意大利与泰国对比

意大利与泰国:热带夜

2014 年热带夜:意大利为 26.3 夜,泰国为 286.4 夜(CMIP6 气候模型中位数模拟)。 2014 年泰国的数值较高,高出 260.1 夜,是意大利的 11 倍。

每年夜数 · CMIP6

意大利与泰国:热带夜2014 年热带夜:意大利为 26.3 夜,泰国为 286.4 夜(CMIP6 气候模型中位数模拟)。 2014 年泰国的数值较高,高出 260.1 夜,是意大利的 11 倍。
意大利泰国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 年意大利为 65.1 夜,泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份意大利泰国
201426.3286.4
201324.7289.1
201224.8286.6
201124.6286.4
201027.1286
200923.7286.9
200824.1284.8
200721.5283.2
200624.6284.3
200522.5281.7
200424.5287.5
200323.8279.3
200220.6280
200120.8285.5
200021.7283.4
199920.3282.5
199818.9282.7
199718.9284.8
199618.9279.8
199517.9278.7
199417.4280.8
199316.3275.6
199215.1268.8
199118276.7
199018.2279.2
198916.6278.4
198815.5279.6
198716277.9
198615277.5
198514.5276
198415.7277.9
198315.3273.9
198214.1275.7
198115.3277.8
198015.9277.9
197914.5278
197816.5276
197713.5277.3
197613.8275.6
197514274.4
197414.8276
197313.5280.6
197213.7273.9
197115.3273.2
197014276
196914.5274.8
196813.8277
196713.6270.3
196613.2274.4
196512.8275.8
196413.2271.9
196314.2274.7
196215.5275.4
196113.9278.5
196014.9276.2
195916.6274.4
195814.4278.7
195715.5277.4
195616.7277
195516.6274.6
195415.7275
195315.4275.4
195216.6275.1
195116277.5
195015.3276.2
CMIP6 模型中位数(SSP2-4.5,中间路径) · 2015–2100
年份意大利泰国
20153021.7–40.4290.6272.2–305
201629.618–42.2287.1269.8–306.2
201731.820.2–43.7290273.8–302.8
20183122–44.3292.6275.1–308.7
201931.521.3–43.2291.2272.8–306.7
202031.619.7–44.3292.4272.2–307.8
20213420.8–46.9294.2276.3–308.5
202237.121.3–50.6294.8277.2–311.9
202333.121.3–47.4296.1281.9–310.2
202435.521.6–48.4291.7275.5–307.8
202537.720.5–51.1294276.7–306.3
202638.926.6–52.2296278–309.3
202734.322.4–49.7295.8276.3–311.1
202837.724.4–53.1297279.3–315.1
202937.824.9–55300.3278.7–315
203037.925.7–54.7297.7280.2–312.5
203137.223.8–51300.8282.8–317.1
203239.226.2–53.8297.2280.9–311.4
203340.426–50.3300281.9–315.8
203442.525.1–57.2300.8279–318.4
203542.728.9–58.3298.6281.5–317.8
203641.127.7–59.9300.4279.9–316.9
20374328.1–54.8299.8280–315.1
203841.628.5–61.3304.8286.6–319.3
20394129.4–56.4300.9281.9–317
204042.428.1–59.1301.6284.5–315.7
204141.927.2–58.7303.1285.1–318.8
204243.529.6–59303.8290–318.3
20434528.7–59.5302285.8–317.9
204444.929.4–59.9304.3286.3–318.8
204545.230.3–59.2307.1287.7–324.2
20464627.3–62.4305.9285.2–321
204749.132.4–63.6306.6289.5–321.5
204846.228.3–65.7309.4288.9–325.7
204948.229.5–65.7308.1287.2–324.1
205049.536.4–64.4307.5291–321.5
205148.831.6–68.3312.8294.8–326
205250.330.9–68.1310.9291.2–323.4
205348.235.9–67308.3289.5–323.3
205449.435.3–66.1308.8292.8–322.3
205552.233.7–67.7308.6290.6–325.1
205650.836.2–71.6311.3294.9–326.3
205750.232.8–65.6308.5286.7–326.4
205855.337.5–70.8308291.1–325.1
205951.934.5–74.1312.7295.8–325.3
206052.938.2–68.1313.1294.6–328.6
206154.338.3–69.8314.4289.5–331.1
206253.936.9–69311.4293.4–330.3
206356.437.6–72.1314.8296.9–327.3
206455.938.5–71.3312.5295.4–330
20655537.3–73.3309.6293.1–329.3
206653.935.8–73.8312.1292.6–328
206761.141.2–76.6311.2289.6–329.4
206856.241.7–73310.8292.4–330.6
206958.741.8–73315.5296.1–329.5
207055.738.9–74.4314.2292.9–330.7
207159.637.8–76.6313.8296.4–330.8
207259.643.5–74.6314.8296–329.6
207356.939.4–71.6316.5299.9–332.1
207454.836.7–73.7317.2295–333.8
207556.941.8–75.4317.2295.3–331.4
207659.941.9–77.7317.4299.8–335
207757.437.9–74.1317.5297.3–335.9
207860.540.5–80.7315.9297.1–331.6
207960.637.1–83.3318.5300.5–332.3
208059.743.1–78319.8297.4–337.5
20815943.7–78.9317.7299.5–334.9
208263.945.5–80.2317.9294.8–333
208360.842–79.7315297.8–332.9
208462.547.3–82.1316295.5–330
208565.246.3–79322.6300.8–334.7
208664.445.6–80.1319.4295.2–335.2
208763.743.8–84320.2302.2–334.7
208867.247.4–84.4321.4299.8–334.8
208964.546–82.9318.9296.4–338.1
209065.842.8–80.5317.6304–337.4
209166.745.3–84.7320.1299.8–336.1
209264.838.5–82.3316.3298–336.4
209363.644.7–83316.1297.7–333.7
209462.445–82323.4301.8–337.3
20956643.6–83.5322.9302.4–338.9
20966542.9–85.8319.6302.8–336.7
209765.844.9–84.4319.8299.1–336
209864.647.9–84.2320.5303.9–336
209967.742.2–81.9319.9303.1–334.4
210065.142.5–83.2320.8301.1–336.7

分别查看各国

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

意大利与泰国对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境