Abstract

Abstract. We present a method for the analysis and compact description of large-scale multivariate weather extremes. Spatial patterns of extreme events are identified using the tail pairwise dependence matrix (TPDM) proposed by Cooley and Thibaud (2019). We also introduce the cross-TPDM to identify patterns of common extremes in two variables. An extremal pattern index (EPI) is developed to provide a pattern-based aggregation of temperature. A heat wave definition based on EPI is able to detect the most important heat waves over Europe. As an extension for considering simultaneous extremes in two variables, we propose the threshold-based EPI (TEPI) that captures the compound character of spatial extremes. We investigate daily temperature maxima and precipitation deficits at different accumulation times and find evidence that preceding precipitation deficits have a significant influence on the development of heat waves and that heat waves often co-occur with short-term drought conditions. We exemplarily show for the European heat waves of 2003 and 2010 that TEPI is suitable for describing the large-scale compound character of heat waves.

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