 0.7 |
| 1980 | 109.7 | 0.7 |
| 1979 | 108.7 | 0.8 |
| 1978 | 108.6 | 0.5 |
| 1977 | 106.5 | 0.7 |
| 1976 | 108.2 | 0.6 |
| 1975 | 105 | 0.4 |
| 1974 | 108.8 | 0.5 |
| 1973 | 108 | 0.6 |
| 1972 | 104.5 | 0.6 |
| 1971 | 106.2 | 0.6 |
| 1970 | 106.5 | 0.4 |
| 1969 | 105.8 | 0.6 |
| 1968 | 104.4 | 0.5 |
| 1967 | 106.4 | 0.5 |
| 1966 | 106.4 | 0.5 |
| 1965 | 106 | 0.5 |
| 1964 | 103 | 0.5 |
| 1963 | 104.3 | 0.5 |
| 1962 | 106.7 | 0.7 |
| 1961 | 108.7 | 0.7 |
| 1960 | 108.7 | 0.7 |
| 1959 | 110.4 | 0.5 |
| 1958 | 108.5 | 0.7 |
| 1957 | 110.7 | 0.7 |
| 1956 | 108.8 | 0.5 |
| 1955 | 108.3 | 0.8 |
| 1954 | 107 | 0.6 |
| 1953 | 107.6 | 0.5 |
| 1952 | 108.9 | 0.6 |
| 1951 | 108.1 | 0.6 |
| 1950 | 110.5 | 0.5 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 巴基斯坦 | 菲律宾 |
|---|---|---|
| 2015 | 122100.8–136.6 | 1.70.6–3.5 |
| 2016 | 119.5104.9–132 | 1.30.5–3.2 |
| 2017 | 119.999.5–134.3 | 1.60.7–3.4 |
| 2018 | 119.7103–133.8 | 1.70.6–3.9 |
| 2019 | 118.997.2–133.8 | 1.60.5–4.2 |
| 2020 | 122.8105–136.3 | 1.60.4–4 |
| 2021 | 122.9103.2–138.2 | 20.7–3.8 |
| 2022 | 120.7101.9–136.4 | 2.20.9–4.3 |
| 2023 | 123.3104.8–138.8 | 20.6–4.1 |
| 2024 | 124.4105.4–139.1 | 2.31–4.3 |
| 2025 | 123.8102.8–139.1 | 2.11–4.8 |
| 2026 | 122.5101.9–141.8 | 2.30.7–5.3 |
| 2027 | 124.4101.5–141 | 2.30.9–4.5 |
| 2028 | 124.8103.6–140.2 | 2.40.9–4.4 |
| 2029 | 126.499.2–141.6 | 2.91.2–6.3 |
| 2030 | 122.5103.5–140.1 | 2.41.3–4.5 |
| 2031 | 122.7105.6–139.9 | 2.31.1–4.9 |
| 2032 | 126104–143.9 | 2.61–6.4 |
| 2033 | 125.9106.6–144.1 | 2.81.4–5 |
| 2034 | 130.9113.2–147.8 | 2.40.9–5 |
| 2035 | 127.1107.6–143.6 | 2.41–5.8 |
| 2036 | 125.5108.3–143.4 | 2.61.1–5.4 |
| 2037 | 130.7112.4–147.9 | 31.4–5.8 |
| 2038 | 130.9108.6–144.9 | 3.31.6–6.7 |
| 2039 | 128.6110.2–144.9 | 31.4–5.9 |
| 2040 | 133.2115.1–146.1 | 3.31.3–7.2 |
| 2041 | 127.2108.3–143.5 | 3.41.5–6.9 |
| 2042 | 134.6112.8–150.7 | 2.81.2–6.8 |
| 2043 | 131.6112.5–149.3 | 31.1–6.2 |
| 2044 | 128.2108.1–145.9 | 3.41.5–7.3 |
| 2045 | 133.4116.7–148.7 | 3.41.2–6.5 |
| 2046 | 133.8109–151.1 | 3.91.6–8.2 |
| 2047 | 134.6110–150.9 | 3.91.6–8.6 |
| 2048 | 136117.1–152.3 | 41.8–8.4 |
| 2049 | 133.3115.2–152.5 | 4.21.9–8 |
| 2050 | 138.4119.4–157.4 | 4.22.3–8.4 |
| 2051 | 138115.5–158.2 | 41.8–9 |
| 2052 | 138.3120.3–155.3 | 4.72.2–8.9 |
| 2053 | 137.4117.7–155.8 | 4.31.9–8.5 |
| 2054 | 137116–152.4 | 4.52.3–11.5 |
| 2055 | 139.6120–157.2 | 4.52–9 |
| 2056 | 135.8117.3–154.1 | 4.52.2–10.4 |
| 2057 | 141.5119.5–158.8 | 5.12.2–9.2 |
| 2058 | 137.1114.3–154.7 | 4.71.9–10.9 |
| 2059 | 141.4122.6–156.6 | 5.42.1–11.7 |
| 2060 | 142.5124.1–158.6 | 6.32.3–10.8 |
| 2061 | 142.3123.2–157.4 | 5.42–10.7 |
| 2062 | 141.3118.8–161.2 | 5.31.5–13.1 |
| 2063 | 143.1125.6–160.6 | 5.72.1–12.5 |
| 2064 | 140.7119.8–163.5 | 5.11.8–10.3 |
| 2065 | 141.1121.5–159.3 | 5.12.5–11.6 |
| 2066 | 143.8122.5–163.4 | 6.12.7–12.2 |
| 2067 | 144.2125.9–162.3 | 4.82–11.1 |
| 2068 | 143.2126–162.2 | 6.32.5–12.4 |
| 2069 | 144.7119.8–163.2 | 5.62.6–13.3 |
| 2070 | 143.7126.5–163 | 4.92.5–11.7 |
| 2071 | 145.5121.8–164.4 | 6.42.6–13.3 |
| 2072 | 147.1125.5–165.1 | 6.52.2–12.7 |
| 2073 | 149.2122.1–164.7 | 7.22.9–16 |
| 2074 | 145.8126.7–162.2 | 6.32.8–14.3 |
| 2075 | 145.1126.2–160.5 | 6.42.3–13.7 |
| 2076 | 145.7126.4–165.9 | 6.62.6–12.8 |
| 2077 | 146.1126.2–164.4 | 7.72.8–16.5 |
| 2078 | 146.5121.4–164.4 | 6.53.4–17.4 |
| 2079 | 144.6122.7–161 | 6.82.6–15.7 |
| 2080 | 148.2123.7–166.4 | 7.62.7–17.5 |
| 2081 | 145.8122.2–167 | 7.33.2–17.8 |
| 2082 | 146123.3–168.8 | 7.52.8–14.9 |
| 2083 | 148.3127–167.4 | 7.62.9–18.8 |
| 2084 | 150.5128.5–167.6 | 7.52.3–15.2 |
| 2085 | 149.9126.1–170.8 | 83.2–17.4 |
| 2086 | 146.3124.2–165 | 8.32.6–17 |
| 2087 | 149.9124.3–167.3 | 7.83.1–16.5 |
| 2088 | 149.3127.9–169.7 | 7.73.3–19.2 |
| 2089 | 148.9129.6–166.7 | 8.23–17.9 |
| 2090 | 150.3131.5–166.7 | 7.43.3–19.9 |
| 2091 | 151.1128.4–168.7 | 83.2–20.9 |
| 2092 | 150.5129.8–170.2 | 8.23.3–18 |
| 2093 | 151.6131.8–167.9 | 7.83.3–23.5 |
| 2094 | 151.5130.4–168.6 | 8.43.3–18.7 |
| 2095 | 152.5130.6–169.2 | 9.73–19.4 |
| 2096 | 150.8124.2–169 | 8.72.9–23 |
| 2097 | 149.4130.3–167.5 | 83.4–16.7 |
| 2098 | 151.7125.4–168.2 | 8.33.2–21.6 |
| 2099 | 151.6124.4–170.6 | 7.53–20.4 |
| 2100 | 147.6125.2–167.5 | 8.83.5–17 |
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须知
- 一年中最高气温超过 35 °C 的天数,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
巴基斯坦与菲律宾对比
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冲突
军用
- 军费开支巴基斯坦:2025 年为 GDP 的 2.91%菲律宾:2025 年为 GDP 的 1.3%
- 军费开支(美元)巴基斯坦:2025 年为 US$115亿菲律宾:2025 年为 US$63亿
- 人均军费开支巴基斯坦:2025 年为 US$47菲律宾:2025 年为 US$55
- 军费占政府支出比例巴基斯坦:2025 年为 13.8%(占政府支出)菲律宾:2025 年为 5.4%(占政府支出)
- 武装部队人员巴基斯坦:2020 年为 943,000 人菲律宾:2020 年为 157,000 人
- 国家实力巴基斯坦:2022 年为 1.77%(占全球实力)菲律宾:2022 年为 0.68%(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)菲律宾:2020 年为 0.37%(占劳动力)
- 武器进口巴基斯坦:2025 年为 7.06亿 TIV菲律宾:2025 年为 8.46亿 TIV
- 武器出口巴基斯坦:2025 年为 1.27亿 TIV菲律宾:2007 年为 400万 TIV