Articles | Volume 29, issue 3
Research article
05 Jul 2022
Research article |  | 05 Jul 2022

Empirical adaptive wavelet decomposition (EAWD): an adaptive decomposition for the variability analysis of observation time series in atmospheric science

Olivier Delage, Thierry Portafaix, Hassan Bencherif, Alain Bourdier, and Emma Lagracie

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Cited articles

Ayenu-Prah, A. Y. and Attoh-Okine, N.: A Criterion for Selecting Relevant Intrinsic Mode Functions in Empirical Mode Decomposition, Advances in Adaptive Data Analysis, 2, 1–24,, 2010. 
Bègue, N., Bencherif, H., Sivakumar, V., Kirgis, G., Mze, N., and Leclair de Bellevue, J.: Temperature variability and trends in the UT-LS over a subtropical site: Reunion (20.8 S, 55.5 E), Atmos. Chem. Phys., 10, 8563–8574,, 2010. 
Bencherif, H., Diab, R. D., Portafaix, T., Morel, B., Keckhut, P., and Moorgawa, A.: Temperature climatology and trend estimates in the UTLS region as observed over a southern subtropical site, Durban, South Africa, Atmos. Chem. Phys., 6, 5121–5128,, 2006. 
Bourassa, A. E., Degenstein, D. A., Randel, W. J., Zawodny, J. M., Kyrölä, E., McLinden, C. A., Sioris, C. E., and Roth, C. Z.: Trends in stratospheric ozone derived from merged SAGE II and Odin-OSIRIS satellite observations, Atmos. Chem. Phys., 14, 6983–6994,, 2014. 
Brunner, D., Staehelin, J., Maeder, J. A., Wohltmann, I., and Bodeker, G. E.: Variability and trends in total and vertically resolved stratospheric ozone based on the CATO ozone data set, Atmos. Chem. Phys., 6, 4985–5008,, 2006. 
Short summary
The complexity of geophysics systems results in time series with fluctuations at all timescales. The analysis of their variability then consists in decomposing them into a set of basis signals. We developed here a new adaptive filtering method called empirical adaptive wavelet decomposition that optimizes the empirical-mode decomposition existing technique, overcoming its drawbacks using the rigour of wavelets as defined in the recently published empirical wavelet transform method.