摘要
This study assesses the historical climate trends of surface air temperature(SAT), their spatial distributions, and the hindcast skills for SAT during 1901– 2000 from 24 Coupled Model Intercomparison Project Phase 5(CMIP5) models. For the global averaged SAT, most of the models(17/24) effectively captured the increasing trends(0.64°C/century for the ensemble mean) as the observed values(- 0.6°C/century) during the period of 1901–2000, particularly during a rapid warming period of 1970–2000 with the small model spread. In addition, most of the models(22/24) showed high hindcast skills(the correlation coefficient, R 〉 0.8). For the spatial pattern of SAT, the models better simulated the relatively larger warming at the middle-to-high latitudes in the Northern Hemisphere than that in the Southern Hemisphere and the greater warming on the land than that in the ocean between 40°S and 40°N. The simulations underestimated the warming along some ocean boundaries but overestimated warming in the Arctic Ocean. Most of the coupled models were able to reproduce the large-scale features of SAT trends in most regions excluding Antarctica, some parts of the Pacific Ocean, the North Atlantic Ocean near Greenland, the southwestern Indian Ocean, and the Arctic Ocean. The outgoing longwave radiation(OLR) and incoming shortwave radiation(ISR) at the top of the atmosphere(TOA) and the downward longwave(LW) radiation and sensible heat flux at the surface had positive contributions to the increasing trends in most of the models.
这研究估计表面空气温度的历史的气候趋势(坐) ,他们的空间分布,和 hindcast 技巧为从 24 联合模型 Intercomparison 工程阶段坐在 19012000 期间(CMTP5 ) 5 当模特儿。为全球平均坐,大多数模型(17/24 ) 有效地捕获了增加的趋势(0.64 婂愠摮琠敨琠睯牥 ? 敷敲猠灥牡瑡汥? 潬慣整 ? 敢敮瑡 ? 睴? 虧溎訙U @ 眠瑩 ? 潬 ? 污楴畴敤 ? 景㈠ ?欠
基金
supported by the National Basic Research Program of China (Grant No. 2010CB950502)
the National Natural Science Foundation of China (Grant Nos. 41376019, 41023002, and 41376039)
Joint Center for Global Change Studies (Grant No. 105019)
the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant Nos. XDA05110302 and XDA11010304)