Preprints
https://doi.org/10.5194/npg-2020-46
https://doi.org/10.5194/npg-2020-46

  02 Dec 2020

02 Dec 2020

Review status: a revised version of this preprint was accepted for the journal NPG and is expected to appear here in due course.

Identification of Droughts and Heat Waves in Germany with Regional Climate Networks

Gerd Schädler and Marcus Breil Gerd Schädler and Marcus Breil
  • Institute of Meteorology and Climate Research - Department Troposphere Research, Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract. Regional Climate Networks (RCNs) are used to identify heat waves and droughts in Germany and two subregions for the summer half years resp. summer seasons of the period 1951 to 2019. RCNs provide information for whole areas (in contrast to the point-wise information from standard indices), the underlying nodes can be distributed arbitrarily, they are easy to 5 construct and provide details otherwise difficult to avail of like extent, intensity and collective behaviour of extreme events. The RCNs were constructed on the regular 0.25 degree grid of the E-Obs data set. The season-wise correlation of time series of daily maximum temperature Tmax and precipitation were used to construct the adjacency matrix of the networks. Metrics to identify extremes were the edge density, the 90th percentile of the correlations and the average clustering coefficient, which turned out to be highly correlated; they increased considerably during extreme events. The standard indices for comparison 10 were the effective drought and heat index (EDI and EHI) respectively, based on the same time series, and complemented by other published data. Our results show that the RCNs are able to identify severe extremes in all cases and moderate extremes in most cases. An interesting finding is that during average years, the distribution of the node degrees is close to the Poisson distribution, characteristic of random networks, while for extreme years the distribution is more uniform and heavy tailed.

Gerd Schädler and Marcus Breil

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Gerd Schädler and Marcus Breil

Gerd Schädler and Marcus Breil

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Short summary
We used regional climate networks (RCNs) to identify heat waves and droughts in Germany. RCNs provide information for whole areas and provide many details of extreme events. The RCNs were constructed on the grid of the E-Obs data set. Time series correlation was used to construct the networks. Network metrics were compared to standard extreme indices. The results show that RCNs have skill to identify severe and moderate extremes. In average years, distributions resemble Poisson distributions.