Nonlinear time series models for the North Atlantic Oscillation
<p>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,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-10-01
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| Series: | Advances in Statistical Climatology, Meteorology and Oceanography |
| Online Access: | https://ascmo.copernicus.org/articles/6/141/2020/ascmo-6-141-2020.pdf |
| Summary: | <p>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.</p> |
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| ISSN: | 2364-3579 2364-3587 |