Articles | Volume 7, issue 2
https://doi.org/10.5194/esd-7-517-2016
https://doi.org/10.5194/esd-7-517-2016
Research article
 | 
20 Jun 2016
Research article |  | 20 Jun 2016

A wavelet-based approach to detect climate change on the coherent and turbulent component of the atmospheric circulation

Davide Faranda and Dimitri Defrance

Abstract. The modifications of atmospheric circulation induced by anthropogenic effects are difficult to capture because wind fields feature a complex spectrum where the signal of large-scale coherent structures (planetary, baroclinic waves and other long-term oscillations) is mixed up with turbulence. Our purpose is to study the effects of climate changes on these two components separately by applying a wavelet analysis to the 700 hPa wind fields obtained in climate simulations for different forcing scenarios. We study the coherent component of the signal via a correlation analysis to detect the persistence of large-scale or long-lasting structures, whereas we use the theory of autoregressive moving-average stochastic processes to measure the spectral complexity of the turbulent component. Under strong anthropogenic forcing, we detect a significant climate change signal. The analysis suggests that coherent structures will play a dominant role in future climate, whereas turbulent spectra will approach a classical Kolmogorov behaviour.

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Short summary
We introduce a general technique to detect a climate change signal in the coherent and turbulent components of the atmospheric circulation. Our analysis suggests that the coherent components (atmospheric waves, long-term oscillations) will experience the greatest changes in future climate, proportionally to the greenhouse gas emission scenario considered.
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