Long-term snow measurements are crucial for climatological analyses. However, the longer a time series, the more like for it to include breaks or inhomogeneities, potentially introduced by station relocation or changes of the station environment.
These inhomogeneities can have a huge effect on trends and other climatological analyses.
A possible solution to address this problem is the homogenisation of the time series.
During this thesis, the three steps of homogenisation (identify breakpoints in a time series, verify the breakpoints, and adjust the time series accordingly) are carried out in detail. Breakpoints are identified using a robust approch of combining the results from three well-established homogenisation toolboxes: ACMANT, Climatol, and HOMER.
The impact assessment is carried out using Climatol, HOMER and interpQM.