Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2147-2022
https://doi.org/10.5194/tc-16-2147-2022
Research article
 | 
09 Jun 2022
Research article |  | 09 Jun 2022

Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods

Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty

Data sets

Input data for break detection of Swiss snow depth series Moritz Buchmann, Johannes Aschauer, Michael Begert, and Christoph Marty https://doi.org/10.16904/envidat.297

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Short summary
Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.