The purpose of this paper is to investigate the functionality and main results of the ImmoRisk tool. The aim of the project of the Federal Ministry for Transport, Building and Urban Development (BMVBS), in corporation with the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR), was to develop a user-friendly tool that provides a sound basis with respect to the risk situation caused by extreme weather events.
The tool calculates the annual expected losses (AEL) for different types of extreme weather hazard and the damage rate as the proportion of AEL on building value, based on a trinomial approach: natural hazard, vulnerability and the value of the property.
The paper provides property-specific risk profiles of both the present and future risk situation caused by various extreme weather events.
The approach described in the paper can serve as a model for the realization of subsequent tools in further countries bound with other climatic risks.
The real estate industry is affected by a significant rise in monetary damages caused by extreme weather events. Accordingly, the approach is suitable for implementation in the companies’ real estate risk management systems.
The tool offers homeowners a profound basis for investment decisions with regard to adaptation measures.
The approach pioneers fourfold: first, by meeting the needs of the housing and real estate industry based on a trinomial approach; second, by using a property-specific bottom-up approach; third, by offering both a comprehensive risk assessment of the hazards storms, flood and hailstorm and finally, by providing results with respect to the future climatic risk situation.
The authors are grateful to Ute Birk and Tobias Held from the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR) for initiating and supporting the ImmoRisk project, Guido Halbig, Bruno Merz, Marita Roos and Martin Vaché and the members of the steering committee for their scientific support, the German Weather Service (DWD), the German Research Centre for Geosciences (GFZ), the Karlsruhe Institute of Technology (KIT) and companies of the insurance industry for providing the crucial data set. They also express their appreciation to Marcelo Cajias and Peter Geiger for their valuable research assistance, Brian Bloch for his comprehensive editing of the manuscript, several conference audiences for helpful advices. The authors received funding from the German Society of Property Researchers (gif) and the Vielberth Foundation. They express their gratitude for this financial support.
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