The benefits of homogenising snow depth series – Impacts on decadal trends and extremes for Switzerland

Buchmann, Moritz; Resch, Gernot; Begert, Michael; Brönnimann, Stefan; Chimani, Barbara; Schöner, Wolfgang; Marty, Christoph

doi:https://doi.org/10.5194/tc-17-653-2023

Articles | Volume 17, issue 2

https://doi.org/10.5194/tc-17-653-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-17-653-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 2

Research article

|

09 Feb 2023

Research article |

| 09 Feb 2023

The benefits of homogenising snow depth series – Impacts on decadal trends and extremes for Switzerland

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

Data sets

Input data for the following research article: Impact assessment of homogenised snow depth series on trends Moritz Buchmann and Gernot Resch https://doi.org/10.16904/envidat.336

Short summary

Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.