Abstract:In order to study the non-stationary dynamics of atmospheric circulation regimes, the use of model ensembles is often necessary. However, the regime representation within models exhibits substantial variability, making it difficult to detect robust signals. To this end we employ a regularised k-means clustering algorithm to prevent overfitting. The approach allows for the identification of six robust regimes and helps filter out noise in the transition probabilities and frequency of occurrence of the regimes. … Show more
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