Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 29, issue 3
Articles | Volume 29, issue 3
https://doi.org/10.5194/npg-29-265-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-29-265-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
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

Viewed

Total article views: 2,876 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,119 685 72 2,876 73 69
  • HTML: 2,119
  • PDF: 685
  • XML: 72
  • Total: 2,876
  • BibTeX: 73
  • EndNote: 69
Views and downloads (calculated since 07 Jan 2022)
Cumulative views and downloads (calculated since 07 Jan 2022)

Viewed (geographical distribution)

Total article views: 2,876 (including HTML, PDF, and XML) Thereof 2,705 with geography defined and 171 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 31 Jul 2025
Download
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.
Read more
Share