巴西与泰国对比

巴西与泰国:35 °C 以上天数

2014 年35 °C 以上天数:巴西为 18.8 天,泰国为 39.9 天(CMIP6 气候模型中位数模拟)。 2014 年泰国的数值较高,高出 21.1 天,是巴西的 2.12 倍。

每年天数 · CMIP6

巴西与泰国:35 °C 以上天数2014 年35 °C 以上天数:巴西为 18.8 天,泰国为 39.9 天(CMIP6 气候模型中位数模拟)。 2014 年泰国的数值较高,高出 21.1 天,是巴西的 2.12 倍。
巴西泰国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,泰国的数值都更高。
  • 根据CMIP6 模型中位数(SSP2-4.5,中间路径),2100 年巴西为 80.8 天,泰国为 95.9 天。

逐年数据

每年天数 · CMIP6

年份巴西泰国
201418.839.9
201321.842.1
201219.540.1
201119.639.9
201015.439.8
200916.637.9
200814.636
200711.633
20061239.2
200514.234.9
200416.239.4
200315.534.1
200212.436.3
200116.137.8
200013.532.5
199911.429.7
199812.833.3
199711.733.7
19961031.3
19958.833.5
19949.133.5
19937.830.4
19925.625.5
19918.535.4
199013.337.7
198910.229.3
19889.730.6
19879.431.2
19869.934.3
19857.529.3
1984732.4
19836.430.4
19828.533.1
19819.429.5
19808.128.8
19799.132.4
1978926.1
1977831.5
19766.929.7
19756.825
19747.131.5
19737.334.5
1972730.3
19715.827.1
19706.728.7
19696.929.9
19686.429.4
19676.428.3
19666.425.4
1965627.1
19645.926.6
19634.926
19627.228.7
19617.531.1
19607.832.9
19597.524.4
19587.933
1957827.8
19566.927.1
19558.631.2
19548.330.3
19536.828.2
19527.234.1
19517.233
19507.728.5
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
年份巴西泰国
201518.56.9–38.841.123.5–66.3
201618.57–35.938.915.7–61.2
201719.47.7–41.441.420.8–64.9
201819.87.6–41.443.521.7–65.5
2019218.9–47.140.916.5–61.9
202021.98.7–43.245.617.3–66.6
202124.69.7–51.843.720.7–70.7
202223.410–51.247.826.4–73.3
202325.710.5–55.541.822.3–67.2
202427.713.3–51.144.726.9–70.9
202527.210.5–57.650.227.3–77
202624.48.1–53.144.425.2–80.5
202728.28.9–55.747.126.2–75.6
202829.411.9–61.951.123.1–73.3
202933.916.4–66.756.733.9–84.7
203028.211.6–56.650.726.1–78.9
203135.315.2–70.750.531.5–81.2
203235.616.6–67.349.823.6–85.7
20333113.5–63.253.432–73.7
203431.214.1–75.151.531.6–83.4
203530.814.4–6852.228.9–89.2
203632.413.7–58.753.335.2–77.4
203739.419.6–66.557.632–82.5
203838.215.4–71.362.238.5–91.5
203937.214.6–75.555.127.8–78.8
204038.518.6–76.253.728.4–91.3
204141.819.9–76.66337.5–86.6
204239.917–86.154.826.4–94.7
204337.614.9–81.257.129.8–85.3
204438.416.1–84.457.336.7–95.7
204540.420.4–74.954.934.2–90.2
20465023.7–86.762.736.4–102.1
204743.522.9–86.463.635–98.5
204850.424.6–96.272.237.4–110.4
204949.823.9–90.266.240.8–98.3
205046.922–92.764.536.9–95.3
205147.324.9–95.666.135.5–97.1
205254.728.7–97.574.339.3–108.1
205347.122.6–92.364.635–106.7
205445.221.6–92.269.144.2–112.1
205552.228.6–103.871.445.3–107.6
205653.223.6–110.870.536.5–117.7
205750.620.2–94.77240–104.6
205855.325–117.373.140.6–107.3
205961.229–118.577.251.2–121.4
20606531.1–111.380.946–117
206154.123.5–115.477.335.3–117.8
206254.924.7–127.773.535.5–125.8
206359.428.6–112.983.640.3–122.6
206454.828.7–106.174.746.9–111.8
206562.330.3–119.569.939.5–124.8
206662.330.6–113.580.250.7–122.7
206760.926.9–113.169.437.9–116
206866.730.1–119.776.445.8–131.7
206960.631.5–113.877.747.4–128.7
207059.932.1–124.873.839.2–129.5
207164.433.8–11180.642.2–131.6
20726830.5–128.181.347.5–135.3
207372.736–127.688.854.2–133.4
207468.832.6–125.78444.3–128.1
207567.832.7–116.482.838.3–123.9
207667.933.7–124.982.937.1–132.9
207772.535.5–128.98849.4–132.4
20787336.7–13291.252–137
207969.233.6–125.585.749.5–144.4
208067.834.9–122.288.552.7–143.6
208170.936.9–140.487.150.9–135.1
208270.640.7–125.889.953.5–133.6
208375.735.7–152.587.145.8–149.7
20847734.1–140.38447.7–131
208583.937.2–147.893.853.8–141.8
208673.334.6–14187.745.8–139.2
208778.439.2–144.286.447.4–139.2
208879.335.1–15290.441.7–153.2
208975.239–146.490.149–151.2
209078.341.8–148.687.853.3–154.1
20918135.2–147.98648.2–148.6
20927936.6–14892.650.2–149.9
20937739.3–148.789.854.6–159
20947939.6–144.595.549.6–143.6
209588.636.5–155.9103.458.2–156.3
209675.736.1–152.889.951.3–155.4
20977936.7–135.694.550.2–142.6
209882.737.9–166.489.851.6–149.6
209977.941–144.788.244.7–147.4
210080.840.2–141.395.951.1–153.3

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

巴西与泰国对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境