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

• Autor(a) principal: Lind, Pedro Gonçalves
• Data de Publicação: 2005
• Outros Autores: Mora, Alejandro, Gallas, Jason Alfredo Carlson, Haase, Maria
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/101619
• topic: Climatologia; Processos de Markov; Processos estocásticos; Séries temporais

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.