以色列与泰国对比

以色列与泰国：热带夜

2014 年热带夜：以色列为 97.9 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 188.5 夜，是以色列的 2.93 倍。

在地图上查看其变化

每年夜数 · CMIP6

以色列与泰国：热带夜2014 年热带夜：以色列为 97.9 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 188.5 夜，是以色列的 2.93 倍。
以色列泰国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 年以色列为 149.4 夜，泰国为 320.8 夜。

逐年数据

每年夜数 · CMIP6

年份以色列泰国
201497.9286.4
201398289.1
201296.3286.6
201196.1286.4
201095.5286
200992.5286.9
200894.1284.8
200792.7283.2
200692284.3
200592.3281.7
200490.7287.5
200393.9279.3
200289.5280
200191285.5
200089.5283.4
199986.2282.5
199884.8282.7
199784.2284.8
199683.7279.8
199579.3278.7
199480.1280.8
199371.6275.6
199274.9268.8
199178.4276.7
199080.2279.2
198976.9278.4
198876.5279.6
198775.1277.9
198678.3277.5
198574276
198469.4277.9
198368.9273.9
198273.5275.7
198173.5277.8
198075.3277.9
197968.7278
197871.6276
197772.3277.3
197673.2275.6
197570.9274.4
197472.5276
197371.9280.6
197269.9273.9
197173.1273.2
197071.6276
196970.6274.8
196869.6277
196766.9270.3
196668.8274.4
196563.5275.8
196466.1271.9
196370.9274.7
196273275.4
196171.5278.5
196074.9276.2
195975274.4
195873278.7
195774.8277.4
195674.3277
195572.8274.6
195471.4275
195373.7275.4
195272275.1
195175.1277.5
195069.5276.2
CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100
年份以色列泰国
2015105.988.4–122.7290.6272.2–305
2016104.186.9–120.1287.1269.8–306.2
2017107.892.2–121.4290273.8–302.8
201810993.8–124.2292.6275.1–308.7
201910989.1–124.5291.2272.8–306.7
2020111.594.8–123.5292.4272.2–307.8
202111097.7–128.4294.2276.3–308.5
2022111.493.6–130.2294.8277.2–311.9
2023117.297.9–130.5296.1281.9–310.2
2024114.5100.4–127.3291.7275.5–307.8
2025116.698.3–129.2294276.7–306.3
2026115.9104.9–126.2296278–309.3
2027115.699–127.1295.8276.3–311.1
2028116.3100.2–127.9297279.3–315.1
2029117103.1–129.2300.3278.7–315
2030118.6102.1–131.2297.7280.2–312.5
2031116.8104.4–132.8300.8282.8–317.1
2032121.4106.5–134.7297.2280.9–311.4
2033122.1108.9–134.7300281.9–315.8
2034119.7103.1–133.4300.8279–318.4
2035122.8105.8–138.8298.6281.5–317.8
2036120.2105.5–136.2300.4279.9–316.9
2037121.6106.3–139.4299.8280–315.1
2038126.5105.7–142.1304.8286.6–319.3
2039127.7110.5–147.1300.9281.9–317
2040124.2109.7–144.9301.6284.5–315.7
2041126108.4–141.5303.1285.1–318.8
2042128.5105.8–144.3303.8290–318.3
2043126.5111.8–144.3302285.8–317.9
2044125.9108.5–142.9304.3286.3–318.8
2045130.9117.5–148.6307.1287.7–324.2
2046131114.4–147.2305.9285.2–321
2047132.3116.1–145.4306.6289.5–321.5
2048129.9118.5–146.9309.4288.9–325.7
2049127.9108.7–143.9308.1287.2–324.1
2050133.3114.3–147307.5291–321.5
2051130.3116.7–143.9312.8294.8–326
2052130.3119.9–143.5310.9291.2–323.4
2053135120.4–149.7308.3289.5–323.3
2054134.1118.8–149.3308.8292.8–322.3
2055134.1115.2–150.3308.6290.6–325.1
2056136110.1–151.1311.3294.9–326.3
2057132.7110.9–155308.5286.7–326.4
2058135.7119.1–155.4308291.1–325.1
2059138.8118.5–156.7312.7295.8–325.3
2060136.1116.3–159.2313.1294.6–328.6
2061136119–150.7314.4289.5–331.1
2062139118.7–156311.4293.4–330.3
2063137.4120.1–151.2314.8296.9–327.3
2064139.3121–154.3312.5295.4–330
2065139.6122.3–154.3309.6293.1–329.3
2066137.3119.6–153.7312.1292.6–328
2067142.8126–157.8311.2289.6–329.4
2068141.2122.8–156.4310.8292.4–330.6
2069141.5123.7–157.6315.5296.1–329.5
2070141.8120.5–157.5314.2292.9–330.7
2071142.9124.3–161.8313.8296.4–330.8
2072144.3127–158.5314.8296–329.6
2073143.6127.3–159.2316.5299.9–332.1
2074138.8123–162.2317.2295–333.8
2075138.1120.8–154.6317.2295.3–331.4
2076143.2126.8–161.5317.4299.8–335
2077142.8120.5–161.6317.5297.3–335.9
2078143.6128.2–160.6315.9297.1–331.6
2079148.6123.7–160.2318.5300.5–332.3
2080145.5123.5–163.7319.8297.4–337.5
2081143.7128.1–161.2317.7299.5–334.9
2082145.8129.5–160.6317.9294.8–333
2083149.4126–163.1315297.8–332.9
2084148128.2–164316295.5–330
2085149127.9–162.4322.6300.8–334.7
2086148127.4–167.1319.4295.2–335.2
2087146.4123.7–165.7320.2302.2–334.7
2088147.6133.5–165.3321.4299.8–334.8
2089148.4131.4–169.1318.9296.4–338.1
2090147.6132.4–168.8317.6304–337.4
2091151.9131.7–170.6320.1299.8–336.1
2092148.2132–167.4316.3298–336.4
2093154.1135.3–172.2316.1297.7–333.7
2094153.2133.6–170.3323.4301.8–337.3
2095148.2131.4–164.1322.9302.4–338.9
2096150.5130.5–172.6319.6302.8–336.7
2097149.8134.4–172.7319.8299.1–336
2098150.9131.3–170.1320.5303.9–336
2099149.5129–166.6319.9303.1–334.4
2100149.4130.1–168.5320.8301.1–336.7

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

以色列与泰国对比

健康

人口与社会

经济

教育

政治

冲突

军用

气候

技术与环境