Empirical Decomposition of Low-Frequency Atmospheric Variability for Climate Dynamics Studies

本项目将把经验模式分解(EMD)技术应用于NCEP再分析同化中，以研究大气低频变率存在的时空结构。这种变化包括全球准两年振荡、可能的厄尔尼诺-南方涛动模式、可能的11年太阳周期信号、22年周期(迄今尚未确定)以及据信由平流层冷却引起的对流层变暖趋势。这项工作的主要目标是了解大气中低频变化的性质，也许可以提供一种工具来区分这种变化的自然发生和人类诱导的成分。一种新方法(EMD)的使用将扩大分析技术的范围，以探索大气中的长期变化。这些成果预计将惠及科学界，并将通过国际科学期刊和主要会议进行传播。一名女性博士后将接受支持和培训。

This project will apply Empirical Mode Decomposition (EMD), a technique for analyzing time series recently developed by Huang et alia (1998), to the 45-year long NCEP reanalysis assimilation in order to study the spatial and temporal structure present in low frequency atmospheric variability. Such variability includes the global Quasi-Biennial Oscillation, a possible El Nino-Southern Oscillation mode, a possible 11-year solar cycle signal, a 22-year cycle (so far unidentified) and a warming trend in the troposphere believed to arise from cooling of the stratosphere. The principal objective of this work is to understand the nature of low frequency variability in the atmosphere, perhaps offering a facility to differentiate between the naturally-occurring and anthropogenically-induced components of this variability.The use of a new method (EMD) will broaden the scope of analysis techniques to probe long-term variability in the atmosphere. The results are expected to benefit the scientific community, and will be disseminated via international scientific journals and major conferences. One female post-doctoral student will receive support and training.