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...
| Authors: | , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2005 |
| Country: | Brasil |
| Institution: | Universidade Federal do Rio Grande do Sul (UFRGS) |
| Repository: | Repositório Institucional da UFRGS |
| Language: | English |
| OAI Identifier: | oai:www.lume.ufrgs.br:10183/101619 |
| Online Access: | http://hdl.handle.net/10183/101619 |
| Access Level: | Open access |
| Keyword: | Climatologia Processos de Markov Processos estocásticos Séries temporais |
| 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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