A statistical model to estimate the local vulnerability to severe weather

Tobias Pardowitz

doi:10.5194/nhess-18-1617-2018

Abstract

Abstract. We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors – which are often not available – we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

Highlights

It has been stated within the Sendai Framework for Disaster Risk Reduction 2015–2030 by the United Nations (UNISDR, 2015) that the implementation of effective disaster risk reduction measures should be based on an understanding of disaster risks, including all its dimensions of vulnerability, capacity, exposure of persons and assets, hazard characteristics and the environment
While insured losses on residential housing comprise specific impacts caused by windstorms and thunderstorms, fire brigade operations can be caused by meteorological phenomena such as flooding or impacts due to freezing rain or road icing
Operation counts in the period 2002–2011 for the whole of Berlin are correlated to daily building losses in Berlin

Summary

Introduction

It has been stated within the Sendai Framework for Disaster Risk Reduction 2015–2030 by the United Nations (UNISDR, 2015) that the implementation of effective disaster risk reduction measures should be based on an understanding of disaster risks, including all its dimensions of vulnerability, capacity, exposure of persons and assets, hazard characteristics and the environment. On local and national levels, this requires to systematically evaluate, record, share and publicly account for disaster losses to gain understanding of the impacts in the context of event-specific hazard, exposure and vulnerability information. Making use of records of local emergency managers (first responders) yields an immense potential as an alternative database for analysing weather impacts, on local scales. While often such records exist, they mostly lack systematic and homogenous data format and quality standards.

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