Nonlinear time series models for the North Atlantic Oscillation
The North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. This is the result of complex and nonlinear interactions between many spatio-temporal scales. Here, the auth...
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ftdoajarticles:oai:doaj.org/article:639fae3ebef24bad80995c81f64bb682 2023-05-15T17:28:05+02:00 Nonlinear time series models for the North Atlantic Oscillation T. Önskog C. L. E. Franzke A. Hannachi 2020-10-01T00:00:00Z https://doi.org/10.5194/ascmo-6-141-2020 https://doaj.org/article/639fae3ebef24bad80995c81f64bb682 EN eng Copernicus Publications https://ascmo.copernicus.org/articles/6/141/2020/ascmo-6-141-2020.pdf https://doaj.org/toc/2364-3579 https://doaj.org/toc/2364-3587 doi:10.5194/ascmo-6-141-2020 2364-3579 2364-3587 https://doaj.org/article/639fae3ebef24bad80995c81f64bb682 Advances in Statistical Climatology, Meteorology and Oceanography, Vol 6, Pp 141-157 (2020) Oceanography GC1-1581 Meteorology. Climatology QC851-999 Probabilities. Mathematical statistics QA273-280 article 2020 ftdoajarticles https://doi.org/10.5194/ascmo-6-141-2020 2022-12-31T03:14:10Z The North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. This is the result of complex and nonlinear interactions between many spatio-temporal scales. Here, the authors study a number of linear and nonlinear models for a station-based time series of the daily winter NAO index. It is found that nonlinear autoregressive models, including both short and long lags, perform excellently in reproducing the characteristic statistical properties of the NAO, such as skewness and fat tails of the distribution, and the different timescales of the two phases. As a spin-off of the modelling procedure, we can deduce that the interannual dependence of the NAO mostly affects the positive phase, and that timescales of 1 to 3 weeks are more dominant for the negative phase. Furthermore, the statistical properties of the model make it useful for the generation of realistic climate noise. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Directory of Open Access Journals: DOAJ Articles Advances in Statistical Climatology, Meteorology and Oceanography 6 2 141 157 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Oceanography GC1-1581 Meteorology. Climatology QC851-999 Probabilities. Mathematical statistics QA273-280 |
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Oceanography GC1-1581 Meteorology. Climatology QC851-999 Probabilities. Mathematical statistics QA273-280 T. Önskog C. L. E. Franzke A. Hannachi Nonlinear time series models for the North Atlantic Oscillation |
topic_facet |
Oceanography GC1-1581 Meteorology. Climatology QC851-999 Probabilities. Mathematical statistics QA273-280 |
description |
The North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. This is the result of complex and nonlinear interactions between many spatio-temporal scales. Here, the authors study a number of linear and nonlinear models for a station-based time series of the daily winter NAO index. It is found that nonlinear autoregressive models, including both short and long lags, perform excellently in reproducing the characteristic statistical properties of the NAO, such as skewness and fat tails of the distribution, and the different timescales of the two phases. As a spin-off of the modelling procedure, we can deduce that the interannual dependence of the NAO mostly affects the positive phase, and that timescales of 1 to 3 weeks are more dominant for the negative phase. Furthermore, the statistical properties of the model make it useful for the generation of realistic climate noise. |
format |
Article in Journal/Newspaper |
author |
T. Önskog C. L. E. Franzke A. Hannachi |
author_facet |
T. Önskog C. L. E. Franzke A. Hannachi |
author_sort |
T. Önskog |
title |
Nonlinear time series models for the North Atlantic Oscillation |
title_short |
Nonlinear time series models for the North Atlantic Oscillation |
title_full |
Nonlinear time series models for the North Atlantic Oscillation |
title_fullStr |
Nonlinear time series models for the North Atlantic Oscillation |
title_full_unstemmed |
Nonlinear time series models for the North Atlantic Oscillation |
title_sort |
nonlinear time series models for the north atlantic oscillation |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/ascmo-6-141-2020 https://doaj.org/article/639fae3ebef24bad80995c81f64bb682 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Advances in Statistical Climatology, Meteorology and Oceanography, Vol 6, Pp 141-157 (2020) |
op_relation |
https://ascmo.copernicus.org/articles/6/141/2020/ascmo-6-141-2020.pdf https://doaj.org/toc/2364-3579 https://doaj.org/toc/2364-3587 doi:10.5194/ascmo-6-141-2020 2364-3579 2364-3587 https://doaj.org/article/639fae3ebef24bad80995c81f64bb682 |
op_doi |
https://doi.org/10.5194/ascmo-6-141-2020 |
container_title |
Advances in Statistical Climatology, Meteorology and Oceanography |
container_volume |
6 |
container_issue |
2 |
container_start_page |
141 |
op_container_end_page |
157 |
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