学术动态
当前位置:首页 >> 学术动态
2016-2017学年第一学期航空航天系第十三期学术讲座
发表时间:2016-12-28 阅读次数:731次

题目:Simple Stochastic Dynamical Models Capturing the Statistical Diversity of El Nino Southern Oscillation

主讲:Dr. Nan Chen

主持:艾剑良 教授

时间:2016年12月28日(周三)下午1:30 - 3: 00

地点:光华楼东主楼2601室

 

教授简介

CURRENT POSITION:

Postdoc Research Associate

Courant Institute of Mathematical Sciences, New York, NY 

EDUCATION:

PhD in Mathematics/Atmosphere and Ocean Sciences, April 2016 

Courant Institute of Mathematical Sciences, New York, NY

Master in Computational Mathematics, July 2011

Bachelor in Theoretic and Applied Mechanics1

Fudan University, Shanghai, P. R. China

RESEARCH INTEREST:

Uncertainty Quantification, Reduced Model Prediction,

Data Assimilation or State Estimation,

Madden-Julian Oscillation, El Nin ̃o Southern Oscillation, Stochastic Models, Fluids and Geophysical Flows, Inverse Problems

内容简介

The El Nino Southern Oscillation (ENSO) has significant impact on global climate and seasonal prediction. The well-known traditional El Nino involves anomalous warm sea surface temperature (SST) in the equatorial eastern Pacific ocean, where its atmospheric response is the eastward shift of the anomalous Walker circulation with strong convection occurring near the west coast of America. In the recent decades, a new type of El Nino has been frequently observed, which is called the central Pacific (CP) El Nino. The CP El Nino is characterized by warm SST anomalies confined to the central Pacific. In this talk, I will introduce a new simple modeling framework that automatically captures the statistical diversity of ENSO. Particularly, this is the first simple model that captures the key feature of CP El Nino. In addition to simulating different types of El Nino and La Nina with realistic features, the model succeeds in capturing both the variance and the non-Gaussian statistical properties in different Nino regions spanning the Pacific. Particularly, the observed episode during 1990s, where a 5-year central Pacific El Nino is followed by a super El Nino and then a La Nina, is reproduced by the model. Key features of the model are state-dependent stochastic wind bursts and nonlinear advection of SST which allow effective transitions between different ENSO states.

Copyright © 2013 复旦大学航空航天系   旧版入口

上海市邯郸路220号  电话:021-65642741 传真:021-65642742

技术支持:维程互联