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Multivariate statistical modelling of compound flooding events for southern African coasts
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  • Jessica Kelln,
  • Matthias Hirt,
  • Sönke Dangendorf,
  • Arne Arns,
  • Franziska Schwarzkopf,
  • Sara Santamaria Aguilar,
  • Jürgen Jensen
Jessica Kelln
University of Siegen

Corresponding Author:jessica.kelln@uni-siegen.de

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Matthias Hirt
University of Siegen
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Sönke Dangendorf
Old Dominion University
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Arne Arns
University of Siegen
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Franziska Schwarzkopf
GEOMAR Helmholtz Centre for Ocean Research Kiel
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Sara Santamaria Aguilar
University of Kiel
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Jürgen Jensen
University of Siegen
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Abstract

In March 2019 cyclone Idai led to a compound flooding event in Mozambique combining high river runoff and storm induced water level extremes and causing damages up to 2 billion USD and more than 1200 fatalities. The co-occurrence of storm surges, wind waves, and flooding through heavy precipitation and runoff increases the risk of flooding and exacerbates the impacts along the vulnerable Southern African coasts. To mitigate the associated high-impacts, it is essential to know the probability of theses compound events (multivariate extreme event analysis) and understand the processes driving them (Wahl et al. 2015). In the project CASISAC*, we propose a regionalized multivariate assessment of extreme events to model extremes as combination of storm surge, waves, river discharge and high precipitation at southern African coasts (Namibia, South Africa, Mozambique). We develop a multivariate statistical model based on copulas to represent and analyze the physical mechanism underlying compound events and their return periods under present day climate conditions. The African regions are particularly poor sampled by tide gauges and available records include large gaps. To overcome the data scarcity, ancillary data from high-resolution ocean model hindcasts (Schwarzkopf et al. 2019) based on the NEMO model will complement the analysis. An integrated analysis of observational records from tide gauges in combination with ocean model hindcasts allows us to regionalize compound extreme events corresponding to certain return periods along the entire coastline. In this presentation, we will show preliminary results of the multivariate extreme value model analysis chain. *CASISAC (Changes in the Agulhas System and its Impact on Southern African Coasts: Sea level and coastal extremes) is funded by the German Federal Ministry of Education and Research (BMBF) under the grant number 03F0796C. Schwarzkopf et al. (2019): The INALT family – a set of high-resolution nests for the Agulhas Current system within global NEMO ocean/sea-ice configurations. In: Geoscientific Model Development, Vol. 12, 7, 3329-3355, doi: 10.5194/gmd-12-3329-2019. Wahl et al. (2015): Increasing risk of compound flooding from storm surge and rainfall for major US cities. In: Nature Climate Change, Vol. 5, 12, 1093-1097, doi: 10.1038/nclimate2736.