Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales

doi:10.2172/1240272

GSTDTAP > 地球科学

DOI	10.2172/1240272
报告编号	DOE-COLUMBIA--06712
来源ID	OSTI ID: 1240272
	Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales
	Tselioudis, George
	2016-03-04
出版年	2016
页数	7
语种	英语
国家	美国
领域	地球科学
英文摘要	From its location on the subtropics-midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes, and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets to deep convective systems. This project combined three types of data sets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three data sets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high-pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for post-frontal environments and northwesterly flows. An evaluation of CMIP5 climate model cloud regimes over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that carefully selected case studies can be related through regime analysis to climatological cloud distributions, and a methodology is suggested utilizing process-resolving model simulations of individual cases to better understand cloud-dynamics interactions and attempt to explain and correct climate model cloud deficiencies.
英文关键词	CLOUDS. RADIATION. MODELING.
URL	查看原文
来源平台	US Department of Energy (DOE)
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/7123
专题	地球科学
推荐引用方式 GB/T 7714	Tselioudis, George. Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales,2016.