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Three-Dimensional Modal and Nonmodal Structures in Frontal Rainbands

Three-Dimensional Modal and Nonmodal Structures in Frontal Rainbands
锋面雨带中的三维模态和非模态结构
批准号:
9983077
负责人:
Qin Xu
金额:
$25.73万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-05-01 至 2004-04-30

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中文摘要
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英文摘要
It has been observed that mid-latitude precipitation is commonly associated with frontal systems and frontal precipitation is organized into bands, which exhibit three-dimensional substructures. Prediction of fronts and associated precipitation on the synoptic scale has steadily improved over the past decade; however, prediction of frontal substructures and associated precipitation on the mesoscale has experienced less success. The goal of this research is to explore new instability mechanisms that will provide possible explanations for some observed three-dimensional substructures, including severe storm elements, embedded in frontal rainbands. As one of the possible dynamic mechanisms, symmetric instability (SI) and conditional SI have been shown to have many attractive features in interpreting the gross structures of some observed frontal rainbands. However, the often-observed three-dimensional substructures in frontal rainbands are beyond the description of current SI theories. Recent research by the Principal Investigator (PI) suggests that nonlinear SI circulations are unstable in three dimensions and the related secondary unstable modes resemble some observed mesoscale substructures. The results obtained so far are still very preliminary but shed light on a number of important issues, which need further investigation.Successful completion of this research will advance theoretical understanding of precipitation systems and potentially lead to better forecasts.
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会议论文
Balanced and Unbalanced Mesoscale Dynamics
Theoretical Studies of Cold Air Damming
Theories and Methods for Diagnoses of Moist Frontal Circulations
Theoretical Studies on Baroclinic Waves and Frontogenesis inthe Presence of Small Moist Symmetric Stability
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis