Articles | Volume 33, issue 1
https://doi.org/10.5194/npg-33-85-2026
https://doi.org/10.5194/npg-33-85-2026
Research article
 | 
12 Feb 2026
Research article |  | 12 Feb 2026

Dynamic mode decomposition of extreme events

Maša Ann, Jörn Behrens, and Jana Sillmann

Viewed

Total article views: 7,363 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
5,597 1,552 214 7,363 265 351
  • HTML: 5,597
  • PDF: 1,552
  • XML: 214
  • Total: 7,363
  • BibTeX: 265
  • EndNote: 351
Views and downloads (calculated since 14 Aug 2025)
Cumulative views and downloads (calculated since 14 Aug 2025)

Viewed (geographical distribution)

Total article views: 7,363 (including HTML, PDF, and XML) Thereof 7,237 with geography defined and 126 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 31 Oct 2026
Download
Short summary
We present a new framework based on Dynamic Mode Decomposition (DMD) to better detect outliers and model extremes. Unlike standard DMD, which focuses on average system behaviour, our approach targets rare, exceptional dynamics. Applied to climate data, it improves extreme event approximation and reveals meaningful spatiotemporal patterns. The method may generalise to other types of extremes.
Share