Timescale: Oct. 2021 – Sept. 2024
PD Dr. Maik Heistermann, University of Potsdam
Prof. Dr. Henning Rust, FU Berlin
Mentor: Dr. Gerd Bürger, University of Potsdam
Flash floods and pluvial floods are among the most ubiquitous and destructive natural hazards in the world. Caused by short and intense rainfall followed by the rapid concentration of generated runoff in the landscape or in urban environments, they can, formally, be considered as a convolution in space and time. That convolution occurs exactly at those scales in which rainfall and runoff processes critically intersect: convective systems extend over orders of 101-102 minutes and 103-104 meters – the same scale at which quick runoff components concentrate to a level that conveys a relevant hazard exposure. As a consequence, any change in the dominant spatio-temporal properties of extreme convective events could affect the local flood hazard.
Only in the most recent years have we begun to better understand the spatio-temporal signatures of extreme convective events. Weather radar, in combination with adequate processing algorithms, is the only option to coherently observe and sufficiently resolve such rainfall events in space and time, and observational records at many services have just now become long enough to allow for robust statistics. E.g., Lochbihler et al. (2017) found evidence that, for severe convective features, higher intensities might be accompanied by larger rainfall areas. Furthermore, there is worrying, though still fragmentary, evidence that global warming might affect the spatio-temporal properties of future convective features towards higher intensities and larger spatial extents (e.g. Prein et al. 2017).
The fundamental research question of this project is whether and, if so, to what extent the frequency and amplitude of flood events at the meteorological meso-gamma scale change as a response to global warming. While that question is not asked for the first time, cross-scale interactions of extreme convective rainfall with the concentration of runoff in the landscape and in urban environments have not been explicitly acknowledged, yet. To that end, we will build on previous (NatRiskChange) and upcoming (BMBF ClimXtreme Module C) research projects to extract spatio-temporal attributes (i.e. intensity distribution in space and time) of extreme convective features from long (~20 years) archives of weather radar observations in Central Europe. Since these records are not long enough to robustly detect trends, we will instead attempt to identify co-variates which significantly link these attributes to regional and large-scale circulation patterns as represented by climate reanalyses. These relationships will be used to stochastically synthesize extreme rainfall with representative combinations of spatio-temporal attributes under transient climate conditions. In order to understand the consequences of such changes in terms of hydrological response, we construct the travel time distribution of runoff in the landscape based on the geomorphic instantaneous unit hydrograph framework (Rigon et al. 2016). That way, we can represent the space-time convolution of effective rainfall for any point in the landscape. A change, e.g., towards larger convective cells, would activate runoff generation at larger areas, yet the local organisation of runoff concentration would control whether such a larger activation would in fact propagate towards higher peak flows.
This project builds on previous and ongoing research on the space-time properties of extreme rainfall under climate change. Its main result and contribution, though, will be to analyse these properties in a scale-sensitive framework that takes into account the geomorphological controls of hydrological response, as relevant for flood hazards at and below the meso-gamma scale.
Dedicated Regional Cluster: Central Europe
Related PhD-projects: P3 (first cohort, Madlen Fischer), P6 (second cohort, Jana Ulrich), and Q13 (third cohort, see below); the project might also benefit from methodological approaches developed by Q6 (second cohort, Matthias Kemter) for river floods.