Classification of synoptic circulation patterns with a two-stage clustering algorithm using the modified structural similarity index metric (SSIM)

Winderlich, Kristina; Dalelane, Clementine; Walter, Andreas

doi:https://doi.org/10.5194/esd-15-607-2024

Articles | Volume 15, issue 3

https://doi.org/10.5194/esd-15-607-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-15-607-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 3

Research article

|

21 May 2024

Research article |

| 21 May 2024

Classification of synoptic circulation patterns with a two-stage clustering algorithm using the modified structural similarity index metric (SSIM)

Kristina Winderlich, Clementine Dalelane, and Andreas Walter

Supplement

https://doi.org/10.5194/esd-15-607-2024-supplement

Data sets

The NCEP/NCAR 40-Year Reanalysis Project (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html) E. Kalnay et al. https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2

CMIP6 ESGF https://aims2.llnl.gov/search/cmip6/

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Short summary

We develop a new classification method for synoptic circulation patterns. Its unique novelty is the use of the modified structural similarity index metric (SSIM). We demonstrate an exemplary application of the synoptic circulation classes obtained with the new classification method for evaluating historical climate simulations. We introduce a distance metric to measure the match in frequency and duration of synoptic classes between a climate simulation and the reference.