马拉维与尼日利亚对比

马拉维与尼日利亚:35 °C 以上天数

2014 年35 °C 以上天数:马拉维为 3.7 天,尼日利亚为 107.4 天(CMIP6 气候模型中位数模拟)。 2014 年尼日利亚的数值较高,高出 103.7 天,是马拉维的 29 倍。

每年天数 · CMIP6

马拉维与尼日利亚:35 °C 以上天数2014 年35 °C 以上天数:马拉维为 3.7 天,尼日利亚为 107.4 天(CMIP6 气候模型中位数模拟)。 2014 年尼日利亚的数值较高,高出 103.7 天,是马拉维的 29 倍。
马拉维尼日利亚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 1950 年以来,在两国都有数据的每一年,尼日利亚的数值都更高。
  • 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年马拉维为 16.3 天,尼日利亚为 163.6 天。

逐年数据

每年天数 · CMIP6

年份马拉维尼日利亚
20143.7107.4
20134.3104.3
20123.5104.4
20113.1103.7
20103.4101.1
20093.299.4
20083.298.6
20073.597.4
20063.197.9
2005397.2
20043.499.2
20033.798.2
20023.598.3
20013.6102.2
20003.296.3
19992.792.3
19983.191.6
19972.895.2
19962.789.5
19952.390.2
19942.386.1
19931.783.5
19922.381.3
19912.394.2
19902.595
19892.589.3
19882.693.4
19872.490.4
19862.593.2
1985287
19842.289.5
19832.588.5
19822.289.6
19812.391.9
19802.489.5
19792.389.8
19782.188
19772.488.4
1976283.6
19752.487.3
19742.584.9
19732.188.3
1972287.1
1971284.5
19702.387.3
19692.387.1
1968284.9
1967284.8
19661.785.7
19652.485.7
19641.477.7
1963281.7
19622.289.3
19612.391.6
19602.591.4
19592.688.3
19582.689.9
19572.291.2
1956284.6
19552.388.4
19542.588.8
19531.991.7
19522.187.9
19511.992.1
19502.288.9
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
年份马拉维尼日利亚
20154.62.2–8.3105.581.2–130.1
20164.22.1–8.2101.478.2–120.6
20174.12.3–7.610680.5–130.9
20184.22.2–7.4105.177.2–129
20194.32.4–7.7104.378.3–130.3
20204.82–8.5104.778.2–130.2
20213.72.1–6.7104.885.2–128.6
20224.82.5–8.6111.184.4–135.5
20235.52.5–9106.585.6–130.6
20244.72.7–7.7114.493.3–136.4
20254.71.4–9.6112.191.1–132
20264.82.7–9.2108.574.8–133.8
202762.9–13114.581.7–136.4
20285.32.7–8.9113.487.6–141.8
20295.32.4–10.7116.591.5–141
20305.42.5–13.1117.785.5–145.3
20315.53.1–9.9116.388.2–141.7
20325.72.9–11118.785.8–144.2
203372.9–12.9118.490.6–146
20346.73.3–13117.689–144.4
20356.73.1–13.612087.5–144.3
20365.52.8–11.8116.889.2–143.5
20377.13.6–13.7124.790.9–151.6
20387.34.2–13.7126.696.2–152.6
20396.33.2–13.5122.697–147.4
20406.33.1–12.1121.193.5–153.7
204172.9–13.3127.599.5–154.2
20426.83.8–12.412896.1–152.5
20436.53.5–16.7124.298.9–149.7
20446.92.8–15.2125.496.3–152.8
20457.13.9–12.2129.499.4–156.4
20467.83.8–14.2135.999.9–158.5
20478.34–17.8135.299–159.5
20489.14.7–17.3133.1103.7–160.3
20497.33.8–15135.4104.4–161.8
20509.54.7–18.2131.3102–166.4
205110.64.5–23.3131.6106.2–166.5
2052105–21139.6101.6–171.1
20538.72.4–19.7135.1105–166.8
20549.93.7–23.4139102.4–172.2
205510.64.6–20.7140113.8–172.2
205610.33.7–22.2141.8102.8–177.8
205710.54.6–21.4148.8113.3–178.3
205811.35.9–20.5140112–171.9
205911.55.6–21.2142.3114.3–176.6
206010.84.1–22.7144.3110.6–176.5
206111.34.8–22.1145109.2–180.3
206211.35.1–22.7146111.1–181.8
206310.15.2–23.7147.1114.5–182.6
206411.85–20.3146.4112.8–179.9
206512.85.1–26.9149.2116.8–179
2066126–29.8148.8117.8–185.3
206710.44.9–22.7142.6114.9–185.1
206811.45–23.2152.4114.1–187.8
206913.15.1–24.7148.2114.1–185.4
207012.15.2–23.4151.6111–187.8
207113.75–26.6155.2117.6–192.8
207214.36.3–26.1155.2118.4–190.6
207314.85.2–31154.8115.7–196.8
207411.45.2–26.8151.6114.2–195.8
207511.65.5–26.2158.4117.9–190.2
207613.35.3–28.2154.5120–193.1
207713.56.6–25.7164121.3–203.7
207813.95–24.9158.9117–196.9
207914.37–26.2157.6123.7–192.5
208013.56.3–29.4161.3118.7–197.4
208113.94.7–26.2158.9119.1–200.5
208212.46.4–28.7156.9118.5–201.5
208314.47.5–27.7160.4121.6–203.2
208414.76.5–27.6157.7118.3–198.5
208515.77.8–31.7165.1122.6–201.9
2086136.6–27.8160.4122–201.3
208713.96.4–30.6164.1121.4–199.1
208817.15.9–35.2162.3124.7–205.8
208915.67–28.8157.8122.5–206.2
209017.34.8–37.7163124.3–204.5
209117.95.2–35.8167.5124.5–204.5
209216.76.7–34.9173.2125.1–206.7
209315.95.8–32.8166.1126.9–212.1
209418.86–34.8167.8130.5–205.1
209516.77.4–29.2173.9123–212.7
209616.36.4–31.6164.5127.5–213
2097145.6–30.8161.2123.5–206.8
209815.77.8–29.3167.8128.2–206.2
209918.37.2–39.1171129.1–212.5
210016.36.6–32.1163.6126.1–210.4

分别查看各国

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

马拉维与尼日利亚对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境