Open Collections

A Markov regime-switching framework application for describing El Niño Southern Oscillation (ENSO) patterns

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

The El Niño-Southern Oscillation (ENSO) is an ocean – atmosphere phenomenon that involves sustained sea surface temperature fluctuations in the Pacific Ocean. This causes disruption in the behavior of the ocean and the atmosphere having important consequences on the global weather. This paper develops a stochastic model to describe El Niño-Southern Oscillation patterns. A Markov Switching Autoregressive model (MS-AR) was implemented to fit the Southern Oscillation Index (SOI), a variable that explains the phenomenon. The model consists of two autoregressive processes describing the time evolution of SOI, each of which associated with a specific phase of ENSO (El Niño and la Niña). The switching between these two models is governed by a discrete time Markov chain. We study the advantages of incorporating time-varying transition probabilities between them and show that the fitted model provides an adequate description of the time series, and demonstrate its utility in analysis and evaluation of the phenomenon.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076152

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/