Climate Indices for Adaptation of the German Transport System

16:15 Wednesday 29 May


Room S8


Andreas Walter (Germany) 1; Stephanie Hänsel (Germany) 1; Stefan Krähenmann (Germany) 1; Christoph Brendel (Germany) 1; Michael Haller (Germany) 1; Kelley Stanley (Germany) 1; Christene Sylvia Razafimaharo (Germany) 1; Susanne Brienen (Germany) 1; Enno Nilson (Germany) 2; Markus Forbriger (Germany) 3

1 - Deutscher Wetterdienst; 2 - Bundesanstalt für Gewässerkunde; 3 - Eisenbahn-Bundesamt

We present climatological datasets, methodological approaches and first results obtained within the Network of Experts for the German transport system. The Network of Experts aims at contributing to a resilient and sustainable transport system in Germany by combining the competencies and resources of seven departmental research authorities and specialist authorities of the German Federal Ministry of Transport and Digital Infrastructure BMVI.

Within the Network of Experts an index catalogue has been compiled in order to assess the impacts of climate change and extreme weather events on transport infrastructure and mobility. Considered hazards are, e.g., flooding, storms, heat and landslides. Relevant indices were discussed with scientists, engineers and practitioners in the agencies responsible for road, railway and water transport.

Many climate indices depend on exceeding absolute thresholds (e.g., numbers of frost days, summer days, and heavy precipitation days), some more complex indices combine different climate variables (e.g., number of potential snow days; days with precipitation and low mean temperature 1-2 Beispiele). Thus, adjusting the simulations for systematic deviations (biases) between simulated and observed climate variables is essential for climate change impact and adaptation studies. Thereby, a multivariate bias correction algorithm is applied, applied to optimally fit the historical runs of the climate models to the observed data and ensure the consistency between the climate variables.

Climate indices are calculated and assessed for ensembles of regional climate projections for three RCP (Representative Concentration Pathways) scenarios (RCP2.6, RCP4.5, and RCP8.5). The assessment of future climate trends is supported by observational datasets that allow validating climate models for a reference period and identifying recent climate trends.

The introduced climatological datasets, the proposed analysis and assessment methods, and the compiled catalogue of climate indices are important foundations for subsequent climate impact and risk assessment within the BMVI Network of Experts.