Reconstructed daily mean sea level pressure patterns of the North Atlantic-European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum ...
This dataset is an updated version of the gridded climate reconstruction by Sjolte et al. 2018 (SEA1...
We use sophisticated machine-learning techniques on a network of summer temperature and precipitatio...
We analyze European temperature variability from station data with the method of detrended fluctuati...
Reconstructed daily mean sea level pressure patterns of the North Atlantic-European region are class...
Using pressure fields classified by the SANDRA algorithm, this study investigates the changes in the...
We analyze the influence of the Atlantic sea surface temperature multi-decadal variability on the da...
While the evidence for anthropogenic climate change continues to strengthen, and concerns about seve...
This study investigates the importance of large-scale atmospheric circulation changes for Central Eu...
Atmospheric circulation is often clustered in so‐called circulation regimes, which are persistent an...
Long-term changes in the persistence of atmospheric circulation (measured by the mean residence time...
The stability of the relationships between atmospheric circulation and the surface climatic variable...
We determine robust modes of the northern hemisphere (NH) sea ice variability on interannual timesca...
Boreal winter wind storm situations over Central Europe are investigated by means of an objective cl...
Abstract. European climate variability is shaped by atmospheric dynamics and local physical processe...
Under particular large-scale atmospheric conditions, several windstorms may affect Europe within a s...
This dataset is an updated version of the gridded climate reconstruction by Sjolte et al. 2018 (SEA1...
We use sophisticated machine-learning techniques on a network of summer temperature and precipitatio...
We analyze European temperature variability from station data with the method of detrended fluctuati...
Reconstructed daily mean sea level pressure patterns of the North Atlantic-European region are class...
Using pressure fields classified by the SANDRA algorithm, this study investigates the changes in the...
We analyze the influence of the Atlantic sea surface temperature multi-decadal variability on the da...
While the evidence for anthropogenic climate change continues to strengthen, and concerns about seve...
This study investigates the importance of large-scale atmospheric circulation changes for Central Eu...
Atmospheric circulation is often clustered in so‐called circulation regimes, which are persistent an...
Long-term changes in the persistence of atmospheric circulation (measured by the mean residence time...
The stability of the relationships between atmospheric circulation and the surface climatic variable...
We determine robust modes of the northern hemisphere (NH) sea ice variability on interannual timesca...
Boreal winter wind storm situations over Central Europe are investigated by means of an objective cl...
Abstract. European climate variability is shaped by atmospheric dynamics and local physical processe...
Under particular large-scale atmospheric conditions, several windstorms may affect Europe within a s...
This dataset is an updated version of the gridded climate reconstruction by Sjolte et al. 2018 (SEA1...
We use sophisticated machine-learning techniques on a network of summer temperature and precipitatio...
We analyze European temperature variability from station data with the method of detrended fluctuati...