Non‐linear time series analysis of precipitation events using regional climate networks for Germany

In Germany, spatial structures of precipitation are mainly determined by the orography and its position in relation to the sea. This is not only the case for long-term means of precipitation sums (Klein and Menz 2003), but holds true for heavy precipitation as well, as shown on the basis of the frequency of daily sums of 10 mm and more (Gerstengarbe and Werner 2009). As visualized in Fig. 1, large precipitation sums occur mainly in mountainous areas and in regions close to the coast of the North Sea. Small daily sums occur especially in the northeast. In this study, our focus is exclusively on heavy precipitation in Germany, which we define as precipitation that leads to daily sums of at least 10 mm. A weather station with a daily precipitation sum larger than or equal to this threshold is considered to have a precipitation event on the corresponding day. Variations in the spatial distribution of precipitation are well-captured by precipitation events defined by said threshold: The spatial precipitation pattern, given by average daily precipitation sums, is very similar to the spatial pattern of average event rates (see Fig. 1). Furthermore, we consider 10 mm as a good compromise between having a sufficient number of events at each location and a rather high threshold in order to study heavy precipitation. The average event rate for all event series of the entire period with a threshold of 10 mm is around 0.064. On average, we have 1300 events per event series. In order to study synchronous occurrences of heavy precipitation events, we specify synchronization scores between all 2337 meteorological stations and precipitation gauges in Germany. These scores are defined as the number of synchronous occurrences of events in the pairs of event series, standardized to the expected number of Abstract Synchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We propose a novel standardization of this number that results in synchronization scores which are not biased by the number of events in the respective time series. Additionally, we introduce a new version of the network measure directionality that measures the spatial directionality of weighted links by also taking account of the effects of the spatial embedding of the network. This measure provides an estimate of heavy precipitation isochrones by pointing out directions along which rainfall events synchronize. We propose a climatological interpretation of this measure in terms of propagating fronts or event traces and confirm it for Germany by comparing our results to known atmospheric circulation patterns.