玻利维亚与洪都拉斯对比
玻利维亚与洪都拉斯:热带夜
2014 年热带夜:玻利维亚为 179.5 夜,洪都拉斯为 176.7 夜(CMIP6 气候模型中位数模拟)。 2014 年玻利维亚的数值较高,高出 2.8 夜,是洪都拉斯的 1.02 倍。
每年夜数 · CMIP6
数据解读
- 自 2014 年超过洪都拉斯以来,玻利维亚的数值一直更高。
- 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年玻利维亚为 210.8 夜,洪都拉斯为 279.1 夜。
逐年数据
每年夜数 · CMIP6
| 年份 | 玻利维亚 | 洪都拉斯 |
|---|---|---|
| 2014 | 179.5 | 176.7 |
| 2013 | 176.3 | 181.1 |
| 2012 | 177 | 181.4 |
| 2011 | 177.2 | 180.5 |
| 2010 | 176.7 | 176.9 |
| 2009 | 175.9 | 174.4 |
| 2008 | 174.1 | 170.5 |
| 2007 | 169 | 171.8 |
| 2006 | 169.8 | 171 |
| 2005 | 170.5 | 171.6 |
| 2004 | 175.5 | 174.2 |
| 2003 | 170.6 | 170.2 |
| 2002 | 173.3 | 169.1 |
| 2001 | 172.9 | 168.2 |
| 2000 | 169 | 164.8 |
| 1999 | 167.3 | 162.2 |
| 1998 | 170.7 | 163 |
| 1997 | 167.7 | 160.4 |
| 1996 | 163.3 | 154.7 |
| 1995 | 164.4 | 152.5 |
| 1994 | 162.7 | 151.9 |
| 1993 | 160.4 | 149 |
| 1992 | 155.4 | 145 |
| 1991 | 169.7 | 156.7 |
| 1990 | 172 | 162.1 |
| 1989 | 164.4 | 153.8 |
| 1988 | 161.5 | 151.1 |
| 1987 | 162.5 | 151.9 |
| 1986 | 163.8 | 151.3 |
| 1985 | 157.8 | 146.1 |
| 1984 | 159.8 | 147.5 |
| 1983 | 156.8 | 143.7 |
| 1982 | 164.2 | 148.4 |
| 1981 | 166.5 | 150.9 |
| 1980 | 162.2 | 147.8 |
| 1979 | 162.7 | 148.9 |
| 1978 | 161.1 | 146 |
| 1977 | 161 | 148.6 |
| 1976 | 160.1 | 145.5 |
| 1975 | 155.5 | 141.8 |
| 1974 | 160.5 | 146.8 |
| 1973 | 160.5 | 145.1 |
| 1972 | 158.8 | 140.4 |
| 1971 | 156.7 | 141.1 |
| 1970 | 155.1 | 140.6 |
| 1969 | 155.7 | 142.2 |
| 1968 | 155.9 | 141.9 |
| 1967 | 153.3 | 138.4 |
| 1966 | 156.7 | 139.9 |
| 1965 | 154.2 | 138.1 |
| 1964 | 150.7 | 138.4 |
| 1963 | 148.4 | 136.8 |
| 1962 | 157.9 | 144.2 |
| 1961 | 158.7 | 145.5 |
| 1960 | 160.3 | 146.1 |
| 1959 | 159 | 143.3 |
| 1958 | 157.5 | 147.6 |
| 1957 | 159.3 | 144.5 |
| 1956 | 154.5 | 143.8 |
| 1955 | 160.3 | 146.3 |
| 1954 | 159.7 | 144 |
| 1953 | 157.8 | 143.2 |
| 1952 | 159.1 | 143.6 |
| 1951 | 157.6 | 145.5 |
| 1950 | 158.6 | 143.7 |
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
| 年份 | 玻利维亚 | 洪都拉斯 |
|---|---|---|
| 2015 | 177.7162.4–194.8 | 186.4151.3–215.3 |
| 2016 | 177.1155.9–190.7 | 185.7154.8–211.9 |
| 2017 | 179.6164.6–190.9 | 194.4164.9–215.2 |
| 2018 | 177.8162.1–196.3 | 190.6168.8–218.5 |
| 2019 | 180.1164.5–199.9 | 189161–221 |
| 2020 | 180.5162–200.6 | 196.8164.4–223 |
| 2021 | 185.6169.2–197.3 | 199.3176.3–226.8 |
| 2022 | 184.7165.7–200.5 | 202.9173–227.6 |
| 2023 | 181.3166.6–196.7 | 198.1175.2–230.1 |
| 2024 | 187.1168.2–202.1 | 204.7177.9–233.2 |
| 2025 | 183.5168.8–195.7 | 202.7173.9–230.8 |
| 2026 | 182.5164.8–198.1 | 206.8174–235.2 |
| 2027 | 182.7165–201.6 | 206.5177.9–235.7 |
| 2028 | 186.3169.6–200.3 | 211.3184–238.7 |
| 2029 | 192.5175.6–205.4 | 210.3185.4–244.5 |
| 2030 | 185.5161.7–204.2 | 208.9176.9–241.7 |
| 2031 | 189.2166.2–205.3 | 217.3187.1–246.4 |
| 2032 | 189.7173.8–209.6 | 218.9194.5–247.9 |
| 2033 | 188.2167.7–204.1 | 213.3188.2–239.7 |
| 2034 | 188172.2–207.8 | 211.3186.1–248.7 |
| 2035 | 186.7169.1–206.1 | 215.3184.2–248.2 |
| 2036 | 190.5173.5–205.2 | 215.5194.1–242.5 |
| 2037 | 195.3181.4–208.5 | 226.4202.4–251.6 |
| 2038 | 189.2174.7–207.8 | 228.9198.7–256.2 |
| 2039 | 192.7175.7–205.5 | 224.4196.6–256.2 |
| 2040 | 192.3176.8–204.2 | 225.1201–258 |
| 2041 | 193.9179–209 | 225.9203–251.8 |
| 2042 | 191.3171.9–207.6 | 229.3200.2–262.8 |
| 2043 | 191.2174.4–209.9 | 224.4199–262.5 |
| 2044 | 194.5179.1–209.4 | 224.8201.2–262.7 |
| 2045 | 194.4180.2–209 | 231206.1–262.3 |
| 2046 | 194.8181.4–213 | 236.9204.5–267.7 |
| 2047 | 196.5181.4–213.3 | 236.3213.3–269.3 |
| 2048 | 200.2184.6–212.8 | 241.2216.7–268.9 |
| 2049 | 199.8181.3–214.4 | 244.8213.5–270.7 |
| 2050 | 196.3173.9–210.9 | 241.1207.2–277.8 |
| 2051 | 198.5184.2–213.3 | 239.9210.5–270.2 |
| 2052 | 200.6185.7–214.8 | 245.1215.7–271.2 |
| 2053 | 198182.1–211 | 240.8211.7–277.5 |
| 2054 | 195.9179.8–211 | 243.9220.4–286.6 |
| 2055 | 201.2187.1–215 | 248.1220.1–282.1 |
| 2056 | 201.3181.5–216.1 | 245.6213.1–279 |
| 2057 | 200.6184.3–214.4 | 249.4214.2–279.1 |
| 2058 | 200.8182.8–216.5 | 248.4217.2–289.1 |
| 2059 | 203.2186.1–215.8 | 252.6220.5–283.1 |
| 2060 | 203.4186.2–219.7 | 256.8225.2–289.4 |
| 2061 | 197.9184–216.3 | 254.5220.4–285.9 |
| 2062 | 201.4186.2–219.1 | 252.8217.4–291.1 |
| 2063 | 201.5184.9–217 | 258.7226.2–288 |
| 2064 | 200.5184.6–216.1 | 252.1224.1–285.7 |
| 2065 | 204.9187.3–218.4 | 258.1226.9–288.9 |
| 2066 | 203.3186.8–218.1 | 256.4227.7–287.4 |
| 2067 | 203.6187.7–215.6 | 258.3228.2–294.9 |
| 2068 | 204.4188–218 | 264.6231.2–295 |
| 2069 | 203.8184.5–219 | 258.1229.3–292 |
| 2070 | 205.1188.3–221.4 | 256.9225.3–297.9 |
| 2071 | 203186.9–214.6 | 261.9231–292.9 |
| 2072 | 206186.6–221.5 | 267.3235.2–300.4 |
| 2073 | 206.5193.2–220.7 | 268.1233.7–304.7 |
| 2074 | 204.5184.1–219.5 | 263.7234.2–295.9 |
| 2075 | 203.8185.8–217.9 | 262.1229.5–295.4 |
| 2076 | 206.5190.1–220.4 | 266.8231.8–298.5 |
| 2077 | 209.1185.4–221.4 | 268.6232.1–298.8 |
| 2078 | 208.1192.7–222.9 | 270.1236.8–299.6 |
| 2079 | 204.7186.2–218.6 | 265.3229.5–304.2 |
| 2080 | 208.7192.4–221.1 | 268.4230.2–304.2 |
| 2081 | 208.1190.7–221.1 | 268231.9–300.8 |
| 2082 | 208.2189.7–220.1 | 267.4230.2–301.8 |
| 2083 | 209.3192.8–222.6 | 268.3236.2–307.4 |
| 2084 | 208.2193.3–223.1 | 273.9235.2–307.1 |
| 2085 | 210.4194–225 | 276.4234.2–305.9 |
| 2086 | 210.4189.7–225.4 | 267.9238.8–305.2 |
| 2087 | 207.9193.8–222 | 270.4233.7–301.8 |
| 2088 | 210.3193.4–225.2 | 277239.9–310.2 |
| 2089 | 208.2191.3–222.9 | 275.4246–309.8 |
| 2090 | 209.7195.5–225.2 | 275.3244.1–307 |
| 2091 | 209.7192.5–227.1 | 281.9240.6–310.6 |
| 2092 | 209.8192.1–223.9 | 277.1245.6–312.3 |
| 2093 | 209.4195.7–222.1 | 272.8244.2–311.6 |
| 2094 | 208.9194.6–222.7 | 274.9245.2–308.4 |
| 2095 | 210.3191.2–225.3 | 280.8244.6–313.5 |
| 2096 | 211.6193.9–225 | 275.2245.8–313.5 |
| 2097 | 208.6189.8–220.3 | 276247.2–305.4 |
| 2098 | 211.7196.2–226.5 | 278.9238.9–313.4 |
| 2099 | 211.2195.3–224 | 280.8240.6–312.8 |
| 2100 | 210.8195.8–226.8 | 279.1248.3–309.6 |
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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
玻利维亚与洪都拉斯对比
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冲突
军用
- 军费开支玻利维亚:2025 年为 GDP 的 1.22%洪都拉斯:2025 年为 GDP 的 1.46%
- 军费开支(美元)玻利维亚:2025 年为 US$5.7亿洪都拉斯:2025 年为 US$5.82亿
- 人均军费开支玻利维亚:2025 年为 US$55洪都拉斯:2025 年为 US$53
- 军费占政府支出比例玻利维亚:2025 年为 3.2%(占政府支出)洪都拉斯:2025 年为 5.7%(占政府支出)
- 武装部队人员玻利维亚:2020 年为 71,000 人洪都拉斯:2020 年为 23,000 人
- 国家实力玻利维亚:2022 年为 0.1%(占全球实力)洪都拉斯:2022 年为 0.06%(占全球实力)
- 武装部队占劳动力比例玻利维亚:2020 年为 1.21%(占劳动力)洪都拉斯:2020 年为 0.56%(占劳动力)
- 武器进口玻利维亚:2024 年为 0 TIV洪都拉斯:2024 年为 700万 TIV