Software FZJ-2025-04958

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KSC - Observational Data Clustering Preprocessor

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2025

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Abstract: Preprocessing routine for ground-based atmospheric monitoring network data. Utilizing a k-means soft constrained clustering algorithm to derive a representative sub-sampling of the availiable data into an assimilation and validation set.  This work was partially performed as part of the Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) and received funding from the Helmholtz Association of German Research Centres.


Contributing Institute(s):
  1. Troposphäre (ICE-3)
Research Program(s):
  1. 899 - ohne Topic (POF4-899) (POF4-899)

Appears in the scientific report 2025
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 Record created 2025-12-04, last modified 2025-12-04



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