Meteorologische Zeitschrift (Aug 2021)

Multivariate analysis and regionalization of climate variability and trends in Germany from 1951–2010

  • Annika Uebachs,
  • Silke Trömel,
  • Alice Kapala,
  • Clemens Simmer

DOI
https://doi.org/10.1127/metz/2021/1038
Journal volume & issue
Vol. 30, no. 4
pp. 297 – 314

Abstract

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Most statements on climate and climate change are made on the basis of single climate parameters or individual sites analyzed independently. Since climate rather consists of many variables including their covariability, we introduce a multi-index approach and apply it for an assessment of climate change over Germany, over the past 50–60 years based on in total 47 climate indices.In a first step we delineate climate regions characterized by similar temporal behaviors of seasonal and annual climate indices using a principal component analysis (PCA) in S mode with Varimax-rotation based on the correlation matrix of the detrended indices time series. The PCA is applied to the four seasons separately but also to the indices describing the entire year. Three to five climate regions are detected, representing distinct geographical regions and roughly dividing the country in a northern, middle and southern part. The number of regions varies with seasons and considered indices. As expected, the inclusion of indices representing extreme events increases the number of detected climate regions. The mean values and trends of spatially-weighted average time series of the single indices for the detected regions provide a first comprehensive characterization of the regional climate and its change.In a second step the regional climate variability and change are analyzed via regional multi-indices. Multi-indices constitute synthetic time-series of a group of well-correlated single indices, which are clustered by applying the PCA in P‑mode to the weighted regional time series of the indices. Depending on season and region, 8–10 multi-indices are found, which can be related to typical weather situations. Several significant trends on a 95 percent significance level are detected in the weighted time series of the multi-indices and indicate a change of climate particularly for the summer season. Generally, the trends suggest a change to more sunny, warm and dry summer weather with less cloudiness and lower relative humidity, a larger anticyclonic influence, longer dry periods, less snow in spring and higher minimum temperatures.

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