How does the homogenisation of snow measurements impact snow climatology in the Alps? (Hom4Snow)
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BORIS DOI
Abstract
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.
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.
Date of Publication
2022
Year of graduation
2022
Theses Type
dissertation
Language(s)
en
Author(s)
Faculty/Graduate School
Access(Rights)
open.access
Primary OA Publication
true