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

Viewed

Total article views: 2,128 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,513 551 64 2,128 158 51 49
  • HTML: 1,513
  • PDF: 551
  • XML: 64
  • Total: 2,128
  • Supplement: 158
  • BibTeX: 51
  • EndNote: 49
Views and downloads (calculated since 17 Mar 2022)
Cumulative views and downloads (calculated since 17 Mar 2022)

Viewed (geographical distribution)

Total article views: 2,128 (including HTML, PDF, and XML) Thereof 2,008 with geography defined and 120 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
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.