摘要
基于第六次耦合模式比较计划(CMIP6)的3个全球气候模式结果,利用经验正交分解方法和参数方法分析了模式模拟的热带地区大尺度大气垂直运动廓线特征并揭示其与云和辐射量的关系。结果表明,基于EOF分解方法,3个模式均可较好地再现热带大气垂直运动特征,即热带大气垂直运动90%以上的方差可由两个主导的垂直结构模态解释,其中EOF1表征大气的整体上升或下沉,EOF2表征一个由深厚的中层辐合辐散占主导的垂直运动廓线。在此基础上定义了一对更为简洁易用的参数(ω和dω),此对参数可较好地描述EOF分解所揭示出的垂直运动廓线特征。利用新定义的参数发现,在西太平洋暖池区域,高云在“上重”下沉区域为低值,中云云量在“下重”上升运动区域为高值。大气层顶对外长波短波辐射均表现出对运动廓线结构的依赖。研究为评估气候模式对云和辐射模拟提供了一组有效因子。
In this study,the characteristics of tropical large scale atmospheric pressure vertical velocity(ω)profiles were analyzed by using the output of three CMIP6 models based on the Empirical Orthogonal Function(EOF)method and the parametric method.Their relationships with cloud and radiation were revealed.It is found that based on EOF method,the three models can reproduce the vertical profile characteristics of the tropical atmosphere,the two leading EOFs explain 90%of the total variance of the structure of theωprofile.The first EOF corresponds to a deep ascending/descending motion of the troposphere.The second EOF represents a thick convergence/divergence layer in the middle troposphere.A pair of parameters(ω and dω)are then defined to characterize of theωprofile.These concise parameters can effectively represent structures captured by the above relatively complex EOF combination,while they are much easier to implement.The relationships between the structure of theωprofile and the model outputted cloud and radiation are then investigated based on the phase space consisted by the and dω.The targeted area is the Western Pacific warm pool region.High clouds are more distributed in the region with strong“top heavy”upward motion,mid clouds are more distributed in the region with strong“bottom heavy”upward motion.TOA radiation shows a strong dependence on the rising motion and sinking motion.This study provides a set of effective factors for assessing climate models for cloud and radiation simulations.
作者
韩波
袁健
HAN Bo;YUAN Jian(School of Atmospheric Sciences,Nanjing University,Nanjing 210023,China)
出处
《气象科学》
北大核心
2023年第4期553-560,共8页
Journal of the Meteorological Sciences
基金
国家重点研发计划资助项目(2016YFC0202000)
国家自然科学基金资助项目(42175021)。
