学术公告

中国科学院大气物理研究所袁乃明副研究员学术报告
发布时间: 2017-05-17 11:06:00   作者:xsgg   来源:   浏览次数:

绿色地球论坛第278期(2017-11)
——环境学院系列学术报告会

题目:Nonlinear time sereis analysis: from scaling behavior to prediction tools
时间:2017年5月19日(周五)下午14:30
地点:丹桂苑105室
报告人简介
        袁乃明,2012年获得博士学位,中国科学院大气物理研究所东亚区域-环境重点实验室副研究员,中科院百人计划C类候选人。主要研究方向:气候预测理论,气候系统的长期记忆性,非线性时间序列分析等.近年来发表SCI论文近30篇。其中在J.Climate, JGR, Sci.Rep等著名期刊发表研究论文8篇。2016年曾获世界气象组织Mariolopoulos教授信托基金奖。目前主持国家自然科学基金青年项目1项,面上项目1项。
报告摘要
        In this talk, long-term memory (LTM) in climate variability is introduced and a new perspective on climate prediction is proposed. Using a recently developed model, Fractional Integral Statistical Model (FISM), any given climatic time series with LTM can be decomposed into two components: historical memory component M(t) and weather scale excitations . M(t) represents the long-lasting influences accumulated from the past history, which can be considered as a kind of “inertia” in climate system. , however, is not a simple white noise, but contains dynamical information which triggers the current climate regime to change. While for , it is still a big challenge to make reliable estimations. In this talk, several potential approaches for the estimation o f  are introduced, among which, we provide more details on a recently proposed method, Detrended Partial-Cross-Correlation Analysis. It is argued that may be better estimated by establishing a hierarchical prediction model, but more efforts are needed in the future.
 


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