危地马拉与秘鲁对比

危地马拉与秘鲁:热带夜

2014 年热带夜:危地马拉为 171.5 夜,秘鲁为 164.5 夜(CMIP6 气候模型中位数模拟)。 2014 年危地马拉的数值较高,高出 7 夜,是秘鲁的 1.04 倍。

每年夜数 · CMIP6

危地马拉与秘鲁:热带夜2014 年热带夜:危地马拉为 171.5 夜,秘鲁为 164.5 夜(CMIP6 气候模型中位数模拟)。 2014 年危地马拉的数值较高,高出 7 夜,是秘鲁的 1.04 倍。
危地马拉秘鲁CMIP6 模型中位数(SSP2-4.5,中间路径)模型第 10–90 百分位

数据解读

  • 自 1987 年超过秘鲁以来,危地马拉的数值一直更高。
  • 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年危地马拉为 230.9 夜,秘鲁为 192.3 夜。

逐年数据

每年夜数 · CMIP6

年份危地马拉秘鲁
2014171.5164.5
2013175.4163.1
2012171.8164.8
2011173.8164.3
2010171.4163.3
2009169.7162.3
2008167.8162
2007167.6159.8
2006167.2159.1
2005169.2159.3
2004167.4161.8
2003165.8160.5
2002165.7159.9
2001165.3160.7
2000163.6158
1999162155.7
1998162.1157.4
1997160.7156.1
1996157.9152.2
1995153.5152.1
1994155150.8
1993153.5148.5
1992151.7144
1991158.2156
1990161.9158.3
1989157.5153.2
1988154.2151.2
1987154.7152
1986153.1153.4
1985150.7149
1984150.3148.3
1983148.1145.4
1982151.3151.4
1981156.7153.1
1980152.3150.9
1979153150.5
1978149.5149.1
1977150.6150.3
1976151.6147.5
1975147.4142.1
1974150.2148.6
1973149.6151.5
1972148.2147.6
1971145.5145.7
1970145.4145.6
1969146.8147
1968146.7146
1967142.7142.3
1966145.9145.7
1965143.3143.3
1964143141.6
1963144.6135.9
1962149.5148.9
1961149.8146.5
1960151.4149.8
1959147.4146.1
1958150.5149.1
1957151.1148.7
1956148.2144
1955152.5148.3
1954150.4148.7
1953149.3148.2
1952150.3148.1
1951151.8147.2
1950148.6147.8
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
年份危地马拉秘鲁
2015177158.4–194.6164.3148.5–174.9
2016178.5161.5–195.5163.4149.8–171.5
2017182.8166.6–194.9165.5155–175.2
2018180.2165–196.4165152.9–176.6
2019181.7159.3–199.5163.7151–176.8
2020184.1161.8–198.6165.3151.6–176.2
2021184.4168.1–201.1167.6154.7–177.3
2022184.6165.7–198.4169.5156.6–179.2
2023186.3171.1–207167.1156.3–178.4
2024187.1169.9–207.3170.6157.3–180.2
2025187.4169.7–205.6168.6155–179.9
2026190.9167.9–211167.8153.3–179.7
2027188.4171.9–210.9168.3155.2–178.8
2028191.3175.8–208.5169.8158.3–179.9
2029192.7175.6–208.8174162.8–181.7
2030191173.3–207.9168.1153.2–180.6
2031193.6175.3–211.4172.5156.2–183.7
2032196.4178.7–214.8173.2162.7–184.7
2033193.3174.6–208.5172156.5–181
2034193.5176.2–214.4171.6158.7–185.6
2035193.4177.7–212.8172159.3–184.1
2036194.4180.5–212.8172.5160.7–183.2
2037199.1180–216.2175.6166.3–185.3
2038202.6184.8–216.7175.8164.6–184.9
2039199181.6–217.6174.1162.7–185
2040200.3182.9–217.9175.4163.9–187
2041200.7182.1–218.2176.5165.3–186.1
2042201.6180.3–222.1176.3161.9–189.7
2043201.7182.3–226.4174.8163.7–185.3
2044200.8184.9–222.3175.3161.9–188.2
2045203.6188.7–225.1177.3165.5–186.9
2046204.5183.3–227.5180.3167.4–189.9
2047207.5190.3–227.5178.6167.5–189
2048208.2188.9–229.4181.2168.2–192.2
2049210.1188.7–227.4180.4168.1–189.8
2050211.4188–230.7178.6166.4–190.8
2051208.1192.7–229.2180.3168.5–190.6
2052207.7193–227.9181.5170.8–191.7
2053209.8186.4–233.2179.5168.3–190.8
2054209.5194.7–233.2180.1167.3–193.9
2055212.4196.2–231.9181.7171–194.8
2056210.9193.3–233.1182.2170–193
2057213.3193.7–232.4181.6168.7–193
2058211.7192.3–238.1183.1169.4–195.5
2059214.5190.4–237.4184.6169.7–195.3
2060217.4196.4–237.3185.6171.1–197.1
2061213.9193.7–237.1182.7169.9–195.8
2062216.3194–237.3184.3168.7–196.9
2063217.2197–240.8184.6170.8–196.9
2064214.5196.1–236.1184.4170.1–194.8
2065217.3195.2–238.2186.3173.3–196.9
2066217.9195.2–240185.6172.3–197.4
2067216.4194.1–241.1184.3169.4–198.2
2068221200.2–243.4186.1172.1–198.3
2069219.9200.5–241.9184.9169–198.3
2070219.6199.9–242.6185.4171.8–198.4
2071222.5203.4–243187.3173.3–198.7
2072225.6200.4–247.6188.1174.9–199.8
2073224.4199.9–248.3187.6175.9–202.1
2074222.5202.2–245.9186.4169.5–198.9
2075220.2198.7–242.6186.4170.6–198.3
2076222.9195.4–247.7188.8174.2–201
2077225.2198.3–245.9189.1174.7–201.8
2078225.4197.8–245.9188.4175.6–202.3
2079223.4199.3–248.2188172–199.7
2080223.4201–250.7189.1172.8–201.7
2081224202.5–246.6188.4173.6–201.8
2082224.8201.3–245.9188.8174.8–199.7
2083225202.3–250.5189.9175.7–204.7
2084227.9204.9–249.9190.7176.3–204.4
2085227.7199.2–251.3192176.2–204.6
2086224.9202.3–249.6189.1175.4–204
2087227.1197.8–249.7189.1175.9–203.6
2088230.6207.4–255.5191.1174.7–204.9
2089229.7207.4–251.4190.1174.3–203
2090228.2210–253.4190.4177–206.2
2091231.4206.6–255.4192.6174.4–205.9
2092230.1207.4–253.4192.6176.6–204.7
2093226.7206–255.5190.6176–206
2094227.3204.4–251.7192.3178.2–204.1
2095231.1207.7–255.5193.4176.5–207.3
2096229.9206.3–255.5191.4176.2–207.6
2097226.7208.6–249.5190.7174.9–202.2
2098231.1202.9–259.1192.9177.8–208.9
2099230.2203.1–256.5191.5176.8–205
2100230.9208.9–255.1192.3176.6–205.6

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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

危地马拉与秘鲁对比

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