Reducing stochasticity in the North Altantic Oscillation index with coupled Langevin equations

We present a critical investigation of the functional relationship between the two pressure time series routinely used to define the index characterizing the North Atlantic Oscillation NAO , well known to regulate global climate variability and change. First, by a standard Markov analysis we show th...

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Bibliographic Details
Main Authors: Lind, Pedro Gonçalves, Mora, Alejandro, Gallas, Jason Alfredo Carlson, Haase, Maria
Format: Article in Journal/Newspaper
Language:English
Published: 2005
Subjects:
Climatologia
Processos de Markov
Processos estocásticos
Séries temporais
North Atlantic
North Atlantic oscillation
Online Access:http://hdl.handle.net/10183/101619
Description
Summary:We present a critical investigation of the functional relationship between the two pressure time series routinely used to define the index characterizing the North Atlantic Oscillation NAO , well known to regulate global climate variability and change. First, by a standard Markov analysis we show that the standard NAO index based on the pressure difference is not optimal in the sense of producing sufficiently reliable forecasts because it contains a dominating stochastic term in the corresponding Langevin equation. Then, we introduce a variationally optimized Markov analysis involving two coupled Langevin equations tailored to produce a NAO quasi-index having the desired minimum possible stochasticity. The variationally optimized Markov analysis is very general and can be applied in other physical situations involving two or more time series.

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