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上升气流速度在全球云水汽凝结体数量时间变化中的作用。

Role of updraft velocity in temporal variability of global cloud hydrometeor number.

作者信息

Sullivan Sylvia C, Lee Dongmin, Oreopoulos Lazaros, Nenes Athanasios

机构信息

School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332;

Goddard Earth Sciences Technology and Research, Morgan State University, Baltimore, MD 21251;

出版信息

Proc Natl Acad Sci U S A. 2016 May 24;113(21):5791-6. doi: 10.1073/pnas.1514039113. Epub 2016 May 16.

Abstract

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

摘要

了解动力学和气溶胶输入如何影响气候模型中水文气象形成的时间变异性,将有助于解释云强迫中模型多样性的来源,与数据进行可靠比较,并最终减少气溶胶间接效应估计中的不确定性。这种变异性归因可以通过从液滴和冰晶数量对相关输入的在线伴随敏感性得出的指标,在各种空间和时间分辨率下进行。此类指标是根据使用美国国家航空航天局戈达德地球观测系统模型第5版(GEOS - 5)和美国国家大气研究中心社区大气模型第5.1版(CAM5.1)的模拟定义和计算的。在GEOS - 5中,输入的上升气流速度波动可解释输出冰晶数量时间变异性的48%以及液滴数量时间变异性的61%,在CAM5.1中可解释输出冰晶数量时间变异性的高达89%。在这两个模型中,这种垂直速度归因在很大程度上取决于高度。尽管其对水文气象形成很重要,但由于相关数据稀少,模拟的垂直速度分布很少与观测结果进行评估。大气科学界共同努力开发更一致的、基于观测的上升气流处理方法,将有助于填补这一知识空白。

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